On the identification of mortality hotspots in linear infrastructures.

One of the main tasks when dealing with the impacts of infrastructures on wildlife is to identify hotspots of high mortality so one can devise and implement mitigation measures. A common strategy to identify hotspots is to divide an infrastructure into several segments and determine when the number of collisions in a segment is above a given threshold, reflecting a desired significance level that is obtained assuming a probability distribution for the number of collisions, which is often the Poisson distribution. The problem with this approach, when applied to each segment individually, is that the probability of identifying false hotspots (Type I error) is potentially high. The way to solve this problem is to recognize that it requires multiple testing corrections or a Bayesian approach. Here, we apply three different methods that implement the required corrections to the identification of hotspots: (i) the familywise error rate …

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Borda-de-Água L. Ascensão F. Sapage M. Barrientos R. y Pereira H.M. On the identification of mortality hotspots in linear infrastructures. Urban & Fischer, 2019. https://doi.org/10.1016/j.baae.2018.11.001

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Resource type Text
Date of creation 2024-12-02
Date of last revision 2025-01-19
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Metadata identifier 025d9723-a169-590d-b7c0-7a89a266c9a4
Metadata language Spanish
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ISO 19115 topic category biota
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Name of the dataset creator Borda-de-Água, L., Ascensão, F., Sapage, M., Barrientos, R. y Pereira, H.M.
Name of the dataset editor Urban & Fischer
Other identifier DOI: 10.1016/j.baae.2018.11.001
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