Delineating the spatial drivers of agri-environment scheme adoption at field and farm levels

Agri-environment schemes (AES), introduced by the EU Common Agricultural Policy (CAP), aim to compensate land owners for implementing environmentally-friendly practices. Whilst literature has examined their effectiveness and how farmer characteristics govern AES adoption, there is a lack of knowledge about the spatial drivers of AES, particularly structural, biophysical and landscape factors in the UK. Using the Humber region as a case study, this paper explores how the uptake of Countryside Stewardship options has varied from 2016 to 2021. It also examines 2500 farms from the field- and farm-level data of 2019 to better understand what type of land British farmers are adopting AES on. Logistic regression analysis is used to identify the factors (including farm and landscape characteristics, designated sites and land quality) that best explain overall AES adoption, as well as specific scheme adoption, at the field- and farm-level. Our analysis reveals that ‘buffer strips’, ‘hedgerow management’, ‘permanent grassland’, and ‘winter bird food’ are the most commonly adopted schemes of 2019. AES are generally adopted on larger fields and farms that feature marginalised, unproductive and vulnerable land, except for ‘buffer strips’ which showed a larger tendency to appear on fields with more profitable, higher quality land. This study, therefore, supports the notion that AES are generally placed on lower quality land and that large proportions of agricultural land owners are not effectively targeted. With the expected loss of direct payments to farmers in the UK as a result of the Department for Environment, Food & Rural Affairs (DEFRA) post-Brexit re-evaluation of rural policy, these results call for the Sustainable Farming Incentive (SFI) to be made more accessible and inclusive to a broader diversity of farmers

Ecological restoration of agricultural land can improve its contribution to economic development.

Given the negative environmental impacts of intensive agriculture, there is an urgent need to reduce the impact of food production on biodiversity. Ecological restoration of farmland could potentially contribute to this goal. While the positive impacts of ecological restoration on biodiversity are well established, less evidence is available regarding impacts on economic development and employment. Potentially, prospects for economic development could be enhanced by ecological restoration though increased provision of ecosystem services, on which some economic activity depends. Here we examined this issue through the development of contrasting land use scenarios for the county of Dorset, southern England. Two scenarios of future agricultural expansion were compared with two scenarios of landscape-scale ecological restoration and the current situation. Impacts on provision of multiple ecosystem services (ES) were explored using InVEST models and proxy values for different land cover types. Impacts on economic employment were examined using an economic input-output model, which was adjusted for variation in ES flows using empirically determined ES dependency values for different economic sectors. Using the unadjusted input-output model, the scenarios had only a slight economic impact (≤ 0.3% Gross Value Added, GVA). Conversely, when the input-output model was adjusted to take account of ES flows, GVA increased by up to 5.4% in the restoration scenarios, whereas under the scenario with greatest agricultural expansion, GVA was reduced by -4.5%. Similarly, employment increased by up to 6.7% following restoration, compared to declines of up to -5.6% following maximum agricultural expansion. These results show that the economic contribution of rural land is far greater than that attributable to agricultural production alone. Landscape-scale restoration of agricultural land can potentially increase the contribution of farmland to economic development and employment, by increasing flows of multiple ES to the many economic sectors that depend on them