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CR ITICAL ASSESSMENT OF BIODIVERSITY ACCOUNTING APPROACHES FOR BUSINESSES

ASSESSMENT OF BIODIVERSITY

MEASUREMENT APPROACHES FOR

BUSINESSES AND FINANCIAL INSTITUTIONS EU Business @ Biodiversity Platform UPDATE REPORT 2 - ANNEXES 6 DECEMBER 2019

ASSESSMENT OF BIODIVERSITY MEASUREMENT APPROACHES FOR BUSINESSES AND FINANCIAL INSTITUTIONS - ANNEXES

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Lead author Contributing authors Reviewers

Johan Lammerant (Arcadis),

Workstream Leader of EU Business &

Biodiversity Platform Workstream on

Natural Capital Accounting

[email protected]

Annelisa Grigg, Julie Dimitrijevic,

Katie Leach, Sharon Brooks & Audrey

Burns (UNEP WCMC)

Joshua Berger (CDC Biodiversité)

Joël Houdet (Endangered Wildlife Trust)

Mark Van Oorschot (PBL Netherlands

Environmental Assessment Agency)

Mark Goedkoop (Pré Consultants)

Lars Müller (DG Environment,

European Commission), leading

the EU Business & Biodiversity

Platform

[email protected]

Jerome Kisielewicz (ICF), project

leader EU Business & Biodiversity

Platform

[email protected]

Cover photo by Johan Lammerant

ACKNOWLEDGEMENTS

We would like to thank the participants to the workshop co-hosted with the EU Business @ Biodiversity

Platform in Brussels in March 2019 and subsequent sub-group discussions and participants at the workshop

held in Rio de Janeiro, Brazil in October 2019 for their insights and inputs into the papers from which this

analysis is drawn. Thanks also to the measurement approach developers who kindly submitted the information

on their measurement approaches on which this report is based.

mailto:[email protected]



ASSESSMENT OF BIODIVERSITY ACCOUNTING APPROACHES FOR BUSINESSES AND FINANCIAL INSTITUTIONS

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CONTENTS READER’S GUIDE 4

ANNEX 1: GLOBIO AND RECIPE, 2 IMPORTANT UNDERPINNING MODELS 5

GLOBIO 5

RECIPE 12

ANNEX 2: INFORMATION SHEETS OF ASSESSED BIODIVERSITY

MEASUREMENT APPROACHES FOR BUSINESS 22

1. The Agrobiodiversity Index 23

2. The Biological Diversity Protocol 34

3. Biodiversity Footprint for Financial Institutions 46

4. Biodiversity Indicators for Extractives 57

5. Biodiversity Impact Metric 65

6. Biodiversity Monitoring System for the Food Sector 76

7. Biodiversity Performance Tool for Food Sector 88

8. Global Biodiversity Score 104

9. Kering’s Environmental Profit & Loss approach 119

10. Life Key 131

11. Product Biodiversity Footprint 145

12. Species Threat Abatement and Recovery Metric 159

ANNEX 3: COVERAGE OF BUSINESS APPLICATIONS AND ORGANISATIONAL

FOCUS AREAS BY BIODIVERSITY MEASUREMENT APPROACHES 165


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READER’S GUIDE

This is the Annexes document of the 2019 Update 2 Report on “Assessment of biodiversity measurement

approaches for businesses and financial institutions”, which is a follow up to the 2018 Update 1 report

“Assessment of biodiversity accounting approaches for businesses and financial institutions”.

It consists of the following:

• Annex 1: Description of GLOBIO and ReCiPe: additional explanatory sections and reference

sources on Globio and ReCiPe are provided as these appear to be common underpinning datasets

and tools for several biodiversity assessment approaches.

• Annex 2: Technical details of the assessed ‘biodiversity metrics for business’ approaches:

Annex 2 has been updated based on a review by tool developers in summer 2019. While two

approaches were not updated, four additional approaches were included in the assessment.

Furthermore, the assessment template for the technical description of the biodiversity measurement

approaches has been refined to better reflect the key topics for convergence as identified under the

Aligning Biodiversity Measures for Business initiative.

• Annex 3: Matrix with detailed mapping of biodiversity measurement approaches against

business applications and organisational focus areas: The comparative tables under Annex 3 in

the Update 2018 Report have been replaced by more detailed thematic tables comparing the different

approaches, which are now included under the thematic chapters 4 to 7 in the main report.

It should be noted that Annexes 2 and 3 were completed by the measurement approach developers. They

are shared as submitted as a reference resource for developers and users of biodiversity measurement

approaches.


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ANNEX 1: GLOBIO AND RECIPE, 2 IMPORTANT UNDERPINNING MODELS

GLOBIO

GLOBIO/MSA : A model approach to determine biodiversity loss due to anthropogenic pressures,

expressed by an indicator of species abundance

Mark van Oorschot – PBL Netherlands Environmental Assessment Agency, the Hague , the Netherlands

GLOBIO in short

The GLOBIO model and the MSA indicator have initially been developed by a consortium consisting of PBL,

UNEP GRID-Arendal and UNEP-WCMC. Nowadays, the development and application of the model with the

MSA indicator are primarily taking place at PBL Netherlands Environmental Assessment Agency in

cooperation with the Radboud University (Nijmegen, Netherlands), Department of Environmental Science, and

Wageningen University (Netherlands), Environmentals System Analysis Group.

Basic principles

The GLOBIO model calculates the impact on biodiversity of various anthropogenic pressures: infrastructure,

hunting, nitrogen deposition, habitat fragmentation, land-use and climate change. Biodiversity is represented

by the MSA indicator, which indicates the level of ‘intactness’ or ‘naturalness’ of species communities in

ecosystems. It is expressed as the mean abundance of original species, compared to the undisturbed situation

in percentages, where 100% represents an intact undisturbed ecosystem, and 0% a completely destroyed

ecosystem. Changes in MSA due to increasing environmental pressures over time can be attributed to different

responsible economic sectors.

For each of the pressures included, the model contains a regression equation, linking the intensity of the

pressure to the impact on MSA-biodiversity. The dose-response relationships have been quantified based on

meta-analyses of MSA values retrieved from biodiversity data reported in peer-reviewed scientific research

articles (several hundreds of articles) (Alkemade et al., 2009). The supporting databases and the derived dose-

response relationships are continuously expanded and refined (Schipper et al. 2016; Schipper et al.

submitted).

Land-use is up to now the most prominent driver of global biodiversity loss. The impacts of land-use change

are assessed for a number of different land-use categories. These categories provide a range of different land-

use intensities in food, livestock and wood production systems (Schipper et al., 2016). In future scenario

analyses, climate change is the driver with the highest increase in impact on MSA, with different responses to

global mean temperature increase per biome and species group. The dose-response relationships for each of

the pressures are given in Figure 1.


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Figure 1 Dose-response relationships quantifying impacts on MSA for plants (green) and warm-blooded

vertebrates (red) due to a) climate change (based on global mean temperature increase), b) atmospheric

nitrogen deposition, c) land use, d) habitat fragmentation (based on patch size), e) disturbance by roads (based

on distance to roads), and f) hunting (based on distance to access points). Dashed lines and error bars

represent the 95% confidence interval. Point size reflects the weights of the observations. Land-use classes

include cropland (Cr), pasture (Pa), plantations (Pl), secondary vegetation (Se) and urban (Ur), with M =

minimal use and I = intense use. (from Schipper et al. submitted).

IMAGE-GLOBIO modelling framework

The GLOBIO model is part of the IMAGE model framework (Integrated Model to Assess the Global

Environment), developed at PBL for analysis of global change scenarios (Stehfest et al., 2014). To analyse

future development in global biodiversity, information on environmental pressures are generated by the IMAGE

model and used as input for GLOBIO. The IMAGE framework consists of several coupled models that describe

global environmental change under different assumptions of economic and demographic development. These

sub-models represent different aspects of the earth system, such as water flows, carbon cycling and natural

vegetation, in relation to various environmental impacts, including land use change, climate change and water

stress. The land-use model is primarily driven by the demand for food, feed, animal products, wood and bio-

energy.


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Scenario analysis

The GLOBIO model is used to quantify the consequences of alternative future developments for MSA

worldwide. For example, it is used to provide the Secretariat of the UN-Convention on Biological Diversity (UN-

CBD) with analyses of future developments and the potential of policy options to reduce further biodiversity

loss. The results are published in several Biodiversity Outlook studies produced by the secretariat of the CBD

(sCBD, 2010; sCBD, 2014). It has also been applied to support the recently published global IPBES

assessment report on biodiversity and ecosystem services (IPBES, 2019).

Most of the analysed scenarios have originally been developed in the context of climate change mitigation and

adaptation pathways. These have been adapted to cover options relevant for reducing global biodiversity loss

(Kok et al., 2014; Kok et al., 2018; ten Brink et al., 2010). For the next Conference of Parties of the CBD in

China (2020), specific biodiversity scenarios are now being developed and analysed, based on different so-

called SSPs (shared socio-economic pathways). Also, a comparative analysis of different modelling

frameworks is now being performed, with different pathways to “bend the curve of biodiversity decline” (Leclere

et al., in prep.).

Applications at different scales and levels

The GLOBIO model is developed to cover global developments and produces spatially explicit results for land

and aquatic (freshwater) biodiversity at a resolution of 0.5° by 0.5° (i.e., 50 km by 50 km at the equator). The

resolution has been increased for the update to GLOBIO 4 (10 arc-seconds for terrestrial and 30 arc-seconds

for aquatic calculations). However, the dose-response relationships can also be applied at other geographical

levels, as long as information on environmental change is available for the relevant pressures. This flexibility

has facilitated applications at multiple levels, informing governance systems operating at different levels (figure

2). The applications range from the global level (OECD, 2012; Kok et al. 2018 – see figure 3) to national,

regional and landscape levels (Meijer et al., 2018). The model results have also been used in footprint

analyses, including biodiversity footprints of countries and world regions as well as industry sectors and their

supply-chains (Wilting et al., 2017; Wilting and van Oorschot, 2017). A recent development is the application

at company level, where alternative modes of operation (conventional, improved) are compared to assess the

effects of measures on biodiversity impacts (Berger et al., 2019; van Rooij and Arets, 2017).

Figure 2 The MSA dose-response relationships originally developed for global outlooks have also been applied

for other purposes, from strategic analysis at global levels to operational analysis at company levels.


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Figure 3 Application of the GLOBIO model and MSA indicator in an analysis of future economic and

demographic developments that lead to further biodiversity loss, and the potential to halt that loss using

different sets of solution packages that are representative of different scenarios for future development (from

Kok et al. 2014).

New developments

The GLOBIO model is continuously refined and further developed (Schipper et al., submitted). The GLOBIO4

model runs at a higher spatial resolution (10 arc-seconds; 300 x 300m cells) and contains a new relationship

for quantifying impacts of hunting in the tropics. It also has updated modules for quantifying impacts of climate

change, land use, habitat fragmentation and nitrogen pollution. Next to that, new individual species models

are now being developed that provide information on species' distribution and abundance, which can be used

to quantify the Red List Index (RLI) and the Living Planet Index (LPI) (Santini et al. 2019). These indicators will

be integrated in the GLOBIO framework in near future.

Next to the terrestrial model, a separate version (GLOBIO-Aquatic) has been developed to cover freshwater

habitats (Janse et al., 2015). Major pressures on biodiversity in freshwater ecosystems – rivers, lakes and

wetlands - are land use change, eutrophication, hydrological disturbance, climate change, overexploitation and

invasive species. The pressures currently included in GLOBIO-Aquatic are land use and nutrient loading

affecting water quality, and hydrological disturbance and climate change affecting water flow.

Strengths and limitations

Strengths

The MSA indicator is easy to interpret as relative “naturalness” or “intactness” of biodiversity (Mace, 2005). As

abundance-based indicator, it can provide an early warning signal that can be acted upon.

The GLOBIO model is pressure-based, which enhances policy relevance (Spangenberg, 2007). It enables

analyses of measures that target these pressures (Kok et al. 2018). Moreover, the drivers of biodiversity loss

can be attributed to different sectors and actors (see for instance Wilting and van Oorschot 2017).

The GLOBIO model is internationally well-known. MSA is an indicator of trends in species abundance, one of

the indicators included in the CBD-framework for measuring state and progress on biodiversity. Assessments

and scenario analyses have been performed for multi-lateral global governance institutions, such as the

OECD, UN-Environment Program and the UN-CBD and IPBES. It is also used as an example in the IPBES

guidance on the use of scenarios and models to analyse global biodiversity change (Ferrier et al. 2016).


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The MSA indicator, as a biodiversity intactness indicator, is part of the proposed set of biodiversity indicators

that together provide a representative view on biodiversity loss and possibilities for recovery. Mace et al. (2018)

proposed three indicators: trends in species abundance (for instance LPI), species extinction risks (e.g. RLI)

and ecosystem intactness (BII). MSA is an example of ecosystem intactness.

The GLOBIO knowledge base has been expanded in the last decade, and a number of peer-reviewed papers

have been published (see:Alkemade et al., 2013; Benítez-López et al., 2010; Benítez-López et al., 2017; de

Baan et al., 2013; Midolo et al., 2019; Nunez et al., 2019). Updates have been implemented in GLOBIO v4

and applied in a scenario analysis (Schipper et al. submitted). The knowledge base is freely available for use

by other parties (open access), as long as it is properly referenced. The GLOBIO.info website is now under

reconstruction to serve potential users in a better manner.

Limitations

The MSA indicator represents one of the main aspects of biodiversity, i.e. biodiversity intactness), but does

not provide a picture of specific species. However, to improve the value of GLOBIO scenario analyses, the

indicator set in the model framework is now being expanded to cover species abundance trends and risks of

species extinctions, based on individual species models.

The distinction of different land-use classes and intensities makes it possible to apply the MSA dose-response

relationships to a broad range of primary production sectors. Still, several land-use types are missing in the

GLOBIO model, such as mining industries and mixed land-use types. Research on spatial extent and impacts

of mining industries is ongoing, and will be published.

The databases underlying the dose-response relationships are freely available but not yet integrated in

databases that are used for product comparisons in Life Cycle Assessments. Integration of the knowledge

base would greatly help business applications, such as comparing alternative products and ways of operating.

The GLOBIO model is mostly applied for global analyses, but results cannot easily be translated to national or

even regional levels. To do that, modelling tools must be used that provide information on environmental

pressures that reflect local developments. Also, local case-studies on MSA impacts would help to make

application of GLIOBIO/MSA at local levels more relevant.

Business applications

The dose-response relationships available in GLOBIO have been used in different tools that are specifically

geared for applications at the level of businesses, such as the Global Biodiversity Score (CDC Biodiversité),

the Product Biodiversity Footprint (iCare) (see Annex 2 in this Update 2 Annexes report) and the Biodiversity

Footprint calculator (Plansup) (see Annex 1 in Update 1 Report). With these tools several business applications

are possible. It can provide a measure of the current state of biodiversity, it can be used to compare different

products for their biodiversity impacts, it can be used to track progress towards targets, it can be used in

footprint analysis of products and sectors, and can show trade-offs between different drivers of biodiversity

loss (for instance by comparing fossil fuels with bio-based fuels, where greenhouse gas emissions are replaced

by increased land-use (van Oorschot et al., 2010).

References

Alkemade R, van Oorschot M, Miles L, Nellemann C, Bakkenes M and ten Brink B. (2009). GLOBIO3: A

Framework to Investigate Options for Reducing Global Terrestrial Biodiversity Loss. Ecosystems 12:

pp. 374-390.

Alkemade R, Reid RS, van den Berg M, de Leeuw J and Jeuken M. (2013). Assessing the impacts of livestock

production on biodiversity in rangeland ecosystems. Proceedings of the National Academy of Sciences

110: pp. 20900.

Benítez-López A, Alkemade R and Verweij PA. (2010). The impacts of roads and other infrastructure on

mammal and bird populations: A meta-analysis. Biological Conservation 143: pp. 1307-1316.

Benítez-López A, Alkemade R, Schipper AM, Ingram DJ, Verweij PA, Eikelboom JAJ and Huijbregts MAJ.

(2017). The impact of hunting on tropical mammal and bird populations. Science 356: pp. 180.


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Berger J, Choukroun R and Vallier A. (2019). Global Biodiversity Score: a tool to establish and measure

corporate and financial commitments for biodiversity. 2018 technical update. CDC Biodiversite, Paris.

de Baan L, Alkemade R and Koellner T. (2013). Land use impacts on biodiversity in LCA: a global approach.

The International Journal of Life Cycle Assessment 18: pp. 1216-1230.

Ferrier S, Ninan K, Leadley P, Alkemade R, Acosta L, Akçakaya H, Brotons L, Cheung W, Christensen V,

Harhash K, Kabubo-Mariara J, Lundquist C, Obersteiner M, Pereira H, Peterson G, Pichs-Madruga R,

Ravindranath N, Rondinini C and Wintle B. (2016). The methodological assessment report on

scenarios and models of biodiversity and ecosystem services. IPBES Intergovernmental Science-

Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany.

IPBES. (2019). Summary for policymakers of the global assessment report on biodiversity and ecosystem

services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services,

Bonn.

Janse JH, Kuiper JJ, Weijters MJ, Westerbeek EP, Jeuken MHJL, Bakkenes M, Alkemade R, Mooij WM and

Verhoeven JTA. (2015). GLOBIO-Aquatic, a global model of human impact on the biodiversity of inland

aquatic ecosystems. Environmental Science & Policy 48: pp. 99-114.

Kok M, Alkemade A, Bakkenes M, Boelee E, Christensen V, van Eerdt M, van der Esch S, Janse J, Karlsson-

Vinkhuyzen S, Kram T, Lazarova T, Linderhof V, Lucas P, Mandryk M, Meijer J, van Oorschot M, Teh

L, van Hoof L, Westhoek H and Zagt R. (2014). How sectors can contribute to sustainable use and

conservation of biodiversity. PBL Netherlands Environmental Assessment Agency, the Hague.

Kok MTJ, Alkemade R, Bakkenes M, van Eerdt M, Janse J, Mandryk M, Kram T, Lazarova T, Meijer J, van

Oorschot M, Westhoek H, van der Zagt R, van der Berg M, van der Esch S, Prins A-G and van Vuuren

DP. (2018). Pathways for agriculture and forestry to contribute to terrestrial biodiversity conservation:

A global scenario-study. Biological Conservation 221: pp. 137-150.

Leclere D, Obersteiner M, Alkemade R. et al. (in prep). Towards pathways bending the curve of terrestrial

biodiversity trends within the 21st century.

Mace GM. (2005). Biodiversity: An index of intactness. Nature 434: pp. 32-33.

Mace GM, Barrett M, Burgess ND, Cornell SE, Freeman R, Grooten M and Purvis A. (2018). Aiming higher to

bend the curve of biodiversity loss. Nature Sustainability 1: pp. 448-451.

Meijer J, Giesen P, Shames S and Scherr SJ. (2018). Spatial modelling of participatory landscape scenarios:

synthesis and lessons learned from exploring potential SDG progress in 3 case studies. PBL

Netherlands Environmental Assessment Agency The Hague.

Midolo G, Alkemade R, Schipper AM, Benítez-López A, Perring MP and De Vries W. (2019). Impacts of

nitrogen addition on plant species richness and abundance: A global meta-analysis. 28: pp. 398-413.

Nunez S, Arets E, Alkemade R, Verwer C and Leemans R. (2019). Assessing the impacts of climate change

on biodiversity: is below 2 °C enough? Climatic Change 154: pp. 351-365.OECD (2012). OECD

Environmental Outlook to 2050. OECD - Organisation for Economic Co-Operation and Development,

Paris.

sCBD (2010). Global Biodiversity Outlook 3. Montreal, Canada, Secretariat of the Convention on Biological

Diversity.

sCBD (2014). Global Biodiversity Outlook 4. A mid-term assessment of progress towards the implementation

of the Strategic Plan for Biodiversity 2011-2020. Montreal, Canada, Secretariat of the Convention on

Biological Diversity.

Santini L, Butchart SHM, Rondinini C, Benítez-López A, Hilbers JP, Schipper AM, Cengic M, Tobias JA and

Huijbregts MAJ 2019. Applying habitat and population-density models to land-cover time series to

inform IUCN Red List assessments. Journal.

Schipper A, Bakkenes M, Meijer J, Alkemade R and Huijbregts M. (2016). The GLOBIO model. A technical

description of version 3.5. PBL Netherlands Environmental Assessment Agency, the Hague.

Schipper A, Hilbers J, Meijer J, Antao L, Benitez-Lopez A, de Jonge M, Leemans L, Schepers E, Alkemade A,

Doelman J, Mylius S, van Zeist W and Huijbregts M. (submitted). Projecting future terrestrial

biodiversity intactness with GLOBIO 4. Global Change Biology.

Spangenberg JH. (2007). Biodiversity pressure and the driving forces behind. Ecological Economics 61: pp.

146-158.

Stehfest E, van Vuuren D, Kram T, Bouwman L, Alkemade R, Bakkenes M, Biemans H, Bouwman A, den

Elzen M, Janse J, Lucas P, van Minnen J, Müller M and Prins A. (2014). Integrated Assessment of

Global Environmental Change with IMAGE 3.0. Model description and policy applications. PBL

Netherlands Environmental Assessment Agency, the Hague.


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ten Brink B, van der Esch S, Kram T, van Oorschot M, Alkemade R, Ahrens R, Bakkenes M, Bakkes J, van

den Berg M, Christensen V, Janse J, Jeuken M, Lucas P, Manders T, van Meijl H, Stehfest E, Tabeau

A, van Vuuren D and Wilting HC. (2010). Rethinking Global Biodiversity Strategies: Exploring structural

changes in production and consumption to reduce biodiversity loss. PBL Netherlands Environmental

Assessment Agency, the Hague, the Netherlands.

van Oorschot M, Ros J and Notenboom J. (2010). Evaluation of the indirect effects of biofuels on biodiversity:

assessing across spatial and temporal scales. PBL Netherlands Environmental Assessment Agency,

Bilthoven, the Netherlands.

van Rooij W and E. A. (2017). Biodiversity footprint of companies, summary report. Platform BEE - Biodiversity,

Ecosystems and Economy, the Hague, the Netherlands,.

Wilting HC, Schipper AM, Bakkenes M, Meijer JR and Huijbregts MAJ. (2017). Quantifying Biodiversity Losses

Due to Human Consumption: A Global-Scale Footprint Analysis. Environmental Science & Technology

51: pp. 3298-3306.

Wilting HC and van Oorschot MMP. (2017). Quantifying biodiversity footprints of Dutch economic sectors: A

global supply-chain analysis. Journal of Cleaner Production 156: pp. 194-202.


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RECIPE

The use of ReCiPe 2016 as a methodology to determine biodiversity impacts

Mark Goedkoop; PRé Sustainability, Amersfoort, The Netherlands [email protected]

Introduction

Background

The ReCiPe method was first developed in 2008 through cooperation between RIVM, Radboud University

Nijmegen, Leiden University and PRé Consultants (lead). The current 2016 version was developed through

cooperation of Radboud University in Nijmegen, RIVM, NTNU Trondheim and PRé1. Note there is a

considerable overlap of experts working both on the development of ReCiPe and Globio2. Even though there

is an overlap in the science used, the meaning of the results are quite different as both methods aim to answer

a different question.

ReCiPe was developed for Life Cycle Assessment (LCA)

Life cycle assessment (LCA) developed in the early nineties as a systematic and consistent tool to assess the

environmental impacts throughout the value chain. The basic rules for the methodology are defined in the ISO

14040 and 14044 standards, that define terminology, procedures and the most relevant requirements.

Figure 1: Typical phases in LCA

There are four basic main steps in an environmental Life Cycle assessment, and these can also be recognised

in the first four steps in the BFFI procedure (see Figure 2).

1. Define the goal and scope. An important element is defining the system under investigation that is to

be assessed; in BFFI this translates in understanding the activities a company is engaged in. when a

Financial Institution invests in it.

2. Collect the data; each production, use and waste handling process uses resources and has emissions.

The generic term for these items is “elementary flow” the list of all elementary flows is what is called

the Life Cycle Inventory result or LCI

3. Apply Life Cycle Impact assessment. This is a methodology that converts the long list of elementary

flows into a number of impact category result indicators. Various research groups have developed

several methodologies. ReCiPe is one of these; a very frequently used method3.

1 The 2008 method was a further development of the Eco-indicator 99 method. The history of ReCiPe started in 1995 when the Eco indicator 95 methodology was developed; these projects were led by PRé 2 Both group of experts are based in the Netherlands; there are close links between RIVM, PBL (the developers of Globio) and Radbout University in Nijmegen. The main author of the ReCiPe report, Mark Huijbrechts, is also a Co-author of the 2016 Globio report, no mention an example. 3 The EU JRC has published an extensive review of the most widely used methods: https://eplca.jrc.ec.europa.eu/uploads/ILCD-Recommendation-of-methods-for-LCIA-def.pdf


https://eplca.jrc.ec.europa.eu/uploads/ILCD-Recommendation-of-methods-for-LCIA-def.pdf


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4. Interpretation. This can include steps like uncertainty analysis and sensitivity analysis to test the

influence of different assumptions, methodological choices and inventory databases In the case of the

application of BFFI, the interpretation focusses on identifying the hotspots in the investment portfolio.

Figure 2: The procedure used in BFFI; the first 4 steps are very similar as the 4 steps in the LCA process described here

Textbox 1: Terminology

• Life Cycle Inventory: The procedure to collect all relevant emissions extraction of

resources like water, land use and land conversion. Often a distinction is made between

various type of data:

o Activity data: the amount material an organisation purchases: for instance, the

amount of cotton that goes into a T-shirt, or in the BFFI application, the amount a

financial institute invests in a company

o Primary data: emission and resource data that are collected directly, from the

lifecycle actor that operates a process. For instance The supplier may be willing

to specify the emission and resource data for the weaving and colouring process

in his company, or in the BFFI context, a Financial institute that invests directly in

a wind park, may be able to get all the data caused by building the wind park.

o Secondary data: emission and resource data that has been collected by others,

often available in databases. In BFFI the Exiobase database is often used.

• Life Cycle Impact Assessment The process to convert the Life Cycle inventory results

into a number of impact category indicator results. This procedure is always based on a

quantitative cause-effect Mechanism that links the inventory results to an endpoint. Often

this is done in two steps:

o Midpoint Impact Category Indicator Results. The midpoint indicator is placed

on the cause effect mechanisms, somewhere halfway between the inventory

result. Midpoints. For example, the CO2 equivalents defined by IPCC can be

used as a midpoint. Temperature increase can also be defined as a midpoint.

o Endpoint Impact Category Indicator Results. In the case of BFFI the endpoint

is “Ecosystem Quality”; to measure this the indicator refers to species loss, see

below) Biodiversity is one of the three endpoint indicators in ReCiPe. The other

endpoint indicators reflect the impact on human health (DALY) and resources ($

future mining costs).


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ReCiPe modelling framework from inventory to endpoint

ReCiPe is built on a number of environmental models. The number of models used exceeds the number of

impact categories, which makes it rather difficult to summarise the basic modelling approach. However, in this

paragraph we will do an attempt. Figure 3 provides an overview.

Figure 3 overview of the structure of the ReCiPe model; the Biodiversity part. The arrows represent environmental cause effect models, that are briefly referenced to in the annexe. The midpoints are generally expressed as equivalents. All emissions or resources that contribute to an impact category are characterised by their relative contribution for toxicity the substance 1,4-dichlorobenzene-equivalents (1,4 DCB) was used. The conversion between the aquatic and terrestrial impacts is needed, as the impact in aquatic systems is per cubic meter, while the impact in terrestrial systems is per square meter.

The biodiversity metric4

The biodiversity impact used in BFFI is in ReCiPe aims to express the potential disappearance of species. In

a certain area during a given time. We refer to the potential disappearance with the term PDF (Potentially

Disappeared Fraction). The PDF can have a max value of 1 (or 100%), all species disappeared. Or zero; all

species are still there5.

It is important to realise that a discrete emission, like the release of a kilogram of CO or a kg of CO2, cannot

have an eternal effect; Carbon Monoxide will have an atmospheric life time of a few weeks, and Carbon Dioxide

will have an atmospheric lifetime of at least a century. It is also important to realise that the Carbon Monoxide

will not spread throughout the world, but only will have an impact in a certain region; so there is always an area

size included. This reasoning also applies for instance the extraction of ground water and the conversion of

forests to an agricultural area. It only produces damage in a certain area, and there can be a restoration during

x years, so also here is a time and area element. This is why the unit is a multiplication of the PDF, the area

4 According to the ReCiPe report the biodiversity metric is expressed as Species.year, The species year is based on de PDF.m2.yr. This unit can be converted to species.year by multiplying the PDF.m2.yr with the species density on terrestrial land. For BFFI we ignore the Species.year unit as this is confusing 5 In Globio the Species Richness concept is uses which has an inverse scale; 1 means no damage, 0 means all species lost


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and the time, or PDF.m2.yr. This means if we find a PDF.m2.yr of 40, we can interpret this in the following

ways:

• 40% of the species disappear on an area of 100 m2 during one year.

• 20% of the species disappear in an area of 10 m2 during 20 year.

• Or any other way as long as the product of PDF, area and time equals to 40

This applies for terrestrial impacts; for impacts on aquatic system the surface area is not a good metric, and

there we use the impact per unit of volume: PDF.m3.yr. We convert these volumes to surface by taking into

account the ratio between average species density on land and the average species densities in fresh and

marine water (see Goedkoop at. All 2008).

Emission related impact categories

The inventory results for emissions are almost always expressed in mass units, i.e kg of CO2, kg of Cadmium

etc. These emissions are fed into a fate model. This model calculates the environmental fate of a substance,

as the time it takes to degrade, the share of an airborne emission that will be ending in soil or water bodies,

and vice versa, waterborne emissions that end up in soil or air. The result is change in concentration of a

substance on top of the background concentration. This change in concentration is fed into an effect model,

which translates a change in concentration into an effect.

Emission -→concentration change -→ change in effect

Figure 4, schematic illustration of a fate model used for toxic substances. There are three boxes, representing urban air, a regional continental scale and a global scale. Emissions release in agricultural soil can transfer to air and water in the regional scale, and substances with a long environmental residence time can transfer from the continental scale to the global scale and the urban scale. It also calculates the transfer to food produced on the agricultural soil. This is a simplified model; many fate models are nowadays based on a regionally differentiated map of the world, and the fate can be determined per grid cell

Environmental fate models do not use mass as an input, but a steady flow (flux) of emissions. They are

designed to determine a steady state concentration in the different compartments due to such a steady state

flux. The effect model then determines the likelihood species will disappear due to the change in concentration.

For toxicity the link between concentration and effect is relatively straightforward, for instance climate it is

necessary to fist determine the temperature change due to the change in CO2 equivalents.

A simple way to explain this6 is as follows:

1. Suppose an environmental fate model is set to use a steady state flow that represents the current

background level of emission, and we add one kg of an emission per hour to this flow.

2. Fate models always have a defined area. Otherwise the emission would be diluted endlessly. Although

this is unusual small, let’s assume the area is 10 m2

3. Suppose this causes a certain concentration increase of x%

4. The next step is the effect model which translates a change in concentration into an effect, for instance

let’s assume this change of concentrations causes a marginal loss of species of 5% (PDF)

5. If we want to know the impact of an emission of 1 kg, we can “allocate” one hour or that species loss

to this emission.

6 Of course this is a huge over simplification and it is much more complex for many impact categories


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6. The result is that we can determine one kg, has an impact of 0.5 PDF.m2.hour

The fate model and the first part of the effect model is generally used for the midpoints, the link between

midpoints and endpoints is based on another effect model, or consecutive effect models7.

Resource use related impact categories

There are two very important forms of resource use (extraction) that affect biodiversity:

• Water use and

• Land Use, which can be split into

o Land occupation

o Land conversion.

While ReCiPe has a separate section on mineral and fossil fuel depletion8, for biodiversity assessment, these

are less relevant. Mining operations do cause land conversion and land occupation and this is captured under

the land-use impact. Also silvicultural extractions such as wood harvesting, have very significant impacts on

biodiversity, but this is also captured via assessing the impacts on land transformation and land-occupation.

Water use

Using water as such does not need to have an impact on biodiversity as long as the extraction does not lead

to scarcity or changes in water levels. The model used in ReCiPe therefore focuses on the impact of local

water scarcity. In principle ReCiPe can assess water scarcity on a very high level of site specificity. In the

current BFFI application this potential is not always used as the Exiobase database inventory has water

extraction only on the country level for 41 countries and 5 “rest of the world” regions.

This means if we can obtain more site specific water extraction data this can be used to get a more detailed

result.

7 ReCiPe has been designed to keep the midpoints as close as possible to the inventory result, at the point in the environmental mechanism where all emissions can be unified into a single substance equivalent like CO2 equivalents. This is done as each step in the environmental mechanism adds uncertainty, and by avoiding steps, the midpoint has the lowest uncertainty. 8 These impact categories determine te risk that resources are at one point in time depleted, which can have a significant economic impact.


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Figure 5 illustration of the water scarcity index developed by Phister at all; this model is one of the models used in ReCiPe to determine water scarcity and it consequential PDF

The land-use model

Land use in LCA is usually modelled using what is sometimes referred to the Bathtub curve. Figure 6 shows

two transitions when land is converted, used and at one point (in the future) abandoned:

Figure 6: Modelling of land use in LCA

1. At T1 conversion from nature starts, till T2, reduced species during occupation

2. Between T5 and T 6 nature gets the opportunity to restore, can last many decades.

The issue is now how do we represent the impact of a farmer using an already converted field during one year,

and how do we represent the impact of an entity that converts nature into an artificial area (agriculture, mining,

urban area, etc.)

• The entity that occupies, between T3 and T4, is charged with the duration times reduced PDF (dark

blue square)

• The entity that converts, is charged with restoration, i.e. the area in the triangle (PDF times years)

This means that In ReCiPe a farmer who is not responsible for converting the land andis only responsible for

the occupation time that is supposed to delay the point in time where land can be abandoned, and nature can

restore itself. The entity for converting bears a much greater responsibility, as it is charged with the time needed

for the restoration. This restoration time is estimated for various ecosystems, based on literature.

This is of course a simplified model of a complex reality, as during the occupation time the biodiversity may

also change. It is also not clear if it is realistic that an abandoned area will at some point have a biodiversity

level that matches the original area.

The models used in Recipe can be used in a site specific way when detailed inventory data are available. Like

in the case of water, this cannot be fully exploited in BFFI, as long as we use the Exiobase inventory database,

which specifies data only on the level of countries and some rest of the world regions


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Applications at different scales and levels

While the modelling in ReCiPe is relatively coarse, it is possible to zoom in into the model and get more specific

data at site level. Using again the example of land use, the illustration below shows two ways to assess positive

impacts if restoration measures are applied in a specific area.

The figure on the right-hand side shows how an investment in restoring degraded land could speed-up the

restoration. The pink triangle linking T5, T6’ and T6 can be interpreted as a positive effect of this investment.

In the left-hand figure, a change in agricultural practices during occupation (T3-T4) results in a higher species

number during occupation, plus the added benefit that the restoration may be realised at an earlier moment.

Currently this is further explored in a separate project.

A similar more site specific approach can be used for most impact categories, as ReCiPe is generally built on

site specific models.

Business applications

As explained the primary function of ReCiPe is to translate the list of emissions and resource uses (land and

water) into a number of impact categories and from there to an endpoint expressing biodiversity. The intended

application is LCA, but the application area of LCA is quite broad:

1. Assessing the lifecycle impacts of a product throughout the lifecycle, in order to find the hotspots and

priorities for improvement, or for making environmental product declarations

2. Comparing between different products

3. Consequential modelling: understanding the price elasticities, for instance if less cotton is produced,

less cotton seed will be on the market as cattle feed, which means cattle feed will need to be produced

in another way.

4. Scenario analysis, for instance developing insights in future agricultural practices or energy systems.

In the BFFI approach the focus is on identifying hotspots, and currently also tested for understanding scenarios

related to positive impacts, often using locally specified data and not background databases like Exiobase.

Future developments

There is a lively community of experts further develop methods like ReCiPe, and like in the case with GLOBIO

often considerable personal overlap of experts. A clear example is the LC-impact community9, which is the

result of an EU sponsored research program, where many researchers developed and explored new impact

pathways not yet included in methods like ReCiPe; for biodiversity modelling they generally use the PDF

concept.

Next to this the UNEP Life Cycle Initiative10 is developing consensus on the best available methodologies per

impact category, and this consensus building is providing guidance to future developments.

Strength and limitations

9 https://lc-impact.eu 10 https://www.lifecycleinitiative.org/reaching-consensus-on-recommended-environmental-indicators-and-characterisation-factors-for-life-cycle-impact-assessment-lcia/

https://lc-impact.eu/

https://www.lifecycleinitiative.org/reaching-consensus-on-recommended-environmental-indicators-and-characterisation-factors-for-life-cycle-impact-assessment-lcia/

https://www.lifecycleinitiative.org/reaching-consensus-on-recommended-environmental-indicators-and-characterisation-factors-for-life-cycle-impact-assessment-lcia/


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The LCA methodology can be seen as aiming to do something really ambitious; providing a systematic way to

understand all relevant supply chains, product use and disposal routes (LC-inventory) and mapping these on

all environmental impact categories we think are relevant (LC-impact assessment). This means, results can

be uncertain, as it is difficult to know the exact impacts of all supply chain actors. In spite of this problem the

key strength is that there is to date no alternative for systematically trying to approach and address this

problem.; GLOBIO is assessing another question, so this is not an alternative to address the same question,

but a different equally ambitious question on future scenario outcomes.

Below we only focus on the strength and weaknesses of the ReCiPe LCIA methodology, but the use of the

inventory databases like Exiobase also create some strength and weaknesses.

Strengths

We see the following strengths in ReCiPe

1. Developed as business decision support tool; it highlights the impacts of a specific decision directly

without needing to consider scenarios. It expresses results as time integrated impacts. The full future

impact of the addition of a kg of methane is represented in the result.

2. Broad range of coverage of environmental impact categories;

3. Can be linked directly to LCA databases and global economy models such as Exiobase

4. Implemented in many LCA softwares, ready to use (no IP required, all information transparent and

available),

5. Peer reviewed literature as a basis, widely used and tested in the LCA community and in fact the third

generation of a long development process; relatively stable if ReCiPe 2008 and 2016 are compared.

6. Still being updated.

7. Well documented set of modelling assumptions, see also “weakness point 5”

Weaknesses

One of the issues is that, while it is clear data should be collected on a site specific basis, this is often not

possible in the inventory data collection stage. Supply chains are often quite lack transparency, and change

all the time. A company that buys a ton of steel is not able to trace from which mines the iron comes from. This

means that LCA results are always a “best possible” approximation of the real impacts and considerable

uncertainties cannot be avoided.

We see the following weaknesses

1. Although the coverage of impact pathway is broad, still several are missing, for instance ocean

acidification, plastic soup, non-indigenous species damage to water bodies with trawling nets, hunting

and gathering, erosion, etc. There are projects running to solve some of these problems, like the plastic

soup problem, and as this is an open framework this can be easily added.

2. The PDF metric cannot differentiate between Red List and non-Red List species, although sometimes

the concept of target species is used to identify species that should naturally occur in an specific

habitat11. However this is not always done.

3. Limited coverage of taxa. Mainly vascular plants and lower organisms are modelled. This can be

partially justified as these organisms are at the bottom of the nutrient chain.

4. The conversion of PDF’s in aquatic systems to terrestrial systems, using species density data on a

global scale is highly uncertain, as it is far from clear how many species there are; potentially this

explains why impacts in waterbodies never seem to show up in BFFI.

5. A model like this cannot be made without making many assumptions like for instance the level of

scientific evidence that is needed to support an element of the pathway (precautionary principles or

hard evidence), the timeframe used etc. While not explained here, ReCiPe is available in three

different versions each representing a different, but consistently modelled worldview. So, there is a

version using the precautionary principle as one of the starting point, a version that only considers

hard evidence, and a consensus version; the latter is used in BFFI

11 Example: Eutrophication can lead to an increase in species, but not the species that should occur in an ecosystem; the stronger, “undesirable species” can drive out the species that thrive on soil that has low levels of nutrients


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6. Each cause and effect pathway has some individual weaknesses and points that need further

improvement.

Box 1 Summaries of impact pathways

This box provides a very short identification of the science used in every impact pathway. More information can be found

in the ReCiPe report .

Emission related impact categories

Impact categories that have emissions as an input are the following:

Climate change

There is broad consensus that the fate model used in IPCC can be used to calculate CO2 equivalents. IPCC has produced

three versions with different timeframes: 20 years, 100 years and 500 years. The 100 year timeframe is used, which

implies that the impact of substances with a longer environmental residence times than 100 years (CO2 and N2O for

instance) are cut off12. The next step is the link between time-integrated radiative forcing and time-integrated temperature

increase for CO2. For terrestrial ecosystems, the increase in potentially disappeared fraction of species (PDF) due to an

increase in global temperature was derived from the review by Urban (2015). The influence of global temperature increase

on river discharge and expected changes in fish species occurrences was taken from Hanafiah et al. (2011).

Ozone formation (tropospheric)

The ecosystem ozone formation potential (EOFP), expressed in kg NOx e.q, expresses the sum of the differences

between the hourly mean ozone concentration and 40 ppb during daylight hours over the relevant growing season in

ppm∙h. For the mid to endpoint model, the effect factor describes the change in PDF of forest and grassland species due

to the change in ground level ozone exposure over forest and grassland area.

Terrestrial acidification

Marginal changes in acid deposition, following changes in air emission of NOx, NH3 and SO2, were calculated with the

GEOS-Chem model, resulting in a change in acidity in the soil due to a change in acid deposition which was derived with

the geochemical steady-state model. The effect factor quantifies the change in the PDF of vascular plant species due to

a change in the H+ concentration and was derived for specific biomes, such as temperate broadleaf mixed forest, tundra

and (sub)tropical moist broadleaf forest.

Freshwater eutrophication

The fate of phosphorus forms the basis of the midpoint characterisation factors for freshwater eutrophication. Freshwater

eutrophication potentials (FEP) are expressed in kg P to freshwater-equivalents. For emissions to agricultural soils, it was

assumed that typically 10% of all P is transported from agricultural soil to surface waters.

The effect factor, added to the midpoint calculations, describes the absence of species due to phosphorus concentrations

in freshwater. It reflects the change in PDF of species due to a change in total P concentration and depends on the

freshwater type (rivers or lakes), species group (heterotrophs and autotrophs) and climate type (warm, temperate, xeric

or cold).

Eco-Toxicity

The fate and effects of chemical emissions expressed in kg 1,4-dichlorobenzene-equivalents (1,4DCB-eq) was used as

characterisation factor at the midpoint level for freshwater ecotoxicity, marine ecotoxicity and terrestrial ecotoxicity. A

global multimedia fate, exposure and effects model USES-LCA 2.0, as a basis for our calculations, updated to deal with

dissociating chemicals and using the chemical data from the USEtox database. The ecotoxicological effect factor

represents the change in PDF of species due to a change in the environmental concentration of a chemical.

Resource related impact categories

The impact categories for water scarcity and land use have the following scientific references.

Water scarcity The impacts of water consumption on terrestrial ecosystems were taken from a detailed global model by Pfister et al.

(2009), who quantified them based on the damage for vascular plant species using net primary productivity (NPP) as a

proxy. Impacts of water consumption on freshwater ecosystems were taken from an equally detailed global model by

Hanafiah et al. (2011), who quantified them as the change in fish species lost associated with a decrease in discharge.

Both methods are in line with the ISO 14046 standard on water footprinting

12 In ReCiPe two other versions of the methodology are developed, one with a short term approach, one with a long term approach; almost everybody uses the middle version with 100 year.


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Land use and land conversion

The data on land occupation in the inventory is expressed in m2·yr annual crop equivalents. This causes a relative

species loss specific for a land use type (annual crops, permanent crops, mosaic agriculture, forestry, urban land,

pasture). Relative species loss was determined by comparing field data on local species richness in specific types of

natural and human-made land covers (De Baan et al. 2013; Elshout et al. 2014). These factors are differentiated on a

regional basis. For land conversion, passive recovery towards a (semi-)natural, old growth habitat was assumed, based

on average recovery times from Curran et al. (2014).

References

A very compact, yet comprehensive source to all the literature used, is by retrieving the following article:

1. Mark A. J. Huijbregts & Zoran J. N. Steinmann. Pieter M. F. Elshout. Gea Stam

Francesca Verones. Marisa Vieira. Michiel Zijp. Anne Hollander. Rosalie van Zelm. ReCiPe2016: a

harmonised life cycle impact assessment method at midpoint and endpoint level 29 Nov 2016, Int J Life

Cycle Assess (2017) 22:138–147. DOI 10.1007/s11367-016-1246-y

Or the following report, available on the www.rivm.nl website

2. Huijbregts MAJ, Steinmann ZJN, Elshout PMF, Stam G, Verones F, Vieira MDM, Hollander A, Van Zelm

R, 2016. ReCiPe2016: A harmonized life cycle impact assessment method at midpoint and endpoint level.

RIVM Report 2016-0104. Bilthoven, The Netherlands.

The two predecessor reports describing earlier versions of ReCiPe are:

3. Goedkoop M, Heijungs R, Huijbregts MAJ, De Schryver A, Struijs J, and van Zelm R. 2009. ReCiPe 2008:

A life cycle impact assessment method which comprises harmonised category indicators at the

midpoint and endpoint levels. First edition. Report i: Characterization. the Netherlands: Ruimte en Milieu,

Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer.

4. Goedkoop M.J., Heijungs R., Huijbregts M., De Schryver A.; Struijs J., Van Zelm R. ReCiPe 2008, A life

cycle impact assessment method which comprises harmonised category indicators at the midpoint and

the endpoint level; First edition Report I: Characterisation. 6 January 2009 (updated May 2013)

In this paper a few of the very long list of references from the ReCiPe report are quoted:

5. De Baan L, Alkemade R, and Köllner T. 2013. Land use impacts on biodiversity in LCA: A global approach.

International Journal of Life Cycle Assessment 18 (6):1216-1230. doi: Global land use impacts on

biodiversity and ecosystem services in LCA.

6. Curran M, Hellweg S, and Beck J. 2014. Is there any empirical support for biodiversity offset policy?

Ecological Applications 24 (4):617- 632. doi: 10.1890/13-0243.1.

7. Elshout PMF, Van Zelm R, Karuppiah R, Laurenzi IJ, and Huijbregts MAJ. 2014. A spatially explicit data-

driven approach to assess the effect of agricultural land occupation on species groups. The International

Journal of Life Cycle Assessment 19 (4):758-769. doi: 10.1007/s11367-014-0701-x.

8. Hanafiah MM, Xenopoulos MA, Pfister S, Leuven RS, and Huijbregts MAJ. 2011. Characterization Factors

for Water Consumption and Greenhouse Gas Emissions Based on Freshwater Fish Species Extinction.

Environmental Science & Technology 45 (12):5572- 5278.

9. Pfister S, Koehler A, and Hellweg S. 2009. Assessing the Environmental Impacts of Freshwater

Consumption in LCA. Environmental Science & Technology 43 (11):4098-4104.

10. Urban MC (2015) Accelerating extinction risk from climate change. Science 348:571–573

http://www.rivm.nl/

https://www.rivm.nl/

https://www.rivm.nl/documenten/a-lcia-method-which-comprises-harmonised-category-indicators-at-midpoint-and-endpoint




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ANNEX 2: INFORMATION SHEETS OF ASSESSED BIODIVERSITY MEASUREMENT APPROACHES FOR BUSINESS

UPDATE 2 REPORT ON ASSESSMENT OF BIODIVERSITY MEASUREMENT APPROACHES FOR BUSINESSES AND FINANCIAL INSITUTIONS

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1. The Agrobiodiversity Index

FICHE NR 1 THE AGROBIODIVERSITY INDEX

1. Date of assessment

• First version by Bioversity International on August 1, 2018

• First review by EU B@B Platform on 7 August

• Update on July 9, 2019

2.Actors • Lead: Bioversity International

• Others: since the inception, the Agrobiodiversity Index team has partnered with Clarmondial - a Swiss investment advisory

company focused on sustainable natural resource investments in emerging markets - to tailor the tool to the needs of the

finance sector. In particular, joint work focuses on helping corporate or government issuers to demonstrate the value for money

of their agrobiodiversity-themed green bonds, as well as helping investors to re-orient investments towards less risky and more

remunerative investments in food and agriculture.

Throughout the index development, Bioversity International has also worked in close collaboration with a wide range of stakeholders, representing its target users (governments, companies and investors) to make sure it addresses their needs. The development of the Index started with a feasibility study in 2017 that mapped the demand and specific needs for an Agrobiodiversity Index among a wide range of stakeholders, including representatives from:

✓ Governmental and intergovernmental organizations: India; Nepal; Pakistan; Italy; Mexico; Peru; Philippines; Ethiopia; UN Environment; Food and Agriculture Organization of the United Nations; Global Environment Facility; Convention on Biological Diversity; International Center for Advanced Mediterranean Agronomic Studies.

✓ Investors: Global Alliance for the Future of Food; Rockefeller Foundation; AXA; Vanguard; Swiss RE; Amundi; World Bank; Rabobank; Barclays; HSBC; Univest; Credit Suisse.

✓ CSO and conservation organizations: World Farmers' Organization; International Union for Conservation of Nature; Conservation International; Family Farming Knowledge Platform; The Prince of Wales's Charitable Foundation; Global Youth Biodiversity Network; AfricaSeeds.

✓ Knowledge and data partners: Access to Seeds Index; Enabling the Business of Agriculture; Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (PREDICTS, The UN Environment World Conservation Monitoring Centre and Natural History Museum, London); Economist Intelligence Unit; Commonwealth Scientic and Industrial Research Organisation (CSIRO); Bern University of Applied Sciences; Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA); Barilla Center for Food & Nutrition.


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During the Index development phase, scientific and science–policy collaborators from a variety of institutions provided perspective to the methodology development, helping the team realize a tool that is complementarity to the ones already existing. The development process has benefited from the interaction with colleagues at: World Benchmark Alliance; PREDICTS - Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (a project of the UN Environment World Conservation Monitoring Centre and the National History Museum, London); Access to Seeds Index; FAO; Commonwealth Scientific and Industrial Research Organisation (CSIRO); University of Ghent; Cambridge Institute for Sustainable Leadership; Economist Intelligence Unit; Barilla’s Food Sustainability Index; World Bank Enabling the Business of Agriculture Initiative; and the Biodiversity Finance Initiative of the UN Development Programme. Within the wider CGIAR family, we thank colleagues at the Big Data Platform; the International Tropical Research Center (CIAT); and the CGIAR Research Programs on Agriculture for Nutrition and Health (A4NH); and Water, Land and Ecosystems (WLE).

The Agrobiodiversity Index team has also worked closely with countries to pilot the Index. This includes collaborations with the Peruvian Ministries of Agriculture and Environment, the Indian Ministry of Agriculture, and National Biodiversity Authority, and the Indian Council of Agricultural Research. The Agrobiodiversity Index team, led by Dr Remans, is now running the analysis on 10 countries. Companies have also provided feedback and engaged with the Agrobiodiversity Index team to test the relevance of the tool for the private sector. These include Nestlé, Syngenta the European Landowners' Organization, and Sainsbury’s Supermarkets. Finally, the Index is part of the World Benchmarking Alliance and the team is partnering with global networks such as the EAT forum, the Food and Land Use Coalition (FOLU) and international NGOs, including the World Wide Fund (WWF).

3.Process and current position

➢ Please describe the development process and stages ➢ Please describe if the tool has been road-tested (add this information also in the table ‘Categories of

Business Applications!) and if case studies are available (please refer to links or publications) Process:

• In 2017, a feasibility study mapped the demand and specific needs for an Agrobiodiversity Index among food and agriculture companies, institutional investors, governments as well as other index groups (see above, section 2). In the same year, a review of the scientific literature was published and provides the scientific foundations of the Agrobiodiversity Index (https://www.bioversityinternational.org/fileadmin/user_upload/online_library/Mainstreaming_Agrobiodiversity/Mainstreaming_Agrobiodiversity_Sustainable_Food_Systems_WEB.pdf), in particular the importance of agrobiodiversity to achieve sustainable and resilient food systems, based on healthy and diverse diets, production systems and genetic resources.

• In 2018, the team developed the first prototype of the Agrobiodiversity Index and the first version of the methodology

(https://www.bioversityinternational.org/fileadmin/user_upload/AA_Publications/Methodology_Index_1.pdf). The methodology is

currently being reviewed to add more data sources and improve the tool. In fact, the Agrobiodiversity Index development and

implementation takes a design approach. The tool will continue to evolve and improve, as more information, datasets and

analytical work can be undertaken. For example, we will integrate data and analyses from Bioversity’s Alliance partner, the

International Center for Tropical Agriculture, to enhance the Index robustness and resolution. The methodology was tested in

Peru, and 3 cases studies were produced to show the application of the Index at different levels (national, local and project

level). Contacts were also made (and are ongoing) with companies to understand how the tool can be useful to assess their

https://www.bioversityinternational.org/e-library/publications/detail/mainstreaming-agrobiodiversity-in-sustainable-food-systems/

https://www.bioversityinternational.org/fileadmin/user_upload/online_library/Mainstreaming_Agrobiodiversity/Mainstreaming_Agrobiodiversity_Sustainable_Food_Systems_WEB.pdf

https://www.bioversityinternational.org/fileadmin/user_upload/online_library/Mainstreaming_Agrobiodiversity/Mainstreaming_Agrobiodiversity_Sustainable_Food_Systems_WEB.pdf

https://www.bioversityinternational.org/fileadmin/user_upload/AA_Publications/Methodology_Index_1.pdf)


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impact on agrobiodiversity and help them understand how to make the most of it. The plan is to apply the index to a set of

companies by the end of 2019. Current position:

• In 2019, the team applied the Agrobiodiversity Index to a first sample of 10 countries and produced the Agrobiodiversity index

report 2019: Risk and resilience (https://cgspace.cgiar.org/handle/10568/100820). The ten profiles span across all major

continents and cover a large diversity of agro-ecological and socio-economic settings. Results show that agrobiodiversity is highly

present across the pilot countries, and that there is great potential to better manage and conserve it for it to contribute to more

sustainable and resilient food systems. More developed countries tend to do better in terms of current status score, but emerging

economies are performing better in terms of future commitments and actions.

• Country profiles are currently being presented and discussed with country governments. In fact, the aim of the Index is to aims to

stimulate dialogue and exchange on how to better integrate agrobiodiversity into diets, production and genetic resource

management to achieve sustainable and resilient food systems, from local to global, and encourage a ‘race to the top’.

• Learning from the current applications of the Agrobiodiversity Index to countries (and later companies) will allow us to enhance the

framework and will provide incentives to those measured to give us access to key data that can improve the results over time.

Feedback will be used to further upgrade the tool and the country profiles and to expand the application of the Index to other

countries.

• Together with the report, Bioversity International has also launched the Agrobiodiversity Index online portal available at:

https://www.agrobiodiversityindex.org/

• As mentioned above, we are now in the process of adapting the methodology to company applications.

4.Business applications

➢ Complete table ‘Categories of Business Applications’ ➢ Add short summary in the style below, highlighting not only the BA that are supported by the tool but also

those not supported by the tool and the reasons why!

Today, global food production is the single largest driver of environmental degradation and biodiversity loss. Rising global food demand and limited arable land are pushing us to expand agricultural frontiers and increase production. This often happens without regard to the environment, causing biodiversity loss, and land and water degradation.

Climate change is also a major cause of biodiversity loss. Higher temperatures are already disrupting pollination and natural pest control, affecting the quality of food. In many of the poorest regions of the world, climate change will reduce crop yields and increase the incidence of animal diseases, leading to higher food prices – up to even 84% by 2050 – and food insecurity for farmers.

At the same time, the need to feed an additional 2 billion people by 2050 is tempting us to increase yields of a few staple foods, which in turn is eroding food diversity and genetic resources. Today, of the 6,000 plant species cultivated for food, fewer than 200 make major contributions to food production globally, regionally or nationally. Only nine of these plants account for 66% of total crop production. Livestock and fish biodiversity are also at stake. Of the 7,745 local breeds of livestock still in existence, 26% risk extinction. In addition, nearly a third of fish stocks are overfished and a third of freshwater fish species assessed are considered threatened.

https://cgspace.cgiar.org/handle/10568/100820

https://www.agrobiodiversityindex.org/


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Biodiversity loss in our food systems leaves farmers with fewer options to deal with risks of crop failure, declining soil fertility or increasingly variable weather. This is already causing production losses, increasing food insecurity and malnutrition. Today, more than 820 million people still suffer from hunger, and many more consume an unhealthy diet that contributes to premature death and disease, with about 2 billion people lacking one or more essential micronutrients and just under 2 billion obese or overweight (sometimes the same people).

The way we produce and consume our food is clearly hurting both people and the planet. Business as usual is not working and it is time for a paradigm shift. What we need is to be able to produce and consume more diverse and nutritious foods while having minimal impact on the environment, promoting a sustainable food system. This calls upon all of us, from governments to producers and consumers, to prioritize biodiversity and support actions that protect, foster and mainstream it.

Agricultural biodiversity is essential for building sustainable and resilient food systems. Agrobiodiversity – the wealth of plants, animals and microorganisms used for food and agriculture – boosts productivity and nutrition quality, increases soil and water quality, and reduces the need for synthetic fertilizers. It also makes farmers’ livelihoods more resilient, reducing yield losses due to climate change and pest damage. Broadening the types of cultivated plants is also good for the environment, increasing the abundance of pollinators and beneficial soil organisms, and reducing the risk of pest epidemics.

Today, the importance of biodiversity for food and agriculture is widely recognized at the global level. From the 2030 Agenda for Sustainable Development, to the United Nations Framework Convention on Climate Change and its Paris Agreement, the United Nations Convention on Biological Diversity and the United Nations Convention to Combat Desertification, all the main international agreements embed considerations on the role of biodiversity in addressing today’s global challenges. International development frameworks are essential to guide and align our actions to conserve and sustainably use biodiversity. However, on their own political commitments are not enough.

To sustainably use and conserve biodiversity in food and agriculture, we need to go the extra mile. Governments will need to initiate dedicated, multisectoral and evidence-based policies and interventions that integrate agrobiodiversity as a strategy to address today’s global challenges. Public–private partnerships will also be needed. From smallholder farmers to multinational companies, food producers are becoming increasingly important in conserving genetic resources and adopting sustainable agricultural practices. Consumers will need to become more aware of the impact of their food choices on the planet and their role in preserving the environment.

What actions do we need to put in place to make change happen? To answer this question, we need to be able to measure biodiversity in food systems. While decades of efforts have advanced our understanding of sustainable food systems, agrobiodiversity data remain uneven and oftentimes information is analyzed from sectoral perspectives (e.g. production, consumption or conservation). To transform food systems, we need to look at the broader picture and understand the systemic linkages between biodiversity, food security and nutrition, agricultural production, and the environment. While evidence shows the potential of agrobiodiversity for resilient and sustainable food systems, translation of this knowledge into policy and investment decisions has been tenuous. One of the reasons is multiple ways of measuring agrobiodiversity for multiple goals.


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To address this, Bioversity International has developed the Agrobiodiversity Index, an innovative tool that, crossing disciplinary boundaries, brings together existing measures and data on diets and markets, production and genetic resources, analyzing them under the lens of agricultural biodiversity for multiple goals. By accessing open data on food and agriculture, the tool allows biodiversity trends in food systems to be understood and monitored. In particular, it helps food systems actors to measure agrobiodiversity in selected areas or value chains, and understand to what extent their commitments and actions are contributing to its sustainable use and conservation. The Agrobiodiversity Index equips food system actors, including businesses, with the data needed to make informed decisions to achieve sustainability and resilience. The Agrobiodiversity Index in different ways. First, it assesses risks in food and agriculture related to low agrobiodiversity. Based on the Index results, food systems actors can understand how much they can build resilience for six risk areas by leveraging agrobiodiversity: malnutrition, poverty trap, climate change and variability, land degradation, pests and diseases, and biodiversity loss. Second, food systems actors can use the information generated through the Index to plan interventions and formulate evidence-based strategies and actions that address efficiently today’s global challenges – including malnutrition, climate change and natural resource degradation. Despite its importance, the majority of the interactions between biodiversity, ecosystem services and the agricultural sector are often invisible in established information systems – including food and agricultural trade, markets and supply and demand quantities and respective prices. The Agrobiodiversity Index addresses this information gap and makes these interactions more visible. This information will, therefore, constitute solid policy and management guidance to decision-makers. The tool provides insights into how biodiversity, at every level from genetic to ecosystem, is a driver that influences food systems sustainability and, as such, how it needs to be considered and integrated into national and regional environmental, agricultural, health and food research infrastructure, strategies and policies. Third, the Agrobiodiversity Index results allow company’s performance related to use and conservation of agrobiodiversity to be compared. This can stimulate positive competition to improve performance related to maintaining and enhancing agrobiodiversity, a race to the top. In addition, the Agrobiodiversity Index can help monitor company’s contribution to the global development goals and targets related to agricultural agrobiodiversity. The 2030 Development Agenda makes an ambitious call for a transformation in food and agriculture systems: it insists on an integrated and holistic approach to sustainable use of natural resources, including natural capital, biodiversity and ecosystem services. The Agrobiodiversity Index supports progress towards Sustainable Development Goals 3, 12, 13 and 15 and Aichi Biodiversity Targets 7 and 13. Last but not least, the Agrobiodiversity Index can help leverage investments for sustainable and resilient food systems. With almost US$162.5 billion in green bonds issued in 2017, the world is getting serious about protecting and preserving our planet. Food systems actors can apply the Agrobiodiversity Index to demonstrate the value for money of their agrobiodiversity-themed green bonds. In particular, green bond issuers can use the Index to produce a baseline assessment of the status of agrobiodiversity in specific areas where they plan to implement an intervention financed through the bonds and to monitor progress once the intervention is implemented.

5.Business sectors ➢ Describe business sectors covered by the tool

• Food and agriculture, from producers to consumers


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6.Key features of methodology

➢ Provide concise but clear description of the methodology. Please be aware that we will add separate sections in the

new update report on Globio and ReCiPe, so if your tool is making use of these models, you only need to make a brief

reference to them. The Agrobiodiversity Index is an innovative tool that helps measure agrobiodiversity and identify concrete actions to help achieve diverse, sustainable and resilient food systems. In measuring agrobiodiversity, we look at its potential contribution to healthy diets, sustainable agriculture and genetic resource management for future options. These constitute the three pillars of the Index. The Agrobiodiversity Index measures:

• Status - the current state of agrobiodiversity in markets and consumption, in agricultural production, and in genetic resource

management, looking at diversity in terms of species, varieties, functions, soil biodiversity and landscape complexity. i

• Progress - the extent to which commitments and actions at national level support sustainable use and conservation of

agrobiodiversity for healthy diets, sustainable agriculture and future options.

It does so by bringing together existing data, reports and policies, on markets and consumption, production and genetic resource management, analyzing them through the lens of agrobiodiversity:

• Status indicators are scored based on spatially explicit global data sets (such as those in Collect Earth and Earth Map) and

national data sets (mainly accessed through global databases at United Nations agencies). Seven types of Status indicators

(including 15 indicators):

✓ Type 1 - Varietal diversity: The number of varieties within a specific species. This indicator applies to each of the pillars

as the number of varieties of the main species available in the targeted food basket (Pillar 1), production system (Pillar 2)

or genetic resource system (Pillar 3). Depending on data availability, varietal diversity can be measured at two scales (local

and total) in order to consider alpha, beta and gamma varietal diversity. (Box 2.1). (3 indicators)

✓ Type 2 - Species diversity: The diversity of biological species. This indicator applies to each of the pillars as the diversity

available in the targeted food basket (Pillar 1), the production system (Pillar 2) or genetic resource system (Pillar 3).

Depending on data availability, species diversity can be measured at two scales (local and total) in order to consider alpha,

beta and gamma species diversity. (3 indicators)

✓ Type 3 - Functional diversity: Currently this is focused only on the diversity of nutritional functional groups, based on

nutritional composition and quantity of the species available in the targeted food basket (Pillar 1), production system (Pillar

2) or genetic resource system (Pillar 3). In future, the aim is also to consider other functions, such as nitrogen fixation and

water-holding capacity. Depending on data availability, functional diversity can be measured at two scales (local and total)

in order to consider alpha, beta and gamma species diversity. (3 indicators)

✓ Type 4 - Local or underutilized species: The proportion of underutilized local species in the total energy supply (kcal)

(Pillar 1), production area (Pillar 2), or number of samples in genebanks and occurrence data from herbaria (Pillar 3). As

underutilized local species, we currently consider species that can grow naturally under local conditions and that differ from

the top 15 globally produced species, i.e. the ‘global’ grains (rice, wheat, maize), the ‘global’ tubers and plantains (Irish

potatoes, sweet potatoes, plantains), the ‘global’ sugar and oil crops (sugarcane, oil palm), ‘global’ fruits and vegetables

(tomatoes, onions, bananas, melons), and the ‘global’ animal products (beef, pork, chicken). (3 indicators)


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✓ Type 5 - Pollinator diversity: The pollinator diversity index developed by the PREDICTS (Projecting Responses of

Ecological Diversity in Changing Terrestrial Systems) team. This index describes the estimated level of pollinator diversity,

based on land use, habitat cover and land use intensity and is only applicable to Pillar 2. (1 indicator)

✓ Type 6 - Soil biodiversity: The soil biodiversity index developed by the Global Soil Biodiversity Atlas. This index describes

the potential level of diversity living in the targeted soils, based on the distribution of microbial soil carbon as a proxy for soil

microbial diversity [7], and the distribution of the main groups of soil macrofauna soil macro fauna (unpublished data,

Mathieu), as a proxy for soil fauna diversity. This indicator applies only to Pillar 2. (1 indicator)

✓ Type 7 - Landscape complexity: Habitat diversity, calculated using ecosystem unit and land use and cover data (Pillar 2).

Landscape heterogeneity helps to maintain species diversity [8] and thus conservation of wild crop relatives, pollinators

and natural pest and disease controls which directly or indirectly support the maintenance of agrobiodiversity. This indicator

applies only to Pillar 2. (1 indicator)

Examples of Data sources used as input for status scoring include spatial datasets and country/company documents, reports,

databases. The Status indicators are based on spatially explicit globally available datasets. To populate values for these

indicators, we create a boundary around the area under analysis (i.e. the country or project area). This works well for countries,

defined by national boundaries, and for projects when the intervention extent can be clearly defined.

For companies, Status indicators cannot be calculated at present because data on the spatial footprint of a company (e.g.

extent of all farms in its supply chain, or locations of all its consumers) is not readily available. Initial work in consultation with

external scientific advisors led to identification of a long-list of desirable indicators for monitoring the status of agrobiodiversity

conservation and use. No datasets were identified for several of the indicators, highlighting a shortage of information and data

on agrobiodiversity, particularly at the variety and local level and for the healthy diets pillar (Pillar 1). Filling these data gaps is

an aim of the next stage of the Index.

To calculate diversity values, we use the Gini-Simpson index where possible. The Gini-Simpson index represents the

probability that the two randomly taken individuals correspond to different units of measurement (i.e. species, varieties or food

groups). For two indicators, we use the Shannon’s diversity index because pre-calculated diversity values were used, namely

for ‘Species diversity’ under Pillar 1 and Pillar 2.

Action indicators focus on what countries, companies, or projects are actually doing to increase agrobiodiversity across the

food system. It shows where countries, companies or projects put policies into action to achieve what they committed to.

Four Action indicators are included:

✓ Action Indicator 1 - Consumption and market management practices supporting the use and conservation of

agrobiodiversity (Pillar 1)

✓ Action Indicator 2 - Production management practices supporting the use and conservation of agrobiodiversity (Pillar

2)

✓ Action Indicator 3 - Production diversity based practices (Pillar 2)


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✓ Action Indicator 4 - Genetic resource management practices supporting the use and conservation of agrobiodiversity

(Pillar 3).

For countries, Action indicators are measured using spatially explicit, globally available datasets. An online search was

conducted to identify globally and readily accessible spatial datasets that can be used as direct or proxy measures of

implementation of each practice. At present, 14 global datasets are used to monitor actions, including data from the Food and

Agriculture Organization, the Organisation for Economic Co-operation and Development (OECD), the World Agroforestry

Centre, Bioversity International and academic journals.

For companies and projects, the Index uses publicly available information provided by active programmes, annual reports and

press releases, as well as scores-stored in collaborating indices (e.g. agrobiodiversity relevant indicators within the Access to

Seeds Index). These are complemented where feasible with information obtained directly from the project team through

completion of a questionnaire.

• Commitment indicators measure the country, company or project values, strategies, policies and codes of conduct for

improving the management of and enabling the potential of agrobiodiversity for healthy diets, sustainable agriculture and for

future use options. The country, company or project receives more credit for commitments that have a specific agrobiodiversity

strategy and measurable target.

Three Commitment indicators are included in the Index:

✓ Commitment Indicator 1 - Level of commitment to enhancing agrobiodiversity in consumption and markets for healthy

diets (Pillar 1)

✓ Commitment Indicator 2 - Level of commitment to enhancing production and maintenance of agrobiodiversity for

sustainable agriculture (Pillar 2)

✓ Commitment Indicator 3 - Level of commitment to enhancing agrobiodiversity genetic resource management for

current and future use options (Pillar 3) Commitments are assessed though a text-mining tool that analyses countries, companies, and project-related documents. For countries: The main data sources for Commitment indicators are two major United Nations databases, covering nutrition policies (the Global database on the Implementation of Nutrition Action GINA) and food and agriculture policies and legislation (FAOLEX). For companies and projects: The data sources are strategies, policies and reports downloaded from the official website of the company (e.g. sustainability and corporate responsibility reports, annual reports, guidelines) The documents collected are used as inputs to the text mining script, designed to search for occurrences of keywords related to each indicator. Clauses are extracted where keywords or phrases appear. For each occurrence, the sentences directly preceding, succeeding and containing the keyword are extracted and stored in a spreadsheet.

Taken together, currently 64 measurements feed into 22 indicators, comprising 3 commitment indicators, 4 action indicators, 15 status indicators. The indicators are aggregated by pillar (healthy diets, sustainable agriculture, and genetic resource management for future options) to calculate the overall status score (based on the status indicators) and the progress score (based on actions and commitments). The full version the Agrobiodiversity Index methodology 1.0 is available at: https://www.bioversityinternational.org/fileadmin/user_upload/AA_Publications/Methodology_Index_1.pdf

https://www.bioversityinternational.org/fileadmin/user_upload/AA_Publications/Methodology_Index_1.pdf


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7.Additional features Baseline or reference

➢ Please describe if this is defined in the tool and how (be aware subgroup 2 is working on clear definitions but we just want to know how these terms are interpreted in your tool)

n/a

Materiality assessment

➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken

Impact boundaries

➢ Only for tools that cover site level and project level business applications: Please describe if the perimeter assessed in the tool is limited to the direct operations within the site controlled by the company? Or does it cover a wider area of influence?

Impacts and dependencies

➢ Please describe if the tool also addresses dependencies (see also question on ecosystem services below), and how.

Valuation

➢ Please describe: o if impacts are valued in a qualitative, quantitative or monetized way o if the valuation perspective is business value or societal value or both o monetization techniques if monetization is applied

8.Ecosystem services

➢ Please describe if the tool also covers ecosystem services, and if so, which ecosystem services and how they are assessed

9.Granularity level ➢ Please describe the range of granularity levels (in quantitative terms) that can be applied by the tool (if relevant for each of the different organisational focus areas referred to in the ‘Business applications’ table)

10.User friendliness ➢ Please describe: o if the tool is easy to use by non-experts or requires specialist knowledge o what time efforts are required to apply the tool o if the tool has similarities with tools for other environmental issues and if so, please describe o Indicate whether these are estimated or based on application of the methodology by the company

11.Sensitivity to management action

➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured


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12.External disclosure

➢ Please describe if the measurement approach has been designed to reflect external reporting requirements, if so, which and how

13.Policy targets ➢ Please describe if the measurement approach is designed to reflect or link into global targets on biodiversity e.g. Aichi targets or the SDGs and if so, how you envisage this link developing

As mentioned above, the Agrobiodiversity Index results allow company’s performance related to use and conservation of agrobiodiversity to be compared. This can stimulate positive competition to improve performance related to maintaining and enhancing agrobiodiversity, a race to the top. In addition, the Agrobiodiversity Index can help monitor company’s contribution to the global development goals and targets related to agricultural agrobiodiversity. The 2030 Development Agenda makes an ambitious call for a transformation in food and agriculture systems: it insists on an integrated and holistic approach to sustainable use of natural resources, including natural capital, biodiversity and ecosystem services. The Agrobiodiversity Index supports progress towards Sustainable Development Goals 3, 12, 13 and 15 and Aichi Biodiversity Targets 7 and 13.

14.Strengths recognised by initiators

➢ Please describe the strengths of the tool according to your insights

1. EVIDENCE BASED The scientific foundations of the Agrobiodiversity Index are summarized in a peer-reviewed book. The

Index will integrate new knowledge about the role of agrobiodiversity in sustainable food systems as it emerges.

2. COMPLEMENTARY We build upon the work done by others and add value to existing initiatives and mechanisms.

3. FOCUS ON CONTRIBUTION The Agrobiodiversity Index clarifies and assesses the contributions that countries, companies

and projects can make through agrobiodiversity to food system sustainability.

4. TRANSPARENT The Agrobiodiversity Index is transparent about its methodology, development process, data sources and

outcomes. Countries, companies and projects understand how and why they are assessed in order to drive change and

engage decision-makers.

5. ITERATIVE Continual improvement is an iterative process. The cyclical nature of the Agrobiodiversity Index will provide users

with an incentive to improve and show progress and accountability over time.

6. INDEPENDENT AND IMPARTIAL The Agrobiodiversity Index realizes its role in convening stakeholders with divergent views

by being independent. The Index is equally responsive to all stakeholders and remains impartial.

7. RESPONSIVE Societal expectations evolve. The Index will respond by updating its methodology where necessary with each

successive iteration. Boundaries will be set to ensure comparability of information across iterations.

8. CONSULTATIVE: The influence of the Agrobiodiversity Index rests on its legitimacy and credibility. The methodology has been

developed in cooperation with a wide range of stakeholders. Thorough reviews by teams of recognized experts are an integral

part of the process.

15.Weaknesses recognised by initiators

➢ Please describe the weaknesses of the tool according to your insights

• Specific data gaps, particularly varietal diversity – identified as a critical aspect to make progress on.

• The limited quality or resolution of some secondary databases – identified as a critical aspect to make progress on.


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• The aggregated ABD Index can be presented and communicated in a relatively simple way but the underlying measurements

and indicators are quite complex.

16.Next steps for the tool

➢ Please describe planned improvements

The Agrobiodiversity Index development and implementation takes a design approach. The tool will continue to evolve and improve, as more information, datasets and analytical work can be undertaken. For example, we will integrate data and analyses from Bioversity’s Alliance partner, the International Center for Tropical Agriculture, to enhance the Index robustness and resolution. Learning from the current applications of the Agrobiodiversity Index to countries (and later companies) will allow us to enhance the framework and will provide incentives to those measured to give us access to key data that can improve the results over time. Feedback will be used to further upgrade the tool and the country profiles and to expand the application of the Index to other countries. We are currently looking at how Artificial intelligence can help accelerate and improve the scoring process, especially for Commitments, and how remote sensing can help fill some key data gaps, for expel varietal data.


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2. The Biological Diversity Protocol

FICHE NR 2 Biological Diversity Protocol (BD Protocol)


• First assessment submitted on 2 August 2019

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: Endangered Wildlife Trust (South Africa) Other: Many co-authors and contributors. Natural Capital Coalition hosting an online consultation process through Collaborase.



Business Applications!) and if case studies are available (please refer to links or publications) The BD Protocol is an output of the Biodiversity Disclosure Project (BDP), managed by the National Biodiversity and Business Network (NBBN) of South Africa and hosted by the Endangered Wildlife Trust (EWT). A concept document for the Biological Diversity Protocol was widely circulated in late 2018. A first comprehensive draft was produced in March 2019. EWT then launched a consultation process, including an online one hosted by the Natural Capital Coalition through Collaborase. The consultation process will officially end on August 15, 2019, after which all comments, questions and contributions will be collected, analysed and summarised in a stakeholder feedback report for public release in late 2019. The BD Protocol will then be revised accordingly for official publication at a later date, prior the 2020 CoP of the Convention on Biological Diversity which will be hosted by China. As part of this consultation process, any commentator may request to be recognised as a co-author or contributor to the BD Protocol. 2 case studies in the energy sectors are being undertaken. More are expected soon. URL: http://bdprotocol.org/


Complete table ‘Categories of Business Applications’ Add short summary in the style below, highlighting not only the BA that are supported by the tool but also those not supported by the tool and the reasons why! The BD Protocol helps business compile a biodiversity impact inventory – may be essential for various reasons, including:

• Responding to information requests from investors regarding your biodiversity risks and performance;

• Participating in a voluntary disclosure, reporting, certification or labelling programme;

• Implementing the impact mitigation hierarchy for a new project as per legal requirements;

• Public, client or other key stakeholder recognition for early biodiversity leadership. Building a comprehensive biodiversity impact inventory allows your company to assess and understand its biodiversity impacts, notably:

• Any potential biodiversity exposure or liability due to its negative impacts;

• Any potential biodiversity contribution to local, national or international targets due to its positive impacts. BD Protocol can be used over the three major parts of the value chain:

• Scope 1: Direct operations (gate-to-gate), which covers activities over which your business holds ownership or control.

• Scope 2: Upstream (cradle-to-gate), which covers the activities of suppliers;

https://collaborase.com/bdprotocol

http://www.bdprotocol.org/b

https://www.ewt.org.za/what-we-do/what-we-do-people/national-biodiversity-and-business-network/

https://www.ewt.org.za/what-we-do/what-we-do-people/national-biodiversity-and-business-network/

https://www.ewt.org.za/


http://bdprotocol.org/


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• Scope 3: Downstream (gate-to-grave), which covers activities linked to the purchase, use, re-use, recovery, recycling, and final

disposal of your business’ products and services. It thus enables corporate level assessments, can include supply chain aspects. It is based on data (land cover, species) from individual sites which is consolidated at the business level. Two main types of biodiversity components are recognised by the BD Protocol: land cover types (i.e. habitat, ecosystem or vegetation type, as recognised by applicable laws or authorities) and taxa (i.e. species, sub-species). Once the inventory boundary of the biodiversity impact assessment has been established, the BD Protocol prescribes that the inventory accounts and records biodiversity impacts as changes in:

• The extent and condition of land cover (i.e. impacts on vegetation, habitats or ecosystems13) as appropriate, given the concept

chosen by relevant legislations or authorities;

• The population size and viability of taxa.


• All sectors



new update report on Globio and ReCiPe, so if your tool is making use of these models, you only need to make a brief

reference to them. While various tools and approaches are already used by business to measure changes in biodiversity across their value chain, the lack of standardised, comparable, credible and unbiased methodology to help them consolidate and report their impacts on biodiversity needs to be addressed. This is why the Biological Diversity Protocol (BD Protocol) is being developed in close collaboration with a wide range of stakeholders through an online consultation process. The BD Protocol is designed as a comprehensive biological diversity accounting and reporting framework that can help you produce the credible and unbiased information needed for various biodiversity-related applications, from site management to disclosure. While the GHG Protocol Corporate Accounting and Reporting Standard was the benchmark standard for the vision and structure of the BD Protocol, the BD Protocol is aligned to the Natural Capital Protocol. It helps provide biodiversity-specific guidance to account for changes in the state of natural capital (step 6 of the Natural Capital Protocol), by providing guidance on how to account for change(s) in biodiversity components impacted by business. The BD Protocol includes guidance on how to:

• Develop and manage a biodiversity impact inventory according to the appropriate organisational and value chain boundaries;

• Identify and determine material biodiversity impacts;

• Assess impacts on biodiversity, considering the nature of the biodiversity components impacted;

• Account for net changes in biodiversity, in accordance with the mitigation hierarchy and the associated equivalency principle;

13 This does not specifically include transition areas between land cover types, also known as ecotones. In some cases, stakeholders may argue that ecotones should be included in your inventory due to the presence of key ecological features warranting their conservation.


https://naturalcapitalcoalition.org/natural-capital-protocol/


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• Apply the biodiversity accounting framework to build Statements of Biodiversity Position and Performance and account for biodiversity gains and losses over time;

• Validate and verify a biodiversity impact assessment;

• Disclose or report on an organisation’s impacts on biodiversity in a coherent and meaningful manner.



For any impact accounting framework to be able to present a complete and accurate representation of the net consequences of an organisation, it must be able to account for both periodic (e.g. annual) and historical (e.g. since the start of a business) performance. This is the case with financial accounting and reporting. The BD Protocol embraces an accounting framework that enables the measurement of net impacts over time. This involves the development of biodiversity accounts which record and allow the monitoring of both periodic and accumulated changes in biodiversity. The BD Protocol builds on the foundations of financial accounting and adopts two simple equations, also based on double entry accounting, which ensure that the biodiversity impacts of a company are equal to the sum of its positive and negative impacts. Accounting for biodiversity impacts thus revolves around the following equations:

• Statement of Biodiversity Position: (A) total biodiversity impacts (i.e. biodiversity assets or stocks) = (B) accumulated positive impacts + (C) accumulated negative impacts;

• Statement of Biodiversity Performance: (E) net biodiversity impacts over the accounting period = (F) periodic positive impacts or gains - (G) periodic negative impacts or losses.

Furthermore, the BD Protocol recommends that business accounts for all its impacts on land cover (i.e. the different ecosystems, habitats or vegetation types impacted), a relatively good (through imperfect) proxy of biodiversity status. When assessing the condition or quality of impacted land cover categories, it is worth emphasising the importance of making use of the most suitable (which often means local) biodiversity expertise. There may be different generally-accepted condition-scoring methodologies for different land cover types (e.g. unique methodologies for wetlands) and countries (reflecting both the spatial heterogeneity of biodiversity and different perceptions of nature). The BD Protocol requires using those which express the relative intactness of the target land cover type. This means assessing cover type against a reference or original “natural” state (i.e. without human impacts); which may not always be known or understood (e.g. Europe mostly holds transformed ecosystems so that experts may have limited knowledge of their original or reference condition or quality and may tend to overestimate the condition of land cover in largely transformed landscapes), hence the need to ensure transparency regarding the assumptions and estimations made. This is particularly important when monitoring changes in condition over time, for instance to ensure that the consequences of any management activity aimed at improving habitat quality or condition can be measured against a comparable baseline.


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Materiality assessment ➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken

In line with the Natural Capital Protocol, the BD Protocol defines an impact on biodiversity as material if consideration of its importance to internal and/or external stakeholders, as part of the set of information used for decision making, has the potential to alter that decision. A materiality assessment is the process that involves identifying what is (or is potentially) material in relation to the objective of providing a relevant, complete, consistent, transparent and accurate account of the biodiversity impacts of your company to its target stakeholders. The BD Protocol recommends that business accounts for:

• All its impacts on land cover (i.e. the different ecosystems, habitats or vegetation types impacted), a relatively good (through imperfect) proxy of biodiversity status, as it will enable the company to assess its biodiversity footprint, the headline key performance indicator for reporting or disclosure purposes;

• Only its impacts on taxa (species and sub-species) that are important to its internal and/or external stakeholders In other words, a materiality assessment should only be carried out for selecting which taxa are accounted for within your biodiversity impact inventory. This is due to the likely lack of adequate resources to obtain, record and maintain accurate information on the impacts of your business and its value chain on all species they interact with. The BD Protocol does not prescribe any method for assessing materiality, but instead underlines the importance of a generic, systematic and transparent process to assess what matters to your internal and/or external stakeholders. Most companies have experienced with at least one materiality assessment approach through their risk, governance, finance or strategy functions. This process may have involved using qualitative, quantitative or monetary information, or a combination of these. There are several criteria worth considering in order to determine whether a taxon should be included in your biodiversity impact inventory, including whether:

• The taxon is legally protected, according to local, national and international laws and conventions (e.g. listed by the Convention on International Trade in Endangered Species of Wild Fauna and Flora, CITIES);

• The taxon is recognised as a threatened species at a local, national or international level (e.g. species listed on an IUCN red list);

• Your business impacts on the taxon are likely to result in a change in its overall population or viability;

• The effective management (or lack thereof) of the taxon generates significant financial revenues (or receivables) and/or expenses (or liabilities);

• The taxon plays a critical role in the ecosystem, and can thus be defined as a keystone, umbrella or engineer species;

• The taxon plays a significant cultural or economic role (e.g. hunting, harvesting) for your stakeholders.

Impact boundaries


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The value chain boundaries of the BD Protocol defer significantly from the three scopes of the GHG Protocol. In line with the Natural Capital Protocol (Natural Capital Coalition 2016), the BD Protocol first recognises three major parts of the value chain:

• Scope 1: Direct operations (gate-to-gate), which covers activities over which your business holds ownership or control.

• Scope 2: Upstream (cradle-to-gate), which covers the activities of suppliers;

• Scope 3: Downstream (gate-to-grave), which covers activities linked to the purchase, use, re-use, recovery, recycling, and final disposal of your business’ products and services.

In addition, the BD Protocol distinguishes between direct and indirect impacts as follows:

• Scope 1 - Controlled operations (gate-to-gate):

• A: Direct biodiversity impacts;

• B: Indirect biodiversity impacts;

• Scope 2 - Upstream (cradle-to-gate):


• B: Indirect biodiversity impacts;

• Scope 3 - Downstream (gate-to-grave):


• B: Indirect biodiversity impacts.


➢ Please describe if the tool also addresses dependencies (see also question on ecosystem services below), and how. NO

Valuation


The BD Protocol recommends that your biodiversity impact report includes:

• Narratives about your company’s approach to managing biodiversity, notably: o your approach and targets with regards to implementing the impact mitigation hierarchy and


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o how biodiversity impacts affect value creation and other forms of capital within your organisation (i.e. integrated reporting perspective);

• Quantitative, non-monetary information about the scale of your biodiversity positive and negative impacts, across the selected value chain boundaries of your inventory.

First, both the Statement of Biodiversity Position and Statement of Biodiversity Performance of your business should be presented . While the former shows accumulated impact data, from the time of baseline assessments up to the time of reporting, the latter expresses periodic net impacts on biodiversity (e.g. your biodiversity performance over the past year). You may elect to also show previous Statements of Biodiversity Performance (i.e. previous periodic net impacts) for comparison and trend analysis purposes. Secondly, consolidated impact data should always be presented separately for each value chain boundary component or scope, to clearly distinguish between different levels of responsibility and control over impacts. Finally, it is critical to note that:

• Land cover data may be consolidated into three key performance indicators, your company’s total biodiversity footprint, its negative biodiversity footprint, and its positive biodiversity footprint;

• Impact data cannot be aggregated across taxa so that Statements of Taxa Position and Performance, when relevant for the given reporting or disclosure context, should be disclosed separately for each taxon.

The BD Protocol defines your company’s biodiversity footprint as the total land footprint of an organisation, which can be expressed in any surface area metric (e.g. hectares, square miles or square kilometres) and is made up of two components – the positive biodiversity footprint and the negative biodiversity footprint of the organisation – reflecting the land cover condition. The biodiversity footprint of a business is thus equal to the sum of all positive and negative impacts on land cover types within your inventory, that is the equation of the Statement of Land Cover Position. These positive and negative footprints should be expressed in an appropriate relative surface area indicator, such as hectare, square mile or square kilometre equivalents, while their respective share of total footprint may be shown as percentages.



NO


The BD Protocol allows business to choose its relevant scale for biodiversity impact accounting (ha, Km2), as appropriate for the business context.



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Biodiversity experts are required to understand how to assess biodiversity impacts. Accounting training would be required to use the double-entry bookkeeping approach. Because the BD Protocol aims to produce comprehensive impact data account for disclosure purposes, a transparent audit trail is key. It is similar to GHG accounting as per the GHG Protocol (impact inventory, audit).





The BD Protocol is an accounting framework which is compatible with some measurement approaches / tools, those that are based on primary / real impact data which can traced to GIS coordinates.


The BD Protocol can help business show progress with respect to Targets 5, 11 and 12 in particular.

Strategic Goal B: Reduce the direct pressures on biodiversity and promote sustainable use

Target 5

By 2020, the rate of loss of all natural habitats, including forests, is at least halved and where

feasible brought close to zero, and degradation and fragmentation is significantly reduced.

Strategic Goal C: To improve the status of biodiversity by safeguarding ecosystems, species and genetic

diversity

Target 11

By 2020, at least 17 per cent of terrestrial and inland water, and 10 per cent of coastal and

marine areas, especially areas of particular importance for biodiversity and ecosystem services,

are conserved through effectively and equitably managed, ecologically representative and well

connected systems of protected areas and other effective area-based conservation measures,

and integrated into the wider landscapes and seascapes.

Target 12

By 2020 the extinction of known threatened species has been prevented and their conservation

status, particularly of those most in decline, has been improved and sustained.


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o Accounting framework which enables the consolidation of site impact data at the company level o Can support biodiversity impact disclosure (CDP, GRI, integrated reporting) o Based on / aligned with mitigation hierarchy, NNL principles and permitting requirements; o Accounts for both accumulated and periodic net impacts: Statements of Biodiversity Position and Performance o No need for impact driver / pressure data => Focus on actual changes in biodiversity o Spatially explicit, which is based on actual land cover / taxa data and existing EIA assessments o Covers all industry sectors and all countries


➢ Please describe the weaknesses of the tool according to your insights o Requires primary impact data (time consuming, expansive) o Requires double-entry accounting knowledge / understanding


➢ Please describe planned improvements Version 1 planned for 2020 (consultation process now). Future plans not agreed upon yet.


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SPECIFIC INFORMATION ON DATA AND METRICS

The below information mainly serves to support the work of Subgroup 3 on data and metrics. For any clarification questions, please contact Joshua

Berger ([email protected]).

17.Methods and data on pressures, state and impact

➢ Please complete the following tables. These are intended to collect more insights on input data, midpoint indicators, impact pathway approaches etc. You can add additional info if you wish. Be aware that these tables also replace separate rows in the previous template: ‘type of modelling’, ‘drivers for biodiversity loss’ (now covered by impact groups), ‘data’.

Four tables are distinguished:

• Economic activity input data

• Biodiversity state input data

• Pressure input data

• Impact pathways The first 3 tables are about input data, i.e. specific data required by the tools to either conduct biodiversity impact assessments (“data inputs”) or to build impact factors. The 4th table is more about the dose-response relationships and the midpoints used, if any, to assess the impacts.

Table 1: Economic activity data inputs Economic activity indicator (unit) ((e.g. turnover of company, purchases in €, etc.)

Nomenclature used Data source (company or global data sets? if global data sets, which one?)

Real ( R) or Modelled data (M)? Confidence level of data

ADD ADDITIONAL INFO FOR YOUR TOOL:

Not relevant for BD Protocol

Table 2: Biodiversity state data inputs Biodiversity state indicator (unit)

Data input (DI) or used to build impact factors (IF)?

Nomenclature used Data source (company or global data sets? if global




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data sets, which one?)

Any surface area metrics, adjusted for condition, based on primary data (no modelling)

Use nationally accepted method

R

Population metric (amount or surface area-based metric_

Use taxon or nationally accepted method

R


Table 3: Pressure data inputs Pressure indicator (unit)



ADD ADDITIONAL INFO FOR YOUR TOOL: Not relevant

Table 4: Impact pathways and dose-response relationships Pressure on biodiversity (IPBES main drivers)

Dose-response relationships, impact pathways? Source?

Midpoints14 involved?

Confidence level of the dose- response relationships?

14 A point in the cause-effect chain (environmental mechanism) of a particular impact category, prior to the endpoint (e.g. measure expressed in the final unit such as PDF.m2.yr or MSA.m2), at which characterization factors can be calculated to reflect the relative importance of an emission or extraction in a Life Cycle


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Land / sea use change

Direct exploitation of organisms

Climate change

Pollution

Invasive alien species

Other

➢ Please list below all pressures (or direct drivers of biodiversity loss) which are covered (and those not covered) by your methodology:

Not relevant

18.Metrics ➢ Please describe the type of impact metrics applied by the tool ➢ If the tool does not use any synthetic metric, please describe briefly the specific metrics of each of its

components High level proxy indicator (at macro-economic level) The BD Protocol defines your company’s biodiversity footprint as the total land footprint of an organisation, which can be expressed in any surface area metric (e.g. hectares, square miles or square kilometres) and is made up of two components – the positive biodiversity footprint and the negative biodiversity footprint of the organisation – reflecting the land cover condition. The biodiversity footprint of a business is thus equal to the sum of all positive and negative impacts on land cover types within your inventory, that is the equation of the Statement of Land Cover Position. These positive and negative footprints should be expressed in an appropriate relative surface area indicator, such as hectare, square mile or square kilometre equivalents, while their respective share of total footprint may be shown as percentages.

19.Principles for metric

➢ Please describe principles if available Principles: The BD Protocol is based on seven accounting and reporting principles which are derived, in part, from the GHG Protocol and generally accepted financial accounting and reporting principles. These principles are intended to underpin all aspects of biodiversity impact accounting and reporting. Their application will ensure that the biodiversity impact inventory constitutes a credible and unbiased representation of the company’s biodiversity impacts. These accounting and reporting principles are defined as follows:

Inventory. Examples of midpoints (in a broad sense) for biodiversity impacts include for instance the global mean temperature increase (GMTI), water withdrawal and consumption, etc.


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• Relevance: Ensure the biodiversity impact inventory appropriately reflects the biodiversity impacts of the company and its

value chain. It shall serve the decision-making needs of users, both internal and external to the company.

• Equivalency: Ensure that the notion of equity in the type of biodiversity (i.e. ecological equivalency or like-for-like principle) is

integral to biodiversity impact inventory development and accounting. Undertake net impact accounting only for equivalent

biodiversity losses (negative impacts) and gains (positive impacts).

• Completeness: Account for and report on all biodiversity impacts within the chosen organisational and value chain

boundaries. Disclose and justify any exclusion.

• Consistency: Use consistent methodologies to allow for meaningful comparisons of biodiversity impacts over time.

Transparently document any changes to the data, inventory boundary, methods or any other relevant factors in the time

series.

• Transparency: Address all relevant issues in a factual and coherent manner, based on a clear audit trail. Disclose any

relevant assumptions and make appropriate references to the data collection and estimation methodologies used.

• Accuracy: Ensure that the measurement of biodiversity impacts is systematically accurate, as far as can be judged, notably

by reducing uncertainties as far as is practicable. Achieve suitable accuracy to enable users to make decisions with

reasonable assurance as to the integrity of the reported information. When no direct observation is possible, estimate impacts

on the basis that they are reasonably likely to occur, recording all methodological limitations.

• Time period assumption: Account for biodiversity impacts consistently across business reporting periods


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3. Biodiversity Footprint for Financial Institutions

FICHE NR 3 BIODIVERSITY FOOTPRINT FINANCIAL INSTITUTIONS (BFFI)

1. Date of assessment • Update by ASN Bank, CREM and PRé on 15 August 2019

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: ASN Bank (The Netherlands) Other: The methodology is co-developed with CREM (The Netherlands) and PRé Sustainability (The Netherlands)



Business Applications!) and if case studies are available (please refer to links or publications) Process

• ASN Bank launched the methodology in 2016 (not yet called BFFI at the time). The first footprint was conducted in 2016 and the

results were published in the associated report in August 2016.

• In 2017, a second report was published in which a footprint of the whole balance sheet is presented for the years 2014, 2015 &

2016. The methodology was adjusted with this second footprint, based on external and internal methodological updates and data

updates.

• In 2018, this updated footprinting methodology was used to assess the 2017 footprint of ASN Bank. Moreover, a common ground

for biodiversity footprinting for financial institutions was developed together with CDC Biodiversité, ACTIAM and Finance in

Motion.

• In 2018, the footprinting methodology is named ‘Biodiversity Footprint Financial Institutions’, BFFI.

• In 2018 and 2019, an approach to integrate biodiversity positive investments in the BFFI was developed (including some case

studies) and discussed during a workshop with financial institutions, footprinting experts and nature conservation organisations.

The report is published in September 2019.

• In 2019, the options to automatize a BFFI footprint is explored by ASN Bank and PRé Sustainability. Automisation will allow

financial institutions to calculate the biodiversity impact of investments with little or no expert support, using a user friendly

interface.

• Reports can be found at: https://www.asnbank.nl/over-asn-bank/duurzaamheid/biodiversiteit/biodiversity-in-2030.html Road testing and case studies

• The BFFI has been used by ASN Bank to calculate the footprint for 2014, 2015, 2016 and 2017.

• Case studies on integrating biodiversity-positive investments in the BFFI are included in the report ‘Positive impacts in the

Biodiversity Footprint Financial Institutions’ and a separate case-study report, both to be published in September 2019.



those not supported by the tool and the reasons why! Short summary:

• The BFFI is suitable for the following applications:

https://www.asnbank.nl/over-asn-bank/duurzaamheid/biodiversiteit/biodiversity-in-2030.html


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o Calculating the footprint of a financial asset portfolio as a basis for portfolio investment decisions by financial institutions, at the level of asset classes, sectors or companies (when enough company-specific data is available). The result is an analysis of biodiversity impact hot-spots within an investment portfolio, allowing a financial institution to focus biodiversity related actions (like the development of investment criteria) on the right asset classes and sectors.

o No Net Loss or Net Gain approaches by financial institutions, provided a baseline scenario is available to assess biodiversity losses and gains.

o The footprinting approach and underlying methodology, ReCiPe 2016, can also be used for corporate level assessments focusing on impacts in supply chains.

• The BFFI is not the most suitable for the following applications: o Assessments at site level and project level. Impacts at site and project level can be included in the BFFI but detailed

assessments taking into account location specific characteristics are better served with other assessment methodologies.

o Regulatory No Net Loss project assessments (which usually require particular attention for endangered and protected species).

Due to: o The fact that the BFFI and underlying ReCiPe methodology are limited in taking into account location specific

characteristics. o The fact that the BFFI and underlying ReCiPe are not species specific and only to a limited extent habitat specific.


• The financial sector: Banks, Asset managers, Impact investors.



new update report on Globio and ReCiPe, so if your tool is making use of these models, you only need to make a

brief reference to them. The BFFI is designed to provide an overall biodiversity footprint of the economic activities a financial institution (FI) invests in. The quantitative methodology consists of 3 steps (see also the figure below): The first step is to create an overview of the economic activities the FI invests in. This step includes:

• A ‘definition’ of the activities of a company: what is the company producing (in what sectors is the company active?) and where does production take place?

• Decisions on the scope of the assessment, like the inclusion of supply chains of companies the FI invests in (included in the BFFI);

• A selection of the investments included in the assessment (all major investments of the FI)


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In the second step the environmental impact of the economic activities of the companies invested in is assessed. The environmental data in the ‘Exiobase’ input-output database (https://www.exiobase.eu/) is used to assess what land use, water use, emissions, etc. is linked to the economic activities of the companies. Exiobase takes into account world-wide trade flows between countries and between sectors. In the third step, the ReCiPe methodology is used to calculate the environmental footprint on a midpoint level (e.g. climate change resulting from CO2 emissions) and to calculate the resulting impact on ecosystem quality or biodiversity (endpoint level). This latter step is based on science based ‘dose-response‘ relations (e.g. the effect of a 1 degree temperature rise on biodiversity). This results in an impact on terrestrial biodiversity and an impact on aquatic biodiversity. The unit used to express the impact on biodiversity is PDF.ha.yr, the Potentially Disappeared Fraction of species per hectare (per cubic meter for aquatic biodiversity) per year. The result is then used to calculate the biodiversity footprint in m2 per Euro invested (for each investment category) and the total biodiversity footprint in m2 for all investments. A qualitative analysis is used to guide the interpretation and the use of the footprint results, looking at (among others) the limitations of the quantitative footprinting methodology and how to take these limitations into account in the use of the footprint and at the relations between the footprint results and (potential) investment decisions (what could the footprint result mean for the FI’s investment policy?).

Figure: The steps in the BFFI methodology, including the input of data and the questions answered in each step



https://www.exiobase.eu/


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• The baseline used to assess the biodiversity impact of economic activities (see step 2 in ‘key features of the methodology’) is

the same as the reference used by the ReCiPe methodology, which is a ‘pristine’ situation. The ‘pristine’ situation in this case

is the (biodiversity) situation without any economic activities taking place over a longer period of time.

• The baseline or reference in case biodiversity-positive investments are included in the footprint is the situation without the

investment taking place. This is a future situation for which data may not always be available. When such data are lacking,

the biodiversity situation preceding the investment will often be taken as second best data.


➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken The BFFI includes four steps which add to the materiality of the assessment:

• In the first step an analysis s made of all the main investments of the financial institution for which the footprint is conducted to maximise the probability that material impacts are covered.

• In the first step a decision is made on the scope of the impact assessment. In case of ASN bank, the decision has been made to include the supply chains (full scope 3) of the companies and organisations the bank invests in. In this way, the footprint provides a complete picture of the impacts that may be material to the financial institution (e.g. from the viewpoint of reputational risks) and which the financial institutions may be able to influence (directly or indirectly) through its investment policy.

• In the third step, key drivers for biodiversity loss are taken into account, including (among others) climate change, land occupation, land transformation and water use/scarcity. Impact drivers not included in the quantitative assessment, like the introduction of invasive species, are covered by the qualitative analysis (see the next bullet).

• In the qualitative analysis an assessment is made of the potential significance of impact drivers not covered by the quantitative impact assessment, thereby providing insight in the materiality of these impact drivers.

Impact boundaries


• Not applicable




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• The BFFI does not address dependencies, although the use of life cycle assessment data also shows to what extent production processes require inputs like land, water and (a)biotic resources.

Valuation


• The BFFI assesses impacts on biodiversity in a quantitative way (using the potentially disappeared fraction of species times hectare times year as a unit) and in a qualitative way by assessing the significance/materiality of impacts not covered by the quantitative assessment. Valuation of these impacts is not explicitly included, although some qualitative valuation may take place in the qualitative analysis supporting the interpretation of the footprint results (e.g. the business and societal value of addressing the impact hot spots identified).

8.Ecosystem services ➢ Please describe if the tool also covers ecosystem services, and if so, which ecosystem services and how they are assessed

• The BFFI does not address ecosystem services.

9.Granularity level ➢ Please describe the range of granularity levels (in quantitative terms) that can be applied by the tool (if relevant for each of the different organisational focus areas referred to in the ‘Business applications’ table) • The BFFI is best suited to determine the hot spots of biodiversity impact in the portfolio /balance sheet and the reasons

behind this impact.

• PM (PRé) (GBS: “The pressure-impact relationships become imprecise below areas of about 1000 ha.”)


Based on the footprint calculations for ASN Bank:


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• Using the results of the BFFI does not require specialist knowledge, although a basic knowledge of biodiversity impacts is

important to enable a correct interpretation of the footprint results and the potential consequences of these results for

investment (policy) related action.

• The footprint methodology itself is user friendly, but requires the use of impact calculation software fit to deal with the

(high number of) input data and the calculation of impacts based on the ReCiPe methodology. Depending on the level of

knowledge within the financial institution using the BFFI, expert input may be needed to stay informed of data and

methodology updates and to enable a correct interpretation of the footprint results.

• An impact assessment on a portfolio level takes a couple of weeks and mainly uses easily accessible (and existing) data.

This time may be reduced to a couple of days when automisation of the BFFI is successful (see next bullet).

• Until now, the most time consuming step has proven to be the first step in the BFFI methodology: linking investments to

clearly defined economic activities and sectors. The options to automise this step are currently explored. When

automisation of this step is possible and can be combined with the second step (environmental effects of the activities)

and third step (impact on biodiversity) of the BFFI in a single online tool, using the BFFI will become quite straightforward,

requiring little time and effort.

• Carbon footprinting data and results can be re-used as direct inputs into the BFFI. The approach is very similar, both in

terms of data collection and of concepts (e.g. scopes 1, 2 and 3, attribution of responsibilities across the value chain).

The same is true for other, life cycle assessment based assessments, like a water footprint.



• The BFFI uses country specific, sector-average data from Exiobase to calculate the environmental footprint on a midpoint

level and uses dose-response modelling to calculate the biodiversity footprint. No primary data (actual data from the

companies invested in) are used in this step. This means that the BFFI is not yet sensitive to corporate action (apart from

the fact that corporate action will find its way into the country-specific sector averages, used by Exiobase.

• A first step is currently considered for the BFFI to become more sensitive to corporate action: adjusting the footprint score

for the use of biodiversity relevant, independent standards and certifications (like FSC or RSPO).

• Please note that the underlying ReCiPe methodology does allows for the use of direct data, but this is not considered to

be feasible on the level of an investment portfolio, the primary focus of the BFFI.

12.External disclosure ➢ Please describe if the measurement approach has been designed to reflect external reporting requirements, if so, which and how

• The BFFI has not been designed to reflect external reporting requirements. This may change if biodiversity reporting

requirements for financial institutions are introduced.



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• The BFFI has not been designed to reflect or link into global targets on biodiversity. However, a financial institution can link the footprint result to references like the Aichi targets and SDGs to decide on the steps following the footprint.


o Please describe the strengths of the tool according to your insights • Scientifically well underpinned

• Use of open source and free database (no black box calculations)

• The Exiobase input/output model shows trade flows between countries and sectors and therefore allows for a geographical identification of impact hot spots on a country level

• Supported by range of stakeholders (including government, knowledge institutes and NGOs) after stakeholder consultations

• Covers most drivers for biodiversity loss

• Location/region specific data can be used when they are/become available

• Scalable to be used by other banks

• The ReCiPe methodology takes into account pollution (besides nutrient load and other impact drivers)

• The complementary qualitative analysis complements the calculations and guides correct interpretation and use


➢ Please describe the weaknesses of the tool according to your insights • Exiobase limitation (use of sector average data). This weakness is expected to improve and change in time when better data

will become available.

• Land-use related impacts are biased to temperate regions which means that land-use related impacts will be less accurate for tropical regions.

• Inclusion of location specific characteristics is limited, limiting the methodology’s fitness for use on a project level. On a portfolio level, with the aim of identifying biodiversity impact hot spots, this limitation is fine.

• Not all drivers of the loss of biodiversity are covered by the ReCiPe methodology. For example, the introduction of invasive species and overexploitation are not covered. This limitation is addressed by means of a complementary qualitative analysis, analysing the significance of this limitation and what this means for the interpretation of results.


➢ Please describe planned improvements • Further improvement of the sensitivity to corporate action by integrating biodiversity-positive investments in the BFFI and

introducing footprint correction factors for biodiversity relevant, independent certification/standardization.

• Automisation of the BFFI steps and development of a user friendly interface, enabling financial institutions to conduct their own impact calculations.



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ADD ADDITIONAL INFO FOR YOUR TOOL: With regard to modelling a hybrid approach is applied. Modelled results of GLOBIO are used to estimate average industry pressures (and impacts) when real data are not available (= ‘default assessment’). When real data on pressures are available, they are instead combined to the pressure-impact relationships provided by GLOBIO to conduct a ‘refined assessment’. At each stage, the best available data are used, with a preference for real data over modelled average values. The GBS can work with different datasets listed below, by increasing order of usefulness in terms of the precision that can be expected from assessments:

• Economic activity data: turnover by country and industry (of the company assessed or of the company a financial institution invested in);

• Pressure data: - Carbon emissions on scope 1, 2 and 3 - Land use changes (ideally using a 13 habitat types nomenclature including different use intensity for forests, grasslands, agriculture, etc.)

• Comprehensive biodiversity direct data: when very detailed ecological monitoring data are available, the mean species abundance might be directly calculated.

Table 4: Impact pathways and dose-response relationships


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Pressure on biodiversity (IPBES main drivers)






Climate change

Pollution


Other


Drivers (GLOBIO) include: land conversion, fragmentation, encroachment, atmospheric N deposition (eutrophication) and climate change for terrestrial biodiversity, and wetlands conversion, local and network land-use in catchment of wetlands, hydrological disturbance of wetlands and rivers, land-use in catchment of rivers and eutrophication of lakes for aquatic biodiversity. Missing drivers will be added to GLOBIO through future developments.


components High level proxy indicator (at macro-economic level) GBS uses mean species abundance (MSA) and its surface area equivalent, i.e., km² MSA. The latter is the product of MSA multiplied by the area to which it applies (expressed in km²). MSA measures biodiversity intactness relative to its abundance in undisturbed ecosystems. A 100% ratio indicates an intact ecosystem while damages caused by an increase of pressures bring the MSA progressively to 0% when all originally occurring species are extinct in the ecosystem.


➢ Please describe principles if available Principles:

15 A point in the cause-effect chain (environmental mechanism) of a particular impact category, prior to the endpoint (e.g. measure expressed in the final unit such as PDF.m2.yr or MSA.m2), at which characterization factors can be calculated to reflect the relative importance of an emission or extraction in a Life Cycle Inventory. Examples of midpoints (in a broad sense) for biodiversity impacts include for instance the global mean temperature increase (GMTI), water withdrawal and consumption, etc.


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• Quantitative (‘a number’)

• Entire value chain coverage

• Concise (‘which is good for communication purposes’)

• Measures intrinsic biodiversity value (not ES, but is assumed that ES flourish when intrinsic values are OK)

• Consensual (developed with and accepted by scientists, NGOs, businesses)

• Complement and be compatible with local indicators

➢


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4. Biodiversity Indicators for Extractives

FICHE NR 4 BIODIVERSITY INDICATORS FOR EXTRACTIVES

1. Date of assessment • First assessment by UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) on 2nd April 2018

• Updates on 15th July 2018 and 21st August 2018

• New assessment by UNEP-WCMC on 14th August 2019

2.Actors Lead: UNEP-WCMC, Conservation International, and Fauna & Flora International Other: With support from IPIECA and the Proteus Partnership An advisory group of IPIECA, Netherlands Enterprise Agency, ICMM, CDC Biodiversité, The Biodiversity Consultancy, BP, Natural Capital Coalition, Oxford University, CDP, Fairfield Consulting and Stuart Anstee and Associates



Business Applications!) and if case studies are available (please refer to links or publications) UNEP-WCMC initiated the Biodiversity Indicators for Extractives project in March 2017. Phase 1 determined the needs and current practices of the sector, through desk reviews and interviews with industry representatives. The key findings of Phase 1 highlighted two potential models to take forward for further methodological development and piloting: • A single composite indicator • A framework approach For a detailed description of the findings of phase 1, please find the report here. Phase 2 of the project was conducted throughout 2018. A shortlist of suitable methodologies, that fit the models described above, was created and explored with industry representatives at a half day workshop. Participants highlighted that a single metric may not provide the necessary resolution, flexibility or information to meet the indicator needs of the extractives sector. Current data gaps and lack of comparability may in the short-term render a single indicator challenging. Learning from Greenhouse Gas reporting, a tiered approach, incorporating high-level screening of all sites within a portfolio followed by the development of indicators for “high-risk” sites using a Pressure-State-Response model, was recognised as a potential first step in the development of improved biodiversity indicators for the extractives sector which would draw from existing methodologies and both globally compiled data and site-level company data. The draft methodology was presented to corporate representatives and indicator experts in the annual Proteus Partnership meeting in June 2018 and at the IPIECA Biodiversity and Ecosystem Services Working Group meeting in September 2018. Feedback on the draft methodology was positive with a number of companies expressing a willingness to pilot test the methodology. In 2019, the draft methodology is now in a piloting phase with 7 companies from across the extractives sector applying the methodology to a range of projects, both marine and terrestrial and spanning the project lifecycle, from projects at the pre-construction phase to long-running operations. Piloting will be completed and a finalised methodology published at the end of 2019.

https://wcmc.io/Biodiversity_indicators_for_extractive_companies_report


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4. Business applications

The Biodiversity Indicators for Extractives methodology can support the following business applications: • Assessing and monitoring progress of biodiversity risks at project, site and corporate level • Comparing options at project and site level • Applying a No Net Loss or Net Gain approach at project, site and corporate level (establishing baselines and monitoring progress) • Communication and reporting (e.g. compliance with GRI reporting) • FIs can compare biodiversity risk of companies within the extractives sector The methodology is best suited for project or site level assessments of biodiversity impact and performance. This can then be aggregated to corporate level to inform wider decision-making. The methodology is not suitable for the following applications:

• Assessments by third parties based on external data only.

5.Business sectors

• Extractives sector primarily, however there is also potential for the methodology to be applied to other sectors which have large physical footprints and direct impacts on biodiversity at a site-level. This will be explored further following the piloting phase.


The methodology follows a three stage process (see Figure 1):

Figure 1: Process for site prioritization and biodiversity indicator development


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• First stage: screening of the company’s portfolio of operations to identify sites with potentially high biodiversity sensitivity, based on global datasets (World Database of Protected Areas, IUCN Red List, Critical Habitat Screening layer) accessed via IBAT. This is combined with validation by site managers to identify sensitive sites for prioritisation of reporting effort;

• Second stage: development of site level biodiversity indicators using a state-pressure-response (SPR) framework (a widely accepted organizing framework for biodiversity management and monitoring based on BirdLife’s framework for monitoring Important Bird Areas). Priority biodiversity features are identified informed by the first stage above but based on site level data and documentation for high sensitivity habitats and species. Relevant pressures and company responses are then attributed to these features and then scored against framework thresholds;

• Third stage: aggregation of scores for SPR at site level up to business unit, division, and corporate level to provide insight into performance on the ground.

7.Additional features Baseline or reference A baseline is required for the calculation of the state of each priority biodiversity feature identified. This baseline is taken from the pre-project state, which is identified from existing site documentation (e.g. baseline study of Environmental Impact Assessments).

Materiality assessment Global screening stage incorporates materiality by prioritizing sites where a company’s activities may pose higher risk to biodiversity. Materiality is then further considered when selecting priority biodiversity features from candidates identified from the global screening stage and site level documentation. This includes consideration for the likely impacts company activities could have upon the biodiversity feature.

Impact boundaries The methodology considers impacts within the physical footprint of the site, as well as the sites Area of Influence. During the global screening stage, Area of Influence is set at 50km (the maximum reporting buffer in IBAT). This is then refined with site-level managers to provide a tailored Area of Influence for the second stage. Please note that this may lead to either a reduction or increase of the Area of Influence.

Impacts and dependencies The tool does not explicitly account for dependencies on biodiversity. There are potential links between State and Pressure on the business (as opposed to on the biodiversity feature itself), but these have not been explored to date.

Valuation State, Pressure, and Response are valued separately.

https://protectedplanet.net/

https://www.iucnredlist.org/

https://data.unep-wcmc.org/datasets/44

https://data.unep-wcmc.org/datasets/44

https://ibat-alliance.org/

http://datazone.birdlife.org/userfiles/file/IBAs/MonitoringPDFs/IBA_Monitoring_Framework.pdf


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➢ State is valued quantitatively based on the percentage remaining of a biodiversity feature compared to the pre-project baseline. This may be either percentage of population or percentage of habitat extent depending on the nature of the biodiversity feature.

➢ Pressure is valued quasi-quantitatively using categories for the scope, severity and timing of pressures on the biodiversity feature.

➢ Response is valued quasi-quantitatively using category scores linked to the planning and implementation of actions in line with the mitigation hierarchy.

8.Ecosystem services Ecosystem services are not automatically considered by the methodology. However, depending on the priority biodiversity features selected, it is possible for them to be explicitly or implicitly incorporated.

9.Granularity level The methodology is best suited for project or site level assessments of biodiversity impact and performance. This can then be aggregated to corporate level to inform wider decision-making.


The tool requires a degree of specialist knowledge to identify appropriate priority biodiversity features. This process needs to be conducted once per site. Calculating State, Pressure and Response indicators does not require specialist knowledge and indicators can be calculated repeatedly over time without any additional knowledge. The initial application of the methodology takes approximately 1-3 months based on piloting to date. This involves identification of priority biodiversity features and a review of existing site-level documents and monitoring data to select appropriate metrics for State, Pressure and Response. Subsequent assessments are likely to take <1 week and involve a review of most recent monitoring data and documentation to update State, Pressure and Response indicators.


Corporate actions at the site-level will be directly reflected in the Response indicator.

12.External disclosure The methodology is primarily designed for internal reporting purposes. The possibility of adapting indicators to meet external reporting needs will be explored once piloting has been completed at the end of 2019.

13.Policy targets The methodology is designed for internal reporting, but can link to corporate contributions to Sustainable Development Goal targets, for example15.5 – “Take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity and, by 2020, protect and prevent the extinction of threatened species” by demonstrating improved performance of State and Response indicators coupled with a reduction in Pressure indicators.


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o Scientifically credible, building on existing tools such as IBAT and BirdLife’s Global Framework for Monitoring Important Bird Areas.

o Linked metrics for State, Pressure and Response allowing companies to track the results of increased response actions. o Flexible in nature to adapt to the most important and/or threatened biodiversity features at a site. o Applicable globally in both marine and terrestrial environments. o Focused at site-level data but able to aggregate to corporate level. o Does not require additional data collection. o Priority biodiversity features can capture all taxa as well as habitats.


o Accuracy of indicators is dependent on the quality of existing site-level company data. o Requires specialist knowledge to identify appropriate priority biodiversity features in order to avoid selecting

unrepresentative indicators.


Once the methodology has been piloted by 7 extractives companies, emerging issues will be addressed as part of the final methodology and published at the end of 2019. The next phase of the project will involve communicating the results and working to integrate the methodology within existing guidance.










• Impact pathways



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The first 3 tables are about input data, i.e. specific data required by the tools to either conduct biodiversity impact assessments (“data inputs”) or to build impact factors. The 4th table is more about the dose-response relationships and the midpoints used, if any, to assess the impacts.





Economic activity data are not used in this methodology. The activities occurring on site (e.g. oil exploration and production) are used to identify priority biodiversity features likely to be most impacted by company activities based on the IUCN Red List Threat Categories associated with the companies operations.





Percentage of baseline extent (habitat) or population (species) remaining

Data Input Existing site-level company data, for example Environmental Impact Assessments.

Real (but we are also exploring the possibility of using proxy/estimated data if real data is unavailable)



Nomenclature used Data source (company or global

Real ( R) or Modelled data (M)?


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data sets? if global data sets, which one?)

Confidence level of data

Pressures scored out of 27 based on a multiplicative aggregation of Scope (1-3), Severity (1-3) and Timing (1-3) of an impact

Existing site-level company data, for example Environmental Impact Assessments and Biodiversity Management Plans.

Real (but we are also exploring the possibility of using proxy/estimated data if real data is unavailable)








Climate change

Pollution


Other



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All pressures on biodiversity can be captured within the methodology but will depend on the priority biodiversity features selected and information available as part of existing site-level documentation. This will that the pressures considered by the indicator will be specifically related to the main pressures that have been identified as likely due to company activity (based on site level documentation such as an environmental impact assessment).


components State, Pressure and Response indicators are categorised into 3 levels Poor, Moderate, and Good, based on thresholds designed for quantitative (State) or quasi-quantitative (Pressure and Response) measures (e.g. percentage of habitat remaining).


➢ Please describe principles if available Indicator principles were defined during Phase 1 as part of an assessment of needs in the extractives sector for biodiversity indicators.

• Relevant – reflect biodiversity of the company and meet decision-making needs or users and stakeholders.

• Completeness – focus on material impacts but consider all impacts to identify these

• Comprehensible – simple, conceptually clear how the measures relates to the purpose

• Consistency – allows for meaningful comparison of impacts and mitigation activities over time.

• Credible – use technically robust and verifiable information, data and methods, responsive over the appropriate timeframe.

• Transparency – methodology and data should be documented with assumptions and limitations laid out.


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5. Biodiversity Impact Metric

FICHE NR 5 Biodiversity Impact Metric

1. Date of assessment • First assessment by CISL on 15 March 2018

• Update on 5 July 2019

2.Actors Lead: Cambridge Institute for Sustainability Leadership (CISL) Recent members of the Natural Capital Impact Group: Kering, ASDA, Mondi, Volac; Mars; The Crown Estate; Anglian Water; Yorkshire water; Primark; Thames Water Other: The Biodiversity Consultancy; UNEP World Conservation Monitoring Centre; various Cambridge academics; Imperial College London


The Natural Capital Impact Group is a global network of companies, working collaboratively, to determine how business strategies and operating practice can sustain the natural world and its resources. The Group has developed a biodiversity metric, recognizing that the largest impacts on biodiversity tend to occur in their upstream value chains, particularly on farms where raw materials are produced. The Biodiversity Impact Metric was developed in consultation with stakeholders in the conservation community including Birdlife International, UNEP WCMC, The Biodiversity Consultancy, Cambridge University and Imperial College London. Whilst all members of the Natural Capital Impact Group have supported the development of the metric, the global luxury group Kering have championed this effort and provided significant input to ensure that it will inform decision-making. The Beta version of the methodology was launched in July 2018 and since been piloted by a number of companies. CISL has also developed metrics for soil and water impacts, which together with biodiversity, will be referred to as the ‘Healthy Ecosystem Metrics’. A report detailing the methodology for these metrics will be released later in 2019.



those not supported by the tool and the reasons why! In its current form, the metric has particular value for companies involved in bringing a product or service from raw material to market in global supply chains. It supports decision making at a corporate level, providing a commodity-level assessment of biodiversity impacts and giving an indication of where and how a company can reduce their impact in specific places. Raw materials could include cotton, rice, coffee, cattle, soybeans, palm oil and other major agricultural commodities. The metric is particularly useful for businesses that do not have precise knowledge of their sourcing locations or land footprints. The Biodiversity Impact Metric has a number of potential business applications, including:

• Establishing an overall potential impact score from commodity sourcing

• Flagging geographic sources of potential elevated impacts in a commodity supply chain

• Comparing potential impacts of different commodities – within a company’s supply chains or more generally


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• Comparing potential impacts of different companies sourcing the same commodity(ies) The metric supports decision making at a corporate level, providing a commodity-level assessment of biodiversity impacts and giving

an indication of where and how a company can reduce their impact in specific places.

The Biodiversity Impact Metric is not suitable for the following business applications:

• Estimating biodiversity impacts in seas/ oceans (it is based on terrestrial data only)

• Direct use in natural capital assessments (it does not provide information at sufficient granularity for this)

5.Business sectors ➢ Describe business sectors covered by the tool All sectors, but it could be particularly relevant to:

- Food, beverage and apparel

- Cosmetics and pharmaceuticals

- Forest based industries

- Other major consumer goods companies sourcing raw materials


The central idea was to develop a robust methodology that is practical, easy to use, and that will help companies to measure their impacts on biodiversity in different parts of the world and provide them with an indication of where these impacts can be reduced. Whilst the accuracy of the metric increases with the granularity and precision of the input data, the metric is also designed to draw on robust external datasets to make inferences when a company’s knowledge of its sourcing is incomplete. The metric is based on the concept that a company’s impact on biodiversity is a combination of three things: i) the area required to produce a commodity, ii) the intensity of the production processes & iii) the relative global importance of the biodiversity in the area they are operating.


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The methodology has been co-developed by a number of different companies representing different industries. The methodology was developed with the view that whilst biodiversity is complex, business need to report on their biodiversity impacts in a simple way if progress is going to be made incorporating biodiversity into decision making. Earlier working papers providing useful background information are:

• Working Paper on Biodiversity and ES in EP&L (https://www.cisl.cam.ac.uk/publications/publication-

pdfs/BESinEPLWorkingPaper.pdf) (Oct 2016). This work was undertaken to support Kering in developing its thinking on

biodiversity and ES in the context of Environmental Profit & Loss (EP&L) accounts.

• Working Paper ‘How businesses measure their impacts on nature’ (https://www.cisl.cam.ac.uk/publications/publication-pdfs/how-

businesses-measure-their-impact-on-nature.pdf) (2016)

Working Paper ‘Healthy ecosystem metric framework: biodiversity impact’ (https://www.cisl.cam.ac.uk/publications/publication-pdfs/healthy-ecosystem-metric-framework.pdf) (May, 2017)

https://www.cisl.cam.ac.uk/publications/publication-pdfs/BESinEPLWorkingPaper.pdf

https://www.cisl.cam.ac.uk/publications/publication-pdfs/BESinEPLWorkingPaper.pdf

https://www.cisl.cam.ac.uk/publications/publication-pdfs/how-businesses-measure-their-impact-on-nature.pdf

https://www.cisl.cam.ac.uk/publications/publication-pdfs/how-businesses-measure-their-impact-on-nature.pdf

https://www.cisl.cam.ac.uk/publications/publication-pdfs/healthy-ecosystem-metric-framework.pdf

https://www.cisl.cam.ac.uk/publications/publication-pdfs/healthy-ecosystem-metric-framework.pdf


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These are not defined in the tool.


➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken This is not included.

Impact boundaries


N/A



N/A

Valuation


N/A


N/A

9.Granularity level The metric can work at any scale, but for the current tool, the underlying data has been developed at the scale of ‘Country Eco-region Component’. Terrestrial Eco-regions of the World are a biogeographic regionalization of the Earth’s terrestrial biodiversity. Eco-regions are defined as relatively large units of land containing a distinct assemblage of natural communities sharing a large majority of species, dynamics and environmental conditions. The new terrestrial eco-region dataset17, updated in 2017, proposes 867 terrestrial

17 (Dinerstein et al. 2017)


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eco-regions, which size ranges from 3 km2 (Central Polynesian tropical moist forests) to 3.9 million km2 (East Siberian taiga), with an average size of eco-regions of 155,748 km2. They are classified into 14 different biomes such as forests, grasslands or deserts. Eco-regions are a convenient size, small enough that ecosystem type and biodiversity ‘quality’ are largely consistent within them, but large enough that precise source information for commodities is not needed. Most eco-regions tend to stretch across national boundaries. A ‘Country Eco-region Component’, or CEC, is the portion of a particular eco-region that falls within a particular country. Metric results are calculated at the scale of Country Eco-region Component and then aggregated to produce a national score for different commodities.


The metric is a simple equation that does not require expert knowledge to calculate. However, some expertise is required to source, import and manipulate the required underlying datasets. CISL has developed a spreadsheet-based tool to facilitate calculations. The metric does draw on several different datasets that are not publically available. The data on biodiversity significance (range rarity) is currently only available under licence from iBAT. Additionally, CISL has calculated a commodity country eco-region layer; this is used when a company is uncertain of from which eco-region they source. This layer helps identify the most likely eco-regions in which production of a particular commodity is likely concentrated within a country. The tool is similar to others that are based on land area, land use intensity and biodiversity significance. One of the differences is this is based on eco-regions and is able to make inferences using alternative data sources when the precise sourcing information of a company is uncertain.


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured There are three variables within the Biodiversity Impact Metric that a company may be able to influence to reduce their impact on natural ecosystems: • Land area: reducing the area of cropland used, either by reducing the quantity of raw materials required or by increasing crop yield on existing agricultural land • Land use intensity: by reducing the intensity of land use or changing the land use type • Source location: sourcing raw materials from areas that are less important for biodiversity and/or have higher yields, requiring less land area to produce the same quantity.


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For most companies, changing their sourcing location is a significant challenge with social, political and environmental consequences. In addition, while switching location may reduce the impact for a particular company, it does not necessarily solve the problem of unsustainable production in the original location. The impact metric’s primary purpose is to provide companies with data that informs and prioritises their actions to reduce biodiversity impacts.


Whilst it has not specifically been designed to reflect reporting requirements, the biodiversity impact metric could be used for external reporting.


The biodiversity impact metric is consistent with monitoring and measuring impacts related to SDG15.



• The metric is simple to use but academically robust.

• It does not involve primary, field based data collection in different sites

• When companies lack precise information about their commodity sourcing the metric can make robust inferences

using alternative data sources.

• It provides a comparable methodology to showcase progress across different industries

• There are a number of steps or stages in Natural Capital protocol, starting with a framing and scoping phase and

then progressing into measurement, valuation and application. The Metric can help companies during the Scoping

and Measuring stages of applying the protocol


Please describe the weaknesses of the tool according to your insights

o The precision of the metric is limited by the accuracy of a company’s input data. o The metric assess an ongoing occupancy impact on biodiversity for maintaining the transformed land in commodity production.

o It will help shed light on high-risk locations where the company is most likely to experience biodiversity risks but will not

provide enough information about a specific site to support completion of a biodiversity action plan. This would require more

detailed information at a finer scale.

o At present, it is focused on the impacts of land use associated with raw material production. It does not provide a measure of

all impacts on natural capital across a supply chain (i.e. manufacturing/processing/distribution, retail etc.)

o The metric does not assess the broader landscape context, nor the indirect effects (outside the land-use footprint) of

commodity production.


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➢ Please describe planned improvements None are currently planned.















n/a



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Biodiversity significance DI Range rarity IBAT data – built using species distributions maps

R/M





Quantity impacted Mean Species Abundance values Company data - answers to high-level land use intensity questionnaire and GLOBIO MSA values, with expert interpolation used for novel habitat categories and intensities.

M

Area impacted Land area under cultivation Company data. If unknown, FAO data on commodity yields by country are used

R (if company data available, otherwise M)


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to convert company data on tonnage sourced to estimate land area.








Climate change

Pollution


Other


18.Metrics The BIM measures the impact of using land that was once natural habitat for commodity production. Note that the metric does not assess when land transformation took place, or who was responsible for it. The metric thus is assessing an ongoing occupancy impact on biodiversity for maintaining the transformed land in commodity production. For a particular commodity sourced from a particular location, the metric assesses impact based on:



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• The land area needed for production of the commodity: estimated using company or FAO yield data when direct land area measurements are unavailable. • the proportion of biodiversity lost through transforming land to produce the commodity: estimated using Mean Species Abundance values, with some values for habitat categories not represented in the MSA dataset interpolated using expert knowledge. • the relative global importance of that biodiversity: based on range rarity The methodology provides a basis for comparing different sourcing options and as such may help a company to compare different investment options. The BIM can be calculated at any scale, but for companies without precise knowledge of their sourcing locations, eco-regions are used.


The methodology for the metric was co designed in line with the following principles: Metric Principles:

Principle Description

Meaningful Meaningful to business and investor communities so it can be used to drive decision making. Methodology is clearly understood.

Measurable and comparable

Allows for comparison across geographies and time.

Possible to aggregate Can be aggregated from site-level to regional and global scales.

Practical Data is accessible, measurable by company or using free, globally available data. Ability to substitute better information where available.


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Replicable and credible Based on a reputable scientific method.

Context based Considers local conditions/levels to reflect ‘impact’ (beyond ‘usage’).

Responsive Responds to changes in company activities, both short and long term.


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6. Biodiversity Monitoring System for the Food Sector

FICHE NR 6 Biodiversity Monitoring System for the Food Sector


• Will be available by January 2020

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: Lake Constance Foundation, Germany Other: Global Nature Fund (Germany), Solagro (France), Fundación Global Nature (Spain), IST Technical Institute of University Lisbon (Portugal)


➢ Please describe the development process and stages ➢ Please describe if the tool has been road-tested (add this information also in the table ‘Categories of Business

Applications!) and if case studies are available (please refer to links or publications) • The monitoring tool is being elaborated in the frame of the EU LIFE Project “Biodiversity in standards and labels for the food

sector”.

• The monitoring indicators were selected out of existing indicator sets and studies and have been discussed intensely with representatives of standards, food companies, and scientific institutes.

• The online tool will be tested in practise from October – December 2019 and will be available for food standards and food companies with own requirements on biodiversity in January 2020.



those not supported by the tool and the reasons why! The tool has been created to offer food standards and food companies the possibility to monitor certain aspects with relevance for biodiversity of their certified farms / their producers. The monitoring is divided into two levels:

• Level 1 monitoring is a system wide approach with indicators to evaluate the potential created for biodiversity (ecological structures, biotope-corridors, buffer zones, etc.) and the reduction of negative impacts on biodiversity (use of chemical pesticides and fertilizers, erosion, water use etc. )

• Level 2 is an In-depth sampling beyond the scope of certification. It monitors mid- and long-term effects of certification on wild biodiversity on the farm and its direct surroundings by selected key indicator species. Level 2 data is gathered from representative certified entities in different geographical settings, cultivating different types of crops in different intensities.

The monitoring system will deliver individual reports for the standards and companies participating on the biodiversity performance of their certified farms or producers in the supply chain. Data can be aggregated for a certain country or region and/or for a certain product. The administrating entity has the possibility to produce monitoring reports on aggregated data for the whole food sector. The monitoring system does not collect scientific data on ecosystems, species or genetic diversity – except within level 2 monitoring which includes the monitoring of 2 – 3 key indicator species, indicating the health of the ecosystems. As level 2 monitoring data need to be collected with the support of an expert, it will be costly and therefore only be carried out on representative farms every 3 – 5 years.


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5.Business sectors

➢ Describe business sectors covered by the tool

• Food sector: Food standards and food companies doing own audits


➢ Provide concise but clear description of the methodology. Please be aware that we will add separate sections in the new

update report on Globio and ReCiPe, so if your tool is making use of these models, you only need to make a brief

reference to them. Level 1 Monitoring is based on 25 key data and indicators related to the creation of potential for biodiversity and the reduction of negative impacts on biodiversity (good agricultutal practises). Most of the key data and indicators selected are beeing asked in the current audits of most of the (international) food standards, but they are not evaluated from the point of view of biodiversity. Standards and companies will have authorized administrators who deliver the data which has been collected during audits, use of sustainability tools, use of Biodiversity Performance Tool….. Besed on the data collected, Monitoring Level 1 will provide indications on the following questions:

1. Are direct Pressures (Threats) on Biodiversity through common agricultural practices reduced? 2. Are potentials to enhance Biodiversity created? And in which quality? 3. Are risks for further loss and degradation of Biodiversity identified and reduced? 4. Is a Continious Improvement of Biodiversity performance evident? 5. Is Agro-Biodiversity enhanced? Does it increase?

Level 2 Monitoring Level 2 is an In-depth sampling beyond the scope of certification. It monitors mid- and long-term effects of certification on wild biodiversity on the farm and its direct surroundings by key indicator species selected on regional level. Level 2 data is gathered from representative certified entities in different geographical settings, cultivating different types of crops in different intensities. Data on the selected key indicator species will be collected every 3 – 5 years indicating the general health of the ecosystems. The monitoring database has not been extended to collect data for level 2 monitoring. A test phase is planned for spring 2020. It will be crucial to test if farmers and farm advisors will be able to collect data on key indicator species (citizens science) or if this needs to be done by experts which would be an additional cost factor for level 2 monitoring. Data for monitoring is collected via an open source content management system. Agricultural farm data is collected by a pre-defined questionnaire which can be downloaded online and installed and executed on a laptop, tablet (or smartphone). This software:

o Has a user friendly input mask; AND o Enables offline storage and export of gathered data sets on the respective electronic device used for data gathering. ; AND o Possesses a built-in API for data upload into a data base (back end) where data can be stored and processed, AND o Runs on Windows/Android environments

• The Data Management System (DMS) allows: o Comparison of agricultural farm data sets that were gathered at different points in time; AND o Monitoring of parameter changes that occur from data time series of a particular agricultural farm, AND o Monitoring of parameter changes that occur from aggregated data time series from various farms

Outputs:


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o Data sets of the same farm can be compared and changes of parameters assessed and reported. The way this is done is by comparing the first data set of a farm (baseline or T0) with a subsequent data set of the same farm that is generated at a later point in time (performance data set or Tx).

o Comparison between any performance data set and the baseline is always enabled i.e. T1:T0; T2:T0; Tx:T0. o Comparison between different performance data sets is always enabled i.e. T2:T1; T3:T2; Tx:Tx>0 o Comparison between all data sets shall be enabled Tx:Tx

• Aggregated data requests and performance reporting of various farm data sets according to meta attributes (e.g. GPS location, type of certification, farm type, farm size) in combination with any indicator(s) of interest is enabled ➢ Example: A following data request by a Project Leader is made: Show performance of farms in Germany, located in the federal

state of Baden-Wuerttemberg, farm size >20ha, which buffer zone of more than 10 meters width.

7.Additional features

Baseline or reference


Baseline will be defined by the 25 key data and indicators. For monitoring level 2 it is foreseen to collect a baseline regarding the population of 2 – 3 key indicator species. Data sets of the same farm can be compared and changes of parameters assessed and reported.


➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken No materiality assessment

Impact boundaries


The monitoring tool addresses the agricultural farms as main suppliers of the food sectos.



The monitoring tool focus on parameters of biodiversity performance on farm level. Impacts and dependencies of the food sector can be evaluated to a certain extend.

Valuation


Impacts are evaluated in a quantitative way. Few qualitative indicators are collected and evaluated.


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No monetization techniques.




The pressure-impact relationships become imprecise below areas of about 1000 ha.

10.User friendliness

➢ Please describe: o if the tool is easy to use by non-experts or requires specialist knowledge o what time efforts are required to apply the tool o if the tool has similarities with tools for other environmental issues and if so, please describe o Indicate whether these are estimated or based on application of the methodology by the company

The monitoring system has been prepared for food standards and for food companies with own requirements on biodiversity protection and carrying out own audits. Data for level 1 monitoring can be collected by farmers, farm advisors, auditors /certifiers. Most of the data is collected anyway during the audits for the certification via (international) food standards. Level 2 monitoring is planned and it will be tested if data on key indicator species can be collected by farmers and farm advisors or if the involvement of an expert will be needed. Estimation of time for data collection of level 1 monitoring = 2 – 3 hours per farm.


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured Currently level 1 monitoring includes key data and indicators on certain aspects of biodiversity performance requested by food standards and/or food companies. Objective of the monitoring is to evaluate the impact of these criteria /requirements as well as the level of continuous improvement of the certified farms and suppliers. If criteria /requirements change /are being extended, the monitoring system will be adapted.



Currently no monitoring on biodiversity is taking place in the food sector – except monitoring of pilot initiatives or punctual monitoring on certain crops in certain regions.


Direct link to SDG 15 “protect, restore and promote biodiversity on land”


➢ Please describe the strengths of the tool according to your insights o Quantitative (and scientifically robust) link between pressures and impacts o Covers most drivers for biodiversity loss in food production


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o Can be used by all food standards and all food companies. A joint monitoring system reduces the costs for monitoring and allows cross-standard /cross-companies evaluations

o Compatible with site-level data (micro) and regional /national objectives (macro) o Would allow the introducing weight factors differentiating ecosystem condition based on protection regime, protected species, etc. o Very practical and possible to combine with audits and other kind of data collection o Low costs


➢ Please describe the weaknesses of the tool according to your insights o Covers not all indicators with relevance for biodiversity o Does not provide detailed scientific information on the current situation and development of biodiversity on the farm (just potential

created) o


➢ Please describe planned improvements o Elaboration of level 2 monitoring (in 2020) o Extension of indicators for level 1 monitoring (in 2022)











Table 1: Economic activity data inputs



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Economic activity indicator (unit) ((e.g. turnover of company, purchases in €, etc.)








Total utilized agricultural area (UAA) (ha); temporary semi-natural area (SNH) (ha); permanent SNH (ha)

Standard/company audits, farm book, farm self-assessment, BPT

Real data

A Biodiversity Action plan (BAP) has been elaborated for the farm. Yes/No. Implementation degree of the BAP (in %) i.e. implementation degree of identified and agreed measures.

Biodiversity Action Plan and Biodiversity Performance Tool

Real data

Proportion (%) of water courses that have no buffer zone.

Map of the farm Real data

Proportion (%) of water courses that have a



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buffer zone width of 1 to 5 meters.

Proportion (%) of water courses that have a buffer zone width of 5 to 9 meters.


Proportion (%) of water courses that have a buffer zone width of 10 meters or more


Indication of semi-natural habitat connectivity according to the following options: - No connectivity between Semi-natural habitat areas - Semi-natural habitat areas are connected but show discontinuities - Semi-natural habitat areas are composed in a way that they build a network of biological corridors


Alien invasive species are present on the farm. Yes/No

e.g. Alien Invasive Species Inventories for Europe

Estimated data

Number of traditional crop species


Real data

Number of traditional breeds


Real data



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Real (R) or Modelled data (M)? Confidence level of data

Proportion (%) of required animal forage (per season) that can be produced on farm or that can be sourced within the region (50km radius) according to the following range: <30%, 31-50%, 51-80%, >80%


Real data

Maximum average livestock density (LU/ha) of the main fodder area.


Real data

Proportion (%) of animal fodder that is based on soy. From animal fodder based on soy indicate the proportion that is certified to be deforestation-free (e.g. Round Table on Responsible Soy certification, or any other reliable and transparent proof that the cultivation of the purchased soy did not lead to deforestation)


Real data


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From animal fodder based on soy indicate the proportion (%) that originates from a manufacturer based in an EU country where there is a transparent commitment to sustainable production by providing a reference


Real data

Pesticides or fertilizers applied on Semi-natural habitat areas. Yes/No


Real data

Number of crop species. Including: - Temporary grassland (considered as equivalent to a crop); - Permanent grassland not under extensive management (considered as equivalent to a crop).


Real data

Number of breeds (animals)


Real data

Are there GMO used on the farm? Yes/No If yes: Proportion of farming area (%) that is planted with GMO; Proportion of breed species (%) that are genetically modified.


Real data


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Indicate the proportion of feed concentrate that is certified to be GMO-free (e.g. ProTerra certification, others)?


Real data

The farm is involved in any water management activities/programmes. Yes/No


Real data

A decision support tool to assess the appropriate amount of irrigation on the farm is applied. Yes/No. If yes, please describe.


Real data

If respective soil maps are available, it shall be assessed if the farm is located in an area where soil loss rates are higher than 1 tonne/ha/year. Yes/No If soil loss rates are >1 tonne/ha/year, which and how many measures are implemented to prevent soil erosion?

Standard/company audits, farm book, farm self-assessment, BPT. An erosion map for soil loss rates in arable lands for Europe is available here: http://ec.europa.eu/eurostat/statistics-explained/index.php/Agri-environmental_indicator_-_soil_erosion

Estimated data Real data

Proportion (%) of covered soil from entire farming area during critical periods (e.g. peak precipitation months)

Standard/company audits, farm book, farm self-assessment, BPT.

Real data


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Length of crop rotation (years) of main crops.


Real data

Area of UAA (ha) on which alternative measures are applied to avoid and to reduce pesticide application.


Real data

Total application rate of pesticides on utilised agricultural area (kg/ha/year). Area (ha) of UAA where broad-spectrum herbicides are applied.


Real data

Total amount of Nitrogen (mineral & organic) fertilisation applied on the farm in kg/ha/year


Real data

Participation of farm operators in training or education activities with relevance for biodiversity. Yes/No. On a regular basis? Yes/No.


Real data

Participation in training or education activities with relevance for biodiversity. Yes/No. On a regular basis? Yes/No. Percentage of workers that attend a training with relevance for biodiversity (% of permanent staff)?


Real data


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Climate change

Pollution


Other


The Biodiversity Monitoring System for the food sector collects key data and indicators indicating measures against the main drivers of loss of biodiversity. All main drivers of loss of biodiversity except climate change are addressed.


components


➢ Please describe principles if available

•



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7. Biodiversity Performance Tool for Food Sector

FICHE NR 7 Biodiversity Performance Tool (for Food Sector)

1. Date of assessment • Will be available by January 2020, with a test period from September to December 2019.

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: Solagro, France Other: Global Nature Fund (Germany), Lake Constance Foundation (Germany), Fundación Global Nature (Spain), IST Technical Institute of University Lisbon (Portugal)



Business Applications!) and if case studies are available (please refer to links or publications) • The Biodiversity Performance Tool is being elaborated in the frame of the EU LIFE Project “Biodiversity in standards and

labels for the food sector”.

• The 78 indicators were selected out of existing indicator sets and studies, a beta version was already tested by the Life consortium through our pilot farms (50 assessments). An update of these assessments for the pilot farms will be done during autumn 2019.

• The online tool will be tested in practise from October – December 2019 for food standards and food companies.



those not supported by the tool and the reasons why! This BPT aims at proposing a methodology to quite easily assess the integration of functional biodiversity at farm level for food sector actors (product quality or sourcing managers) as well as for certification companies (certifiers and auditors). The Biodiversity Performance Tool (BPT) should help farmers and farm advisors to elaborate and implement sound Biodiversity Action Plans, which contribute substantially to a better biodiversity performance on farm level. The tool will support auditors and certifiers of standards as well as product, quality and sourcing managers of food companies to better assess the preservation and improvement of integration of biodiversity at farm level. BPT will identify weaknesses and strengths of a farm regarding functional biodiversity and will confirm and illustrate change over time (continuous improvement). The objective of such a tool is to identify and assess the state of potential for biodiversity on a farm in order to propose an action plan to preserve or promote biodiversity. This action plan should recommend some relevant actions in the current socio-technical-economical context. This tool should raise farmer awareness on the potential for biodiversity on each farm and how to realize this potential and deploy the learning process to the whole food chain (quality and product managers; sourcing managers). The BPT is developed from a software that is based on a multi-criteria assessment to help decision-making. Biodiversity is a complex issue – the tool tries to break down the issue as simple as possible but as detailed as needed. Three main components are considered: - characterization of the environment of the farm through its semi-natural habitats (SNH)


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- characterization of farming practices - characterization of socio-economic system

Heterogeneity of landscape: several scientific publications highlight the importance of landscape mosaics in the conservation of either functional or heritage biodiversity. This heterogeneity relies on the crop diversity, but also on the presence of natural environments and semi-natural habitats such as hedgerows, field margins, woodlots, grasslands with no fertilizers and pesticides. The proportion of SNH is a good indicator of this heterogeneity. Quantity of SNHs is important to consider but not sufficient to stop the loss of biodiversity. The quality of these habitats needs to be promoted through their diversity and their management. The intensity of farming practices is impacting directly and indirectly biodiversity at farm and landscape levels. The corresponding indicators will describe the intensity of destruction of habitats (conversion of permanent grasslands into arable crops, soil drainage, plot configuration…), of the overexploitation of resources (maximal average livestock density, water management, actions to reduce water consumption, length of crop rotation, number of breeds, number of rare and endangered breeds, number of crops, number of rare and endangered crop species, preventive measures and monitoring, soil management…), of the pollution (fertilizers, pesticides…). The environmental management system and cooperation are also two elements important to consider within the assessment of biodiversity performance. Indeed, environmental management integrates the monitoring of farm performances (engagement of farm in a product certification process, farm map existence, traceability and transmission of information at least once a year, the use of a multi-criteria assessment) as well as the training and update of knowledge on biodiversity at least of the farmer and preferably also of workers. Cooperation refers to both external experts and the involvement in a local network. In conclusion, here the awareness and involvement of the farmer are both considered in the process of preservation and improvement of biodiversity at farm level and their active behavior on this topic.

5.Business sectors ➢ Describe business sectors covered by the tool • Food sector: Food standards and food companies doing own audits




brief reference to them. The BPT is based on the assessment of 78 basic indicators related to the creation of potential for biodiversity and the reduction of negative impacts on biodiversity (good agricultutal practises). Most of the key data and indicators selected are beeing asked in the current audits of most of the (international) food standards, but they are not evaluated from the point of view of biodiversity. Standards and companies will have authorized administrators who deliver the data which has been collected during audits, use of sustainability tools, use of Biodiversity Performance Tool….. The BPT is based on less than 100 questions. According to the user profile and farm context, users can answer less than 100 questions according to the relevance for the respective farm. The BPT questions are organized by four main categories that are displayed in tabs: General information; A-Characterization of the environment of the farm; B-Characterization of farming practices; C-Insertion of the farm in the socio-economic system.


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Once the questions are answered and filled out, 78 basic indicators are automatically calculated and ordered according to a color scale. For each basic indicator, some threshold values are defined. The minimal score is indicated by a red color and the maximal score by a green color, with some gradients from orange to yellow for some with intermediate scores. To allow a proper analysis of the scores and to identify the points for improvement, the scores are presented per main topic, corresponding to the four main categories of BPT questions i.e. characterization of semi-natural habitats, characterization of farming practices and characterization of socio-economics of the farm, with the possibility for the user to further filter the results display by choosing any sub-categories (Quantity of SNH, Diversity of SNH, Functional composition of SNH, Functional management of SNH; Promotion of cultivated and wild biodiversity, Inputs management, Water management, Soil management, Livestock; Farm performances monitoring, Awareness of farmer(s) and worker(s), Cooperation). Data is collected via an online webtool. Agricultural farm data are collected from farming practices register book, Land Parcel Identification System and some information are provided by farmers and directly on fields. This webtool:

o Has a user-friendly interface; o Has a GIS tool to visualize and calculate linear and surface areas of SNH o Enables storage and export of results (assessments); o Runs on Windows/Android environments o Displays a matrix with strengths and weakness of the farm o Proposes biodiversity actions to be implemented to improve these weakness o And highlights if scores decrease between two assessments (t+1 and t) for a same farm in a continuous improvement

approach. Outputs:

o Farm summary with main indication on biodiversity (ensure non-destruction of SNH, % of grassland converted to arable land on previous year and 2 years before, insertion of the farm into an area of ecological interest (High Conservation Value Areas, Natura 2000…), presence of invasive species, presence of odonates…)

o SWOT matrix o Action plan for each farm o Map of SNHs o Possibility to export the results (excel file) o Possibility to extract some indicators for Biodiversity Monitoring System for Food sector



For each basic indicator, some threshold values are defined.


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No materiality assessment

Impact boundaries


The monitoring tool addresses the agricultural farms as main suppliers of the food sectors.



The monitoring tool focus on parameters of biodiversity performance on farm level. Impacts and dependencies of the food sector can be evaluated to a certain extend.

Valuation


Impacts are evaluated either in a quantitative or in a qualitative way.


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Farm (scale at which farmer could implement actions) and landscape level (scale at which companies could implement collective actions such as connectivity of SNH with natural habitats).


The initial assessment requires the main efforts and inputs. You can rely on the farmers’ data (graphical plot register, farming practices book register) to reduce the time of data collect. Data can be collected by farmers, farm advisors, auditors / certifiers. At least half a day on field and half a day on desk are necessary to well integrate the inventory of semi-natural habitats and their management at farm level. For the elaboration of a BAP and realization of follow up assessments, less than half a day will be needed.




Currently no monitoring on biodiversity is taking place in the food sector – except monitoring of pilot initiatives or punctual monitoring on certain crops in certain regions.


Direct link to SDG 15 “protect, restore and promote biodiversity on land”


o Please describe the strengths of the tool according to your insights o Scoring by basic indicators gathered into categories (Semi-natural habitats; Farming practices and Socio-economic

approach) and sub-categories (Quantity of SNH, Diversity of SNH, Functional composition of SNH, Functional management of SNH; Promotion of cultivated and wild biodiversity, Inputs management, Water management, Soil management, Livestock; Farm performances monitoring, Awareness of farmer(s) and worker(s), Cooperation)

o Continuous improvement (scoring of basic indicators and threats to compare a farm at two different dates) o SWOT matrix o Action plan o Map of SNH


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o Export of the results (excel file) o Extract some indicators to Biodiversity Monitoring System

o Quantitative (and scientifically robust) link between pressures and impacts o Covers most drivers for biodiversity loss in food production o Can be used by all food standards and all food companies. o Compatible with site-level data (micro) and regional /national objectives (macro) o Would allow the introducing weight factors differentiating ecosystem condition based on protection regime, protected species,

etc. o Very practical and possible to combine with audits and other kind of data collection o Low costs


➢ Please describe the weaknesses of the tool according to your insights o Available for temperate climate productions o Does not provide detailed scientific information on the current situation and development of biodiversity on the farm (just

potential created) o No global scoring


➢ Please describe planned improvements o


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Nomenclature used Data source (company or global data sets? if global




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data sets, which one?)

Owner and tenant farming total utilized agricultural area (UAA) (ha)

Standard/company audits, farm book, farm self-assessment

Real data

Insertion of the farm into an area of ecological interest (Yes/No)


Presence of invasive species in the woody elements (Yes/No)

Farm self-assessment, farm advisors

Real data

Presence of invasive species in the grass-herb elements (Yes/No)


Real data

Presence of invasive species in water elements (Yes/No)


Real data

Presence of odonates (Yes/No)


Real data

Presence of amphibians (Yes/No)


Real data

Presence of palustrine plants (Yes/No)


Real data

Presence of wetland-dependent avifauna (Yes/No)


Real data

Notification of any extraordinary elements


Real data

Importance of SNH (proportion, % of UAA)


Importance of permanent grasslands, without pesticides nor fertilizers (% of UAA)


Real data


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Importance of agroforestry (% of UAA)


Real data

Diversity of type of SNH at farm scale (1 to 5 types)


Real data

Share of SNH plot scale (1 to 3 types per plot)


Real data

Connectivity of SNH (- No connectivity between Semi-natural habitat areas - Semi-natural habitat areas are connected but show discontinuities - Semi-natural habitat areas are composed in a way that they build a network of biological corridors)

Farm self-assessment, farm advisors, map of the farm

Real data

Details of linear and surface area for each type of SNH

Farm self-assessment, farm advisors, map of the farm

Real data

Composition of grass strips

Farm self-assessment, farm advisors, Farm book

Real data

Composition of flower strips


Real data

Composition of hedges Farm self-assessment, farm advisors, Farm book

Real data

Composition of agroforestry elements


Real data


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Support of nutritive resources


Real data

Support of shelters or overwintering sites or cavities


Real data

Number of strata or vegetation layers

Farm self-assessment, farm advisors, Farm book, map of the farm

Real data

Average plot size and width

Farm self-assessment, farm advisors, Farm book, map of the farm

Real data

Number of traditional crop species


Real data

Number of traditional breeds


Real data

Number of rare or endangered breeds

Farm book, farm self-assessment

Real data

Number of rare or endangered crop species or varieties


Real data

Special measures for the protection of species


Real data






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Flowering duration of grassy elements (qualitative scale)


Real data

Flowering of hedges (qualitative scale)


Real data

Modality of management of grassy elements (qualitative scale)


Real data

Management of hedges and woody elements (qualitative scale)


Real data

Management of ditches ripisylves ponds (qualitative scale)


Real data

Pesticides or fertilizers applied on Semi-natural habitat areas. (Yes/No)


Real data

Burning of SNH (qualitative scale)


Real data

Export of mowing products (qualitative scale)


Real data

Specific result-based measures of SNH management to improve biodiversity (Yes/No, detail if yes)


Real data

Number of crop species. Farm self-assessment, farm advisors, Farm book

Real data

Number of breeds (animals)


Real data

Are there GMO used on the farm? Yes/No


Real data


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If yes: Proportion of farming area (%) that is planted with GMO; Proportion of breed species (%) that are genetically modified.

Preventive measures and monitoring (check box)


Real data

Surface area non-treated with synthetic pesticides (%)


Real data

Alternative methods against weeds (check box)


Real data

Alternative methods against other pests (check box)


Real data

Type of pesticides used (seed treatment, insecticides including acaricides, fungicides, mollucides, rodenticides) (Yes/No)


Real data

Mineral nitrogen fertilization for dominant crop system (kg N/ha)


Real data

Organic fertilization and awareness of N content richness


Real data

Water management (qualitative scale)


Real data

Actions to reduce water consumption


Real data


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Length of crop rotation (years)


Real data

Proportion of mass-flowering crops (%)


Real data

Presence of soil analysis with SOM and microbiological activities (Yes/No and frequency)


Real data

Presence of cover crops (type and %)


Real data

Presence of intercropping (Yes/No)


Real data

Typology of permanent crops such as orchards or vineyards (qualitative scale)


Real data

Soil management (qualitative scale)


Real data

Maximum average livestock density (LU/ha) of the main fodder area.


Real data

Type of concentrates (qualitative scale, including presence of imported soy, oil and cattle cake, certified GMO-free…)


Real data

Quantity of concentrates (t/LU)


Real data


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Type of forage (fermented products including silage; fermented products and hay; only hay)


Real data

Forage autonomy (produced on farm) (qualitative scale of %)


Real data

Grazing use (%) Farm self-assessment, farm advisors, Farm book

Real data

Management of permanent grasslands (qualitative scale)


Real data

Use of alternative methods for combating diseases and parasitisms (Yes/No)


Real data

Engagement of farm in a product certification process (Yes/No)

Farm self-assessment Real data

Farm map existence (Yes/No)

Farm self-assessment, map of the farm

Real data

Traceability (Yes/No) Farm self-assessment Real data

Multi-criteria diagnostic existence (Yes/No)

Farm self-assessment Real data

Participation in training or education activities with relevance for biodiversity. Yes/No. On a regular basis? Yes/No. Percentage of workers that attend a training with relevance for biodiversity (% of permanent staff)?


Real data


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Cooperation with external experts such as NGOs, administration or scientific institutes (Yes/No)


Real data








Climate change

Pollution


Other


The Biodiversity Performance Tool collects key data and indicators indicating measures against the main drivers of loss of biodiversity. All main drivers of loss of biodiversity except climate change (directly) are addressed. Nevertheless, most of the proposed actions into the Biodiversity Action Plan have a positive impact on climate change and contribute to mitigate or adapt the production system to climate change.


components



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•


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8. Global Biodiversity Score

FICHE NR 8 GLOBAL BIODIVERSITY SCORE (GBS)

1. Date of assessment • First assessment submitted to CDC Biodiversité on 12 January 2018

• Replies by CDC Biodiversité on 24 January 2018, which were all integrated in the text below

• Update by CDC Biodiversité on 22 August 2018

• Update CDC Biodiversité on 21 August 2019

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: CDC Biodiversité (France) Other: Club of Businesses for Positive Biodiversity (B4B+ Club) acts as a platform for the GBS development (a group of +35 businesses representing different sectors, including finance sector)



Business Applications!) and if case studies are available (please refer to links or publications) CDC Biodiversité started working on the GBS, a tool to assess the footprint of businesses and financial institutions, in 2015. At the end of 2016, the B4B+ Club held its first meeting, providing the support and feedback of businesses, financial institutions and technical partners to the development of the GBS. In 2017, a first report described the objectives, founding choices and methodologies of the GBS and its first applications on crop commodities. In 2018, development picked up speed and this acceleration continued in 2019. The tool uses an aggregate metric for biodiversity which focuses on the health (or integrity) of ecosystems: the Mean Species Abundance (MSA). The tool is based on internationally recognised scientific research and in particular the GLOBIO and EXIOBASE models. An excellent description of the GBS approach and state of the art can be found under http://www.mission-economie-biodiversite.com/wp-content/uploads/2017/11/N11-TRAVAUX-DU-CLUB-B4B-INDICATEUR-GBS-UK-BD.pdf and http://www.mission-economie-biodiversite.com/wp-content/uploads/2019/05/N14-TRAVAUX-DU-CLUB-B4B-GBS-UK-WEB.pdf. The GBS will remain under development until early 2020: the first biodiversity footprint assessments will be conducted in 2020.

• Technical developments are ongoing: the scope of raw materials analysed is being expanded.

• The operational relevance of the footprint is being tested thanks to the involvement of future users, i.e. businesses. This happens both through meetings of the B4B+ Club and through several case studies:

o 3 case studies are available in the 2018 GBS report update: ▪ BNP Paribas Asset Management: listed equity portfolio impact assessment ▪ Michelin: sourcing comparison for agricultural commodities ▪ Solvay: sourcing comparison for agricultural commodities

o The tool has also been road-tested for yet unpublished case studies on: ▪ Loan portfolio impact assessment ▪ AFD: project level assessment based on site level ecological surveys and pressure data ▪ GRT Gaz: project level assessment based on site level pressure data

http://www.mission-economie-biodiversite.com/wp-content/uploads/2017/11/N11-TRAVAUX-DU-CLUB-B4B-INDICATEUR-GBS-UK-BD.pdf

http://www.mission-economie-biodiversite.com/wp-content/uploads/2017/11/N11-TRAVAUX-DU-CLUB-B4B-INDICATEUR-GBS-UK-BD.pdf

http://www.mission-economie-biodiversite.com/wp-content/uploads/2019/05/N14-TRAVAUX-DU-CLUB-B4B-GBS-UK-WEB.pdf




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▪ Mirova: assessment of corporates based on publicly available data ▪ Veolia: corporate level assessment (whole business unit) including through the use of site level pressure data

o More case studies and two full scale biodiversity footprint assessments are being launched so the tool should be fully road-tested by early 2020.




• The GBS is suitable for the following applications: o Calculating the footprint of a financial asset portfolio as a basis for portfolio investment decisions by finance

sector, as long as it remains at the level of sectors or companies (when enough company-specific data is available) o Corporate level assessments, including estimation of biodiversity performance along the whole value chain of a

company. The GBS can also be used by non-financial companies themselves to assess a refined footprint if detailed information is available.

o Supply options assessments are possible but not the main focus of the GBS, in order to compare different suppliers and supply chain options, or to screen a supply chain and see where the risks of biodiversity impacts are and identify potential impact hotspots where impact assessment can be refined with better data collection

o Country level assessments (out of interest for business biodiversity performance assessments)

• The GBS is not the most suitable for the following applications: o Assessments at site, product and project levels

Due to: o The uncertainties associated to the pressure-impact statistical relationships, especially at small scales (under 1000

ha). Project level assessments are robust only for very large-scale projects (impacting thousands of hectares) and should generally be limited to internal reporting

o Not species or habitat specific

• The GBS could be used for No Net Loss approaches at the corporate or financial institution-level: o As any assessment tool, it would require as an input a baseline scenario to compare against the biodiversity losses

and gains. o Since the GBS is not the most suitable at site or project level and since it focuses on intactness and not on individual

species or habitats, it is not appropriate to conduct regulatory No Net Loss project assessments (which usually require particular attention for endangered and protected species).

o It could however provide balances expressed as net gains or losses of km2 MSA if fed with appropriate data.


• All sectors except sectors with high impacts related to: o Marine biodiversity (e.g. fishing) as it is not covered by the tool


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o Invasive Alien Species or direct exploitation of biodiversity (e.g. fishing or commercial hunting) as they are not covered by the tool




brief reference to them. GBS is designed to provide an overall and synthetic vision of the biodiversity footprint of economic activities. It is not intended to replace local indicators which are best suited to local or on-site biodiversity assessments. This idea of reconciling different scales is key and it is essential that the GBS results are consistent with analyses conducted on a local scale, making it possible to summarize the data while losing as little information as possible. The GBS follows a hydrid approach to assess the footprint of economic activities, depending on the availability of input data about the company or asset assessed. When availability is limited, a default assessment is conducted based on average industry and region values and EXIOBASE matrix-based input-output model, but it will not distinguish differences between 2 companies in the same industry and country (c.f. orange line on the figure below). A refined assessment will take over when better data is available (blue line on the figure below): if comprehensive field ecological surveys are available, MSA.km² can be directly calculated but such comprehensive data are very rarely available. If pressure data are available (e.g. land use changes by type and location, nutrient emissions, wetland conversion), GLOBIO pressure-impact relationships can be applied to these data in order to obtain biodiversity impact results. When pressure data are not available but the assessed entity can provide inventory data (physical quantities of consumed commodities, services, GHG emissions by Scope), these data can be linked to biodiversity impact thanks to characterisation factors from in-house tools such as the Commodity and Services Tools, or from LCI/LCA databases combined with GLOBIO pressure-impact relationships. Finally, when only monetary data on purchases are available, the corresponding inventory (consumed commodities, emissions…) can be assessed thanks to the EXIOBASE environmental extensions, and then linked to biodiversity impacts as explained above.


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Two reference concepts need to be distinguished. The GBS uses the Mean Species Abundance (MSA) metric, defined as “the mean abundance of original species relative to their abundance in undisturbed ecosystems” (Alkemade et al. 2009; Schipper et al. 2016). The “undisturbed system/pristine state” against which the abundance is assessed is one reference level. It is different from the comparison to an historical baseline abundance. Such a baseline can be chosen by the company in order to report performance against it. For instance a company which had a Scope 1 impact of 10 000 MSA.km2 in 2015 can choose 2015 as


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its baseline and report it reduced its impact by 30% by 2019 if its Scope 1 impact in 2019 was 7 000 MSA.km2. The choice of historical baseline is independent of the tool used to assess the impacts. Finally, counterfactual scenarios can be used to compare what would have happened in the absence of activity by the company. The GBS does not have specific recommendations regarding counterfactual scenarios.



Biodiversity Footprint Assessments conducted with the GBS should include a framing step involving a screening of both the ecological integrity impacts and the risk of extinction impacts. During this step, material impacts are assessed (materiality is defined in line with the Natural Capital Protocol as item which can alter decision-making) and impacts on ecological integrity which are material are then further analysed in the following steps of assessments. The ecological integrity screening is usually conducted with a GBS default assessment (based on monetary flows). The risk of extinction screening would be conducted with IBAT or similar tools.

Impact boundaries


NA



The GBS does not directly assess dependencies, however, it aims to assess biodiversity impacts through the whole value chain, so some upstream inventories needed to assess biodiversity impacts can be considered as dependencies (water use for example).

Valuation


There is no valuation in the sense of the Natural Capital Protocol, only measurements. Impacts are measured in a quantitative way for the GLOBIO terrestrial and freshwater impacts (habitat loss due to land use change, eutrophication due to atmospheric nitrogen deposition, climate change, habitat fragmentation, human encroachment, hydrological disturbance, wetland conversion, nutrient emissions and land use change in catchment). Impacts of pressures that are not covered by


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the GBS (overexploitation, invasive species) are dealt with through a qualitative analysis following the quantitative phase and specific environmental safeguards and policy recommendations are associated to them.


The GBS does not directly cover ecosystem services.


The pressure-impact relationships become imprecise below areas of about 100 to 1000 ha. As a rule of thumb, it means companies with less than EUR 50 million cannot be assessed with enough accuracy.


Using the results of the GBS does not require specialist knowledge and the metrics of MSA.km2 is relatively easy to understand and visualize (the total land area of the Earth is 130 million km2 and about 40 million km2 MSA have been lost, i.e. the combined area of Africa and Europe, which is something anyone can easily understand). Conducting GBS assessments to assess the impact of FI does require specialist knowledge and a training of at least 3 days. The level of efforts depends on the desired level of details, as the GBS can be flexible: quick approximations can be obtained with industry and country-level averages, and more refined assessments can be obtained if more precise data are collected. A quick assessment takes a couple of weeks and uses easily accessible (and existing) data. A typical detailed assessment should require a couple of months and might require the aggregation (or creation) of additional data, e.g. on habitat maps. Carbon footprinting data and results can be re-used as direct inputs of the GBS and the approach is very similar, both in terms of data collection and of concepts (e.g. Scopes 1, 2 and 3, attribution of responsibilities across the value chain, impact factors).


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured The tool can be sensitive to corporate actions if associated detailed data is collected to support these actions. Namely, if the actions impact land use, greenhouse gas emissions, water consumptions, commodity consumptions (or fragmentation, encroachment, hydrological flows at large scales), and data is available to describe the changes, then their impact on biodiversity can be assessed.


The GBS’s main raison d’être is external reporting to meet stakeholders expectations and in particular investors and governments (under future mandatory disclosure of biodiversity footprints). This external disclosure would simply be the direct disclosure of the results of biodiversity footprint assessments conducted with the GBS expressed by Scope (and by business units if relevant).


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Cf. explanations in the table about business applications 3.1 and 3.2. The GBS is designed to assess the contribution of large businesses to the achievement of global and national biodiversity targets. It can also evaluate their contribution towards moving back within the biodiversity planetary boundary. The post-2020 global biodiversity framework may decide to aim (again) to halt the erosion of biodiversity, or set a target expressed with the Living Planet Index (LPI) or with another metric. In both cases, it can be translated into MSA (net variation of MSA = 0 or translation of LPI figures into MSA) and it is possible to assess the contribution of businesses by summing their net impacts up.



o Scientifically well underpinned (best available knowledge and tools e.g. GLOBIO, Exiobase) o Quantitative (and scientifically robust) link between pressures and impacts o Covers all species (not limited to endangered species) and thus adequately captures the trends and risks faced by

biodiversity and associated ecological functionality o Spatially explicit o Covers most drivers for biodiversity loss o Covers most industry sectors and all countries (excluding fishing in particular) o Compatible with site-level data (micro) and international objectives (macro) o Biodiversity input data (MSA, pressure – impact relationships) based on extensive meta-analysis which continuously allows

for adding new studies o Allows for introducing weight factors differentiating ecosystem condition based on protection regime, protected species, etc.


➢ Please describe the weaknesses of the tool according to your insights o Pressure-impact relationships in the GLOBIO model are biased towards the most studied species and ecosystems. o Marine biodiversity is not factored in o Overexploitation, invasive species, chemical pollution and soil degradation are not factored in yet. Quantifying MSA losses

due to pollution (especially pesticides) is being explored. o Remaining shortcomings in reallocation rules (i.e. linking economic activities to pressures)


➢ Please describe planned improvements o Development of characterisation factors for other commodities to cover all sectors:

o Forest logs, oil & gas, raw animal products in 2019 o Other commodities and services (materials from quarries, water and waste services, etc.)

o Including the pollution pressure in 2019 o A critical review of the tool by an independent committee is under way and should be completed by April 2020. The

secretariat of the committee is provided by the (public) French Biodiversity Agency to ensure independence and rigor. o The GBS will remain under development until early 2020: the first biodiversity footprint assessments will be conducted in

2020.


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Turnover by industry and country or production (€)

DI EXIOBASE 3, European NACE rev 2

Company data, public reports

R

Purchases (€) DI EXIOBASE 3, European NACE rev 2

Company data R

Purchases (€) IF EXIOBASE 3, European NACE rev 2

Global dataset from EXIOBASE Input-Output model

M




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Species abundance, species population (number of individuals)

DI Primary data: company data (field ecological surveys)

R

ADD ADDITIONAL INFO FOR YOUR TOOL: Biodiversity state data are rarely (or never) used as it would be extremely costly and complicated. Pressure proxies are used instead.





Biodiversity losses by pressure (MSA.m²)

IF GLOBIO typology of pressures

Secondary data: GLOBIO 3.5

M

GHG emissions (kg CO2-eq)

DI Reported under GHG protocol Scopes

Primary data: company data

Primary data: R

#144 - GHG emissions (kg CO2-eq)


Secondary data: EXIOBASE

Secondary data: M

#15 - GHG emissions (kg CO2-eq) by Scope


Secondary data: EDGAR

Secondary data: M

Land use changes by type and location

DI GLOBIO 16 land use types

Primary data: company data on areas repartitions for each land use between two

R


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time periods (refined assessments)

#142 – GLOBIO & IMAGE land use changes

DI GLOBIO 16 land use types

Secondary data: GLOBIO land use changes (default assessments)

M

N & P concentrations or emissions in terrestrial or freshwater environments

DI - Primary data: o N and P

concentrations

R

#145 – Pollutant emissions (especially N & P)

IF - Secondary data: o EDGAR

pollutants emissions

M

#146 - Pollutant emissions (especially N & P)

IF - Secondary data: EXIOBASE emissions in environmental extensions

M

#1 - Agricultural production data: crops production (t), harvested area (ha)

IF Secondary data: FAOSTAT crops

R

Agricultural production or consumption and associated crops production (t), harvested area (ha)

DI Primary data: company data

R

#18 - Mineral resources throughout the world (t, ha)

IF - Secondary data: USGS

R

Mined mineral consumption or production (t)

DI - Primary data: company data

R


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#129, 130 - Water withdrawal (industrial, agricultural, municipal, total) (m3)

IF - Secondary data: WRI Aqueduct. Water consumption by watershed

M

Water withdrawal (m3) DI - Primary data: company data on water consumption

R

Consumption of commodities other than crops and minerals, services or refined products (in physical units, for example tonnage)


R

#147 – Consumption of commodities deducted from the material account in Environmental Extensions in EXIOBASE

DI - Secondary data: converted from purchases data thanks to the Environmental Extensions of EXIOBASE

M

Wetland conversion (areas and types)


R

Pollution emissions or concentrations

DI and IF - Primary data: company data on

- discharged pollutants - Used pesticides

R

#148, 149 - Pollution emissions or concentrations

DI and IF Secondary data: pollutants databases (CML, USETox)

M


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ADD ADDITIONAL INFO FOR YOUR TOOL: With regard to modelling a hybrid approach is applied. Modelled results of EXIOBASE, GLOBIO and other sources are used to estimate average industry pressures (and impacts) when real data are not available (= ‘default assessment’). When real data on pressures are available, they are instead combined to the pressure-impact relationships provided by GLOBIO to conduct a ‘refined assessment’. At each stage, the best available data are used, with a preference for real data over modelled average values. The GBS can work with different datasets listed below, by increasing order of usefulness in terms of the precision that can be expected from assessments:

• Economic activity data: turnover by country and industry (of the company assessed or of the company a financial institution invested in);

• Pressure data: - Carbon emissions on Scope 1, 2 and 3 - Land use changes (ideally using a 13 habitat types nomenclature including different use intensity for forests, grasslands, agriculture, etc.)

• Comprehensive biodiversity direct data: when very detailed ecological monitoring data are available, the mean species abundance might be directly calculated.






GLOBIO dose-response relationships linking pressures to MSA loss for: - Terrestrial, land use - Terrestrial, human encroachment - Terrestrial, habitat fragmentation - Terrestrial, infrastructure - Freshwater, wetland conversion - Freshwater, hydrological disturbance

Agricultural yields and quantities produced and associated areas Water withdrawal and consumption

Cf. (Janse et al. 2015; Alkemade et al. 2009)



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- Freshwater land use change in catchment: MSA equation linked to the fraction of cropland, pasture and urban land use categories in the catchment


Not treated in the GBS for now / /

Climate change GLOBIO pressure-impact relationship: MSA values (%) and GMTI (°C)

GMTI (Global Mean Temperature Increase) Greenhouse gas (GHG) emissions Global Warming Potential (GWP)

Pollution GLOBIO pressure-impact relationship: - Terrestrial, eutrophication: MSA values (%) linked to nitrogen exceedance - Freshwater, nutrient emissions: MSA values linked to accumulated total nitrogen and phosphorus concentrations Incoming other pollutions: CML databases

Emissions of pesticides, N & P concentrations Other pollutions: PAF (potentially appeared fraction)

Cf. (Janse et al. 2015; Alkemade et al. 2009)


Not treated in the GBS for now / /

Other


Drivers (GLOBIO) include: land conversion, fragmentation, encroachment, atmospheric N deposition (eutrophication) and climate change for terrestrial biodiversity, and wetlands conversion, local and network land-use in catchment of wetlands, hydrological disturbance of wetlands and rivers, land-use in catchment of rivers and eutrophication of lakes for aquatic biodiversity. Missing drivers will be added to GLOBIO through future developments.


components The GBS uses the Mean Species Abundance (MSA) and its surface area equivalent, i.e., MSA.km². The latter is the product of MSA multiplied by the area to which it applies (expressed in km²). MSA measures biodiversity intactness relative to its abundance in undisturbed ecosystems. A 100% ratio indicates an intact ecosystem while damages caused by an increase of pressures bring the


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MSA progressively to 0% when all originally occurring species are extinct in the ecosystem. Cf. the GLOBIO tool for more details on the MSA.



The GBS is based on a single metric focused on biodiversity:

• The Mean Species Abundance (MSA) allows to express the loss of biodiversity as the destruction of virgin natural areas. This synthetic metric gives a quantitative account of the multiple anthropic pressures that simultaneously impact ecosystems and their consequences on all components of biodiversity (species, taxa).

• The MSA represents biodiversity for itself, not the value of the services it provides.

Beside, the tool holds qualities on which any biodiversity footprint assessment tool intended to evaluate the footprint of companies and financial institutions for a reporting purpose should be built:

• The scale of the analysis is global, for the economy is globalized, and spatialised, because biodiversity issues and associated impacts are necessarily local.

• The underlying methodology is transparent and consensual.

• The tool is flexible, so that the footprint of companies improves as they put efforts into the reduction of their impacts.


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9. Kering’s Environmental Profit & Loss approach

FICHE NR 9 ENVIRONMENTAL PROFIT & LOSS ACCOUNT (EP&L)

1. Date of assessment • 19/08/2019

2.Actors ➢ Mention at least ‘lead’ and ‘other’ Lead: KERING A global Luxury group, Kering manages the development of a series of renowned Houses in Fashion, Leather Goods, Jewelry and Watches: Gucci, Saint Laurent, Bottega Veneta, Balenciaga, Alexander McQueen, Brioni, Boucheron, Pomellato, Dodo, Qeelin, Ulysse Nardin, Girard-Perregaux, as well as Kering Eyewear. https://www.kering.com/ Other: The E P&L and the associated methodology were developed with the support of PricewaterhouseCoopers LLP http://www.pwc.co.uk



Business Applications!) and if case studies are available (please refer to links or publications) Since 2012, Kering has been working on the creation and deployment of its Environmental Profit and Loss account (EP&L), the stated objective given in 2012 being to cover 100% of the Group’s activities by 2015. In 2013, six brands were covered by the EP&L (on the basis of their 2012 data), which allowed the Group to report the findings of the project in relation to 73% of the Group’s 2012 revenue. Kering successfully covered all of its activities in 2013. Since then, Kering has measured and quantified its progress toward becoming a more sustainable Group through its Environmental Profit and Loss account (EP&L). The cornerstone of its environmental approach, it also serves as a management tool by which Kering lays out its roadmap for the coming years in terms of sourcing strategy and choice of materials. Kering has undertaken to reduce its EP&L intensity by 40% by 2025 compared with 2015. In 2018, Kering was for the first time able to testify to its progress towards the goal of reducing its EP&L under its new profile as a Luxury pure player. Meanwhile, the methodology is shifting towards even greater robustness, with transparency as the highlight through the increasing number of exchanges and collaborations around natural capital accounting. > https://www.kering.com/en/sustainability/environmental-profit-loss/ > https://keringcorporate.dam.kering.com/m/4cf9e7e0187fd328/original/Environmental-Profit-and-Loss-report-2018.pdf > https://kering-group.opendatasoft.com/



those not supported by the tool and the reasons why! The EP&L measures carbon emissions, water consumption, air and water pollution, land use, and waste production along the entire supply chain, thereby making the various environmental impacts of the Group’s activities visible, quantifiable, and comparable. These

https://www.kering.com/

http://www.pwc.co.uk/

https://www.kering.com/en/sustainability/environmental-profit-loss/

https://keringcorporate.dam.kering.com/m/4cf9e7e0187fd328/original/Environmental-Profit-and-Loss-report-2018.pdf

https://kering-group.opendatasoft.com/


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impacts are then converted into monetary values to quantify the use of natural resources. Kering can thus use the EP&L to guide its sustainability strategy, improve its processes and supply sources, and choose the best-adapted technologies. In doing so it helps us: − Translate environmental impacts into a language business understands; − Compare between different types of impact; − Facilitates comparison between brands and business units. As a result we can: − Identify the most significant drivers of impacts in our business; − Understand the impact of every day decisions; − Develop more robust business policies to address the risks and opportunities presented by environmental challenges; − Implement targeted projects concerning choice of materials, or development of new manufacturing processes, for example; − Monitor progress of our sustainability strategy, while forecasting and preparing for the future; − Be transparent with our stakeholders.

5.Business sectors ➢ Describe business sectors covered by the tool The EP&L methodology is valid for all sectors, however, the underlining datasets and assumptions used in Kering’s EP&L are specific to Kering’s activities and are therefore covering the Luxury and fashion industry. When releasing its first EP&L, Kering committed to open source the EP&L methodology and influence other stakeholders towards natural capital accounting practices. In 2019, linked to the 2018 Group EP&L results, Kering made a major step forward in open sourcing its approach thanks to a dedicated digital EP&L platform. To mark World Environment Day on 5 June, Kering launched an open source platform allowing everyone to access an interactive version of its EP&L results. Through the new digital EP&L platform, the underlying aggregated EP&L data sets have also been shared, including the Environmental Key Performance Indicators (EKPIs). This level of transparency allows unprecedented access to information about the relationship between business and the natural resources business relies on. Consequently, Kering’s stakeholders will have greater understanding of our impacts and supply chain resiliency. Furthermore, the data sets provide enough details to enable other luxury and fashion players to initiate their own EP&L analysis and begin their natural capital accounting journey, which will offer critical new insights into their business and a pathway to mitigate their footprint.


➢ Provide concise but clear description of the methodology.

An EP&L is a means of placing a monetary value on the environmental impacts along the entire value chain of a given business. More than 70 indicators of emissions and resource use, grouped into 6 environmental impact areas, are measured or estimated along


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the supply chain. The likely environmental changes that result from these emissions or resource use are estimated based on the local context and the consequences of these changes on people’s wellbeing, and are valued in monetary terms.


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The 7 step process to generating an EP&L


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7.Additional features Focus on biodiversity Through its Landuse environmental impact Group, the EP&L is valuing ecosystem services and biodiversity impacts: Impact pathway for landuse


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Summary of land use valuation methodology:


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8.Ecosystem services The E P&L methodology aims to estimate the economic value of lost ecosystem services associated with the conversion and occupation of land. These economic values are associated with the benefits society gains from ecosystems, such as climate regulation, bioprospecting, food and fuel as well as recreation, cultural experiences or education. Option values that reflect potential future use values are also considered. The following table presents the classification of different ecosystem services which can be affected by the conversion and occupation of land used in our analysis. It is the change in value to society of these services from different types of natural ecosystems (and subsequent land use practices) that this methodology values. The methodology only explicitly values final ecosystem goods and services, as the inclusion of supporting and intermediary services would lead to double counting. The value of supporting and intermediary services is captured through their contribution to final ecosystem goods and services. For example, the benefits of nutrient cycling in soils is captured by the productivity of those soils and provisioning of food and fibre. This is in line with the methodological recommendations of CICES (Common International Classification of Ecosystem Services). Timing of conversion is an important consideration for this methodology because many natural areas were converted long ago, and have changed uses and ownership many times since while others may have been converted partially or fully more recently. To deal with this in the E P&L, we estimate the ecosystem service reduction in the current year, relative to its natural state, and assign the reduction in value to the current occupant of the land, irrespective of whether that occupant was directly responsible for the conversion of the land. This approach was chosen because: 1. It reflects the flow of impacts which are created as a result of occupation, and are dependent on the management practices which the current occupier chooses to employ (even if others are responsible for the pre-conditions). 2. It incentivises current land occupiers to minimize the loss of ecosystem services, for example through sustainable land management practices. 3. It avoids making highly uncertain assumptions as to the future extent of lost ecosystem services or the date of past conversions.


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9.Granularity level The granularity provided by the EP&L for its Landuse dimension is directly linked to the granularity of the GIS data sourced from the WWF Wildfinder to classify each location of land use into eco-regions.

10.User friendliness In order to support business decision-making, the E P&L has to be based on as much primary, company-specific data as is realistic and feasible to collect from suppliers and Kering’s brands. However, it is not feasible or efficient to collect data from all activities in the supply chain so it is necessary to fill the gaps with secondary data. The table below summarises the main types of secondary data estimation techniques that could be used in the E P&L.


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An Environmental Profit and Loss (EP&L) account is a business management tool providing an in depth analysis of the resulting impacts a company’s activities have on the environment, which also helps decision makers consider this valuable information alongside traditional financial metrics.






➢ Please describe the weaknesses of the tool according to your insights


Kering is committed to add the used phase and end of life step to its EP&L scope and methodology.


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10. Life Key

FICHE NR 10 LIFE Methodology Metrics: Biodiversity Impact Index + LIFE Biodiversity Positive Scoring + LIFE Minimum Biodiversity Compensation


• First version 20/08/2018

• Update on 2/11/2018

• Update on 31/07/2019

2.Actors Lead: LIFE Institute LIFE Institute is a non-profit organization headquartered in Brazil who operates internationally the development and implementation of LIFE Methodology, its tools and Certification System, including the accreditation of independent Certifying Bodies. Other: LIFE Permanent Technical Committee: Business: ABN AMRO; Posigraf; ITAIPU; Boticario Group; Japan Tobacco International – JTI. Civil Society: Sociedade de Pesquisa em Vida Selvagem e Educação Ambiental – SPVS; Boticario Group Foundation; Neotropica Foundation; Mar Brasil Association. Academia: Federal University of Rio de Janeiro – UFRJ; Federal University of Paraná; University of São Paulo; Instituto Nacional de Pesquisas da Amazônia – INPA; Federal Technical University of Paraná. Government: Instituto Chico Mendes de Conservação da Biodiversidade – ICMBIO. Sponsors: Itaipu Binacional, Petrobras. Partners: Fundación Avina, Itaipu Binacional, Fundação Grupo Boticário, Gráfica e Editora Posigraf, JTI, Funbio, Conestega-Rovers e Associados, MPX, Magistral Embalagens. Supporters: Convention on Biological Diversity, Cebds, CNI, Gaia Silva Gaede Advogados, Gryra Paraguay, Prefeitura Municipal de Curitiba, SPVS, Unilivre, KPMG, Zig Koch, Master Comunicação e Tecpar.


Please describe the development process and stages Please describe if the tool has been road-tested (add this information also in the table ‘Categories of Business Applications!) and if case studies are available (please refer to links or publications)

LIFE Metrics process involved the following stages: 1. Methodology and metrics conceptual framework development 2. Public meetings (Rio de Janeiro, São Paulo, Brasilia, Curitiba) and online consultations 3. Establishment of a Permanent Technical Committee (Academia, NGOs, Business) 4. Launch of LIFE Methodology – Brazil 5. Two phases of Pilot testing in companies of secondary and tertiary sectors: hydroelectrical power; thermal power, cosmetic; graphic,

office and industrial printing 6. Development of a third-party audit system framework 7. First LIFE certification in Brazil 8. LIFE Methodology adaptation for Primary Sector


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9. Technical and official data adaptation for LIFE Methodology – Paraguay 10. Launch of LIFE Methodology for Paraguay

a. public consultations focused on GMOs and agrochemical impacts b. research project with IPEF (Forestry Researches and Studies Institute) to define water consumption estimates for forestry

activities c. primary sector pilot testings (9 companies in Brazil and Paraguay) – 2010/2011

11. Development of a software to calculate LIFE metrics 12. First LIFE Certification in Paraguay 13. First public reports of LIFE certified companies (https://www.tecparcert.com.br/en/life/) 14. Companies using LIFE software for biodiversity management purposes, besides the Certification interest 15. European adaptation process under analysis 16. Study analysing the results of LIFE Methodology and metrics application in some companies from 2015-2018. The study will be published

in 2019.


• Complete table ‘Categories of Business Applications’

• Add short summary in the style below, highlighting not only the BA that are supported by the tool but also those not supported by the tool and the reasons why!

Short summary of 3 LIFE Metrics:

o A. Biodiversity Impact Index (BII) What is it? Index varying from 0-1.000 that considers technical data related to companies´ impacts and their relationship with ecosystem´s risks. Business applications supported: Corporate level assessments: Definition, calculation, comparison in the same scale (among business units of the same company, or among companies or sectors), and monitoring of biodiversity footprint. Basis for portfolio and supply chain analysis, as long as it remains at the biodiversity impact level of sectors or companies Country and project level assessments: information not available yet. It depends on future studies and simulations. Business applications not supported: It is not the most suitable index for assessments at project level. It is not suitable to indicate no net loss. Not species specific. But it is ecoregion and hydrographic region specific (this indicates it can be used for country assessments – but more studies are needed for this case).

o B. Biodiversity Conservation Actions (BCA) What is it?


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A score that indicates biodiversity positive performance considering different biodiversity and ecosystem services results expected from different kinds of environmental projects and actions implemented. The scoring system considers national, international, regional and local biodiversity conservation priorities and the information is country based. Business applications supported: Corporate level assessments: Allows the project´s calculation, monitoring, and “investment x results” analysis considering Biodiversity Positive Performance, relating them to national, international, regional and local conservation priorities Country level assessments: the scoring allows to identify the ecoregions and protected areas that are receiving more investment and attention by the private sector. Project level assessments: the scoring applies to evaluate and compare different projects related to their biodiversity and ecosystem services performance. Business applications not supported: It is not suitable to indicate no net loss. Why: it does not relate deforestation area with conservation or protected areas. C. Minimum Biodiversity Performance (BCAmin) What is it? A minimum scoring calculated using BII and company size (gross revenue) that indicates a minimum biodiversity positive scoring to be performed by the company. Business applications supported: Corporate level assessments: allows a common basis analysis of the “balance” between negative and positive performance of business units, companies and sectors. Business applications not supported: studies needed for country and project level assessments availability. Why: it was first designed to be applicable to the corporate level.

5.Business sectors

➢ Describe business sectors covered by the tool

• The metrics are applied for any sector.

• Already used in companies of primary, secondary and tertiary sectors: finance sector; hydroelectrical power; thermal power, cosmetic; graphic, office and industrial printing; agriculture; forestry; cattlement.

• Scenarios and estimatives can be provided for any sector.


➢ Provide concise but clear description of the methodology. Please be aware that we will add separate sections in the new

update report on Globio and ReCiPe, so if your tool is making use of these models, you only need to make a brief reference to

them. LIFE Methodology points of intervention are:


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• Biodiversity impacts analysis (BII metric) – described before

• Biodiversity positive performance (BCA and BCAmin) – described before

• Biodiversity Management Performance: 74 management indicators with objective verifiers – here the Methodology contemplates HCV (High Conservation Value and No Net Loss approaches (Principle 3 – relations between land conversion and protected areas).

All this steps or modules of LIFE Methodology are available for LIFE Key software users.

7.Additional features

Baseline or reference ➢ Please describe if this is defined in the tool and how (be aware subgroup 2 is working on clear definitions but we just want to

know how these terms are interpreted in your tool) Reference Value: is a term used in LIFE Technical Guide 01 meaning the national reference value used to calculate the company relative impact in the country on a national basis.

Materiality assessment ➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken

Not yet. It will be available in the module for Ecosystem Services Analysis – impacts, risks and opportunities.

Impact boundaries ➢ Only for tools that cover site level and project level business applications: Please describe if the perimeter assessed in the

tool is limited to the direct operations within the site controlled by the company? Or does it cover a wider area of influence? The perimeter assessed by BII is limited to the direct operations within the site controlled by the company. Even if there is another companies operating there, their impacts also should be informed. For the BCA scoring (positive performance on biodiversity) all corporate projects must be evaluated, even those being implemented somewhere else. LIFE Methodology requires a minimum of 30% scoring in the same ecoregion where the negative impact occurs.

Impacts and dependencies ➢ Please describe if the tool also addresses dependencies (see also question on ecosystem services below), and how.

To be developed a specific module integrating negative/ positive metrics with risks, opportunities and dependencies on Ecosystem Services.

Valuation ➢ Still to be developed a financial valuation module (negative/ positive impacts and dependencies on ES) ➢ LIFE metrics of LIFE Methodology evaluates positive and negative impacts on biodiversity on a quantitative way ➢ LIFE Methodology evaluates performance and changes on biodiversity management on a qualitative way


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Ecosystem Services ➢ LIFE Methodology still covers ecosystem services in a qualitative way ➢ To be launched the specific Ecosystem Services module (integrating negative/ positive impacts and dependencies on ES) ➢ The classification used is that from Ecosystem Services Review (ESR) ➢ Company will have to fulfill the information for each service, relating the impacts (using BII), risks and opportunities

9.Granularity level

➢ Please describe the range of granularity levels (in quantitative terms) that can be applied by the tool (if relevant for each of the different organisational focus areas referred to in the ‘Business applications’ table) The BII value remains nearby 1,0 or less in the 0-1.000 scale for small companies. It is part of the normal behaviour of the index and its monitoring keeps the same results on the corporate level management.

10.User friendliness

➢ Please describe: o LIFE Key Software is accessible via the Internet. Navigation based on Windows and Office templates. o The tool can be used by non-experts o Specialist knowledge is desirable for better data refining, strategies definition and results interpretation o The time needed to apply the tool depends of the business boundaries and complexity and can vary from some hours to some

weeks or months o Efforts depend on the level of detail sought, especially in relation to conservation projects and biodiversity action plan. The first

full and detailed assessment should take a few weeks and annual updates are much quicker taking some hours or days d depending on the size and complexity of the business.

o The tool uses also data generated by external tools as Water Footprint (for agriculture only) and GHG Protocol o As the regional evapotranspiration of forest plantations is not available in the water footprint tool and is an information required

for the BII in the forestry sector, it was developed by LIFE/IPEF and is also available in the software. This calculation requires only the selection of the species and municipality.

o MSA (Mean Species Abundance is applied to better analyse biodiversity in the area occupied by the company o Data not available by the company or not generated by external tools can be estimated by the company o The different modules of the methodology can be used separately for specific evaluations


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured Corporate Action Tool Sensitivity

Water consumption reduction BII reduction Water Impact Index reduction

Energy usage reduction BII reduction Energy Impact Index reduction

Waste generation reduction BII reduction


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Waste Impact Index reduction

Area restoration BII reduction Area Impact Index reduction

GHG emissions reduction BII reduction GHG Impact Index reduction

Areas restored Threaten species protection Protected areas implemented and managed for conservation Biodiversity studies and conservation projects implemented Biodiversity corridors implemented Biodiversity data collection and dissemination

BCA scoring improvement

Benefit sharing implementation Biodiversity conservation statement on the Environmental Policy Biodiversity risks evaluation on the supply chain Commitment with biodiversity laws and treaties Biodiversity negative and positive impacts monitoring Biodiversity Conservation Actions as law additionality

% of management indicators attendance improvement


➢ Please describe if the measurement approach has been designed to reflect external reporting requirements, if so, which and how LIFE Methodology was designed to reflect the Convention of Biological Diversity purposes, mainly: converging private sector efforts to national biodiversity priorities. This is done by the BCA metric which scores highly the areas, ecoregions and species with higher national conservation priority. LIFE also includes Aichi targets in the Principle 7 of LIFE Biodiversity management standards (qualitative indicators). For example, company has to present their ways to share the benefits of the use of biodiversity resources.

13.Policy targets

➢ Please describe if the measurement approach is designed to reflect or link into global targets on biodiversity e.g. Aichi targets or the SDGs and if so, how you envisage this link developing Yes, the Methodology was designed to global targets, as: o Aichi Target: see Principle 7 of LIFE Biodiversity Management Standards. o Global targets on biodiversity: Ecorregions classification and fragility (WWF – Wildfinder); national biodiversity priorities; IUCN

protected areas classification. o SDGs:


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➢ Please describe the strengths of the tool according to your insights o Scientifically well underpinned (best available knowledge and tools e.g. GLOBIO, Exiobase) o Quantitative (and scientifically robust) link between pressures and impacts o Covers all types of biodiversity and thus adequately captures the trends and risks faced by biodiversity and associated ecological

functionality o Spatially explicit o Covers most drivers for biodiversity loss o Covers all industry sectors and all countries o Compatible with site-level data (micro) and international objectives (macro) o Biodiversity input data (MSA, pressure – impact relationships) based on extensive meta-analysis which continuously allows for

adding new studies o Allows for introducing weight factors differentiating ecosystem condition based on protection regime, protected species, etc. o Focused on Biodiversity and ES conservation o Pragmatic tool (software) applicable to organizations of any size and sector o Complementarity between qualitative and quantitative approaches o Designing of strategic conservation plan scenarios considering international and national biodiversity priorities o Measures, evaluates, monitors and compares business positive and negative impacts o Enables comparability between companies, business units and sectors o Issues executive and detailed reports for clear and transparent results communication to different stakeholders o Possibility of recognition by third-party Certification o Strategic orientation to assure investment return in conservation by focusing on concrete actions


➢ Please describe the weaknesses of the tool according to your insights o Need for prior adaptation by country or region o Visibility of returns on investment (business as usual perspective) o Scaling-up pace o Still to be developed a financial valuation module (negative/ positive impacts and dependencies on ES)


➢ Please describe planned improvements o Develop the Ecosystem Services module to integrate positive and negative impacts, as well as monetary values for the ES o Continuous mathematical calibration o Update national environmental data o Continuous on estimates for sectorial comparisons o Publish the first study of LIFE Methodology: behaviour and use of its results o Adaptation for Europe and Latin America.


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➢ Please complete the following tables. These are intended to collect more insights on input data, midpoint indicators, impact

pathway approaches etc. You can add additional info if you wish. Be aware that these tables also replace separate rows in the

previous template: ‘type of modelling’, ‘drivers for biodiversity loss’ (now covered by impact groups), ‘data’. Four tables are distinguished:





Table 1: Economic activity data inputs

Economic activity indicator (unit) ((e.g. turnover of company, purchases in €, etc.)



Gross revenue (U$/year) – updated annually

Gross revenue Company Real

Investment on environmental projects (U$ or local currency)

Investment Company Real

ADD ADDITIONAL INFO FOR YOUR TOOL: Gross revenue is used besides the Biodiversity Impact Index (BII) to calibrate the minimum biodiversity performance of the companies. Investments on each one of the environmental projects allows to analyze the balance between investment and biodiversity performance (scoring).

Table 2: Biodiversity state data inputs

Biodiversity state indicator (unit)

Data input (DI) or used to build

Nomenclature used

Data source (company or global data sets? if global data sets, which one?)




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impact factors (IF)?

Severity of ecoregion occupation with business activities.

IF Area occupation - severity index

LIFE severity index for area occupation. Uses MSA (Globio) as part of the calculations. Categories must be adapted to each country (validated by a national technical committee). Company informs the occupation areas and their classification.

Modelled.

Ecoregions world classification

IF Ecoregion WildFinder (WWF). Modelled.

Ecoregion Fragility – terrestrial and marine ones

IF Technical Qualifier: Ecoregion hierarchy

LIFE Research&Development (Projects designed and developed by LIFE with universities).

Modelled. Confidence data: high

Status of conservation of natural vegetation

DI Technical Qualifier: Status of conservation of natural vegetation

Company. Real: images and field confirmation

Biological Importance of the Area

IF Technical Qualifier: Biological Importance

Governmental. Modelled

Threaten category of species IF Technical Qualifier: Threaten category

Global data – IUCN and local government. Real

Length and width of biodiversity corridors

DI Technical Qualifier: Biodiversity corridors

Company. Real

Stage of vegetal dynamics DI Technical Qualifier: Vegetal dynamics

Company. Real – field assessment

Protected area category DI Technical Qualifier:

Government/company (IUCN categories).

Real


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Protected Area Category

Restored areas DI Technical Qualifier: Restored Areas

Company. Real

ADD ADDITIONAL INFO FOR YOUR TOOL: Ecoregion classification, fragility and severity of ecoregion occupation with business activities are information used to calculate Biodiversity Impact Index (BII). Information used in Biodiversity Positive Performance Scoring (BCA metric– Biodiversity Conservation Actions): Ecoregion fragility hierarchy/importance for conservation Status of conservation of natural vegetation Biological Importance of the area preserved Threaten category of species Length and width of biodiversity corridors Stage of vegetal dynamics Protected area category Restored areas

Table 3: Pressure data inputs

Pressure indicator (unit)



Water usage – quantity Water Impact Index (component of BBI)

Company: water consumption in m3/year). Governmental agencies: country total consumption.

Company: Real Government: modelled.

Water usage – severity Water Balance (use x scarcity) by hydrographic region.

Government: modelled.

Waste generation – quantity Waste Impact Index (component of BBI)

Company: annual generation in t/year. Governmental agencies: country total generation.


Waste generation – severity LIFE impact matrix that considers hazardous and destination

Information by LIFE Institute.

Energy consumption – quantity

Energy Impact Index (component of BBI)

Company: annual consumption. Governmental agencies: country total consumption.



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Energy consumption – severity

LIFE impact matrix that considers kind of energy (for 15 different sources) and their biodiversity impact.

Information by LIFE Institute.

Greenhouse gas emissions – quantity and severity

GHG Impact Index (component of BBI)

Company: annual emissions – scopes 1, 2 and 3 (tCO2/year). Governmental agencies: country total emissions. Global Warming Potential (GWP): as informed by IPCC last report.

Company: Real Government: modelled. IPCC: modelled.

Area occupation – quantity Area Impact Index (component of BBI)

Company: area occupied and classified by MSA. Governmental agencies: original natural areas of each ecoregion.

Company: Real Government:Real

Area occupation – severity Ecoregion fragility hierarchy Information by LIFE Institute.

ADD ADDITIONAL INFO FOR YOUR TOOL: Results of BBI are used to estimate average industry pressures, impacts or risks on local ecosystems – here represented by ecoregion and hydrographic region. The impact of business activities, as water consumption, energy usage, GHG emissions, waste generation and area occupation are put together to represent the risk of biodiversity loss in a determined ecosystem. At each company, the best available impact data are used and monitored by auditors annually, so data can be improved each year. There is a preference for real data over modelled average values (acceptable when real data is not available). In such cases companies are required to provide data for next years. To estimate GHG emissions companies are using GHG Protocol. To estimate water footprint in the agriculture, LIFE indicates the use of the tool provided by Water Footprint Network. But, as it does not covers forestry information, LIFE Institute has developed together with Forestry Studies and Research Institute (IPEF) an estimation of regional evapotranspiration for pinus and eucalyptus plantations in Brazil. Land use changes are represented in two ways: kind of occupied area informed by company (builds, forests, grasslands, agriculture, etc.) using MSA index; and changes in the ecoregions, as indexes developed by LIFE Institute (using official data), considering original and updated information about deforestation in ecoregions.

Table 4: Impact pathways and dose-response relationships


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Pressure on biodiversity (IPBES main drivers)


Midpoints22 involved? Confidence level of the dose- response relationships?

Land / sea use change Area Impact Index. Sources: company information, MSA, Ecoregions fragility hierarchy (% of lost of natural ecosystems´ areas (terrestrial and marine). Sources: ecoregions international classification (WWF-Wildfinder); deforestation governmental official data.

Limited to the boundary of the business unit under evaluation.

Medium


Supply-chain impact analysis. Evaluation developed by each company considering LIFE guidelines (identify the threaten and invasive categories of organisms used in the production; identify of invasive categories of organisms used species, sectorial certifications involved for control, law attendance verification).

Extended to 100% of direct suppliers. (LIFE Methodology considers as direct suppliers all those which materials or products compounds the final costs of the client).

Climate change GHG emissions Impact Index. Sources: company information, Global Warming Potential, GHG Protocol, IPCC.

Scopes 1, 2 and 3.

Pollution In part can be evaluated by waste generation, hazardous and destination. Verified company by company considering sectorial law.

Limited to the activities developed by the business unit under evaluation.



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Data nor informed directly in the BII calculations because the index development required standardization among companies and sectors.

Invasive alien species Verified company by company. Specific number or value related to invasive species is not informed directly in the BII calculations.

Limited to the boundary of the business unit being evaluated.

Other


BII drivers include land conversion, terrestrial and marine ecoregion fragilities, climate change, water use (green and blue water) and water scarcity, pollution (waste generation, hazardous and destination). Fragmentation, encroachment, atmospheric N deposition and others are evaluated by the qualitative approach of LIFE Methodology (Biodiversity Management Standards – Principles, criteria, indicators and verifiers).

18.Metrics ➢ Please describe the type of impact metrics applied by the tool ➢ If the tool does not use any synthetic metric, please describe briefly the specific metrics of each of its components

BII measures environmental impact and works as a proxy indicator to represent the risks for ecosystems loss. BII uses water, GHG, area, waste and energy impact indexes calculated by the software individually. Afterwards theses indexes are multiplied and results on the BII, which varies from zero to one thousand. In that scale zero would be none risk and 1.000 would be very risky. The mathematical formula does not allow a risk of 1.000 because it would be represented by the consumption or degradation of 100% of natural resources of the country. BII is country calibrated using real environmental information made available by companies sustainability reports. For the national calibration the higher impacts for each variable is considered as the number 850 in that scale. So, the BII represents the relative impact of the company in the national scenario, where the total national impact would be 1.000.




• Feasible to any kind of company (size and sector)


• Measures biodiversity negative and positive performance (balance)



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• Validated by public consultation

• Mathematical behaviour tested and validated

• Complemented and compatible with management indicators


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11. Product Biodiversity Footprint

FICHE NR 11 PRODUCT BIODIVERSITY FOOTPRINT (PBF)

1. Date of assessment • First version by I Care & Consult on 20 June 2018

• First review EU B@B Platform on 6 August 2018

• Update by I Care & Consult on 23 August 2018

• Update I Care & Consult in August 2019

2.Actors Lead: I Care & Consult, Sayari Other:

- Public support (AFB, ADEME) + Companies who tested the PBF methodology (L’Oreal, Kering, Avril)

- Scientific committee: members of the following organizations: MNHN, UN Environment, IUCN, Irstea, Solinnen, IUCN, ELSA

Pact



Business Applications!) and if case studies are available (please refer to links or publications) I Care & Consult launched Product Biodiversity Footprint project in 2017 and was rapidly joined by Sayari as co-developer. Aim of the project is to elaborate an operational methodology to assess biodiversity impact at product level, mixing ecology know-how with LCA know-how

The project is progressing at 3 levels

o Global PBF methodology: overall principles to evaluate the impact on biodiversity at product level (metric,

LCA methodology, biodiversity databases, …)

o PBF sector referential: specific rules for each sector in order to integrate the specific sector pressures and

ecological studies

o Case study: real tests on real company products to ensure applicability of the PBF sector referential The phase 1 of the project (2017/2018) enabled

- Release of first Global PBF methodology

- Definition of PBF Agriculture and agri-based products referential

- 3 case studies on 3 products: shower gel, cashmere wool pullover, rapeseed oil

- Peered reviewed publication (submitted) Phase 2 of the project (2019/2020) is underway with

- Upgrade of Global PBF methodology: aggregation of impacts, integration of ecotoxicity, ..

- 2 new Sector referentials: Energy, Extraction & Construction materials

- 5 to 10 new case studies


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• PBF is mainly a LCA based approach and as such its best business application is Comparing options at Product Level,

• Like other LCA approaches, other business applications are possible o Assessment of current biodiversity performance: the absolute performance can be evaluated by PBF, based on

current practices and formula of the product o Assessment of future biodiversity performance: PBF, such as other LCA approaches, can also be used as a

simulation tool, using future formulas and practices o Tracking progress to targets: as an LCA quantification tool, PBF can also support

▪ Planetary Boundaries approach: Links between LCA and Planetary Boundaries are being established since a few years and PBF could serve as a tool to support tracking progress to Planetary Boundaries targets at product level.

▪ No Net Loss approach: as other LCA approach, PBF is able to assess net positive and negative impact and can therefore be used to support such an approach

▪ Voluntary standards at product level: PBF can support voluntary standards to assess the quantification of the benefits of the standard, and has been doing so in one case study (RSPO)

▪ Corporate-level biodiversity commitments or engagements: PBF can support corporate engagement of designing and manufacturing products with lower impact on biodiversity

• As other LCA approaches, PBF is also suitable for assessment at other organisational levels, even if it is less practical than at product level

o Project level: a specific project can be modelized with LCA approach, taking therefore into account upstream and downstream life cycle phases of the project. As PBF enables the use of adapted impact factors, it can be adapted to specific project characteristics.

o Supply chain level: Supply chain assessment is within the DNA of PBF, helping companies to focus at the stage of the supply chain that matters, very often at the raw material stage.

o Corporate level: if a company produces a limited number of products/services, its impact on biodiversity can be assessed by adding the impact of its products and services, using PBF approach. It would nevertheless require that PBF assess the main products of the company, which might not be always possible.

• PBF is not the most suitable for the assessment at the following organisational levels: o Assessments at site level: as PBF is a “process modelization tool”, very site-specific data are better taken into

account by other approaches


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o Assessment at portfolio level: investment portfolio is a combination of different companies and PBF is not yet simplified enough to be scaled to this level of assessment

• PBF is not the most suitable tool for the following business applications: o Tracking progress to high level societal targets such as Aichi targets or EMS requirements, Regulatory and permitting

requirements, o Biodiversity Return on Investment o Assessment/rating of biodiversity performance by third parties o Certification by third parties

5.Business sectors • All sectors




brief reference to them.

Global scheme of PBF.

Enhancing LCA with biodiversity knowledge


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To be easily adopted by companies for product assessment, the method is ‘LCA based’, meaning it adopts a value chain approach, uses LCA is connected to LCA databases and compatible with LCA assessment framework (Chaudhary et al. 2015, Verones et al. 2017), so that this additional biodiversity assessment can be seen as an add-on to LCA global assessment. Therefore, the choice made for PBF method is to enhance LCA with biodiversity knowledge. PBF has a spatialised approach and focuses to the specific location where biodiversity impact happens. LCA methodology used so far by PBF is ‘LC Impact’ but PBF can connect to other reference methodologies, such as ‘ReCiPe’ or ‘Impact World +’. Covering a large scope of impacts The method covers the 5 pressures on biodiversity identified in the Millennium Ecosystem Assessment (2005). Biodiversity knowledge included in the LCA framework is based on ecological publications specific for each pressure and on available global biodiversity database to assess the state of biodiversity. Discriminating capacity The main objective of PBF is to improve the biodiversity performance of a product by identifying biodiversity hotspots that can be improved and support eco-design approaches. In order to have such a capacity the PBF has a strong discriminating capacity: the method aims to identify between the variants of a product the one with lowest impacts on biodiversity. This discriminating capacity is fuelled by the introduction of correction factors to LCA methodologies, these correction factors being provided by biodiversity studies and databases.


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Baseline or reference


Baseline used for PBF assessment if Pristine state; However as main business application is comparing options, the question of baseline is not so important in the use of PBF, as thy are substracted when comparing options. PBF is then completely flexible for the choice of the refernce product: in most cases, reference is the “standard” production of the product within a standard value chain and raw material supply chains.




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The first phase of PBF (module 1) can be used as a biodiversity impact screening and therefore for materiality assessment. Module 2 will focus on the biodiversity hotspot(s) both within the value chain and amongst the drivers. For this part, it then adopts a spatialized approach looking deeper into specific practices.

Impact boundaries


The tool is designed to cover the whole value chain or supply chain, depending on the boundaries set by the company for their product or service design.



PBF delivers explicitly a measure of impact and not of dependence. However, as PBF is tracking the substances used in the product, it could also support partially a process of assessment of dependency.

Valuation

Impact is valued in a quantitative way but is not monetized

8.Ecosystem services No coverage of ecosystemi services


The granularity level of PBF can be adapted thanks to the integration of ecological studies to specific areas important for the biodiversity impact of the product. It can therefore integrate some specific practices at a very granular level (eg. One Ha).


• Required expertise:


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There is a need for both an LCA expert and a biodiversity expert, to gather the necessary input data for PBF tool. • Time effort Time effort is limited, quite similar to a normal LCA (provided that underlying biodiversity data are already existing): 10% ETP during 4 months for LCA specialist and 10% ETP during 4 months for biodiversity specialist • Specificity of the approach The approach is actually a mix of other environmental approaches already existing in the company: LCA approach and impact study approach • Communication of results Thanks to the spider graphic, it is very easy for a non-expert to understand the results of PBF NB : We are currently working on integrating the results of the main raw material assessment in the ecodesign database and system of a large company. This data will then be used by product developers in their design process with minimum effort.


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured The tool is very sensitive to management actions, as it integrates the impact of company processes (through LCA), local biodiversity practices (ie. agricultural, mining biodiversity practices), localization of sourcing, …. PBF has been explicitly designed to be sensitive to corporate management actions


The tool can be used indirectly to assess and report on ecodesign efforts on the topic of biodiversity.



• Please describe the strengths of the tool according to your insights The testing of the PBF methodology has revealed the following main strengths

• A full “product” approach, encompassing all the lifecycle of the product and not only one specific phase (e.g. agriculture production)

• Ability to reveal the impact of the positive biodiversity actions of a company along the product lifecycle (sourcing, production practices, …)

• Capacity to combine both “database modelized information” and real company data, so that it reduces the need for input data from the company but also positions the specific product performance vs. average product performance

• coverage of all pressures on biodiversity (and not only impact of land use or climate change, but also pollution, exploitation of species, … )

• Quantitative (and scientifically robust) link between pressures and impacts

• Covers all industry sectors and all countries


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• Biodiversity and LCA databases based on extensive meta-analysis which continuously allows for adding new studies .


➢ Please describe the weaknesses of the tool according to your insights o Methodology needs to include or complete some cause-effect pathways, by example adding ecotoxicity in pollution;

vulnerability in further LCA categories, … o Marine biodiversity is not factored in o Semi-quantitative pressures (Overexploitation and, invasive species) have to be better calibrated to other pressures o Graphic interface (maps) needs to be improved to facilitate vision of impacts geographically


➢ Please describe planned improvements o Aggregation of impact in single indicator (based on m2 eq) o Add-on within ecodesign tool for mainstreaming within product design teams o Integration of ecotoxicity o Calibrating of overexploitation / invasive species pressures o Improvement of user interface










• Impact pathways



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The first 3 tables are about input data, i.e. specific data required by the tools to either conduct biodiversity impact assessments (“data inputs”) or to build impact factors. The 4th table is more about the dose-response relationships and the midpoints used, if any, to assess the impacts.




Unit of product or service (tonne, kWh, …)

No specific nomenclature

ADD ADDITIONAL INFO FOR YOUR TOOL: PBF, as other LCA-based methodology, is using activity data input, mostly physical activity data





In PBF Module 1, Characterization factors used in LCA methodologies integrate biodiversity richness and vulnerability data

IF Eco-regions for terrestrial Watersheds for freshwater

IUCN Modelled data

In PBF Module 2, LCA characterization factors are adapted, based on ecological

IF Ad-hoc Sectoral and local ecological studies

Real data


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studies on impact of practices on biodiversity state

In PBF Module 2, LCA characterization factors are adapted to account for additional data on biodiversity richness

IF various Globio / IBAT Real data

ADD ADDITIONAL INFO FOR YOUR TOOL: - PBF is integrating biodiversity state data to build impact factors, at 3 different levels




Energy use (MJ) Type of energy carrier (Ex: Energy, from coal) LCI dataset or specific company dataset

R or M depending on data availability

Water use (m3) Type of water used and localisation of use (Ex: Water, irrigation, well, in ground, FR)

LCI dataset or specific company dataset


Land occupation (m2*yr)

Type of land use (Ex: Occupation, annual crops)



Land transformation (m2)

Initial land use type (Ex: Transformation, from forest, extensive)



Emissions to water Substance name, to water LCI dataset or specific company dataset


Emissions to soil Substance name, to soil LCI dataset or specific company dataset



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Emissions to air Substance name, to air LCI dataset or specific company dataset


ADD ADDITIONAL INFO FOR YOUR TOOL: Specific data from company (R) are completed with generic data from LCI databases (Ex: ecoinvent) and thus are modelled data (M)





Land use occupation

Impact pathway: Land transformation and land occupation → physical changes to flora and fauna locally → alteration of species composition and species richness → if too much habitat is lost, this leads to species extinction on regional or global scales → damage to ecosystem quality LC-Impact (Verones et al., 2016); (Chaudhary, Verones, Baan, Pfister, & Hellweg, 2015)

No midpoint calculated

Evaluated through Monte-Carlo simulations: median values along with 95% confidence intervals were calculated for CFs for each taxa per land use type and ecoregion

Land use transformation

Impact pathway: Land transformation and land occupation → physical changes to flora and fauna locally → alteration of species composition and species richness → if too much habitat is lost, this leads to species extinction on regional or global scales → damage to ecosystem quality LC-Impact (Verones et al., 2016); (Chaudhary et al., 2015)


Evaluated through Monte-Carlo simulations: median values along with 95% confidence intervals were calculated for CFs for each taxa per land use type and ecoregion

Water stress Water consumption → changed surface water volumes and groundwater tables → change in


Sensitivity analyses performed for water depth, the chosen



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wetland area → disappeared terrestrial and freshwater species Water consumption → loss of vascular plants LC-Impact (Verones et al., 2016); (Pfister, Verones, & Mutel, 2014)

wetland geometry, and the amount of water consumed

Terrestrial Acidification Increase in emissions of acidifying pollutants → Increase in concentration of acidifying pollutant in the atmosphere → increase in deposition of acidifying pollutant on the soil→ decrease in soil pH→ decrease in richness of vascular plants LC-Impact (Verones et al., 2016); (Azevedo, Roy, Verones, Zelm, & Huijbregts, 2014)


Confidence index assessed per impact pathway and combined per pressure (I Care & Consult & Sayari, 2019)

Freshwater Eutrophication

1. Emission of total phosphorus to freshwater 2. Emission of phosphorus to soil and 3. Erosion of soil to freshwater → Increase in phosphorus concentration in freshwater → Decrease in fish species richness LC-Impact (Verones et al., 2016); (Azevedo, Verones, Henderson, Zelm, & Jolliet, 2014)



Photochemical Ozone

Emission of NOx or NMVOC→ Atmospheric fate and chemistry → plant uptake of ozone→ disappearance of plant species → damage to terrestrial ecosystems LC-Impact (Verones et al., 2016); (Zelm, Preiss, Goethem, Verones, & Dingenen, 2016)



Climate change GHG emissions→ Increase in GHG concentration→ Increased radiative forcing> Increase in global mean temperature→ 1) Change in biome distribution>

Disappeared terrestrial species 2) and 2) Change in river change>

Disappeared freshwater fish; LC-Impact (Verones et al., 2016), (Steinmann & Huijbregts, 2014)


Confidence index assessed per impact pathway (I Care & Consult & Sayari, 2019)

Species Management

Qualitative evaluation through assessment of: - Level of impact


Confidence index assessed per MEA


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- Level of action (Asselin et al., 2019; I Care & Consult & Sayari, 2019)

pressure (I Care & Consult & Sayari, 2019)

Invasive species Qualitative evaluation through assessment of: - Level of impact - Level of action

(Asselin et al., 2019; I Care & Consult & Sayari, 2019)


Confidence index assessed per MEA pressure (I Care & Consult & Sayari, 2019)


The five pressures on biodiversity expressed in the Millennium Ecosystem Assessment are covered with this methodology through a quantitative approach for three pressures (Habitat change, Pollution, Climate change) and a qualitative approach for two pressures (Species management and Invasive species)


components PBF uses impact indicator PDF (Potential Species Loss), expressed in the so called “potential disappeared fraction of species within a year” or PDF*yr. This indicator is developed by LCA researchers, and which is used by most LCA methodologies (ReCiPe, LC Impact, Impact World +, …).. It can be applied both as a regional and global indicator, as recommended by the UNEP SETAC 2016 guidance:

- Regional indicator (PDFreg*yr) quantifies the potential for disappearance of species at regional level; region is understood as an

ecologically homogeneous area, practically identifies as ecoregions for terrestrial ecosystems, and the water basins for

freshwater ecosystems).

- Global indicator (PDFglo*yr) quantifies the potential for global extinction of species, accounting for their vulnerability at global

level. The Phase 2 of PBF development will convert the PDF in surface area equivalent: m2 eq, by using as a standard equivalent the impact on biodiversity of artificialization of 1 m2.




• Science-based (peered-review publication underway), looking at cause-effect chains.

• Entire value chain coverage


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• Measures intrinsic biodiversity value,

• Measures positive and negative biodiversity impacts


• Complement and compatible with local indicators

Asselin, A., Rabaud, S., Catalan, C., Leveque, B., L’Haridon, J., Martz, P., & Neveux, G. (2019). Product Biodiversity Footprint – A novel approach to compare

the impact of products on biodiversity combining Life Cycle Assessment and Ecology. In Review (Journal of Cleaner Production).

Azevedo, L. B., Roy, P., Verones, F., Zelm, R. Van, & Huijbregts, M. A. J. (2014). Chapter 7 LC-Impact. Terrestrial Acidification.

Azevedo, L. B., Verones, F., Henderson, A. D., Zelm, R. Van, & Jolliet, O. (2014). Chapter 8 LC-Impact Report. Freshwater eutrophication.

Chaudhary, A., Verones, F., Baan, L. De, Pfister, S., & Hellweg, S. (2015). Chapter 11 LC-Impact Report. Land stress : Potential species loss from land use (

global ; PSSRg ). LC-Impact: A spatially differentiated life cycle impact assessment method (Vol. 1).

I Care & Consult, & Sayari. (2019). Product Biodiversity Footprint Methodological Report.

Pfister, S., Verones, F., & Mutel, C. (2014). Chapter 12 LC-Impact Report. Water stress.

Steinmann, Z., & Huijbregts, M. A. J. (2014). Chapter 2 LC-Impact Report. Climate change.

Verones, F., Hellweg, S., Azevedo, L. B., Chaudhary, A., Cosme, N., Fantke, P., … Huijbregts, M. a. J. (2016). LC-Impact Version 0.5, 1–143.

Zelm, R. Van, Preiss, P., Goethem, T. Van, Verones, F., & Dingenen, R. Van. (2016). Chapter 5 LC-Impact. Ozone Formation.


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12. Species Threat Abatement and Recovery Metric

FICHE NR 12 Species Threat Abatement and Restoration Metric (STAR) (ex-BRIM: Biodiversity Return on Investment Metric)

1. Date of assessment • 29 August 2018

• Update submitted by IUCN 28 August 2019

2.Actors Lead: IUCN Other: Vulcan Inc; The Biodiversity Consultancy; Birdlife International; Newcastle University, International Institute of Sustainability (Brazil)., Institute of Botany at the Chinese Academy of Sciences, Biodiversity Research and Monitoring Directorate, South African National Biodiversity Institute), Department of Conservation and Species Management, Secretariat of Biodiversity, Ministry of the Environment, Brazil



Business Applications!) and if case studies are available (please refer to links or publications) Technical development Technical approach and methodology developed during 2017 through a series of consultative workshops and a research program. The threat abatement component of the metric has been through sensitivity testing and has been applied to amphibians, birds and mammals globally. Road tests in Sumatra and El Salvador on commodity production concessions with biodiversity outcomes have demonstrated the viability of the approach, the utility of the metric in contributing to larger-scale targets and have clarified the steps needed to advance from the Ex-Ante Estimate phase to the Ex-Ante Baseline and Ex-Post measurement phases. The restoration component is under development and will be ready for testing soon. In order to include plants, distribution data need to be obtained and AOH modelling carried out. Policy engagement We are engaged with Parties to the CBD through the IUCN SSC Post-2020 Task Force (led by Philip McGowan, Newcastle University). The threat abatement component of the metric was introduced to Parties at a side-event at CBD CoP14. National case studies are being developed with three Parties to demonstrate metric application. Further engagement is planned for proceeding CBD meetings to encourage uptake. Major milestone The aim is to have a high impact manuscript presenting the metric and global analyses under review in advance of the CBD technical meeting in November 2019. A module to measure the estimated ex-ante value of STAR for project/ country polygons will be available within the Integrated Biodiversity Assessment Tool by the end of 2019

4.Business applications • Complete table ‘Categories of Business Applications’

• Add short summary in the style below, highlighting not only the BA that are supported by the tool but also those not supported by the tool and the reasons why!

STAR is appropriate for the following applications: 1. Assessment of current biodiversity performance: Identifying and monitoring conservation interventions at particular sites

2.Assessment of future biodiversity performance: Assessment of potential and achieved impact on species extinction risk at

individual sites and across a portfolio

3. Tracking progress to targets: Developing and tracking global targets on slowing extinction risk, to complement the Red List Index


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for instance in the post 2020 global Aichi targets

4. Comparing options: Assessment of potential and achieved impact on species extinction risk across a portfolio; portfolio screening

for selection of projects with maximum potential conservation impact; Tracking sectoral impacts on extinction risk, across commodity

value chains, given additional information to track source of production.

5. Biodiversity Return on Investment / Testing effectiveness of reduction measures: Assessment of potential and achieved impact on species extinction risk at individual sites and across a portfolio; will need assessment of costs of management in different economic contexts for proper cost-benefit analysis 6. Assessment / rating of biodiversity performance by third parties, using external data: Not applicable 7. Certification by third parties Amenable to external audits

8. Screening and assessment of biodiversity risks and opportunities: Assessment of biodiversity risk against IFC Performance

Standard 6 (subset of Critical Habitat= areas of occurrence of threatened species)


• All sectors with potential or actual spatial impacts


The aim is to develop a metric that informs target-setting across spatial scales, and allows countries and other entities (such as NGOs and businesses) to measure their potential contribution towards species conservation. The metric will consider two complementary site-based actions for species conservation; (i) the abatement of threats in order to prevent further deterioration in species survival probability, and (ii) the restoration of habitat in order to contribute to improving species survival probability. The metric will allow calculation of the contribution that could be made over any spatial scale (from small-scale contribution of businesses, to national, through to global), and for any species or group of species for which data are available. The metric will be scalable and additive, thus allowing, for example, businesses to measure their national contribution, and nations to measure their global contribution. Metric calculation Calculation of the metric requires information on species conservation status (IUCN Red List category), Area of Habitat (AOH; both current and historical, which are calculated using species distribution polygons, habitat associations from the IUCN Red List, and land cover maps) and the threats they face (from the IUCN Red List threat classification hierarchy). The threat abatement component of the metric has already been developed. It is spatially explicit and is calculated for all species present (according to available data) at a defined site (a site can range from a single grid cell to any larger delineated area, e.g. a country). Species AOH is used to determine the percent of the species distribution present at the site. IUCN Red List assessments are used to determine the threats facing the species present, and the relative contribution of those threats to the species extinction risk. The metric calculation for a site is:

∑ ( PSp x WSp x RSpT)


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Where PSp is the percent of distribution of species Sp at the site, WSp is the Red List category weighting of species Sp (NT=1, VU=2, EN=3, CR=4) and RSpT is the relative contribution of threat T to the extinction risk of species Sp. Thus, the total metric score per site indicates the potential contribution to reducing species extinction risk that could be made from abating all threats to species at that site. The metric formulation also allows calculation of the potential contribution to reducing species extinction risk that could be made from abating individual threats to species at that site. The metric is scalable as scores per site can be compared to the total global score to give the relative contribution to species conservation that the particular site could make. The complementary restoration component of the metric is currently under development, but a preliminary formulation will be available soon.



The metric is calculated in three phases: the Estimated Ex Ante phase, based only on existing published information, which enables users to gain a preliminary evaluation of the potential of a site to contribute to threatened species extinction risk reduction; the Baseline Ex-Ante phase, which requires verification of the presence of threatened species and the factors influencing their extinction risk, and the Ex-Post phase which enables users to measure progress against delivery in reducing the impact of extinction risk factors through management.


➢ Please describe whether your approach includes a materiality assessment and if so, how, this is undertaken Not yet

Impact boundaries

➢ Only for tools that cover site level and project level business applications: Please describe if the perimeter assessed in the tool is limited to the direct operations within the site controlled by the company? Or does it cover a wider area of influence? The tool can be used to assess the potential change in species extinction risk caused by direct investment within particular perimeters and also threats to species that apply more widely



The detailed threat assessment for each species considered in the calculation of the STAR metric includes information on dependencies.


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Valuation


Impacts are estimated in a quantitative way but monetization valuation would need to consider local costs


No


The module under development for IBAT will use an underlying global grid of 2x2 km squares. This gives the estimated ex-ante STAR value. Baseline ex-ante value will be calculated at smaller granularity (test cases used polygons of <300 ha). The metric can be aggregated upwards to any scale, eg global.


The IBAT application (giving estimated ex-ante values for sites or countries) will be simple and easy to use (<1 hr). Moving to baseline ex-ante will require further technical input. Measuring progress against the baseline using ex-post measures will require technical investment and analysis The methodology can be interpreted by non-experts (“this value indicates the potential reduction in species extinction risk that could be achieved at this site”) and recommendations made to managers based on results of assessments ).


➢ Please describe how the tool can be sensitive to corporate actions and how this sensitivity is measured ➢ The metric can be used to set baselines for company actions to conserve biodiversity through threat mitigation,

permit them to develop time-bound targets for delivery and measure delivery against these targets over relevant timeframes for corporate reporting


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➢ We are evaluating how the metric values could be incorporated into eg Trucost data or GRI scores


Policy engagement It is anticipated that STAR will form part of the Biodiversity component of the Science-based Targets for the post-2020 Biodiversity Strategy (the replacement for the Aichi targets which expire in 2020). We are engaged with Parties to the CBD through the IUCN secretariat (Chief Scientist and Chief Economist) and through the IUCN SSC Post-2020 Task Force (led by Philip McGowan). The threat abatement component of the metric was introduced to Parties at a side-event at CBD CoP14. National case studies are being developed with three Parties to demonstrate metric application. Further engagement is planned for subsequent CBD meetings to encourage uptake.


o Please describe the strengths of the tool according to your insights o It can help the finance industry and investors target their investments to achieve conservation outcomes o BRIM can enable investors and governments to track conservation gains o BRIM can measure the contributions these investments make to global targets such as the Sustainable Development

Goals, as it can be used to track progress towards changes in the Red List Index o Based on the IUCN Red List of Threatened Species – the global standard for documenting species’ conservation status o Based on quantitative categories and criteria – not extrapolation or modelling o Incorporates compilation of data on range, habitats, threats, etc – not just a list o BRIM allows comparison across investment targets – a change in value in one place is directly comparable to a change

somewhere else on the planet o A fully additive and scalable metric, from pixel to global, or across sites in a portfolio o Responsive at the pace of investors- changes in management can quickly cause changes in pressures affecting species

and thus in the value of the metric o The BRIM can measure ex-ante (potential) and ex-post (achieved) impacts of investments at a range of scales and over a

range of timeframes. o


➢ Please describe the weaknesses of the tool according to your insights ➢ Not all species are adequately scored for extent and intensity of threat- baseline ex-ante calculation of STAR will require

assessment for some or many species present at the site/country ➢ Not all taxa are comprehensively assessed (some species have not been evaluated at all, coverage in some ecosystems,

such as marine and freshwater, is incomplete). These gaps will be substantially filled in the next 2 years ➢ Measurement of ex-post STAR requires identification of linkages between investment and changes in correlates of

population (for instance changes in Extent of Suitable Habitat) ➢ Application to value chains requires knowledge of producer geographical footprint, or a way of attributing pressures on

biodiversity to producer area of impact


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➢ Please describe planned improvements ➢ Publication of metric in scientific journal (November); development of restoration component to metric (October);

development of estimated ex-ante value calculation application in IBAT (Q4 2019). Adoption as Science-based Target for Post-2020 Biodiversity Strategy (November 2020)

ASSESSMENT OF BIODIVERSITY MEASUREMENT APPROACHES FOR BUSINESSES AND FINANCIAL INSTITUTIONS – ANNEXES 2019

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ANNEX 3: COVERAGE OF BUSINESS APPLICATIONS AND ORGANISATIONAL FOCUS AREAS BY BIODIVERSITY MEASUREMENT APPROACHES

Based on consolidated feedback by tool developers on the proposed list of Business Applications Legend:

• extent to which the BA is covered: ‘very well’ (XX), ‘to some extent’ (X), ‘not at all’ (0), ‘only qualitative descriptions’ (Qual)

• number of completed or ongoing case studies is mentioned between brackets. Names of companies that have applied the tool (or applying for the moment) are mentioned under the scores (if not confidential). For instance, XX (6) under BA1 and ‘product level’ as organisational focus area means that the respective tool is strongly supporting BA1 at product level and can refer to 6 case studies.


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Business applications Organisational focus

Product / Service

Site / Project

Supply chain

Corporate Portfolio / Sector

Country / region

1.Assessment of current biodiversity performance

ABD Index

Tool allows for measuring/estimating actual biodiversity performance XX XX XX X X XX

The Agrobiodiversity (ABD) Index is specifically designed to be applicable for multiple organizational foci – at product level, at project level, at corporate level, for a portfolio, and at (sub)national level including the consideration of (sub)national data and policies. The ABD Index measures status, actions and commitment on ABD for healthy diets, sustainable agriculture, and future options at each of those levels. Full ABD Index measurement considers the entire supply chain. Part of the ABD Index (commitment and actions) can be used for private and public corporates. ABD Index scores allow for comparison, aggregation, ranking and allocation across a portfolio or sector. ABD Index can be used to assess government performance overall and in relation to specific policies.

BD Protocol

Tool allows for measuring/estimating actual biodiversity performance XX (2) XX XX

Using the BD Protocol helps business track changes in biodiversity impacts (land cover, species population) which can help show progress against targets. Site/project level: 2 case studies in France, soon to be published in academic paper, others planned in South Africa

BFFI Tool allows for measuring/estimating actual biodiversity performance X 0 X X XX (1) 0

The underlying tools of the BFFI, LCA and ReCiPe, allow for impact calculation on different levels (portfolio, company, supply chain, product/services). However, focus of the BFFI is a biodiversity footprint on portfolio level. Applicable to products/services if product/service-specific data are available. The BFFI can be used to assess the biodiversity footprint on a portfolio level. Please note that the methodology is based on impact drivers and not on location specific measurement. Therefore, the BFFI assesses the potential impact, not the actual impact (for which field work would need to be conducted)

. ASN Bank (annually since 2015)

BIE Your tool allows for measuring/estimating actual biodiversity performance 0 XX 0 XX 0 0

The tool can be used to identify biodiversity performance in relation to the state of biodiversity, the pressures placed upon it by the company, and the companies responses to mitigate these.

Pilots ongoing with 7 companies

Pilots ongoing with 7 companies

BIM Tool allows for measuring/estimating actual biodiversity performance 0 X XX (4) XX X X

The BIM can assess the direct impact of a company’s operations, but has not been tested at the granularity of a site/project. The BIM has been designed to assess upstream impacts of commodity production. This has been piloted. The BIM has been designed to assess impacts across a company’s activities, so it’s applicable to corporate level too. The BIM could be used for assessing portfolio impact but this has not been tested. The BIM could be used for assessing e.g. the impact of national-level commodity production or consumption but this has not been tested.

Names not mentioned

GBS Tool allows for measuring/estimating actual biodiversity performance X X (2) X (2) XX (1) XX (2) X

One of the purposes of the GBS is to measure actual biodiversity performance at the corporate and portfolio/sector scales, and this methodology also could be applied to supply chains or at a national level. Project level assessments are robust only for very large-scale projects (impacting thousands of hectares) and should generally be limited to internal reporting. In France, the new National Biodiversity Plan published in July 2018 has the ambition to generalize the evaluation and disclosure of biodiversity footprint for companies in France but also in Europe (Action 30). The GBS could be one the tools to conduct future mandatory corporate biodiversity footprint reporting.

GRT Gaz, Veolia

Michelin, Solvay

Veolia BNP Paribas Asset Management, Mirova


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LIFE Tool allows for measuring/estimating actual biodiversity performance 0 (0) XX (29) XX (1) XX (4) XX (0) XX (0)

LIFE Methodology presents a quantitative metric for the assessment of the biodiversity positive performance called Biodiversity Conservation Action (BCA). The metric is used to score the performance of environmental projects or actions in relation to biodiversity. The LIFE scoring system considers the phase of project implementation (creation of protected areas, planification, implementation), the relevance of the project for local, regional, national and international biodiversity priorities. The scoring system also considers 16 technical qualifiers for each action implemented on each project. As the scoring system can be applied to any action or project it can be used to evaluate the biodiversity performance related to sites, supply chain, corporate, portfolio, sector and public policies. Case studies

• Site/project level: Brazil: Adecoagro; Amaggi; Raizen; Agricert; Masisa; Tamanduá; JBS; Petrobras RPBC; Petrobras UTE-BLS;

Petrobras TASSE; Petrobras GEI; Itaipu; Boticario; Posigraf; Udu; Catallini; Rocha; Lapinha; ABN/AMRO; Gaia; Cristalino Lodge;

Sanepar; JTI; Suzano; MPX. Paraguay: Payco; Karanda; Itaipu

• Supply chain: JTI (13.000 producers in South Brasil)

• Corporate: Boticario, JTI, Petrobras, Itaipu .

PBF Tool allows for measuring/estimating actual biodiversity performance XX X XX X

As explained in summary section, the PBF is mainly an LCA based approach and as such its best business application is Comparing options at Product Level. To do, PBF needs first to assess different options, mainly “standard” performance and “advanced” performance, so that assessing current level of biodiversity performance at product level is one BA. To assess at product level, one needs also to assess supply chain which is part of the life cycle of the product. In the 3 case studies completed (L’Oréal, Kering and Avril), supply chain assessment was part of the scope and could be disaggregated from the full assessment at product level. Beyond product level, LCA is now also used at project level and at organisation level, that is why PBF could also be used at these levels. A Case study is currently under progress at Site / Project level.

3 case studies completed 4 in progress

1 case study in progress


No case study planned

STAR Tool allows for measuring/estimating actual biodiversity performance XX X X X X

2.Assessment of future biodiversity performance

ABD Index

Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

X X X X X X

The current version of the ABD Index includes measures, actions and commitment that support ABD or that can negatively harm ABD – based on those actions and commitment, a prediction of future trend (positive, neutral, negative) can be made. Basic function now – more quantitative forward looking ABD Index, as mentioned above, can be used qualitatively and semi-quantitative to model future scenarios and the net impact of specific actions but it is not the core focus and power of the current version of ABDI Future work on the ABD Index is planned towards more quantitative if – then scenarios and related predictive modelling building on the UNEP PREDICTS model and approach.

BD Protocol

Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

X X X

The BD Protocol is explicitly based on the mitigation hierarchy and enables the scaling up of impact data. While the focus is on past impacts up to the date of account compilation, future impact scenarios can be modelled.

BFFI Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

X 0 X X XX (1) 0

The underlying tools of the BFFI, LCA and ReCiPe, allow for impact calculation on different levels (portfolio, company, supply chain, product/services). However, focus of the BFFI is a biodiversity footprint on portfolio level.


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BIE Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

0 X 0 X 0 0

Changes in the Response indicator can provide information on the likely future trajectory of Pressure and State at site-level. pilots pilots

BIM Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

0 X X X X X

The BIM is responsive to measures that reduce the intensity of land management, reduce land footprint or shift sourcing to areas of lower biodiversity importance

GBS Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

X X (1) X XX XX X

: Future biodiversity performance can be estimated by assessing hypothetical scenarios. They can include positive impact measures on biodiversity (restoration actions, change in supply options) or on aggregations of positive impact measures across a company or portfolio.

GRT Gaz

LIFE Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

0 (0) XX (6) XX XX XX XX

LIFE Methodology is applied to the present business management situation but can be used to compare future scenarios of biodiversity performance (ex.: considering the investment on different kind of projects). Biodiversity positive performance in LIFE Methodology is evaluated in an indirect way considering the expect results of different actions (ex.: invest on protected areas or in environmental education projects). Case studies

• Site/project : Udu; Catallini; Rocha; ABN/AMRO; Sanepar; JTI.

PBF Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

XX X XX X

PBF, such as other LCA approaches, can also be used as a simulation tool, using future performance based on the implementation of different options or biodiversity action plan. In each of the PBF case studies, a sensibility analysis is performed to test possible future options. Case studies are the same as in BA 1





STAR Tool allows for estimating future biodiversity performance, e.g. as a result of positive impact measures such as ecosystem restoration actions and/or actions that reduce pressures on biodiversity

XX X X X X

impact on reducing threats to species

3. Tracking progress to targets 3.1.High level societal targets, such as Aichi targets and SDGs

ABD Index

Tool refers to such high level targets and facilitates tracking progress towards them XX XX XX XX XX XX

ABD Index (ABDI) refers to and aligns specifically with Aichi target 7 and 13 and with SDG 2.1, 2.4, 2.5; SDG 13.1, SDG 15.1, 15.3 and 15.6 Contribution to those targets is indicated in the ABDI framework. Part of the strength and fundamental usefulness of agrobiodiversity is that it can contribute to multiple goals. The Agrobiodiversity Index captures this multi-functionality of agrobiodiversity. The way we farm is the biggest deteriminant of the future of biodiversity and increasing use and safeguarding of agrobiodiversity is the biggest determinant of the sustainablitity of farming systems and the two way benefit flows between agrobiodiversity and wild biodiversity.

.

BD Protocol

Tool refers to such high level targets and facilitates tracking progress towards them XX XX XX


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Using the BD Protocol helps business track changes in biodiversity impacts (land cover, species population) which can help show progress against targets. More specifically, land cover data can be consolidated into three key performance indicators, the company’s total biodiversity footprint, its negative biodiversity footprint, and its positive biodiversity footprint. Accounting for biodiversity impacts revolves around the following equations:

• Statement of Biodiversity Position: (A) total biodiversity impacts (i.e. biodiversity assets or stocks) = (B) accumulated positive impacts +

(C) accumulated negative impacts;

• Statement of Biodiversity Performance: (E) net biodiversity impacts over the accounting period = (F) periodic positive impacts or gains -

(G) periodic negative impacts or losses.

BIE Tool refers to such high level targets and facilitates tracking progress towards them 0 X 0 X 0 0

pilots pilots

BIM Tool refers to such high level targets and facilitates tracking progress towards them 0 X X X X X

No clarification provided

GBS Tool refers to such high level targets and facilitates tracking progress towards them 0 0 0 XX XX X

Some specific high level targets can be tracked thanks to the GBS, at the Coporate/Portfolio/sector or Public policy levels. In particular the contribution of businesses to the Strategic (Biodiversity) Plan’s goal of halting the erosion of biodiversity can be tracked with the GBS: halting the erosion of biodiversity roughly means a global variation of MSA level of 0 (i.e. no MSA loss), and the gains or losses caused by companies assessed with the GBS can be compared to that goal. The reasoning would work similarly for the future post-2020 framework. Furthermore, the GBS would help tracking quantitatively these targets (or use results of tracking of these targets to assess biodiversity impacts):

- Aichi targets: 4 (sustainable production and consumption, impacts of use of natural resources well within safe ecological limits), 5 (rate of

loss of natural habitats, forest /2, fragmentation), 7 (agricultural areas managed sustainably)

- SDGs: 12.4 (environmentally sound management of chemical and all wastes throughout their life cycle […] reduce their release to air,

water and soil), 15.2 (promote the implementation of sustainable management of all types of forests, halt deforestation, restore degraded

forests…), 15.5 (take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity […])

LIFE Tool refers to such high level targets and facilitates tracking progress towards them X0 XX (3) XX XX XX 0

LIFE Standards have a Principle that mentions specifically the ABS (Access and Benefit Sharing) - The organization or productive unit must fairly and equitably share the benefits from the access to biodiversity genetic resources and/or associated traditional knowledge, in accordance with local legislation or, in the absence of specific legislation, in accordance with the Nagoya Protocol (CBD), regardless of whether the country is a signatory of the Protocol.

Boticario Itaipu Tamandua

STAR Tool refers to such high level targets and facilitates tracking progress towards them XX X X X X

Direct relation to post-2020 Science Based Targets

3.2. Planetary Boundaries, i.e. not exceeding the carrying capacity of the planet

ABD Index

Tool makes use of threshold values that are indicative for exceedance of ecosystem carrying capacity X X X X X X

ABD Index uses several indicative tresholds – e.g. 10% of natural vegetation on agricultural land; % of agricultultural land with <5 species diversity; soil biodiversity index Several measurements feeding into ABDI consider those thresholds and can be applied and traced back at product level, project level, along the supply chain, for a portfolio or at national/ subnational level Most measurements that consider those thresholds are status indicators, which in the current version are not yet applicable at whole corporate level - only if all corporate data of production and sourcing location would be available


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BD Protocol

Tool makes use of threshold values that are indicative for exceedance of ecosystem carrying capacity 0 0 0 0 0 0

The BD Protocol does not prescribe any target or threshold value. It is an accounting tool which enables business to set up its own targets.

GBS Tool makes use of threshold values that are indicative for exceedance of ecosystem carrying capacity 0 0 0 XX XX X

The functional biodiversity part of the “Biosphere integrity” planetary boundary has been estimated by Steffen et al. (2015) in terms of Biodiversity Intactness Index (BII), and translated in MSA by Lucas & Wilting (2018). The results can be downscaled to regional levels according to equity allocation principles and thus useful for Public policy level. National biodiversity loss reduction targets or MSA loss thresholds values can then be attributed at the sectorial and corporate levels. The GBS makes it possible for companies to track how they contribute to keeping the world within the planetary boundaries (or not) through the link between planetary boundaries and MSA.

LIFE Tool makes use of threshold values that are indicative for exceedance of ecosystem carrying capacity 0 XX (29) XX (1) XX (4) XX 0

The Methodology uses information that can indicate pressure under water scarcity and on ecoregion biodiversity Same case studies as mentioned under BA1.

PBF Tool makes use of threshold values that are indicative for exceedance of ecosystem carrying capacity XX

There is a lot of academic work underway to link LCA methodologies and Planetary Boundaries (I Care & Consult conducted a study in 2018 on behalf of SCORE LCA on that matter). In that sense, when there will be a consensus on the carrying capacity of the planet regarding biodiversity, PBF could be used to establish if the current or targeted biodiversity performance at product level is above or beyond the carrying capacity of the planet.

3.3. No Net Loss or Net Gain

ABD Index

Tool allows for calculating losses and gains of biodiversity and for calculating net impact X X X X X X

See above under number 2 Basic function now – more quantitative forward looking. ABD Index, as mentioned above, can be used to model future scenarios and the net impact of specific actions

BD Protocol

Tool allows for calculating losses and gains of biodiversity and for calculating net impact XX XX XX

The BD Protocol is based on the mitigation hierarchy and its accounting framework is dedicated to account for net biodiveristy impacts at the company level (i.e. both accumulated positive and negative impacts + periodic / annual net impacts). See 3.1 for equations accounting framework.

BFFI Tool allows for calculating losses and gains of biodiversity and for calculating net impact X 0 X X XX 0

Rules on how to use biodiversity-positive investments in reaching NNL or NG are now being developed (2019) The underlying tools of the BFFI, LCA and ReCiPe, allow for impact calculation on different levels (portfolio, company, supply chain, product/services). However, focus of the BFFI is a biodiversity footprint on portfolio level.

BIE Your tool allows for calculating losses and gains of biodiversity and for calculating net impact 0 XX 0 XX 0 0

State indicator displays losses or gains in relation to each priority biodiversity feature Pilots Pilots

BIM Tool allows for calculating losses and gains of biodiversity and for calculating net impact 0 X X X X X

The metric provides an estimate of the cost of land occupancy, and this can track increases and decreases. However, it does not operate at the scale of gains or losses of individual species, nor does it directly measure changes on the ground

GBS Tool allows for calculating losses and gains of biodiversity and for calculating net impact 0 X 0 XX XX X


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The GBS could be used for No Net Loss approaches at the corporate and financial institution-levels. The No Net Loss or Net Gain concept can also be applied at the national or international levels with the quantification of the planetary boundaries and associated biodiversity loss reduction goals. It is also possible to use the MSA metric to set up NNL or Net Gain targets at the site level, but they would be different in nature to NNL or Net Gain targets usually used at the site level (which are based on habitats and endangered species).

LIFE Tool allows for calculating losses and gains of biodiversity and for calculating net impact X (29) X X X 0

LIFE developed its own metric to calculate the compensation between negative and positive impact aiming net gain. The metric used here is the “minimum Biodiversity Conservation Action (Min BCA)”. Same case studies

PBF Tool allows for calculating losses and gains of biodiversity and for calculating net impact XX

As other LCA approaches, PBF is able to net positive and negative impact and can therefore be used to support such an approach

STAR Tool allows for calculating losses and gains of biodiversity and for calculating net impact XX X X X X

potential application for losses and gains and net impact

3.4. Environmental management system requirements (e.g., ISO 14001, EMAS)

ABD Index

Tool allows facilitates demonstrating continuous improvement, which is the central objective or environmental management systems XX XX XX XX XX XX

ABD index allows and facilitates demonstrating continuous improvement on agrobiodiversity status, related actions and commitment.

BIE Tool allows facilitates demonstrating continuous improvement, which is the central objective or environmental management systems 0 XX 0 XX 0 0

State, Pressure and Reponse indicators all can demonstrate elements of conintuous improvement in company performance Pilots Pilots

LIFE Tool allows facilitates demonstrating continuous improvement, which is the central objective or environmental management systems X x X x

The metrics allows to calculate, monitor and compare annual negative and positive impacts on biodiversity. Also the qualitative approach allows to monitor biodiversity management performance through 74 indicators.

3.5. Voluntary standards at sector level or product level (e.g. Roundtable on Sustainable Palm Oil RSPO, EU Ecolabel), natural capital assessment and reporting frameworks (e.g. Natural Capital Protocol, GRI) and agreements (e.g. Green Deal agreements with governments, agreements with NGOs)

BD Protocol

Tool refers to specific standards, frameworks or agreements and allows tracking progress towards compliance XX XX XX

While the GHG Protocol Corporate Accounting and Reporting Standard (i.e. the GHG Protocol) was the benchmark standard for the vision and structure of the BD Protocol, the latter differs from the former in two main aspects:

• The BD Protocol focuses its guidance on measuring impacts on biodiversity (i.e. changes in the state of biodiversity caused by business),

while the GHG Protocol provides guidance on measuring the impact drivers of climate change (i.e. greenhouse gas emissions emitted by

business), which do not constitute impacts in themselves but contribute to climate change and its consequences.

• In the BD Protocol, net impact accounting recognises the notion of equity in the type of biodiversity lost or gained (i.e. ecological equivalency

or like-for-like): i.e. biodiversity losses (negative impacts) and gains (positive impacts) can only be aggregated for equivalent biodiversity

components. In net greenhouse gas emission accounting however, any type of greenhouse gas emissions can be reduced or offset by any

type of greenhouse gas offset (e.g. carbon stored in new tree plantations, renewable energy projects).


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The BD Protocol is aligned to the Natural Capital Protocol, which is a standardised framework to identify, measure, and value direct and indirect impacts (positive and negative) and/or dependencies on natural capital. Specifically, it helps provide biodiversity-specific guidance to:

• Measuring changes in the state of natural capital (step 6 of the Natural Capital Protocol), by providing guidance on how to measure

change(s) in the extent (land cover)/amounts (taxa) and condition (land cover)/viability (taxa) of impacted biodiversity components;

• Valuing impacts on natural capital (step 7 of the Natural Capital Protocol), though from only two perspectives: i.e. valuing the financial

implications of biodiversity impacts for your business and valuing the relative importance of your business’ biodiversity impact exposure

and/or contribution to society.

BIE Tool refers to specific standards, frameworks or agreements and allows tracking progress towards compliance 0 X 0 X 0 X

GRI 304:2 – Majority of requirements under A and B can be tracked using the site-level indictors created in Stage 2 IPIECA, API and IOGP’s Oil and gas industry guidance on voluntary sustainability reporting – Requirements under S1 and S2 under Biodiversity and Ecosystem Services can be tracked using the site-level indicators.

Pilots Pilots

LIFE Tool refers to specific standards, frameworks or agreements and allows tracking progress towards compliance X x X x X

HCV (High Conservation Value); sectorial best practices (company has to specify the most important to be checked in the supply chain for each sector. Eg.: FSC).

PBF Tool refers to specific standards, frameworks or agreements and allows tracking progress towards compliance X

An interesting BA of PBF is to evaluate what is the biodiversity performance of voluntary standards such as RSPO, FSC, … , based on the requirements list of these standards. Specific company practices and frameworks could then be compared vs. these voluntary standards.

STAR Tool refers to specific standards, frameworks or agreements and allows tracking progress towards compliance X X X X X

under discussion for inclusion in GRI, Trucost metrics

3.6. Regulatory and permitting requirements

BD Protocol

Tool allows to track compliance with specific regulatory or permitting requirements XX XX XX

The BD Protocol produces the biodiversity impact accounts based on the mitigation hierarchy, which helps track the implementation of permitting requirements, from restoration to offset measures.

BIE Tool allows to track compliance with specific regulatory or permitting requirements 0 X 0 X 0 0

Pilots Pilots

LIFE Tool allows to track compliance with specific regulatory or permitting requirements Qual Qual Qual. Qual. Qual.

LIFE Methodology has a Principle in its Biodiversity Management Standards focused on regulatory aspects.

3.7. Financial institutions (FI) requirements including the guarantees required by the lenders (e.g. International Finance Corporation Performance Standard 6)


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ABD Index

Tool allows to track compliance with specific FI requirements XX XX XX XX XX XX

ABD Index can be used as an environmental impact indicator for green bonds or impact bonds, for example.

BD Protocol

Tool allows to track compliance with specific FI requirements XX XX XX

The BD Protocol produces the biodiversity impact accounts based on the mitigation hierarchy for all key biodiversity imapcts, including material ones as per IFC PS6

BIE Tool allows to track compliance with specific FI requirements 0 X 0 X 0 0

Pilots Pilots

LIFE Tool allows to track compliance with specific FI requirements Qual Qual. Qual. Qual.

LIFE Standards requires law attendance

GBS Tool allows to track compliance with specific FI requirements 0 0 0 0 0 0

lenders could include NNL in MSA in their requirements, in which case the GBS would be useful to meet those requirements. But at this stage, this option has not been explored.

STAR Tool allows to track compliance with specific FI requirements X X X X X

Tracks risk and response to Critical Habitat component of PS6

3.8. Site to landscape level collective impact programme commitments, such as collectively mitigating impacts at ecologically and socially important scales (e.g. catchment, as defined by stakeholders and partners)

ABD Index

Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

XX XX XX XX XX XX

Subject to data granularity, the ABD Index methodology can be used to identify the attribution to each stakeholder.

BD Protocol

Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

0 0 0

The BD Protocol covers direct and indirect impacts but does not yet include cumulative impacts at the landscape level. Apportionment of responsibility is the key limiting factor.

BIE Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

0 XX 0 XX 0 0

Tool assesses impacts within the area of influence of a project, which is refined for a default value of 50km. Pilots Pilots

GBS Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

0 0 0 0 0 0

The GBS is not yet relevant to assess landscape level collective impacts as the minimum area to use the tools and disclose the results with enough confidence on their accuracy is about 1000 ha and such landscapes would likely fall below that threshold.


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LIFE Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

Qual. Qual. Qual. Qual.

LIFE Standards requires that companies of the primary sector identifies their role for biodiversity at a landscape level. The organization or producer must plan landscape composition according to the regional context, considering all properties that belong to the scope of the certification. P5.C9.i1 - Information on properties that provide evidences of landscape planning according to the regional context:

• Maintenance of natural ecosystem coverage beyond the legal requirement.

• Maintenance of connection areas between remnants of the natural ecosystem beyond the legal requirement.

• Maintenance of native vegetation blocks isolated as little as possible in the landscape matrix, inside the property and in relation to the

surroundings

• Map identifying the location of the property in the regional context, including priority and high conservation value (HCV) areas inside and

outside the property for the creation of blocks and corridors of native vegetation.

• Monitoring that provide evidence that the fauna is using the corridors.

• Prioritization of conservation of areas in advanced stage.

STAR Tool allows to identify your company’s attribution to landscape level impacts, which is essential information for identifying joint action at a landscape level

X X X X X

Potential and achieved conservation impacts can be measured at sites within landscapes and aggregated up to landscape scale

3.9. Corporate-level biodiversity commitments or engagements (e.g. to avoid operating in high biodiversity value areas, to exclude purchasing of non-certified palm oil, wood, etc.) as detailed in corporate biodiversity policy/strategy.

ABD Index

Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

XX XX XX XX XX XX

The ABD Index includes measures on actions and commitment that support ABD for healthy diets, sustainable agriculture and future options (fair genetic resource management)

BD Protocol

Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

X X X

The BD Protocol can help demonstrate progress towards corporate targets but is not specifically designed for 3rd party commitments

BFFI Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

0 0 0 0 0 0

For ‘portfolio/sector’, this is currently under development for the BFFI (2019)

BIE Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

0 X 0 X 0 0

Pilots Pilots

BIM Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

0 X X X X X



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GBS Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

0 0 X X X 0

Commitments and voluntary labels (organic agriculture label, certified palm oil etc.) are taken into account quantitatively when it is possible to link them to reduced pressures on biodiversity (ongoing work) and environmental safeguards are taken qualitatively into account in the GBS during the results analysis.

LIFE Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

X XX X X X

LIFE metric BCA – Biodiversity Conservation Actions considers high biodiversity value areas globally, and also nationally and locally, for company scoring. Specific rules for supply-chain.

PBF Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

XX

PBF main objective is to demonstrate that the benefits of biodiversity corporate action plans can be assessed at product level. Impact on biodiversity of actions as listed above (e.g. to avoid operating in high biodiversity value areas, to exclude purchasing of non-certified palm oil, wood, etc.) can be assessed at product level with PBF, comparing standard corporate practices and the implementation of these actions. Therefore PBF can support corporate engagement of designing and manufacturing products with lower impact on biodiversity


STAR Tool allows for including engagements in the performance scores (e.g. certified palm oil gets another score than non-certified palm oil; or the tool is able to identify high biodiversity value areas globally and to take this into account in scoring system)

XX X X X X

Can be used to show impacts of investment at sites through threat reduction at production sites

4. Comparing options

ABD Index

Tool allows for comparing options XX XX XX XX XX XX

The ABDI is designed to allow comparisons, aggregation, and ranking across within all organisational focus areas. ABD Index, as mentioned above, can be used to model future scenarios and the net impact of specific actions. Such results can be translated into investment results and economic indicators.

BD Protocol

Tool allows for comparing options X X X

Not specifically. Focus is on tracking changes in biodiversity due to past activities. However, modelling potential impacts on biodiversity may be undertaken for internal decision-making purposes, for instance to assess the biodiversity exposure of contemplated supply streams or to compare alternative scenarios regarding the implementation of the impact mitigation hierarchy for a greenfield project. These potential impacts may also be disclosed to target external stakeholders to satisfy their ad hoc requirements. In these cases, the BD Protocol recommends that data on potential impacts be accounted for and disclosed separately.

BFFI Tool allows for comparing options X 0 X X XX (4) 0

The BFFI can be used to compare the footprint of different investments, e.g. in different asset classes. The BFFI can be used to calculate the biodiversity impact per Euro invested. However, the economic return on investment (in the sense of economic value) is not calculated.

BIE Tool allows for comparing options 0 XX 0 XX 0 0

Options for investment of resources to improve biodiversity performance. At site-level between priority biodiversity features and at corporate level between sites.

Pilots Pilots

BIM Tool allows for comparing options 0 X XX(4) XX X X



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GBS Tool allows for comparing options X X(1) X (2) XX XX X

The GBS can be used to compare hypothetical scenarios (options), for instance what happens if a company reduces its water consumption by 50% and reforests 50 ha? This scenario can be used as an input in the GBS and its consequences assessed. Different supply options, or 2 sites management options, or different investment options in companies within the same industry (if relevant data are available) can thus be compared. The GBS can estimate potential biodiversity gains thanks to mitigation measures before their implementation (hypothetical scenario), or after their implementation. This can easily be translated into a return on investment by dividing the gains by the cost associated. The GBS does not focus on assessing such return on investments but it is very easy to calculate them if a company wishes to.

AFD Michelin, Solvay

LIFE Tool allows for comparing options X XX X XX XX

The Methodology was designed to compare the biodiversity balance. So, one of the most important uses of LIFE metrics is the comparison among companies´performance in biodiversity. BII (Biodiversity Impact Index) allows to compare biodiversity impact among companies of any size and sector on a scale from 0 to 1.000. BCA (Biodiversity Conservation Actions) allows to compare biodiversity positive performance among companies of any size and sector through a scoring system that considers biodiversity importance at a global and national levels. LIFE Methodology enables companies to compare investment vs biodiversity results. This analysis is done considering the ammount invested on each project vs projects´ scoring.

PBF Tool allows for comparing options XX X X X

As explained earlier, the PBF is mainly a LCA based approach and as such its best business application is Comparing options at Product Level. To assess at product level, one needs alto to assess supply chain which is part of the life cycle of the product. In the 3 case studies completed, supply chain assessment was part of the scope and could be disaggregated from the full assessment at product level. Beyond product level, LCA is now also used at project level and at organisation level, that is why PBF could also be used at these levels. A Case study is currently under progress at Site / Project level.





STAR Tool allows for comparing options XX X X X X

STAR includes an explicit ‘Return on investment’ focus (or Cost benefit analysis) which addresses both biodiversity return and economic return. RoI measured in terms of potential and delivered reduction in species extinction risk; assessment of cost of such actions needed at local scale Values generated at one site/polygon are directly comparable to those generated at any other site/polygon.

5. Assessment / rating of biodiversity performance by third parties, using external data

ABD Index

Tool allows third parties to assess a company’s performance, by only using external data. X X X X X X

Status is measured using external data – but the key information that is needed from the companies is the sourcing information and location

BFFI Tool allows third parties to assess a company’s performance, by only using external data. X 0 X X XX 0

The underlying tools of the BFFI, LCA and ReCiPe, allow for impact calculation on different levels (portfolio, company, supply chain, product/services). However, focus of the BFFI is a biodiversity footprint on portfolio level. For the portfolio/sector focus, BFFI uses external data from the Exiobase database and databases like ecoinvent

GBS Tool allows third parties to assess a company’s performance, by only using external data. 0 0 0 XX XX (2) 0

The GBS can be used to screen companies’ biodiversity footprint risks based on external / public data, If only sectoral data are available, then obviously two companies within the same sector cannot be distinguished. But if company-specific data (on pressures) are publicly available, two companies within the same industry can be distinguished.

Mirova, BNP Paribas Asset Management

LIFE Tool allows third parties to assess a company’s performance, by only using external data. XX XX XX XX

LIFE Certification was designed to allow thidy-party assessment and disclosure of biodiversity performance. Independent certifying bodies are required to publish LIFE companies reports that contains their metrics.


177


Product / Service

Site / Project

Supply chain


Country / region

Ex.: https://www.tecparcert.com.br/en/life/

6. Certification by third parties

BD Protocol

Tool allows third parties to do a certification audit according to a well-established methodological approach. XX XX XX

the BD Protocol helps develop a comprehensive audit trail for all im[act data, for eventual 3rd party audit.

LIFE Tool allows third parties to do a certification audit according to a well-established methodological approach. XX XX XX XX XX

LIFE Certification was designed to allow thidy-party assessment and disclosure of biodiversity performance. LIFE has accredited certifying bodies in Brazil and Paraguay. These certifying bodies are able to make LIFE evaluations in other countries where they are operationg. Certifying bodies are evaluated and accredited by LIFE according ISO requirements to conduct independent audits. LIFE Methodology was developed according ISEAL best practices Code. Independent certifying bodies are required to publish LIFE companies reports that contains their metrics. Eg.: https://www.tecparcert.com.br/en/life/

STAR Tool allows third parties to do a certification audit according to a well-established methodological approach. X X X X X

Methodology for calculating ex-ante and ex-post values is clear and transparent and could be used by an auditor

7. Screening and assessment of biodiversity risks and opportunities

ABD Index

Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

XX XX XX XX XX XX

ABDI assesses 6 areas of increased risk as related to low/high agrobiodiversity: malnutrition risk, poverty risk, biodiversity loss,losses due to pests and diseases, losses due to climate change, losses due to land degradatation ABDI also identifies opportunities for resilience building and for better management and utilization of agrobiodiversity for more constructive contributions to healthy diets, sustainable agriculture and/or future options

BD Protocol

Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

X X X

Not specifically. Individual biodiversity accounts would be valued qualitatively (e.g. red listed species) and quantitatively (e.g. share of land cover with negative impacts) which would highlight risks and opportunities.

BIE Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

0 XX 0 XX 0 0

Stage 1 of the tool prioritizes sites in terms of the biodiversity risk. Pilots Pilots

BFFI Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

0 0 0 0 0 0

The BFFI includes an interpretation step for FI using the tool. This step does not (yet) include an automatic assessment of (financial or operational) risks and opportunities

GBS Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

0 0 0 0 0 0

The GBS results can be compared to sectoral impact intensity averages (MSA.km² loss per monetary value) so that investments at corporate/portfolio/sectorial levels in risky sectors can be identified. This gives an overview of (future) regulatory,reputational and financial (as investors move out of assets with high biodiversity impacts just like they have started moving out of fossil fuels) risks. Other risk and opportunities analysis is rather included in the qualitative step of the assessment and not done automatically.

LIFE Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

X x X x

LIFE Key tool allows translate biodiversity performance outcomes to risk levels through the minimum performance metric developed by LIFE Methodology.

https://www.tecparcert.com.br/en/life/

https://www.tecparcert.com.br/en/life/


178


Product / Service

Site / Project

Supply chain


Country / region

STAR Tool includes information that automatically translates biodiversity performance outcomes (as identified by applying business applications 1 to 6) to risk levels and/or opportunity levels.

X X X X X

Changes in values of STAR metric translate to changes in risk of species extinction- ex-ante baseline value equates to opportunity or risk, ex-post value relates to delivery


179

COLOPHON

ASSESSMENT OF BIODIVERSITY MEASUREMENT APPROACHES FOR BUSINESSES AND FINANCIAL

INSTITUTIONS

UPDATE 2 REPORT BY EU BUSINESS @ BIODIVERSITY PLATFORM

AUTHOR

Johan Lammerant

CO-AUTHORS:

Annelisa Grigg, Katie Leach, Audrey Burns, Julie Dimitrijevic, Sharon Brooks, Joshua Berger, Joêl Houdet,

Mark Goedkoop, Mark Van Oorschot, Jerome Kisielewicz, Lars Müller

DATE

6th December 2019

ABOUT THE EU B@B PLATFORM

The EU B@B Platform is a forum for dialogue and policy interface to discuss the links between business and

biodiversity at EU level. It was set up by the European Commission with the aim to work with and help

businesses integrate natural capital and biodiversity considerations into business practices. The EU B@B

Platform focuses its work on three thematic workstreams: Natural Capital Accounting, Innovation and Finance.

ICF is supporting the European Commission in running the EU B@B Platform since 2013. Arcadis is leading

the Natural Capital Workstream.

ABOUT ALIGNING BIODIVERSITY MEASURES FOR BUSINESS

The Aligning Biodiversity Measures for Business initiative aims to form a common view amongst key

stakeholders on the measurement, monitoring and disclosure of corporate biodiversity impacts and

dependencies. It will encourage the development of more credible indicators of corporate contribution to global

biodiversity goals into corporate reporting and global policy frameworks. Organisations engaging in the

initiative include: IUCN, Cambridge University (Cambridge Institute for Sustainability Leadership), The Nature

Conservancy, the European Business @ Biodiversity Platform, CDC Biodiversité, PRé, CREM, Fauna & Flora

International, Conservation International, Biodiversity International, The Biodiversity Consultancy, Arcadis,

Endangered Wildlife Trust, PBL Netherlands Environment Assessment Agency, the Natural Capital Coalition,

Ecoacsa, Global Nature Fund and Arizona State University

critical assessment of biodiversity accounting approaches for ......the biological diversity...

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