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      Anticipating Knowledge to Inform Species Management: Predicting Spatially Explicit Habitat Suitability of a Colonial Vulture Spreading Its Range

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      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          The knowledge of both potential distribution and habitat suitability is fundamental in spreading species to inform in advance management and conservation planning. After a severe decline in the past decades, the griffon vulture ( Gyps fulvus) is now spreading its breeding range towards the northwest in Spain and Europe. Because of its key ecological function, anticipated spatial knowledge is required to inform appropriately both vulture and ecosystem management.

          Methodology/Findings

          Here we used maximum entropy (Maxent) models to determine the habitat suitability of potential and current breeding distribution of the griffon vulture using presence-only data (N = 124 colonies) in north-western Spain. The most relevant ecological factors shaping this habitat suitability were also identified. The resulting model had a high predictive performance and was able to predict species' historical distribution. 7.5% (∼1,850 km 2) of the study area resulted to be suitable breeding habitat, most of which (∼70%) is already occupied by the species. Cliff availability and livestock density, especially of sheep and goats, around 10 km of the colonies were the fundamental factors determining breeding habitat suitability for this species.

          Conclusions/Significance

          Griffon vultures could still spread 50–60 km towards the west, increasing their breeding range in 1,782 km 2. According to our results, 7.22% of the area suitable for griffon vulture will be affected by wind farms, so our results could help to better plan wind farm locations. The approach here developed could be useful to inform management of reintroductions and recovery programmes currently being implemented for both the griffon vulture and other threatened vulture species.

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          Modeling species' distributions to improve conservation in semiurban landscapes: koala case study.

          Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (Phascolarctos cinereus) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity.
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            Author and article information

            Contributors
            Role: Editor
            Journal
            PLoS One
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2010
            25 August 2010
            : 5
            : 8
            : e12374
            Affiliations
            [1]School of Biology, IE University, Segovia, Spain
            Smithsonian's National Zoological Park, United States of America
            Author notes

            Conceived and designed the experiments: PMT PPO. Performed the experiments: PMT PPO. Analyzed the data: PMT PPO. Contributed reagents/materials/analysis tools: PMT PPO. Wrote the paper: PMT PPO.

            Article
            10-PONE-RA-18643R1
            10.1371/journal.pone.0012374
            2928263
            20811501
            896c6d7c-2796-46a8-959b-9601626b8c5b
            Mateo-Tomás, Olea. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
            History
            : 6 May 2010
            : 2 August 2010
            Page count
            Pages: 11
            Categories
            Research Article
            Ecology/Conservation and Restoration Ecology
            Ecology/Ecosystem Ecology
            Ecology/Population Ecology
            Ecology/Spatial and Landscape Ecology

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