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      Shrub and vegetation cover predict resource selection use by an endangered species of desert lizard

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          Abstract

          Globally, no species is exempt from the constraints associated with limited available habitat or resources, and endangered species in particular warrant critical examination. In most cases, these species are restricted to limited locations, and the relative likelihood of resource use within the space they can access is important. Using Gambelia sila, one of the first vertebrate species listed as endangered, we used resource selection function analysis of telemetry and remotely sensed data to identity key drivers of selected versus available locations for this species in Carrizo Plain National Monument, USA. We examined the probability of selection given different resource types. Increasing shrub cover, lower and relatively more flat sites, increasing normalized difference vegetation index, and solar radiation all significantly predicted likelihood of observed selection within the area sampled. Imagery data were also validated with fine-scale field data showing that large-scale contrasts of selection relative to available location patterns for animal species are a useful lens for potential habitat. Key environmental infrastructure such as foundation plant species including shrubs or local differences in the physical attributes were relevant to this endangered species.

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          Estimating space-use and habitat preference from wildlife telemetry data

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            Selection, use, choice and occupancy: clarifying concepts in resource selection studies.

            1. During the last decade, there has been a proliferation of statistical methods for studying resource selection by animals. While statistical techniques are advancing at a fast pace, there is confusion in the conceptual understanding of the meaning of various quantities that these statistical techniques provide. 2. Terms such as selection, choice, use, occupancy and preference often are employed as if they are synonymous. Many practitioners are unclear about the distinctions between different concepts such as 'probability of selection,' 'probability of use,' 'choice probabilities' and 'probability of occupancy'. 3. Similarly, practitioners are not always clear about the differences between and relevance of 'relative probability of selection' vs. 'probability of selection' to effective management. 4. Practitioners also are unaware that they are using only a single statistical model for modelling resource selection, namely the exponential probability of selection, when other models might be more appropriate. Currently, such multimodel inference is lacking in the resource selection literature. 5. In this paper, we attempt to clarify the concepts and terminology used in animal resource studies by illustrating the relationships among these various concepts and providing their statistical underpinnings. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.
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              Ecological traps: current evidence and future directions

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                Author and article information

                Contributors
                lortie@yorku.ca
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 March 2020
                17 March 2020
                2020
                : 10
                : 4884
                Affiliations
                [1 ]ISNI 0000 0004 1936 9430, GRID grid.21100.32, Department of Biology, , York University, ; Toronto, ON Canada
                [2 ]ISNI 0000 0004 1936 9676, GRID grid.133342.4, The National Center for Ecological Analysis and Synthesis, UCSB, ; Santa Barbara, CA USA
                [3 ]GRID grid.462133.1, The Bureau of Land Management, ; Marina, CA USA
                [4 ]ISNI 0000 0004 0591 6771, GRID grid.422375.5, The Nature Conservancy, ; San Francisco, CA USA
                Article
                61880
                10.1038/s41598-020-61880-9
                7078218
                32184467
                162e26b3-4d70-4531-abcf-571c7bd6e2cd
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 June 2019
                : 3 March 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100002790, Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (NSERC Canadian Network for Research and Innovation in Machining Technology);
                Award ID: 182255
                Award Recipient :
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                © The Author(s) 2020

                Uncategorized
                conservation biology,ecological modelling,behavioural ecology
                Uncategorized
                conservation biology, ecological modelling, behavioural ecology

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