agrev 3 · land use changes 1996-2016: data mining through markov chains mapping of nitrogen...

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Observe Test Improve Marc BENOIT, Arnaud GOBILLOT, Julia AUZERAL, Caroline BERNARD INRA SAD ASTER MIRECOURT FRANCE COST ACTION Payments for Ecosystem Services (Forests for Water) 01/03/2017 Agrivair AGREV 3: (AGRiculture-Environnment Vittel)

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Page 1: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

Observe

Test

Improve

Marc BENOIT, Arnaud GOBILLOT, Julia AUZERAL, Caroline BERNARD INRA SAD ASTER MIRECOURT FRANCE

COST ACTION Payments for Ecosystem Services (Forests for Water)

01/03/2017 Agrivair

AGREV 3: (AGRiculture-Environnment Vittel)

Page 2: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

When and where?

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Page 3: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

60 km² dont 58% de SAU

(3 500 ha)

54 km² dont 50% de SAU

(2 700 ha)

Since 1854: Farming and natural water production

114 km² 54% de SAU (6 200ha)

TOTAL

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Page 4: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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This watershed = f(Nestlé Waters + 30 Farmers + 11 000 ha)

11 400 ha (28 000 acres)

60% of agricultural land

30 farms involved

260 000 Nitrogen unit managed

Meadow

Temporary meadow

Spring culture

Autumn culture

Page 5: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

What was the past of Research-Action ?

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Page 6: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

Role of research team

Research-Action *:

• Knowledge is not produced strictly on line with a field of disciplin stream but in the relationship with action and actors to help them to develop a new « agrarian system.

• Research teams are in a « by pass » position between farmers and SGEMVittel. Research have to take into account

– The multiple faces of this problem : we need interdiciplinarity

– Diversity of actors : a big firm, farmers and their diversity, the profesionnal organization of agriculture ( Chamber of agricculture, cooperative, …)

– The diverse … and even contrary interests of these actors

– Sensibility of farmers to the pollution thema

– Diverse technical, economical, sociological, and anthropological factors influencing the farmer practices … ans so the nitrate lecaching.

– … so we are working with a complex situation.

* : due to Hatchuel, Moisdon, Weill reserach work since 1989 ( Centre de Gestion Scientifique, Ecole des Mines Paris – CNRS.

1988: 8 research teams (INRA, CNRS, CEMAGREF, Lorraine University) are involved

to find problems …and propose solutions .

Disciplins : economy (+1 PhD), agronomy (+1PhD), management (+ 2 PhD), soil

science, biology, sociology, animal science, geology, hydrology ( 1 PhD)

AGREV 1: 7 years ; money: SGEM Vittel + public water agency Rhin-Meuse + Inra .

In 1988, an innovative research programm, built as an « in field lab »

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Page 7: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

The steps of AGREV 1 and AGREV 2 programs:

1) Diagnosis of risks (practices, farming systems)

2) Proposals of changes to do

3) Analysis of real changes ( water, farms, agrarian system)

4) Evaluation of changes effects … and consequences

5) Giving tools ( GIS, evaluation risk, …) to pilot the new

agrarian system

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1988-1993

1992-1996

1997-1998

1998-2001

2002-2004

Page 8: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

The five types of economical helps • By SGEMV via Agrivair

– LAND PROPERTY CHANGES :

– Purchase of farmlands at very interesting prices (20000 F/ ha to landowner, 20000F/ha to farmer ) ,

– Free land use during 18 to 30 years for signatory farmers of the contract

– INCOMES:

– Contract of private law due to private status of water.

– 1500F/an/ha during 7 years

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• INVESTMENT for each farm : - Buildings for drying forage (grassland and alfa-alfa) - Platform of farmyard manure composting

• TRAINING : (i) Learning of new practices by farmers, (ii) Technical support( 2 independant advisory managers were paid), (iii) General advisory: Agrivair • OPERATING Functionning : - Management of composted farmyard manure - Helps for mechanical weed destruction

Page 9: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

TO CONCLUDE FOR THE PAST:

Monitor nitrogen flows at field / water landscape scale +

comprehensive research on diversity of agricultural practices +

temporal and spatial scales on the watershed +

research – action choice =

A book of proposal (first version in August 1991; second version in 2016)

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Best management practices set up:

1. Giving up maize cultivation

2. Giving up agrochemicals (no pesticides)

3. Maintain producing pasture and avoid bare soil

4. Promoting suitable application date, form and level of fertilization

5. Reducing stocking rate to a maximum of one livestock unit per hectare

6. Promoting technical solutions to optimize nitrogen use within the territory

Page 10: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

What is done in AGREV 3?

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Page 11: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

AGREV 3: A « research action » dealing with one main question: How to redesigned this farming system?

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* Hatchuel, Moisdon, 2002

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Allowing a viable farming system for farmers

And

A long term mineral water protection

Providing technical and economical

support

Imaging, implementing and

evaluating redesigned agricultural practices

Farmers challenging us every day!

Since 1992

Since 1986

Page 12: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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Methodological challenges at the watershed scale: RISK ASSESMENT for farmers and Nestlé Waters

Hazard identification

Risk assessment

Risk management

- Bibliography - Observation - Measured

Degree of risk over: - Time - Space - Practice

New “for water” management practices

Page 13: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

Fertilization: Cropping management Date Type Rate

AGREV 3: Monitoring of 3 scales dataset

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2000

20 springs monitored

Field plot

6000 ha and 19 years of land use

Farm:

- 75 analyses of manure and slurry

Nitrogen fluxes: - Animals - Milk production - Feeding - Etc.

Watershed

Observe:

Page 14: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

Result (1): Big Data for a Small Land Some indicators to manage the risk

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Land use changes 1996-2016: data mining through Markov Chains

Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003; De Vries et al. 2011, Benoît et al., 1992, Manneville et al., 2010. Hayo et al., 2002, Aarts et al. 2015

Estimate risk Landscape spatial organization and its temporal evolution PhD El Ghali LAZRAK 2012, Le Ber et al., 2006 ; Castellazzi et al., 2008, Ying Xiao 2015

Page 15: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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Result (2) : Evaluation Indicator of Nitrogen Risk Assesment (INRA)

INRA Watersheds validation (1989-2002)

984 ha of crops dominant

89 ha Grassland dominant

59 ha Forest dominant

Page 16: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

Result(3): Big Data useful for farmer

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Yield on cut grassland (t/ha)

Helping farmers improving their system

Page 17: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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Result(4): Big Data useful for Agrivair to manage the risk

Increasing global knowledge

Improving best management practice (book of proposals : V2)

Helping Nestlé Waters taking agricultural decision on the watershed

RE-defining territorial sensibility and agricultural practice impacting water quality

Involving farmers on field’s experiment to increase their knowledge

Page 18: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

To conclude

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Page 19: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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1. Understand the entire system and farmers perspective, through a common research question,

2. Develop appropriate agricultural practices through a common research protocol, 3. Actively involve the farmers in the entire participatory research process, focusing on: - data acquisition and mining processes - facilitating and providing new idea and/or unknown technology to the

farmers, promoting innovative methodologies and flexibility, 4. Think about the type of results discussion,

5. Build a continuous re-design of questions on the future of this water landscape.

Observe Test Improve

Page 20: AGREV 3 · Land use changes 1996-2016: data mining through Markov Chains Mapping of nitrogen pressure by multicriteria analysis ESCo Inra, Scoones et Toulmin 1998; Oenema et al. 2003;

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Is our AGREV framework a general one?

Agronomy

Agreement between farmers and NW

Personnal motivation

International market Etc.

CAP

Thanks for your attention! AGREV 3

INRA ASTER MIRECOURT [email protected] [email protected]

[email protected] [email protected]

+33 6 84 47 40 57

Give a value for ES

Biodiversity value?

Carbon storage?