Microsoft word - globio rivm ulrmc final _eng_.doc
Assessment of Wild Biodiversity in Agricultural Land Use
First design and perspectives of a pressure-based Global Biodiversity Model
A. Tekelenburg1, V. Prydatko2, JRM. Alkemade3, D. Schaub, E. Luhmann and JR. Meijer
Biodiversity was one of the main issues at the World Summit on Sustainable Development in
Johannesburg 2002. The world target set by its members is to a significantly reduce
biodiversity depletion by 2010. Agreements on how to measure biodiversity and establish a
core set or framework of biodiversity indicators was at the time unattainable in such
international forums as the Convention on Biological Diversity (CBD). Although the
assessment of future trends of biodiversity − generally focused on terrestrial natural
ecosystems and possible effects of policy responses − is difficult, several initial tools in this
field, including the GLOBIO model and the Natural Capital Index (NCI) framework, were
presented in Global Environment Outlook 3 (UNEP 2002; UNEP in press). The situation in
(intensively) managed agricultural and livestock production systems has been virtually
“untouched”, although it is considered a major topic. An Internet search by ULRMC has
shown, however, that the agriculture− biodiversity issue in Europe tends to be rapidly gaining
in prominence on the research and debate agenda, advancing from 25,000 hits in 2001 to
166,000 hits by April 2003. It cannot be denied that livestock production in cultural
landscapes always severely damages biodiversity when seen in the framework of the original
natural ecosystems; however, remaining biodiversity in cultural landscapes should not be
Four main arguments have been presented to show the need to assess the conditions for and
trends of wild-plant and animal species in cultural landscapes. The firs
t one is the conversion
of a significant share of terrestrial ecosystems (about 50% of all European land). Secondly
many species, including rare species threatened with extinction, depend on adequate
management of cultural landscapes. Thirdly
, cultural landscapes are highly valued by the
population (see, for example, the Ukrainian open fields with cereal crops and the hedges
1 Biodiversity assessment researcher at RIVM, The Netherlands (+31 30 2742608 or <[email protected]
2 Biodiversity expert at the Ukrainian Land and Resource Management Center in Kyiv and partner of the BINU (GEF international project: Biodiversity Indicators for National Use), +38 044 2302266 or <[email protected]
3 Project leader, Biodiversity Modelling at RIVM, The Netherlands.
around farmlands in England, some of them already protected (UNESCO cultural heritage
and finally, a policy change has recently occurred in which the biodiversity
conservation strategy of protection was translated into sustainable use. We expect that
possibilities will arise from the assessment of biodiversity in cultural landscapes to reduce the
negative impact or maintain a significant share of biodiversity along with sustainable use.
The National Institute for Public Health and the Environment (RIVM), work together with the
United Nations Environmental program (UNEP) World Conservation and Monitoring Centre
(WCMC) and UNEP GRID Arendal to address both natural and cultural ecosystems, and
terrestrial as well as aquatic and marine ecosystems. Based on their experience on biodiversity
assessment, an international consortium has been founded to build new tools for the
assessment of current state and future biodiversity trends. The Ukrainian Land and Resource
Management Center (ULRMC) is one of the four pilot counterparts at the national level
participating in the two-year GEF funded CBD-WCMC project, “Biodiversity Indicators for
National Use” (BINU). The objective of the project is to assess trends in Ukraine
The focus in this paper is on modelling biodiversity of wild-plant and animal species in
agricultural and livestock production landscapes. Not included are the genetic diversity of
domesticated animals and food crops, or ecosystem (landscapes) diversity. Biodiversity that
directly supports production (for example, soil-quality related species or insects being
pollinators or pest controllers) is considered here to be an integral element of wild
biodiversity. For this reason, we did not follow the functional biodiversity approach of the
OECD Agri Biodiversity Framework (ABF), but took another recommendation into account,
i.e. the classification of production systems into low-to-high intensity or into semi-natural-to-
completely modified ecosystems. According to the suggestions of the Millennium Ecosystem
Assessment (MA), assessment should include analysis on different scales (landscape,
This paper presents the very first insights into and tools used in building a new Global
Biodiversity Model (GLOBIO), which can also be used for assessments of agricultural land
use and landscapes. This model also represents an initial attempt to combine information,
stimulate discussion, promote exchange of knowledge and joint learning, and improve
conceptual thinking. It provides us with the first grasp on application and encourages
scientists and politicians to focus on biodiversity maintenance as an integral part of the
production function. It also presents the GIS software that will be used for interactive
2. The process of biodiversity depletion
The rate of biodiversity loss has accelerated rapidly, especially during the last century. UNEP
and international nature-protection NGOs have published data that indicate extinction rates of
plant and animal species a thousand times the natural rate. However, extinction is the final
step in a long and complex process of ecosystem degradation, a process characterised by the
decline of abundance and distribution of many species and at the same time an increase in
abundance and distribution of a few others. A few common species are becoming more
common, many rare species more rare. This is what we call the uniformity process (Ten Brink
et al. 2000; Ten Brink 2003; RIVM 2002).
Biodiversity depletion has two main causes (UNEP/CBD 1997; OECD 2001b): a) loss of
habitats (size of ecosystem surface) and b) loss of ecosystem quality (decreasing abundance of
many characteristic species). The natural ecosystem area frequently changes because of land
(-use) conversion into agricultural land. Decreasing ecosystem quality is generally caused by
- climate change, pollution, habitat fragmentation, and over-exploitation in natural and
- intensification of the production system, the use of external synthetic inputs (pesticides
and fertilisers), commodity specialisation at farm and regional level and irrigation.
However, marginalisation of natural resources is also a cause, for example, the water-induced
soil erosion in historical landscapes of upland or mountain ecosystems. The European
Environment Agency (EEA) and UNEP warned recently that the degradation of Europe’s
vital soil resources and desertification would continue and even accelerate unless prompt
action is taken now. Quantity and quality have become two main pillars of the proposed
indicator framework linked to the Global Biodiversity Model.
3. Model development
The challenge is to create a model and indicators that are able to describe the above process of
biodiversity depletion for meeting policy requirements on different geographical scales
(national and global). We have followed the April 2003 recommendations of the CBD expert
group on biodiversity indicators: “
to pay attention to species distribution and abundance data
as optimal building blocks for the model, to classify information into quantity and quality
data, and to aggregate species information into species-assemblage trend indices for specific
species groups and into a sort of Natural Capital Index for the condition and trends of
(personal communication of Ben ten Brink, expert group member for the
Netherlands). These recommendations have become the logical bridge between indicator
The Global Biodiversity Model makes use of indirect−direct pressures, and the state and
response (PSR) indicator framework (OECD 2001b). “State” is then further defined as the
“abiotic conditions on which species depend, plant and animal species that live and reproduce
(biodiversity) as well as the goods and services that are provided by biodiversity”. According
to the European Centre for Nature Conservation (Wascher 2000), agricultural practices
(technological applications) are considered as direct pressures changing the (abiotic)
environmental state and thus biodiversity. Indirect pressures are agricultural processes such as
abandonment, marginalisation, intensification, urbanisation, and socio-economic and political
The model represents, in fact, a framework of many existing models (e.g. IMAGE 2.2, see
Alcamo et al.1998) and several new ones. The core business of the Global Biodiversity Model
will be to assess biodiversity from effects of environmental and habitat changes. The model
will be linked to pollution,
climate change models, demographic models, land-cover and land-
use models and other factors. The objective of the model is to assess the impacts of
environmental change and other human pressures on species, ecosystems, biodiversity and
ecosystem services. The framework can also be used for evaluating possible policy strategies.
The design of the model is based on a process approach. It is a generic model, applicable to
species, species groups, ecosystems and pressures on biodiversity. Here, the process does not
indicate an experimentalist approach but, rather, a dynamic understanding of interactions and
ecological processes. The model also links impact on species with impact on biodiversity at
ecosystem level on the basis of rule sets of different pressure – impact relationships. Socio-
economic modelling is outside the scope of the model.
The focus in this paper is on the rule-based short-cut for extensively or intensively managed
agricultural livestock landscapes. The rule-based approach is chosen because we expect a
lack of data on a global scale for most species data. General dose−effect relationships, derived
from the literature, can fill the gap through use in regional assessments and “what-if”
evaluations. This short-cut can be applied in quick assessments and for exchanging
information and results between national and international levels. Data flow in the pressure-
driven Global Biodiversity Model is shown in Figure 1.
Figure 1: Visualisation of data flow in the pressure-driven Global Biodiversity Model.
4. Application to agricultural-livestock landscapes
Several types of pressure and nature management schemes in combination with production or
exploitation, as visualised in Figure 1, will be reviewed here for their relationship to
biodiversity. We should mention at the outset that the dose−effect relationships are not yet
available. Rather than a quantification of possible effects the relevant factors have on
biodiversity, one can expect to find here the scope of factors overviewed, the position these
effects hold among the factors and the availability of data. Other (additional) factors may play
a role on a local scale. Here, only some of the relevant factors on the global scale are
All information relevant to the “pressure-based” biodiversity assessment in cultural
landscapes can be derived from the following research questions:
1. Which relevant land uses (global scale), landscapes (regional to national scale) and
production systems (local to national scale) can be distinguished?
2. What are the actual abiotic production conditions? To what extent are environmental
conditions unsuitable for production (soil and climate conditions)?
3. What kind of natural remnants (tree compositions and water bodies) can be found in
cultural landscapes? To what extent is the landscape fragmented by road
4. Which external factors influence production and biodiversity?
5. What are the relevant management techniques in production systems affecting
biodiversity locally and regionally, and what are the dose−effect relationships of
agricultural management on biodiversity?
6. What are the effects on biodiversity when different levels of limitation to the
application of technology are compared (conventional, integrated management,
7. What are disturbances to production systems and to related biodiversity in cultural
8. What are the trade-offs between agriculture and protected areas?
We extracted important information from the Food and Agriculture Organisation (FAO), the
OECD (2001b) and the EC (Hoffmann 2000) on factors to help us understand the relationship
between agricultural-livestock production and wild-species biodiversity. We have grouped the
factors according to their relationship to biodiversity, and added some sources for the
No (global) assessment is possible without geographical classification according to general
features of the natural resource base. Abiotic characteristics of the land may be soil type,
altitude and slope. These indicate the quality of the land, which will allow land degradation to
be foreseen and suitability of the land for agricultural-livestock production to be ascertained
(selected maps and models, e.g. FAO soil map of the world 1995; IMAGE 2.2 land use and
climate change model; GLOBE DEM 1 km elevation).
Many efforts have been taken to classify the world into land uses or land-cover types. Several
disciplines worked together in order to define where forest, agriculture, extensive grassland
and other natural ecosystems are located (GLC 2000 dataset; Ecological zones in IMAGE
2.2). We need to know the size of land use, landscapes and production systems today and to
what extent each affects wild biodiversity. In the same way as biodiversity is assessed in
natural ecosystems, the change in both area size and system quality will be assessed for
agricultural uses or landscapes (Ten Brink 2002).
Landscape quality cannot be determined in a straightforward manner from effects of a
production system alone. Landscapes consist of a mosaic of production fields, grassland and
forest patches (“green” terrestrial natural remnants), natural water streams and locations with
unsuitable production conditions. Natural remnants provide ecological structures for food,
nesting and shelter for plant and animal species.
Major land-cover types have, therefore, been analysed for composition of different land uses
(e.g. farming systems, FAO data), natural elements (e.g. trees, cultivated fields, freshwater
systems) and fragmentation by road infrastructure. ULRMC recently showed that Remote
Sensing data could be useful in determining landscape structures and or natural remnants in
agricultural land-use areas. ULRMC observed lower surface temperatures at night in
protected areas than in agricultural areas. This unexplained observation still indicates,
however, important future opportunities for inexpensive methods in the analysis of land-cover
mosaic patterns with frequent observations (time series).
External pressures on agroecosystems
Several external pressures from outside agricultural production systems such as climate
change and pollution from urban areas and industry affect biodiversity. Information on
underlying (general) drivers of biodiversity depletion like GNP, technology, poverty and/or
human population density may also be used to show that indirect pressures exert a negative
impact (Some pressures can be calculated with IMAGE 2.2).
Land use and production management
It is possible to obtain further insight into direct production-related pressures from an
overview of the (crop and animal) production technology at farm level, as well as exploitation
systems in (semi-)natural ecosystems in general (hunting, fishery, grazing) (IMAGE 2.2).
Production systems have different impacts on biodiversity because they are constructed from
specific packages for management practice, e.g. pesticides, fertilisers, drainage, irrigation and
levelling production sites affecting biodiversity (FAOSTAT country database, irrigation map
of the world, WATERGAP). The impact of production management on biodiversity is formed
by the sum of pressures based on technological choices or applications.
A consistent strategy for nature conservation can be found in governmental regulations (at
regional, national or international level) to control the exploitation of natural or cultural
ecosystems. Examples of such regulations are the closed season or limitations on the total
yearly extraction (in natural ecosystems) for fisherman and hunters. An example pertaining to
agro-ecosystems in the Netherlands is the regulation of the period of application and the total
amount of organic manure applied per hectare.
Civil society, especially production associations, has also defined regulations for nature
management in production systems and have put limits on the application of technology (for
both agro-ecosystems and natural ecosystems). Examples of production strategies are
conventional, integrated management or organic farming (Stolton 2002). For example, in the
fishing industry, a distinction should be made between technology (and the impact) of high-
tech fishing on board and local fisherman with traditional technology. In general, production
strategies differ in their impact on biodiversity. Such differences offer the opportunity of a
positive impact on biodiversity when transition policies to more sustainable production
systems are implemented. Impact on biodiversity can be assessed with the help of scenario
Agricultural production and exploitation of natural ecosystems are subject to unpredictable
incidents or disturbances that are not related to management practices. These are external
influences that may impact cultural landscapes, for example fire (MODIS, NOAA), diseases,
pests, invasive species, natural hazards (earthobservatory.nasa.gov or WCMC) and human
conflicts (UNEP-WCMC 2002). These factors alter socio-economic production conditions as
well as the quantity and quality of the natural resources in and outside the production zone.
The probability of the disturbance and the level of effects of such events are considered as a
measure of the risk of ecosystem use destabilising with possible decreased production,
accompanied by increased need for land and further land conversion or increased production.
Both may result in biodiversity depletion.
Protection of natural ecosystems
Agroecosystems border on natural ecosystems. Protected areas may be situated in cultural
landscapes or the landscape itself may be under protection. It is necessary to assess to what
extent agricultural land may affect ecological protection goals in the cultural landscape itself
(UNESCO, cultural heritage sites) or in nearby natural ecosystems (UNEP-WCMC or the
IMAGE protected area map). A trade-off between production and protection is also possible.
The protection measures may put limitations on agricultural production through territorial
planning, e.g. the determination of buffer zones.
5. Expectations of the model
The framework described above shows how different factors could be included in the
analysis. Starting point is an analysis of the extent, distribution and composition of cultural
and natural elements in landscapes or land-use systems. The first
hypothesis is that the more
natural elements occur in cultural landscapes, the higher the chance of wild biodiversity and
good connections between natural remnants sustaining even more biodiversity (including top
predators and large herbivores or carnivores). Applying technology to production systems
results in lower biodiversity. It is well known that the application of pesticides and fertilisers
in the system or external pressures outside the system result in decreased abundance and
distribution of plants, insects and, indirectly, animals in the trophic chain. The second
hypothesis is that increased external capital investment would lower biodiversity.
Additionally, nature management is likely to increase biodiversity if it improves
environmental care or specific nature conservation. The same cause−effect relationships on
production and biodiversity in the system, as well as pressures from agriculture on nearby
natural ecosystems, will be calculated for factors from outside the system. In summary, all
factors previously described relate to biodiversity based on dose−response relationships
obtained from a literature review using ecotoxicological risk assessment (Posthuma et al.
2002). The factors are grouped according to their place in the model and the effects of these
groups of factors are calculated by indices. The expectation is that wild plant and animal
species biodiversity in agricultural landscapes will be generally low, depending on the
intensity of the production system. However, important improvements may be obtained if
production systems are moving in a transition phase to ecological sustainability, and if natural
remnants in those areas are carefully managed or protected; they may even be enlarged.
The rule-based pressure approach of the Global Biodiversity Model for agricultural
landscapes is a short-cut method in the species-based model. This model also includes natural
terrestrial, aquatic and marine ecosystems and, more important, makes use of an additional
species-based modelling procedure (RIVM 2002; Ten Brink et al. 2002). The expectation is
that the pressure −impact relationships of the rule-based approach at system level may provide
the required input for working at species level. A set of characteristic wild plant and animal
species must be selected for all relevant agricultural livestock landscapes. Environmental
factors determining species occurrence (abundance or distribution) are combined for each
species. If environmental conditions change due to human action, the changed occurrence
(distribution or abundance) of a species represents a measure of decreasing ecosystem quality,
and thus a measure of decreasing biodiversity.
6. Communication and software requirements
The Global Biodiversity Model will be constructed by an international team. First, team
members will have to communicate frequently on the concepts, data delivery, calculation
procedures and presentation of outcome, and will therefore need Internet support (e.g. a
protected web site for members only). In a second stage, data as well as published model
results, can be distributed on the Internet for the public in general. A clear requirement of the
software is communication enhancement and joint learning.
Past experiences and current IT developments at RIVM have led to the decision to use the
ArcIMS web-mapping technology from ESRI to make the input data and projected results
available on the Internet. Visitors (team members only) are offered simple online GIS
functionality (like zoom, pan, select, buffer, add local data) to use on the global data and
results, and will be able to download the data/results for further modelling. This technology is
also used, for example, at WCMC for publishing I-maps like the World Atlas of Biodiversity.
The IT infrastructure will consist of an ArcIMS 4.01 Internet Map Server (on a Windows
2000 Advanced Server system) in combination with ArcSDE 8.3 (spatial data engine) and the
Oracle 9.i database (both on UNIX). Local analyses, simple grid manipulations and overlays
are carried out at RIVM with ArcINFO / ArcGIS 8.3.
What is currently missing in this framework of GIS software is a model builder with which
users may combine a personal (local) set of relevant pressures or state variables and calculate
their own pressure indices or biodiversity impact. This is especially relevant for future project
members at national level, such as the current pilot counterpart ULRMC for Ukraine. They
will need to combine assessment of global databases with assessment based on country data.
It will be unlikely that the complete model framework software will be offered on Internet,
because of copyright on each model and the complexity of working with the models. But
Internet and ArcIMS software must be the right tools to communicate efficiently and
effectively using quick scans carried out in the pressure approach as proposed in this paper.
7. Call for exchange of databases and joint analysis
The members of the Global Biodiversity Model are now faced with an intellectual and
communicative challenge in building the model and producing biodiversity assessments for
natural and agro-ecosystems with both rule-(quick scan) and species-based approaches.
The most powerful model will result by linking the information at national level with global-
scale analysis and vice versa. Biodiversity assessments are generally carried out on specific
spatial, temporal and organisational scales according to their appropriateness for the process
or phenomenon being examined. However, focusing on one level will probably result in our
missing one or more types of causes or ignoring interactions between scales that are
“critically important in understanding ecosystem determinants and their implications for
human well-being” (MA 2003; see p. 14). We therefore invite the scientific community to
support this effort, to communicate improvements and to link relevant databases at global,
Alcamo, J., E. Kreileman, M. Krol, R. Leemans, J. Bollen, J. van Minnen, M. Schaeffer, S. Toet and B. de Vries (1998).
Global modelling of environmental change. An overview of IMAGE 2.1. In: Alcamo, J., R. Leemans and E. Kreileman.
Global change scenarios of the 21st century. Results from the IMAGE 2.1 model
. Oxford (UK); Elsevier Science (The
Brink B.J.E. ten (2000). Biodiversity indicators for the OECD Environmental Outlook and Strategy: a feasibility study.
RIVM (Bilthoven, The Netherlands). RIVM report 402001014.
Brink B.J.E. ten et al. (2002). Technical design natural Capital Index (NIC) 1.0 and implementation in Nature Outlook 2.
(RIVM Bilthoven, The Netherlands.) Technical report RIVM 40857007/2002.
Hoffmann L.B. (ed.) (2000). Stimulating positive linkages between agriculture and biodiversity. Recommendations for
building blocks for the EC-Agricultural Action Plan on Biodiversity. (European Centre for Nature Conservation, Tilburg, The
Netherlands). ECNC Technical report series).
MA (in press). Ecosystems and People: a Framework for Assessment. Millennium Ecosystem Assessment.
OECD (1999). Environmental Indicators for Agriculture, Volume 2- Issues and Design, The York Workshop. (Organisation
for Economic Co-operation and Development, Paris).
OECD (2001a). Environmental Indicators for Agriculture. Volume 3 - Methods and Results. (Agriculture and Food.
Organisation for Economic Co-operation and development, Paris).
OECD (2001b). OECD Expert meeting on Agri-Biodiversity Indicators: Summary and recommendations. Zurich, 5-8
Posthuma et al. (eds.) (2002). Species sensitivity distributions in ecotoxicology.
Lewis Publishers, Boca Raton, FL.
RIVM (2002). Biodiversity: how much is left? The natural Capital Index framework (NCI). (The National Institute for Public Health and the Environment - RIVM, Bilthoven, The Netherlands). Stolton S. (2002). Organic Agriculture and Biodiversity Dossier 2. (International Federation of Organic Agriculture Movements (IFOAM), Tholey, Germany). UNEP/CBD (1997). Recommendation for a core set of indicators of biological diversity. (Convention of Biological Diversity, Montreal). UNEP/CBD/SBSTTA/3/9 and inf. 13, inf. 14. UNEP (2002). Global Environmental Outlook 3, United Nations Environmental Program, (Earthscan, London). UNEP-WCMC (2002). Mountain Watch, Environmental Change and Sustainable development in Mountains. (UNEP-WCMC, Cambridge, UK). UNEP (in press). Technical Background paper of the Global Environmental Outlook 3. Wascher, D.W. (ed.) (2000). Agri-environmental indicators for sustainable agriculture in Europe. (European Centre for Nature Conservation, Tilburg, The Netherlands).
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