Effects of agri-environmental schemes on farmland birds: do food availability measurements improve patterns obtained from simple habitat models?
Article first published online: 11 JUN 2014
© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Ecology and Evolution
Volume 4, Issue 14, pages 2834–2847, July 2014
How to Cite
Ecology and Evolution 2014; 4(14):2834–2847
- Issue published online: 21 JUL 2014
- Article first published online: 11 JUN 2014
- Manuscript Accepted: 30 APR 2014
- Manuscript Revised: 28 APR 2014
- Manuscript Received: 15 APR 2014
- Dirección General de Investigación of the Spanish Ministry for Science and Innovation. Grant Numbers: CGL2008-02567, CGL2005-04893
- Agri-environmental scheme;
- agricultural intensification;
- habitat management;
- steppe birds;
- wildlife conservation
Studies evaluating agri-environmental schemes (AES) usually focus on responses of single species or functional groups. Analyses are generally based on simple habitat measurements but ignore food availability and other important factors. This can limit our understanding of the ultimate causes determining the reactions of birds to AES. We investigated these issues in detail and throughout the main seasons of a bird's annual cycle (mating, postfledging and wintering) in a dry cereal farmland in a Special Protection Area for farmland birds in central Spain. First, we modeled four bird response parameters (abundance, species richness, diversity and “Species of European Conservation Concern” [SPEC]-score), using detailed food availability and vegetation structure measurements (food models). Second, we fitted new models, built using only substrate composition variables (habitat models). Whereas habitat models revealed that both, fields included and not included in the AES benefited birds, food models went a step further and included seed and arthropod biomass as important predictors, respectively, in winter and during the postfledging season. The validation process showed that food models were on average 13% better (up to 20% in some variables) in predicting bird responses. However, the cost of obtaining data for food models was five times higher than for habitat models. This novel approach highlighted the importance of food availability-related causal processes involved in bird responses to AES, which remained undetected when using conventional substrate composition assessment models. Despite their higher costs, measurements of food availability add important details to interpret the reactions of the bird community to AES interventions and thus facilitate evaluating the real efficiency of AES programs.