Keywords

Agent-based modelling; ecosystem services; landscape modelling; land use; biodiversity

Location

Session G1: Using Simulation Models to Improve Understanding of Environmental Systems

Start Date

16-6-2014 2:00 PM

End Date

16-6-2014 3:20 PM

Abstract

The collective impacts of farmers’ land management decisions on above ground ecosystem services (ES) and their implications for agriculture are poorly understood. Managing habitat to provide ES is costly but at the same time it can support higher yields through, e.g., pollination or natural pest control. Due to the mobility of ES-providers (bees, natural enemies) farmers providing habitat might also benefit their neighbours, creating interdependencies among their decisions. Interdependencies among farmers’ land-use decisions and the flow of ES in space can be considered by integrating agent-based modelling and evidence-based ES models. Such integration requires a trade-off between the land-use details required to capture relevant ecological dynamics of ES in a landscape and the simplified landscape modelling in agent-based models. This paper shows how details of land use can be increased in the agent-based model AgriPoliS that simulates agricultural structural change. Non- agricultural land in AgriPoliS is differentiated into different land uses, i.e. settlements and natural habitats. Furthermore, the size distribution of these landscape elements and their distribution in space are considered. The improvement of the landscape modelling is a prerequisite for detailed analysis of policies supporting biodiversity and their impact on agricultural production and farm income.

 
Jun 16th, 2:00 PM Jun 16th, 3:20 PM

Modelling spatial relationships between ecosystem services and agricultural production in an agent- based model

Session G1: Using Simulation Models to Improve Understanding of Environmental Systems

The collective impacts of farmers’ land management decisions on above ground ecosystem services (ES) and their implications for agriculture are poorly understood. Managing habitat to provide ES is costly but at the same time it can support higher yields through, e.g., pollination or natural pest control. Due to the mobility of ES-providers (bees, natural enemies) farmers providing habitat might also benefit their neighbours, creating interdependencies among their decisions. Interdependencies among farmers’ land-use decisions and the flow of ES in space can be considered by integrating agent-based modelling and evidence-based ES models. Such integration requires a trade-off between the land-use details required to capture relevant ecological dynamics of ES in a landscape and the simplified landscape modelling in agent-based models. This paper shows how details of land use can be increased in the agent-based model AgriPoliS that simulates agricultural structural change. Non- agricultural land in AgriPoliS is differentiated into different land uses, i.e. settlements and natural habitats. Furthermore, the size distribution of these landscape elements and their distribution in space are considered. The improvement of the landscape modelling is a prerequisite for detailed analysis of policies supporting biodiversity and their impact on agricultural production and farm income.