Abstract
Connectivity conservation analysis is based on a wide range of approaches designed to pinpoint key ecological corridors in order to maintain multispecies flows. However, the lack of validation procedures with accessible data prevents one from evaluating the accuracy of ecological corridor locations. We propose a new validation procedure to evaluate the accuracy of ecological corridor locations in landscape connectivity approaches. The ability of the procedure to properly rank the accuracy of different landscape connectivity approaches was illustrated in a study case. Maxent model and circuit theory were used to locate ecological corridors for forest bird species, following three approaches based on land cover, umbrella species and multispecies presence data. The validation procedure was used to compare the three approaches. Our validation procedure ranked the three approaches as expected, considering that accuracy in locating ecological corridors is related to the biological realism of calibration data. The corridors modelled were more accurate with species presence data (umbrella and multispecies approaches) compared to land cover proxy (habitat-based approach). These results confirm the quality of the validation procedure. Our validation procedure can be used to: (1) evaluate the accuracy of the location of ecological corridors; (2) select the best approach to locate ecological corridors, and (3) validate the underlying assumptions of landscape connectivity approaches (e.g., dispersal and matrix resistance values).
Highlights
The increase in anthropogenic pressures has greatly affected species movement worldwide [1]
Validation of Ecological Corridor Locations Based on Corridor Score
If the distribution of matrix resistance values of a first resistance surface is more flat-tailed compared to a second one, the distance between two random pixels has a greater chance of being larger, which can mistakenly lead to the conclusion that the first method is less accurate
Summary
The increase in anthropogenic pressures has greatly affected species movement worldwide [1]. Key conceptual frameworks and accessible tools based on graph and circuit theory have been proposed to help locate ecological corridors through landscape connectivity analysis [7,8,9]. These frameworks are based on different, and often untested, assumptions (e.g., dispersal or matrix resistance) that can lead to inconsistent spatial prioritization [10,11,12]. To overcome this issue, empirical procedures are needed to validate different landscape connectivity approaches that pinpoint ecological corridors
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