Sampling effects on the identification of roadkill hotspots: implications for survey design.

Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. “True” hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. “Estimated” hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1–30 days). Overall, 24.3% of segments were “true” hotspots, concentrating 40.4% of roadkills. For different groups, “true …

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Santos S.M. Marques J.T. Lourenço A. Medinas D. Barbosa A.M. Beja P. y Mira A. Sampling effects on the identification of roadkill hotspots: implications for survey design. Elsevier, 2015. https://doi.org/10.1016/j.jenvman.2015.07.037

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Resource type Text
Date of creation 2025-05-23
Date of last revision 2025-05-23
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Metadata identifier 76c2968b-573f-5816-9416-707412a0fd64
Metadata language Spanish
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ISO 19115 topic category biota
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Name of the dataset creator Santos, S.M., Marques, J.T., Lourenço, A., Medinas, D., Barbosa, A.M., Beja, P. y Mira, A.
Name of the dataset editor Elsevier
Other identifier DOI: 10.1016/j.jenvman.2015.07.037
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