INTEGRATING DISEASE MODELS WITH CROP AND ECOSYSTEM MODELS TO ASSESS THE EFFECTS OF CLIMATE AND LAND-USE CHANGES ON PLANT PATHOSYSTEMS
PS TENG1 and XB YANG2
1IRRI, PO Box 933, Manila 1099, The Philippines; 2Department of Plant Pathology, Iowa State
University, Ames, IA 50011-1020, USA
Conceptual and empirical basis for assessments
Pathosystems are a small, integral part of the earth's terrestrial ecosystems which range from undisturbed natural systems to intensively human-managed and highly modified agricultural systems. However, assessments of the effects of climate and land-use changes on terrestrial ecosystems, whether globally or regionally, would be incomplete without a plant disease component, as microbes are generally more sensitive in response to the ambient environment. Computer simulation modelling using a systems analytical approach provides the main means to capture the complex organizational and functional linkages between elements in biomes, and for assessment purposes, to combine terrestrial natural and man-managed ecosystems within ecoregions. Climate (e.g. temperature, rainfall) and land use (e.g. increase in N use per unit land surface) parameters, treated as driving variables, cause qualitative (e.g. change in plant or pathogen species) and quantitative (e.g. pathogen abundance, geographic range) effects on pathosystems, and on the relationships between pathosystems and other subsystems (e.g. bitrophic disease-crop relationship resulting in yield loss) which collectively constitute the total ecosytem. Interactions are also known between climate and land use. In many parts of the developing world, quantitative measurements are not available for key biophysical variables and surrogates have to be used. The accuracy of assessments to assist decision-making therefore requires much interpretation based on location-specific knowledge.
Disease models as components of ecosystem models
Systems and mathematical models are available to describe the relationships between short- and long-term effects of weather and land-use factors on the key diseases of the world's major crops (wheat, potato, rice, maize), and on the effects of these factors on the crops themselves. However, there have been relatively few attempts to integrate these into ecosystem models. One notable effort was the collaborative project between the International Rice Research Institute (IRRI) and the US Environmental Protection Agency (EPA) in the mid-1990s, from which the effects of changing UV-B and climate on arthropods, blast disease and rice were estimated for the Asian continent. The Global Change in Terrestrial Ecosystems (GCTE) project of the International Geosphere Biosphere Program (IGBP) is facilitating networks of crop and pest modellers, but as yet there is little integration of these to more complex multi-species activities. A significant development is the effort of the International Consortium for Agricultural Systems Applications (ICASA) to develop common platforms, standardized data formats, metadatasets and user-friendly shells to accommodate models of different sources.
Technical issues in model integration and application for assessment
Many issues remain in the methodology that would allow models to be used for determining meaningful assessments that can assist decision-makers. Scaling techniques, to upscale from patch level to landscape levels, are only just receiving attention and are required to make regional-level outputs meaningful by ensuring that the underlying assumptions about processes in models remain valid. Historical time-series data to allow model validation under changed scenarios are difficult to derive, although statistical techniques to detect changes in limited ecological time series are available. Georeferenced datasets are also wanting in their representativeness, although major efforts, such as those of GCTE-LEMA (Long-Term Ecological Modelling Activity), may provide guidance in the mid-term. Lastly, model building is not an end point in research; rather, it is a beginning towards improved decision-making on global change effects, which in turn can only be done by active involvement of social scientists.