A Resource-Based Modelling Framework to Assess Habitat Suitability for Steppe Birds in Semiarid Mediterranean Agricultural Systems

et al. (2014) A Resource-Based Modelling Framework to Assess Habitat Suitability for Steppe Birds in Semiarid Mediterranean Agricultural Systems. PLoS ONE 9(3): e92790. doi:10.1371/journal.pone.0092790 A Resource-Based Modelling Framework to Assess Habitat Suitability for Steppe Birds in Semiarid Mediterranean Agricultural Systems Laura Cardador 0 Miquel De Ca ceres 0 Gerard Bota 0 David Giralt 0 Fabia n Casas 0 Beatriz Arroyo 0 Fran cois Mougeot 0 Carlos Cantero-Martnez 0 Judit Moncunill 0 Simon J. Butler 0 Llus Brotons 0 Francisco Moreira, Institute of Agronomy, University of Lisbon, Portugal 0 1 Forest Sciences Center of Catalonia (CTFC) , Solsona, Catalonia, Spain, 2 Estacio n Experimental de Zonas A ridas (EEZA-CSIC) , La Can ada de San Urbano , Almer a, Spain, 3 Instituto de Investigacio n en Recursos Cinege ticos (IREC)-(CSIC-UCLM-JCCM), Ciudad Real , Spain , 4 Departament de Produccio Vegetal i Cie`ncia Forestal, Universidad de Lleida (UDL) , Lleida , Spain , 5 School of Biological Sciences, University of East Anglia , Norwich , United Kingdom , 6 CREAF, Bellaterra, Catalonia , Spain European agriculture is undergoing widespread changes that are likely to have profound impacts on farmland biodiversity. The development of tools that allow an assessment of the potential biodiversity effects of different land-use alternatives before changes occur is fundamental to guiding management decisions. In this study, we develop a resource-based model framework to estimate habitat suitability for target species, according to simple information on species' key resource requirements (diet, foraging habitat and nesting site), and examine whether it can be used to link land-use and local species' distribution. We take as a study case four steppe bird species in a lowland area of the north-eastern Iberian Peninsula. We also compare the performance of our resource-based approach to that obtained through habitat-based models relating species' occurrence and land-cover variables. Further, we use our resource-based approach to predict the effects that change in farming systems can have on farmland bird habitat suitability and compare these predictions with those obtained using the habitat-based models. Habitat suitability estimates generated by our resource-based models performed similarly (and better for one study species) than habitat based-models when predicting current species distribution. Moderate prediction success was achieved for three out of four species considered by resource-based models and for two of four by habitat-based models. Although, there is potential for improving the performance of resource-based models, they provide a structure for using available knowledge of the functional links between agricultural practices, provision of key resources and the response of organisms to predict potential effects of changing land-uses in a variety of context or the impacts of changes such as altered management practices that are not easily incorporated into habitat-based models. - Funding: This study was supported by the Project Steppeahead funded by Fundacio n General del Consejo Superior de Investigaciones Cientficas from Spain (FGCSIC) and Banco Santander. F.C. was supported by a JAE-Doc contract financed by CSIC and the European Social Fund (ESF). L.C. was supported by a postdoctoral contract funded by FGCSIC and Banco Santander. FARMDINDIS project, funded by Infraestructures.cat (Generalitat de Catalunya) and Aig ues del Segarra-Garrigues SA, provided data on field censuses. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Traditional low-intensity agricultural systems are often associated with high biodiversity conservation value in different regions of the world [1]. As a result of thousands of years of agricultural expansion, a large number of wild species live on land dedicated to human food production, and their preservation strongly depends on traditional low-intensity practices [2,3]. This is particularly relevant in some regions, such as Europe, where agricultural landscapes represent the major part (about 60%) of non-urban areas [2,3]. Here, traditional agricultural systems, based on low intensive farming and extensive grazing, have historically provided highly heterogeneous landscapes capable of holding species-rich communities of organisms [4]. However, in recent decades these systems have come under pressure due to socio-economic changes, increased food demands and new technological opportunities [2]. As a result, farmland in many industrialized countries is being profoundly altered, mainly through agricultural intensification and land abandonment, posing a major challenge for biodiversity conservation today [5,6]. Unless the detrimental impacts of present and future agricultural practices can be prevented or mitigated, many agricultural landscapes will suffer from further degradation in the coming decades [2]. Managing the environmental effects of these agricultural changes thus requires the development of frameworks that allow the exploration of their potential threats and opportunities, even before the changes occur [79]. Habitat models may provide valuable tools for predicting species responses to different land-use alternatives. To date, the potential effects of changing landscapes on species dynamics and biodiversity have tended to be addressed through correlative models whereby species-habitat associations are estimated by statistically relating current distributions to particular structural land cover types [10,11]. When habitat conditions remain fixed temporally and spatially and there is appropriate information to use as a surrogate for factors relevant to species habitat selection [12], such habitat association models can be successful at predicting species occurrence or population dynamics from habitat characteristics. However, they can be much less successful when used to make predictions outside the area or habitat conditions for which the model has been calibrated [13]. As a consequence, it has recently been proposed that, instead of using structural land cover types, land use population dynamics relationships might be better examined in the context of functional cover types, such as foraging or nesting habitat, identified on the basis of resource dependencies of species or species groups [14,15]. Unlike habitat-based approaches, resource-based models assess the relative quality of a selected habitat type (e.g. crop or agricultural practice) on the basis of key factors underpinning the distribution and abundance of the considered species [11,16]. For example, species habitat associations, if present, are largely dictated by the availability of key resources in such habitats, rather than the habitat per se [14,15]. Basing distribution and abundance models on resource availa (...truncated)