2018
DOI: 10.1007/s10980-018-0631-2
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Multi-level, multi-scale habitat selection by a wide-ranging, federally threatened snake

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Cited by 32 publications
(53 citation statements)
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References 91 publications
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“…A second feature of D. couperi life history that reduces opportunity for speciation is the variety of habitats used by these animals throughout a year (e.g., [72]), particularly in peninsular Florida, where individuals will utilize habitats with varying degrees of anthropogenic disturbance [76]. This broad habitat use reduces the opportunity for ecological barriers to gene flow and is consistent with the high rates of gene flow indicated by our microsatellite analysis.…”
Section: Discussionmentioning
confidence: 52%
“…A second feature of D. couperi life history that reduces opportunity for speciation is the variety of habitats used by these animals throughout a year (e.g., [72]), particularly in peninsular Florida, where individuals will utilize habitats with varying degrees of anthropogenic disturbance [76]. This broad habitat use reduces the opportunity for ecological barriers to gene flow and is consistent with the high rates of gene flow indicated by our microsatellite analysis.…”
Section: Discussionmentioning
confidence: 52%
“…Separate models can therefore be used to investigate differences in habitat use that manifest at lower levels between these subcategories, whilst integrating universal higher level model output (e.g. Rettie and Messier 2000;Gabor et al 2001;Bauder et al 2018). By allowing drivers operating at different scales to be disentangled, regionally suitable areas without the local-or landscape-scale features required at lower levels can be identified (Pearson et al 2004;Vicente et al 2011), improving the prescription and spatial targeting of management solutions (Lindenmayer 2000;Whittingham et al 2007;Zeller et al 2017).…”
Section: Discussionmentioning
confidence: 99%
“…(b) Post-hoc multi-level models HSI values from each single-level model were overlaid, harmonised to the finest pixel size without interpolation and multiplied on a pixel-by-pixel basis (e.g. Johnson et al 2004;Fournier et al 2017;Zeller et al 2017;Bauder et al 2018). As this approach involves using the product of the outputs from two or more models using different input data, measures of AICc and three-fold AUC could not be calculated without relying on the mean of these validation metrics across the input models, which we believe to be largely uninformative.…”
Section: Comparisons With Other Approachesmentioning
confidence: 99%
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