Keywords
coupled social-ecological model, spatial analysis, process-based modelling, agent-based modelling
Start Date
1-7-2012 12:00 AM
Abstract
Coupled specialised models have the advantage of high flexibility; processes represented, input requirements and precision levels can be tailored specifically to a given research question. However, as more parameters become endogenous to a coupled model system, tracing back causal relations of processes can become challenging, because conditions vary over time and between scenarios. Such complexity is still increased in spatially explicit representations of fluxes in landscapes, where pixels are not spatially independent. We present the case of a coupled system composed of a pixel-based biophysical and a farm-based socio-economic model. The coupled model system was employed to assess resource degradation, yields and land-use decisions in a mountainous catchment of 31 km2 and 490 households in Northwest Vietnam. Specifically, we looked into impacts of farmers' adoption of different soil conservation techniques on erosion, yields and incomes. From the perspective of the biophysical model, land use change and management were dynamically influenced by crop yields when adding the decision component. After a common starting point the scenarios developed into very different directions and only overall outcomes could be compared. In order to be able to draw conclusions on biophysical processes – as usual in pure biophysical models under stable or at least comparable treatments (here: land uses and management) – we employ tools used for spatial analysis and geostatistics. This paper presents first results of ongoing research.
Interpreting Outputs of a Landscape-Scale Coupled Social-Ecological System
Coupled specialised models have the advantage of high flexibility; processes represented, input requirements and precision levels can be tailored specifically to a given research question. However, as more parameters become endogenous to a coupled model system, tracing back causal relations of processes can become challenging, because conditions vary over time and between scenarios. Such complexity is still increased in spatially explicit representations of fluxes in landscapes, where pixels are not spatially independent. We present the case of a coupled system composed of a pixel-based biophysical and a farm-based socio-economic model. The coupled model system was employed to assess resource degradation, yields and land-use decisions in a mountainous catchment of 31 km2 and 490 households in Northwest Vietnam. Specifically, we looked into impacts of farmers' adoption of different soil conservation techniques on erosion, yields and incomes. From the perspective of the biophysical model, land use change and management were dynamically influenced by crop yields when adding the decision component. After a common starting point the scenarios developed into very different directions and only overall outcomes could be compared. In order to be able to draw conclusions on biophysical processes – as usual in pure biophysical models under stable or at least comparable treatments (here: land uses and management) – we employ tools used for spatial analysis and geostatistics. This paper presents first results of ongoing research.
