title: Forecasting the effects of land use scenarios on farmland birds reveal a potential mitigation of climate change impacts.
abstract: Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.
authors.affiliation: Muséum National d'Histoire Naturelle, UMR 7204 MNHN-CNRS-UPMC, Centre de Recherches sur la Biologie des Populations d'Oiseaux, CP 51, Paris, France; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
authors.forename: Karine
authors.initials: K
authors.lastname: Princé
authors.affiliation: Muséum National d'Histoire Naturelle, UMR 7204 MNHN-CNRS-UPMC, Centre de Recherches sur la Biologie des Populations d'Oiseaux, CP 51, Paris, France.
authors.forename: Romain
authors.initials: R
authors.lastname: Lorrillière
authors.affiliation: Muséum National d'Histoire Naturelle, UMR 7204 MNHN-CNRS-UPMC, Centre de Recherches sur la Biologie des Populations d'Oiseaux, CP 51, Paris, France; Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America.
authors.forename: Morgane
authors.initials: M
authors.lastname: Barbet-Massin
authors.affiliation: AgroParisTech, UMR SAD-APT INRA/AgroParisTech, Paris, France.
authors.forename: François
authors.initials: F
authors.lastname: Léger
authors.affiliation: Muséum National d'Histoire Naturelle, UMR 7204 MNHN-CNRS-UPMC, Centre de Recherches sur la Biologie des Populations d'Oiseaux, CP 51, Paris, France.
authors.forename: Frédéric
authors.initials: F
authors.lastname: Jiguet
mesh_terms: D000383:Agriculture; D025041:Animal Migration / Q000502:physiology*; D000818:Animals; D044822:Biodiversity; D001717:Birds / Q000502:physiology*; D057231:Climate Change; D017753:Ecosystem; D005544:Forecasting