Context Ecological Focus Areas (EFAs) were designed as part of the greening strategy of the common agricultural policy to conserve biodiversity in European farmland, prevent soil erosion and improve soil quality. Farmers receive economic support if they dedicate at least 5% of their arable farmland to any type of EFA, which can be selected from a list of options drawn up at the European Union level. However, EFAs have been criticized for failing to achieve their environmental goals and being ineffective in conserving farmland biodiversity, mainly because they are not spatially targeted and because they promote economic rather than ecological considerations in farm management decisions. Objectives We used a spatially explicit approach to assess the influence of farm and field context as well as field terrain and soil conditions on the likelihood of whether or not a particular EFA type was implemented in a field. Methods We used a multinomial model approach using field-level land use and management data from 879 farms that complied with the EFA policy in 2019 in the Mulde River Basin in Saxony, Germany. Geospatial environmental information was used to assess which predictor variables (related to farm context, field context or field terrain and soil conditions) increased the probability of a field being assigned to a particular EFA. We tested the hypothesis that productive EFAs are more often implemented on fields that are more suitable for agricultural production and that EFA options that are considered more valuable for biodiversity (e.g. non-productive EFAs) are allocated on fields that are less suitable for agricultural production. Results We found that farms embedded in landscapes with a low proportion of small woody features or nature conservation areas mainly fulfilled the EFA policy with productive EFAs (e.g. nitrogen fixing crops). Conversely, farms with a higher proportion of small woody features or nature conservation areas were more likely to adopt non-productive EFAs. As predicted, large and compact fields with higher soil fertility and lower erosion risk were assigned to productive EFAs. Non-productive EFAs were placed on small fields in naturally disadvantaged areas. EFA options considered particularly beneficial for biodiversity, such as fallow land, were allocated far away from other semi-natural or nature protection areas. Conclusions Our results highlight that the lack of spatial targeting of EFAs may result in EFA options being assigned to areas where their relative contribution to conservation goals is lower (e.g. farms with higher shares of protected areas) and absent in areas where they are most needed (e.g. high intensity farms). To ensure that greening policies actually promote biodiversity in European agriculture, incentives are needed to encourage greater uptake of ecologically effective measures on intensively used farms. These should be coupled with additional measures to conserve threatened species with specific habitat requirements.

This deliverable provides a General Framework for the BESTMAP Policy Impact Assessment Modelling (BESTMAP-PIAM) toolset. The BESTMAP-PIAM is based on the notion of defining (a) a typology of agricultural systems, with one (or more) representative case study (CS) in each major system; (b) mapping all individual farms within the case study to a Farm System Archetype (FSA) typology; (c) model the adoption of agri-environmental schemes (AES) within the spatially-mapped FSA population using Agent Based Models (ABM), based on literature and a survey with sufficient representative sample in each FSA of each CS, to elucidate the non-monetary drivers underpinning AES adoption and the relative importance of financial and non-financial/social/identity drivers; (d) linking AES adoption to a set of biophysical, ecological and socio-economic impact models; (e) upscaling the CS level results to EU scale; (f) linking the outputs of these models to indicators developed for the post-2020 CAP output, result and impact reports; (g) visualizing outputs and providing a dashboard for policy makers to explore a range of policy scenarios, focusing on cost-effectiveness of different AES.