Keywords
inverse modeling, ecosystem services, trade-off
Start Date
1-7-2012 12:00 AM
Abstract
In this study we propose an inverse modeling approach to quantify required ecosystem services provision for reaching future planning goals. As a case study we investigate urbanization processes in two regions in Switzerland. We use a binary logistic econometric model to relate probabilities of urbanization to a set of land use determinants such as geographical factors, climate, agricultural subsidies, and ecosystem services. By the use of the inverse modeling we find the necessary trade-offs between ecosystem services in order to achieve a given probability of land use change from agricultural to settlement. From an urban planning perspective such given probability corresponds to a given or desired future urbanization level, which, in turn, is defined by stakeholders. Of particular interest for planners is the trade-off analysis between ecosystem services because it provides a first step in defining a number of transition pathways to achieve future planning decisions. In this way, once a future planning scenario is defined, future demands for ecosystem services under such scenario can be derived from the inverse modeling. Additionally, results of this contribution reveal for the study area that ecosystem services seem not have been included in spatial planning decisions. For this reason, in the conclusion section we encourage and recommend planners and stakeholders in general to not only focus further research on understanding the importance of ecosystem services in urban and landscape systems, but also to incorporate that knowledge in the planning decisions.
Realizing Transition Pathways to Provide Required Ecosystem Services – an Inverse Approach
In this study we propose an inverse modeling approach to quantify required ecosystem services provision for reaching future planning goals. As a case study we investigate urbanization processes in two regions in Switzerland. We use a binary logistic econometric model to relate probabilities of urbanization to a set of land use determinants such as geographical factors, climate, agricultural subsidies, and ecosystem services. By the use of the inverse modeling we find the necessary trade-offs between ecosystem services in order to achieve a given probability of land use change from agricultural to settlement. From an urban planning perspective such given probability corresponds to a given or desired future urbanization level, which, in turn, is defined by stakeholders. Of particular interest for planners is the trade-off analysis between ecosystem services because it provides a first step in defining a number of transition pathways to achieve future planning decisions. In this way, once a future planning scenario is defined, future demands for ecosystem services under such scenario can be derived from the inverse modeling. Additionally, results of this contribution reveal for the study area that ecosystem services seem not have been included in spatial planning decisions. For this reason, in the conclusion section we encourage and recommend planners and stakeholders in general to not only focus further research on understanding the importance of ecosystem services in urban and landscape systems, but also to incorporate that knowledge in the planning decisions.
