Abstract
Few ecological studies have explored landscape suitability using the gradient concept of landscape structure for wildlife species. Identification of conditions influencing the landscape ecology of endangered species allows for development of more robust recovery strategies. Our objectives were to (i) identify the range of landscape metrics (i.e., mean patch area; patch and edge densities; percent land cover; shape, aggregation, and largest patch indices) associated with woody vegetation used by ocelots (Leopardus pardalis), and (ii) quantify the potential distribution of suitable woody cover for ocelots across southern Texas. We used the gradient concept of landscape structure and the theory of slack combined with GPS telemetry data from 10 ocelots. Spatial distribution of high suitable woody cover is comprised of large patches, with low shape-index values (1.07–2.25), patch (27.21–72.50 patches/100 ha), and edge (0–191.50 m/ha) densities. High suitability landscape structure for ocelots occurs in 45.27% of woody cover in southern Texas. Our study demonstrates a new approach for measuring landscape suitability for ocelots in southern Texas. The range of landscape values identified that there are more large woody patches containing the spatial structure used by ocelots than previously suspected, which will aid in evaluating recovery and road planning efforts.
Highlights
Published: 6 October 2021Habitat suitability models are widely used for assessing habitat quality for plant and animal species worldwide [1,2,3]
Habitat or landscape suitability models are often considered a fundamental tool for species survival planning, ecological assessments, and conservation planning
Our objectives were to use the gradient concept of landscape ecology to (i) identify the range of cover metrics associated with woody vegetation used by ocelots, and (ii) quantify the potential distribution of suitable woody cover patches for ocelots across southern Texas
Summary
Habitat suitability models are widely used for assessing habitat quality for plant and animal species worldwide [1,2,3]. Unlike most resource selection analyses, habitat suitability models quantify the amount and spatial distribution of habitat based on characteristics deemed important to a species [1,4,7]. Habitat suitability models generate an index that is used to determine the suitability of an area to be habitat for a species [6] This differs from traditional resource selection functions (RSF), which use logistic regression to relate a binary response of used versus available points to a nonlinear or linear function of environmental resource variables [6]. Habitat or landscape suitability models are often considered a fundamental tool for species survival planning, ecological assessments, and conservation planning
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