land quality

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Agriculture, Ecosystems and Environment 81 (2000) 93102

Land quality indicators: research plan

J. Dumanski a,, C. Pieri b

a 16 Burnbank Street, Ottawa, Canada K2G 0H4b Rural Development Sector, World Bank, Washington, DC, USA

Abstract

Indicators of land quality (LQIs) are being developed as a means to better coordinate actions on land related issues, such

as land degradation. Economic and social indicators are already in regular use to support decision making at global, national

and sub-national levels and in some cases for air and water quality, but few such indicators are available to assess, monitor

and evaluate changes in the quality of land resources. Land refers not just to soil but to the combined resources of terrain,water, soil and biotic resources that provide the basis for land use. Land quality refers to the condition of land relative to the

requirements of land use, including agricultural production, forestry, conservation, and environmental management.

The LQI program addresses the dual objectives of environmental monitoring as well as sector performance monitoring

for managed ecosystems (agriculture, forestry, conservation and environmental management). The primary research issue

in the LQI program is the development of indicators that identify and characterize the impact(s) of human interventions on

the landscape for the major agroecological zones of tropical, sub-tropical and temperate environments. Core LQIs identified

for immediate development are: nutrient balance, yield gap, land use intensity and diversity, and land cover; LQIs requiring

longer term research include: soil quality, land degradation, and agro-biodiversity; LQIs being developedby otherauthoritative

groups include: waterquality, forestland quality, rangeland quality, and land contamination/pollution. 2000 Elsevier Science

B.V. All rights reserved.

Keywords:Land quality; Land use; Land management; Land degradation; Monitoring

1. Introduction

The impacts of human interventions on natural sys-

tems are increasingly critical issues for the future. In-

creasing population pressures and increasing demands

for services from a fixed land base are threatening

the quality and the natural regulating functions of the

soil, water and air resources on which sustainability

depends. For the first time in history, we are crossing

the threshold of new lands available for cultivation.

Corresponding author.

E-mail address: [email protected] (J. Dumanski).

For the first time, the sustainable management of the

land resource is more important than land supply for

development. However, land degradation and misman-

agement are threatening our opportunities and flexi-

bility for increased services from the land, requiring

increased investment in soil conservation and even re-

habilitation and reclamation. Estimates are that about

40% of agricultural lands are affected by human in-

duced land degradation (Oldeman et al., 1990). The

land quality indicators (LQIs) program is being devel-

oped to expand our knowledge and understanding onland management and degradation problems in man-

aged ecosystems, and to provide guidance to decision

0167-8809/00/$ see front matter 2000 Elsevier Science B.V. All rights reserved.

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94 J. Dumanski, C. Pieri / Agriculture, Ecosystems and Environment 81 (2000) 93102

makers on these issues. It is important to know if cur-

rent land management is leading towards or away from

sustainability.

Sustainable land management and the choice of

feasible and cost effective management options is

hampered by the lack of available indicators for mon-

itoring how land is being managed by farmers, the

impacts of policies and programs on land manage-

ment choices at the farm level, and the impacts of

different management scenarios (cause-effect rela-

tionships) on land quality. As illustrated in the World

Bank Action Plan, From Vision to Action in the

Rural Sector (World Bank, 1997a), there is clearly

a major requirement at national and global levels for

increased agricultural production and intensification,

but the challenge is to achieve this while maintaining

and enhancing the quality of the land resource on

which production depends. This implies the need for

standards, such as LQIs, on which to measure and

assess progress towards these goals.Indicators are common instruments for monitoring

progress towards some larger objectives. For exam-

ple, economic indicators, such as GDP, distribution of

employment, etc., are used regularly to monitor per-

formance of national and local economies. Similarly,

access to social services, literacy rates, etc., are used

for comparative assessments of social development.

On the environmental side, indicators are available for

monitoring and reporting on air and water quality (for

which the World Bank played major catalytic roles).

However, indicators which can be used to monitor

change in land quality are still not available, and be-

cause we cannot monitor land quality, we are not ina strong position to take appropriate action on land

related issues such as land degradation (A. Young,

personal communication).

Agriculture is traditionally viewed as an environ-

mental problem, but if carefully managed, it can also

be a significant part of the environmental solution.

However, monitoring the impacts of agriculture on the

environment is much more difficult than monitoring

other sectors. Hundreds of millions of private farmers,

large and small and male and female, are stewards

of the globes land resources, and monitoring the

impacts of their land use decisions is a major under-

taking. Although, the impacts of any one individualis minuscule, the collective impacts of the millions of

management decisions can have major regional and

even global environmental impacts. For example, lack

of soil cover results in erosion and siltation of reser-

voirs; loss of soil organic matter through land degra-

dation contributes significantly to CO2 emissions to

the atmosphere; mismanagement of irrigated lands

results in salinization and water logging. Currently,

our procedures for monitoring the extent and im-

pacts of these processes are rudimentary, and greatly

hampered by the lack of appropriate indicators, the

right kinds of data, and cost-effective monitoring

methods.

This paper reports on the background, criteria, and

research plan for a set of indicators for monitoring

land quality. These evolved from a collaborative pro-

gram being developed and implemented by a coalition

consisting of the World Bank, the Food and Agricul-

ture Organization of the United Nations (FAO), the

United Nations Environment Program (UNEP), the

United Nations Development Program (UNDP) and

the Consultative Group on International AgriculturalResearch (CGIAR). The program addresses the dual

objectives of environmental monitoring as well as sec-

tor performance monitoring for managed ecosystems

(agriculture and forestry). The objective of the paper

is to provide guidance and to focus the research on

LQIs.

In the context of LQIs, land quality is the condition

of land relative to the requirements of land use, includ-

ing agricultural production, forestry, conservation, and

environmental management (Pieri et al., 1995). Land

is an area of the earths surface, including all elements

of the physical and biological environment that influ-

ence land use. Land refers not only to soil, but also tolandforms, climate, hydrology, vegetation and fauna,

together with land improvements, such as terraces and

drainage works (Sombroek and Sims, 1995).

2. Research requirements for the LQI program

The research requirements for the LQI program

were developed from three regional workshops in

1995 (Cali, Nairobi and Washington, DC) and two

further workshops in 1996 (Rome and Washington,

DC Saginaw, MI). These identified a broad frame-

work of activities, including adoption of the pressure-state-response framework as the means for indicator

development, and the agroecological zones (AEZs) or


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J. Dumanski, C. Pieri / Agriculture, Ecosystems and Environment 81 (2000) 93102 95

ecoregions as the basis for geographically stratifying

major land related issues. An AEZ is a spatial (land-

scape) unit for identification and application of re-

source management options to address specific issues.

It is derived from geo-referenced biophysical and

socio-economic information, and it is dynamic and

multiscale in that it reflects human interventions in the

landscape. The meetings also began the difficult pro-

cess of selecting sets of quantifiable and comparable

indicators to be used internationally to evaluate the

impacts of human interventions in important AEZs in

tropical, sub-tropical and temperate zones.

The research plan was developed during a research

planning meeting, 2122 October 1996, Washington,

DC, sponsored by the World Bank. A panel of in-

ternationally acclaimed scientists and administrators

established research priorities and a recommended

research plan, defined strategic alliances to be devel-

oped with existing programs to achieve the research,

and identified potential sources of funding. This planhas since been discussed and generally accepted at

various national and international meetings.

A short and longer-term research plan was recom-

mended involving a set of five core LQIs to be initi-

ated in the short term as international reference stan-

dards. A second set of three indicators for national

and sub-national (project level) monitoring and evalu-

ation was recommended for development over a longer

time period. A third set of four LQIs was recognized,

but development was recommended by liaison with

authoritative institutions already involved in building

these indicators.

2.1. Selecting the right (Core) LQIs

Interest in environmental monitoring has spawned

a virtual indicator development industry in the recent

past. Very often such indicators have been developed

by a priori identification of candidate indicators by

a panel of experts, followed by assembling and ana-

lyzing whatever data are available to support this se-

lection. The success of this approach has been mixed,

since often the final indicator has to be molded to fit

the data available, and to reflect experiences gained

in developing the indicator. Consequently, there is a

strong possibility of bias in development of the indi-cator(s), and the final product is often somewhat less

than what was intended or desired at the outset.

The LQI program takes an alternative approach.

Experience has shown that truly robust indicators are

developed first of all through comprehensive analyses

of the complex systems to be described and monitored.

It is only through such thorough and comprehensive

analyses that sufficient understanding of a system is

developed to ensure indicators that are simple and use-

ful enough to be used at national and international

levels.

The program will have to deal with the important

questions of how to integrate socio-economic (land

management) data with biophysical information in the

definition and development of LQIs, and how to scale

and aggregate indicators from local to regional, na-

tional and global scales. Equally important, the indi-

cators will have to be based on data that are either

available or easily assembled, but they will still have

to sufficiently reliable and robust to stand up under

scientific scrutiny.

Land quality should be assessed for specific typesof land use and management and for specific AEZs

conditions in a country. Otherwise, trends and perfor-

mance cannot be sensibly monitored, interpreted, and

reported. This requires the development and applica-

tion of spatially located and (normally) geo-referenced

temporal data bases of the variables to be used to de-

velop the LQIs. Such data bases are developed through

spatial integration over time of the socio-economic

and biophysical data for the different AEZs of a coun-

try. However, census data and other primary data for

land management, and AEZ boundaries normally do

not coincide, and except for very small countries, most

countries are made of several AEZs. Therefore, pro-cedures of spatial integration are necessary, but these

must follow recognized protocols, such as described

for Hierarchy Theory (Dumanski et al., 1998), and

some criteria of correspondence between the different

data bases must be applied (the 70% spatial coverage

rule is often used, whereby it is assumed that the lo-

cal socio-economic and biophysical data are directly

related if the spatial coverage of the two sources of

data are 70% or higher).

The steps are first of all to characterize the range of

AEZ resources, identify the important issues (prob-

lems) in each AEZ, select LQIs relevant to the issues,

characterize the land management practices used byfarmers in each AEZ, develop the necessary data

bases and GIS coverages, then conduct the research to


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develop, model, test and refine the LQIs (Pieri et al.,

1995; World Bank, 1997b). This normally will result

in a small, select group of LQIs that relate closely

to the (normally limited) AEZs in a given country.

When the LQIs are developed and interpreted, they

can either be reported by the AEZs, or the results can

be aggregated to sub-national and national levels by

weighting the LQIs according to their contribution

towards some national objectives, such as calculating

national wealth, rural poverty reduction, achieving

food security, etc.

2.2. Objectives for the LQI research program

Major gaps in knowledge on the impacts of human

interventions in the landscape were identified in the

various international workshops leading to develop-

ment of the LQI research plan. These are: links between land quality and poverty;

links between land quality and land management,i.e. management practices currently being used by

farmers;

lack of geo-referenced land management informa-

tion; lack of time series data and system resilience infor-

mation; rural-urban land management and land use planning

interactions; impacts of macro-level policies on land decisions

and land quality.

While all the knowledge gaps are important, the first

three are the highest priorities, and these are the basis

for the research program. This results in developmentof the following research objective:

Identifying and testing cause-effect relationships

among land quality, land management, and poverty

is the primary research objective for the LQI

program.

3. Details of the proposed research program

A minimal number of recommended Core LQIs

were identified using criteria and guidelines from ear-

lier workshops (Dumanski, 1994; OECD, SCOPE and

other indicator initiatives, and from the regional LQIworkshops held in 1995 and 1996 in Cali, Nairobi,

Rome and Washington). Emphasis was on making

better use of available data and information, and

integrating these with new information management

technologies such as remote sensing, geographic

information systems (GIS), relational data base man-

agement systems, the internet, etc.

The Core LQIs may be developed from direct mea-

surement (remote sensing, census, etc), or estimated

using well tested, scientifically sound procedures.

Emphasis should be on analyses to identify driving

force(s) of land use change and the impact(s) of the

change. Interpretation of the LQIs should not be done

in isolation, but within the context of what is happen-

ing with land management/land use in the countries

in question. Recommended contextual information to

assist in interpretation of the LQIs include social and

institutional information (tenure, gender, educational

levels, etc), farm household economics , climate, and

land use as available from the census.

Characteristics of Core LQIs are:

measurable in space, i.e. over the landscape and inall countries; reflect change over recognizable time periods (510

years); are a function of independent variables; are quantifiable and usually dimensionless (ratio es-

timates).

3.1. Core LQIs recommended for short term

development

This section provides short descriptions and the cri-

teria for each of the core LQIs being recommended.

The major research issues are identified, along withsome information on data sources and procedures for

assessment and interpretation. The first two LQIs are

already developed, and full instructions are available

on: www.ciesin.org

3.1.1. Nutrient balance (and nutrient depletion)

This LQI describes nutrient stocks and flows as re-

lated to different land management systems in specific

AEZs and specific countries. It is based on several

years of research and experience in East Africa and

Europe (Smaling et al., 1996).

The major research issue is nutrient cycling:

nutrient mining, nutrient imbalance and decreas-ing yields caused by removal of harvested products

(grains and residue), erosion and leaching, primar-


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ily in developing countries with low rates of fertil-

izer use; nutrient loading and environmental degradation

(phosphorus, nitrates, etc) caused by excess fertil-

izer and manure application in developed countries,

but increasingly also in developing countries with

high fertilizer subsidies such as China.

The research process is similar to environmental ac-

counting. It involves establishment of nutrient balance

sheets with losses and additions as estimated from

nutrient removal through crop harvesting, erosion,

etc., compared to nutrient additions due to fertilizers,

organic inputs, recharging of the nutrient supply due

to legume rotations, deep rooting systems, natural

recharging due to atmospheric fixation, etc. Smaling

et al. (1996) have demonstrated how this LQI can be

developed for several hierarchical scales, including

the farm level, region (AEZ) level, and national level.

Actual measurements of nutrient cycling are rarely

available, but Smaling et al. (1996) have demonstratedthat reliable estimates of nutrient balance can be devel-

oped using crop yield statistics from national census,

nutrient additions from fertilizer trade statistics, and

various biophysical models for denitrification, leach-

ing, erosion, etc;

3.1.2. Yield gap

Three closely related statistics are proposed for this

issue: yield trends (direction, rate of change) for the major

food crops in specific AEZs; production risk (change in the expected annual vari-

ability in yield) for the major food crops in specificAEZs;

yield gap (current yields compared to potential farm

level, economically feasible yields) for the major

food crops in specific AEZs.

These are useful indicators because they are so

easily understood, easily converted into economic

terms, and they are useful for monitoring both project

and program performance. However, they have value

as LQIs only if changes in yield are clearly related

to land management in specific AEZs and for spe-

cific management systems. There are many possible

cause-effect relationships with yield, e.g. marketing,

climate change, subsidies, land management, etc.,and the indicator can be misleading without compre-

hensive analyses of the driving forces causing yield

change. Knowledge of farming systems, marketing,

the policy environment and other contextual informa-

tion, as well as cause-effect relationships of current

land management on yield trends and variability are

necessary.

The key research issues are: to what extent are changes in land quality resulting

in corresponding changes in crop yield and produc-

tion risk; how can reliable estimates of yield gaps be devel-

oped for developing countries, and what are the

management options to improve the yield gap; are there practical biological and economic thresh-

olds (yield and variability) to ensure sustainable

production systems.

Yield gap analyses relates to residual yield opportu-

nities that could be realized with improved cultivars,

fertilization, and land management. Alternatively, it

reflects the extent to which the biological production

systems are currently being pushed, realizing that ifpushed beyond a biological threshold, the systems will

likely fail. Knowledge of this threshold is strategically

important for policy, program and management plan-

ning in high production environments, since the mar-

gin for error decreases as the biological production

threshold is approached. Concurrently, the impact of

error at these production levels is likely to be signifi-

cant.

Yield data are available from the FAOSTAT data

base, as well as other sources, such as special surveys,

safety net and farm subsidy programs, international

marketing programs, etc. Alternately, crop growth

models can be used to simulate long-term averageyields and annual yield variability (to a lesser extent),

providing that the models have been thoroughly tested

and found to be reliable. Also, remote sensing data

can be used to estimate level and variability of crop

yields, or to provide agro-meteorological inputs for

crop growth models.

A major concern is that, national yield statistics are

normally a ratio of national production divided by area

harvested. Such estimates can be highly biased, since

experience has shown that expansion of cultivation

on marginal lands, for example, can depress national

average yields at the same time that yields in more

favorable areas are increasing due to increased fertil-izer use, improved soil conservation, adoption of im-

proved cultivars, etc. Ideally, yield data for the major


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food crops should be geographically referenced (dis-

aggregated) on an AEZ basis, and then analyzed in re-

lation to the agricultural production systems and land

management practices being used by farmers.

3.1.3. Agricultural land use intensity and land use

diversity

These two LQIs are intended to assess the general

impacts of current land management at the farm level.

Assessing land use intensity and land use diversity

provides information on trends towards or away from

sustainable land management.

Land use intensity is intended to estimate the im-

pacts of agricultural intensification (and increased

frequency of cultivation) on land quality. Normally,

intensification involves increased cropping, shift to-

wards more value-added production, and increased

amounts and frequency of inputs. Such changes,

without concurrent adjustments in land management

practices, often result in nutrient mining, soil ero-sion and other forms of land degradation. However,

agricultural intensification, if properly implemented,

can also result in improved land quality, as shown

in Kenya, Brazil, and other areas (El-Swaify, 1999).

The difference is the specific management practices

adopted by farmers during the transition towards

intensification (often based on expected increased

profits from the more intensive production systems).

Land use diversity (agro-diversity) is the degree of

diversification of production systems over the land-

scape, including livestock and agro-forestry systems;

it is the antithesis of mono-cropping. Agro-diversity

is often practiced by farmers as part of their risk man-agement strategy, i.e. to guard against crop failure

and financial collapse, but it is also a useful indicator

of flexibility and resilience in regional farming sys-

tems, and their capacity to absorb shocks or respond

to opportunities, e.g. Kenya (English et al., 1994).

Agro-diversity is assessed on the number, kind and

complexity of components in the farming systems, but

it can also be approximated from national statistics by

the number and kinds of crops per growing season,

the extent and frequency of rotations, presence or

absence of livestock in the production systems, etc.

The key research issues are:

is current land management contributing to in-creased land degradation or improving land quality;

are current agricultural management practices

contributing to improved global environmental

management.

A major concern with these LQIs is that data on

current land management practices are generally not

available (except from special surveys), and various

surrogates will have to be developed. Some of these

are already available in the literature, such as land use

intensity based on crops per growing season, extent

and frequency of rotations; cultivation intensity, etc.;

ratio of cultivated land to cultivable land; area and fre-

quency of soil enhancing to soil depleting crops; ra-

tio of mono-cropping to mixed cropping, etc. These

are based on data available from the census and from

agricultural and household surveys. Time series infor-

mation on crop rotations, etc. can be generated from

remote sensing (Huffman et al., 2000).

3.1.4. Land cover

This LQI is intended to estimate the extent, dura-

tion, and time of vegetative cover on the land surfaceduring major periods of erosive events. It is also in-

tended to measure land cover change over time, and

the correlation with land use pressures.

This LQI will be a surrogate for estimating ma-

jor land processes such as erosion, desertification,

deforestation, etc. In combination with land use in-

tensity and agro-diversity, it contributes to increased

understanding on the issue of agriculture and envi-

ronmental sustainability. The land cover LQI (extent,

duration, time series, including critical erosive peri-

ods) will require application of remote sensing data,

supplemented by ground truthing.

The key research issues are: is current ground cover adequate to protect against

land degradation during critical erosion periods; how is the kind, extent and duration of land cover

changing over time; what pressures are causing change in land cover.

Archived remote sensing coverages are already

available in many cases to initiate testing and develop-

ment. Also, some of the required indices, such as the

normalized difference vegetation index (NDVI) and

revised NDVI, are already available (Ashbindu Singh,

UNEP, personal communication). Indices for specific

areas will have to be mapped, and then compared

(overlain) with mapped estimates of erosion risk, asobtained from biophysical models such as EPIC and

others. Such analyses, calculated over to time with


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historic data or simulated using best estimates of land

use and weather data, will provide information on the

degree and probability of erosion risk.

Land cover (kind, extent, and duration) can be in-

terpreted as a surrogate for land degradation. Such

indicators are important for planning and evaluating

national and regional programs in soil conservation

and agricultural production, but increasingly they are

required for estimating the potential impacts of im-

proved land management on issues of global signif-

icance, such as carbon sequestration, desertification,

and biodiversity. Increasing the biomass and extent of

land cover often increases soil organic matter and soil

water storage, and this enhances yield potential and

decreases production risk. At the same time, however,

this process sequesters increasing amounts of atmo-

spheric carbon in the soil, thereby providing global

environmental benefits by mitigating climate change,

controlling desertification, and often increasing the

quality of wildlife habitat.

3.2. Core LQIs recommended for longer term

development (sub-national (AEZ) program)

These are LQIs, where the theoretical basis for de-

velopment is still being developed, e.g. soil quality, or

where reliable data to report on the LQI are generally

not available, e.g. land degradation. These LQIs are

designated for the second phase of the LQI research

plan, they require a longer term commitment, and they

will be more expensive to develop. The recommended

LQIs are:

3.2.1. Soil quality

The scientific basis for this LQI is that soil quality

reflects and is measured by the conditions which make

the soil a living body. There are currently several na-

tional and international working groups trying to de-

velop a relevant and effective indicator of soil quality,

but successes are mixed. The evidence indicates that

traditional soil chemical, physical and taxonomic data

by themselves are not useful to describe soil qual-

ity, but a more definitive indicator may be developed

from integrating these data with soil biology and by

monitoring the soil food chain. Soil life functions also

require favorable chemical and physical conditions,but the latter are not suitable indicators on their own.

In the meantime, a useful surrogate may be developed

from data on soil organic matter, particularly, the

so-called dynamic or microbial carbon pool (bacterial

and fungal carbon). Recent research indicates that soil

quality and soil agro-diversity are closely linked and

could be evaluated by characterizing the resilience

of the main functional groups in the soil, namely

macrofauna (earthworms, termites), nematodes, mi-

crosymbionts (mychorrhiza, N-fixers), and microbial

biomass (fungi, protists, bacteria) (Swift, 1997).

The key research issues are:

do current land management practices maintain, en-

hance or reduce the capacity of soil organic matter

to perform the above functions; do current land management practices maintain the

biological life and biodiversity of the soil, and thus

enhance the environmental resilience of the soil for

maintenance of global life support functions.

Soil organic matter (SOM) is the best surrogate for

soil health, since SOM reflects the residue of plant

and soil organisms that have lived and died in thesoil. The basic functions of SOM are development

and maintenance of soil structure, nutrient and or-

ganic carbon storage, and maintenance of biological

activity. Thus, SOM is the primary source for and a

temporary sink for plant nutrients and soil organic

carbon in agroecosystems, maintains soil tilth, aids

in the infiltration of air and water, promotes water

storage, reduces erosion, and controls the efficacy

and fate of applied pesticides. Specific indicators will

have to be developed to characterize the sensitivity of

organic matter for these functions.

This LQI would need to be linked closely with land

use intensity, agro-diversity, and land cover becauseof the implications and possible impacts for improved

land management.

3.2.2. Land degradation

Land degradation (erosion, salinization, com-

paction, organic matter loss, etc) has been studied

for many years, and there is a strong theoretical base

for several State LQIs to describe the processes. The

major deficiency, however, is the serious lack of sys-

tematic and reliable data for reporting on the extent

and impacts of these indicators, although there are

innumerable small research studies in many parts

of the world all of which provide some informationon the current status of land degradation for small

areas. This information is being assembled through


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programs such as WOCAT and ISRIC, but progress

is slow.

The key issues are: do current land management practices contribute to

loss of agricultural production potential; do current land management practices contribute to

off-site environmental damage and reduced envi-

ronmental resilience, as land becomes degraded or

is allowed to erode due to mismanagement.

Systematic monitoring and application of these

indicators has not been instituted in any country ex-

cept for the USA. Because land degradation is site

specific, monitoring systems have to be highly com-

prehensive and cover all land areas, and these rapidly

become exceedingly expensive. Alternate means of

assessing land degradation are necessary. A consid-

erably less expensive approach is approximated in

Canada by building on the agricultural census with a

few strategic questions on current land management

practices (Dumanski et al., 1994). Improved infor-mation on land management at the farm level thus

become available with each normal census reporting

period.

In addition, some promising new technologies for

estimating the extent, duration and impacts of land

degradation, involving the use of biophysical models

such as EPIC, some remote sensing procedures, or a

combination of these with ground surveys, are becom-

ing available (Ingram and Gregory, 1996). Research is

needed, however, to develop cost effective procedures

for application at local (project) and national scales,

and aggregation of results for policy and program

application.

3.2.3. Agro-biodiversity

Agro-biodiversity is a new concept, and much work

is still required to develop this to the point where

practical indicators could be developed for monitor-

ing and evaluation. By far the majority of the earths

land surface has already been modified by human

interventions, so an understanding of land use sys-

tems, the dynamics of land use change, the driving

forces behind land use change, and the resiliency of

land use systems are fundamental to better managing

biodiversity issues in agriculture.

The primary research issues are: how to better integrate biodiversity in the process

of intensifying agriculture (Srivastava et al., 1996),

and manage the gene pools used in crop and animal

production; how to manage and protect the diversity and healthy

living conditions for soil (micro)organisms, realis-

ing their roles in biologic nitrogen fixation, etc., but

also as sources for antibiotics, etc.; how to manage the coexistence of natural species,

particularly wildlife and water fowl, in agricultural

areas.

It is often argued that intensive agriculture is the

principle cause of habitat destruction and biodiversity

loss, but the alternative, agricultural extensification,

exacerbates habitat decline and species loss (Smith,

1996). This is because extensification normally en-

tails expansion of cultivated areas on marginal lands,

which usually are the prime areas of natural habitat. At

the same time, agricultural systems, particularly those

based on traditional agriculture or systems in transition

that retain some traditional plant varieties and cultiva-

tion practices, are an important conservatory of geneticmaterials important to agriculture. Agricultural sys-

tems, such as mixed systems with integrated crop and

livestock production and those involving agro-forestry,

utilize and manage a wide genetic pool for production.

However, the adoption of high-input, modern farm-

ing, with reliance on monoculture, mechanization, and

pesticides and other agri-chemicals, normally dimin-

ishes biodiversity and destroys many beneficial insects

and soil microorganisms.

Agricultural intensification, however, should not be

considered simply as the adoption of modern farming

systems. Some new technologies such as integrated

pest management, conservation tillage, and agro-forestry actually expand the genetic resources used in

agriculture.

The proper role of agro-biodiversity is to achieve

the balance required to ensure the health and sustain-

ability of agroecosystems, and protect the flexibility

and resilience of farming systems againt outside

stresses and periodic shocks (such as pests, diseases

and droughts) (Smith, 1996). Maintaining a wide

genetic base in agriculture is essential to ensure the

resilience of farming systems, because this provides

greater options for alternative production systems,

and it is the basis for improved risk management and

rapid response management. Ensuring the resiliencyof these systems is an important condition to sustain-

ability.


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Table 1

Proposed indicators for agro-biodiversity

Indicators Surrogates

Natural habitat loss Encroachment by agricultural production systems

Habitat fragmentation Encroachment of agriculture in an uncoordinated manner

Species loss even when natural habitat is intact Pollution; sedimentation; excessive harvesting, etc

Decline of biodiversity of crop species on farms Adoption of monocropping; reduction of mixed cropping

Decline of biodiversity within species Adoption of modern varieties; expansion of intellectual property rights

Although, data with which to assess agro-biodiversity

are universally scarce, various surrogates for this can

be developed using information on land use dynamics.

Smith (1996) proposes some preliminary indicators

and surrogates (Table 1).

Some indicators are specific to managing natural

habitats, while others will be similar to those identified

under land use intensity, land use diversity, and land

cover (see previous section).

3.3. Core LQIs recommended for development byliaison with other authoritative groups

This activity is mostly a matter of liaison with

international and national agencies already working

on indicators, and selecting those indicators which

best meet the requirements of the LQI program. An

associated major activity will be to identify reliable

sources of data, and making these available through

the internet.

The LQIs included in this category are:

3.3.1. Water quality

Primary interest is on water supply and qualityrelated to land use change, e.g. estuarine, in-land

waters, irrigation water quality, etc.; link with water

quality indicators already being developed under the

OECD indicators program, and others.

3.3.2. Forest land quality

Primary interest is on land quality related to enviro-

nmental management and forest production,

specifically land quality changes related in forest

management; link with the international forestry indi-

cators process.

3.3.3. Rangeland qualityPrimary interest is on rangeland quality related to

change in land use intensity and diversity, and the role

of livestock in mixed production systems; link with

range monitoring programs being developed under the

convention to combat desertification, and various re-

mote sensing programs.

3.3.4. Land contamination/pollution

Primary interest is on type, extent and impacts of

land contamination by human interventions; inter-

ested in heavy metals, organic contaminants, radioac-

tive contamination, etc.; link with agencies collating

available information.

4. Conclusions and recommendations

Global populations are increasing rapidly, along

with the tendency to concentrate in certain agroen-

vironments. For the first time in history, populations

pressures are impacting global life support systems,

but it is not the size of populations but the manage-

ment systems practiced that impacts on land quality.

If traditional ways are continued, land degradation

will intensify with the concomitant collapse of certain

land use systems.However, human activities can also be agents for

positive change. New, improved land management

technologies for crop and animal production are

necessary, particularly focusing on the health of the

environment, but applied within the context of inno-

vative and sympathetic social and economic policies.

Indicators of land quality are needed to raise aware-

ness of agricultural and environmental issues, and as

instruments for monitoring progress towards or away

from sustainable land management.

The LQI program has been successful in identi-

fying important research objectives and the research

issues to be addressed. It has also been successful inidentifying core LQIs, and recommending those to

be researched in the short term and those requiring


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longer term research. These are important advances

in providing direction and focus to the research ef-

fort. For example, within a short time scientifically

sound guidelines for several of the core indicators

have been developed, and more will be designed in

the near future. This experience clearly indicates that

much knowledge and experience already exists on

procedures for assessing land quality, and there is a

good interest in the scientific community to contribute

to the initiative. However, these experiences also in-

dicate that the lack of suitable national and global

data bases is emerging as the most severe restriction

to future development and application of land quality

indicators. This will require monitoring procedures

for collecting the required data, but monitoring needs

to be cost-effective. Various procedures can be used,

including agricultural census, remote sensing, spe-

cial surveys, and combinations thereof. Indicators are

valuable instruments for improved decision making,

but to be truly useful, they must be implementedwithin operational programs that provide direct guid-

ance for policies of major importance.

The LQI program of the World Bank and its

partners is increasing being accepted for its strategic

importance within the global scientific community.

Some excellent research activities are being initiated

in many countries, but these often address fringe

issues of local interest. Core funding to drive an

organized global program has been difficult, and

consequently, the big picture still remains untreated.

An associated major concern is the lack of reliable,

long-term data on which to monitor the impacts of

land use change. These are serious obstructions to ourcapacity to muster effective remedial policies, pro-

grams, and activities, and it is recommended that the

global scientific community mobilize its collective

efforts to resolve this problem.

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