摘要
Reconstructing long-term vegetation buffers along streams in agricultural landscapes has become a common environmental restoration strategy for improving water quality and wildlife habitat connectivity.This article developed a linear weighted model to rank the priority of agricultural sub-basins for the establishment of vegetative buffers.The method was applied to an agricultural watershed of 146 km2 in Ontario,Canada.The watershed was divided into 11 sub-basins as basic decision units.In each subbasin,four stream buffer schemes with widths of 5,10,15 and 20m were generated.For each buffer,three benefit-cost attributes of reconstructing vegetation cover were estimated,which include acreage per dollar,sediment abatement per dollar and habitat benefit per dollar.These attributes were first normalized using a linear normalization approach to eliminate the effects across different units.The normalized attributes were then integrated using a simple additive weighting method to rank the 11 sub-basins for prioritizing spatial restoration action.A sensitivity analysis was also conducted to observe the impact of a change in attribute weights on the management decisions.The results suggest that vegetation buffers reconstructed for achieving the water quality goal are not effective in improving habitat connectivity and vice versa.
Reconstructing long-term vegetation buffers along streams in agricultural landscapes has become a common environmental restoration strategy for improving water quality and wildlife habitat connectivity.This article developed a linear weighted model to rank the priority of agricultural sub-basins for the establishment of vegetative buffers.The method was applied to an agricultural watershed of 146 km2 in Ontario,Canada.The watershed was divided into 11 sub-basins as basic decision units.In each subbasin,four stream buffer schemes with widths of 5,10,15 and 20m were generated.For each buffer,three benefit-cost attributes of reconstructing vegetation cover were estimated,which include acreage per dollar,sediment abatement per dollar and habitat benefit per dollar.These attributes were first normalized using a linear normalization approach to eliminate the effects across different units.The normalized attributes were then integrated using a simple additive weighting method to rank the 11 sub-basins for prioritizing spatial restoration action.A sensitivity analysis was also conducted to observe the impact of a change in attribute weights on the management decisions.The results suggest that vegetation buffers reconstructed for achieving the water quality goal are not effective in improving habitat connectivity and vice versa.
基金
supported by "SUST Spring Bud" Project (Grant no.2008AZZ110)
National Key Technology R&D Program of China project (Grant no.2006BAJ15B02)
