Keywords
spatially explicit agent based model, population dynamic modeling, shocks
Start Date
1-7-2012 12:00 AM
Abstract
Floods and droughts are expected to occur more frequently due to climate change. Regional water boards in the Netherlands are anticipating water level variations in streams in rural areas. To moderate adverse effects of those variations, they seek for opportunities to enhance retention of rainfall runoff on agricultural land in the stream valleys. This can be done by contracting farmers to apply agri-environmental measures. We focus on this small-scale and flexible (in space and time) rainfall runoff retention by farmers. Farmers can decide to (temporarily) allocate parts of their land to apply agri-environmental measures, depending on shocks of various nature, e.g. shocks due to increased price fluctuation for agricultural products. These patches of land may then serve as water retention areas and can be temporarily habitat to certain species, and the configuration of the habitat patches is highly dynamic. Spatiotemporal habitat dynamics can have strong effects on species’ viability. This paper develops an index as a proxy to express the persistence of species in the complex socio-ecological system, depending on crucial – but dynamic – factors landscape history and proximity of habitat. The development of such a “dynamic landscape”-index is scientifically innovative. We aim to support water boards by offering a simulation model to evaluate potential effects of alternative agri-environmental policies and to test the robustness of policies to shocks in the socioeconomic environment. This model contains a spatially explicit agent-based model and a population dynamics model. The agent-based model simulates the allocation of agri-environmental measures by the water board and farmers’ land use decisions. To check whether the landscape index indeed promotes species’ persistence, the population dynamics of indicator species are simulated in the dynamic landscapes generated by the agent-based model, using the population-dynamic model METAPOP.
Dairy farming and Newt habitat: How shocks in milk prices influence the optimal design of water retention policies
Floods and droughts are expected to occur more frequently due to climate change. Regional water boards in the Netherlands are anticipating water level variations in streams in rural areas. To moderate adverse effects of those variations, they seek for opportunities to enhance retention of rainfall runoff on agricultural land in the stream valleys. This can be done by contracting farmers to apply agri-environmental measures. We focus on this small-scale and flexible (in space and time) rainfall runoff retention by farmers. Farmers can decide to (temporarily) allocate parts of their land to apply agri-environmental measures, depending on shocks of various nature, e.g. shocks due to increased price fluctuation for agricultural products. These patches of land may then serve as water retention areas and can be temporarily habitat to certain species, and the configuration of the habitat patches is highly dynamic. Spatiotemporal habitat dynamics can have strong effects on species’ viability. This paper develops an index as a proxy to express the persistence of species in the complex socio-ecological system, depending on crucial – but dynamic – factors landscape history and proximity of habitat. The development of such a “dynamic landscape”-index is scientifically innovative. We aim to support water boards by offering a simulation model to evaluate potential effects of alternative agri-environmental policies and to test the robustness of policies to shocks in the socioeconomic environment. This model contains a spatially explicit agent-based model and a population dynamics model. The agent-based model simulates the allocation of agri-environmental measures by the water board and farmers’ land use decisions. To check whether the landscape index indeed promotes species’ persistence, the population dynamics of indicator species are simulated in the dynamic landscapes generated by the agent-based model, using the population-dynamic model METAPOP.
