Maximising the natural capital benefits of habitat creation: Spatially targeting native woodland using GIS

The establishment of the Common Agricultural Policy has dramatically transformed the relationship between the natural environment and agriculture in the UK. Accordingly, the Government now acknowledges that our stock of ‘natural capital’ is being managed unsustainably and is undertaking Common Agricultural Policy reforms to provide a more sustainable form of agriculture. Such reforms will be based on the economic rationale of payment in return for the provision of natural capital benefits such as biodiversity, carbon sequestration, landscape and recreation. A basic lower tier payment is proposed for general environmental practices, with higher tiers of payments being available for ‘benefit generating’ habitat maintenance and creation. In order to maximise the benefits of such habitat creation, some form of spatial targeting is required. Using geographical information systems (GIS), a suite of spatially explicit criteria are adopted to measure how the potential benefits of native woodland creation vary across the agricultural landscape of the Chilterns natural area. Rather than regarding habitat conservation solely in terms of biodiversity benefits, a more holistic natural capital benefit approach is thus adopted. Public preference on the provision of each benefit is integrated into the GIS-based suitability analysis through multicriteria evaluation. We demonstrate how such a targeted approach leads to large improvements in the delivery of natural capital benefits, with the attainment of biodiversity, landscape and recreation benefits being particularly complementary. As such, the targeted pursuit of natural capital benefits does not compromise the attainment of biodiversity goals, but actually aids in their achievement. However, due to limitations in data availability and accuracy, GIS should be regarded as a decision support tool, with validation of targeted sites being undertaken through a farm audit system.