Assessing the environmental impact of agri-environment schemes (AESs) is complicated by the lack of both specific measurable objectives and dedicated environmental monitoring of the impacts. A methodology to estimate the environmental performance of AESs was applied in nine EU case study areas, and reduced the complexity of scheme structure into elements that were assessed by experts. Multi-criteria analysis (MCA) techniques helped produce aggregated judgements about single objectives or measures. Expert panels assessed the link between environmental measures and objectives by scoring specific criteria that reflect important factors for delivering environmental effectiveness: valid research models for measures (cause-and-effect); quality of implementation by farmers and institutions; extent of participation and degree of spatial targeting. Multi-criteria analysis enabled comparison of the degree to which environmental effectiveness (estimated from the criteria scores) within a scheme was achieved across environmental objectives of different importance. There were considerable differences in overall environmental performance across different case study areas, and the experts' scores identified scope for improvement in one or more criteria in most measures. Higher priority environmental objectives (as assessed by stakeholders) did not necessarily demonstrate highest environmental performance. We discuss implications for learning how to improve the design and evaluation of AESs.
Ex post environmental evaluation of agri-environmental schemes using experts’ judgement and multicriteria analysis
BARTOLINI, FABIO;
2009
Abstract
Assessing the environmental impact of agri-environment schemes (AESs) is complicated by the lack of both specific measurable objectives and dedicated environmental monitoring of the impacts. A methodology to estimate the environmental performance of AESs was applied in nine EU case study areas, and reduced the complexity of scheme structure into elements that were assessed by experts. Multi-criteria analysis (MCA) techniques helped produce aggregated judgements about single objectives or measures. Expert panels assessed the link between environmental measures and objectives by scoring specific criteria that reflect important factors for delivering environmental effectiveness: valid research models for measures (cause-and-effect); quality of implementation by farmers and institutions; extent of participation and degree of spatial targeting. Multi-criteria analysis enabled comparison of the degree to which environmental effectiveness (estimated from the criteria scores) within a scheme was achieved across environmental objectives of different importance. There were considerable differences in overall environmental performance across different case study areas, and the experts' scores identified scope for improvement in one or more criteria in most measures. Higher priority environmental objectives (as assessed by stakeholders) did not necessarily demonstrate highest environmental performance. We discuss implications for learning how to improve the design and evaluation of AESs.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
