Selection, use, choice and occupancy: clarifying concepts in resource selection studies
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This paper attempts to clarify the concepts and terminology used in animal resource studies by illustrating the relationships among these various concepts and providing their statistical underpinnings.Abstract:
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.read more
Citations
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Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure
David R. Roberts,Volker Bahn,Simone Ciuti,Mark S. Boyce,Jane Elith,Gurutzeta Guillera-Arroita,Severin Hauenstein,José J. Lahoz-Monfort,Boris Schröder,Wilfried Thuiller,David I. Warton,Brendan A. Wintle,Florian Hartig,Florian Hartig,Carsten F. Dormann +14 more
TL;DR: It is recommended that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations.
Journal ArticleDOI
Is my species distribution model fit for purpose? Matching data and models to applications
Gurutzeta Guillera-Arroita,José J. Lahoz-Monfort,Jane Elith,Ascelin Gordon,Heini Kujala,Pia E. Lentini,Michael A. McCarthy,Reid Tingley,Brendan A. Wintle +8 more
TL;DR: In this paper, the authors synthesize current knowledge and provide a simple framework that summarizes how interactions between data type and the sampling process determine the quantity that is estimated by a species distribution model.
Journal ArticleDOI
On the selection of thresholds for predicting species occurrence with presence-only data.
TL;DR: It is concluded that maxF pb is affected by the KP–RP ratio of the threshold selection datasets, but maxSSS is almost unaffected by this ratio, and unbiased estimations of prevalence are difficult to be determined using the threshold‐based approach.
Journal ArticleDOI
Integrated step selection analysis: bridging the gap between resource selection and animal movement
TL;DR: iSSA relies on simultaneously estimating movement and resource selection parameters, thus allowing simple likelihood‐based inference of resource selection within a mechanistic movement model and demonstrates the utility of iSSA as a general, flexible and user‐friendly approach for both evaluating a variety of ecological hypotheses, and predicting future ecological patterns.
Journal ArticleDOI
Flexible habitat selection by cougars in response to anthropogenic development
TL;DR: In this article, the authors investigated the adaptation of cougars to anthropogenic development in the former ranges of several carnivore species, including cougars (Puma concolor), and found that cougars adjust their behavior to accommodate anthropogenic developments, facilitating successful use of modified habitats.
References
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