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Variation in herpetofauna detection probabilities: implications for study design

Jeremy A. Baumgardt; Michael L. Morrison; Leonard A. Brennan; Madeleine Thornley; Tyler A. Campbell
Environmental Monitoring and Assessment · Vol. 193, Issue 10 · 2021

Abstract

Population monitoring is fundamental for informing management decisions aimed at reducing the rapid rate of global biodiversity decline. Herpetofauna are experiencing declines worldwide and include species that are challenging to monitor. Raw counts and associated metrics such as richness indices are common for monitoring populations of herpetofauna; however, these methods are susceptible to bias as they fail to account for varying detection probabilities. Our goal was to develop a program for efficiently monitoring herpetofauna in southern Texas. Our objectives were to (1) estimate detection probabilities in an occupancy modeling framework using trap arrays for a diverse group of herpetofauna and (2) to evaluate the relative effectiveness of funnel traps, pitfall traps, and cover boards. We collected data with 36 arrays at 2 study sites in 2015 and 2016, for 2105 array-days resulting in 4839 detections of 51 species. We modeled occupancy for 21 species and found support for the hypothesis that detection probability varied over our sampling duration for 10 species and with rainfall for 10 species. For herpetofauna in our study, we found 14 and 12 species were most efficiently captured with funnel traps and pitfall traps, respectively, and no species were most efficiently captured with cover boards. Our results show that using methods that do not account for variations in detection probability are highly subject to bias unless the likelihood of false absences is minimized with exceptionally long capture durations. For monitoring herpetofauna in southern Texas, we recommend using arrays with funnel and pitfall traps and an analytical method such as occupancy modeling that accounts for variation in detection.

Bibliographic Information

JournalEnvironmental Monitoring and Assessment
PublisherSpringer
Publication Date2021-10-01
Publication Year2021
Volume193
Issue10
Document TypeJournal Article
eISSN1573-2959
DOI10.1007/s10661-021-09424-0

Access Information

NARA Access Coverage1981-01-01~Current
Journal Homepagehttps://www.springer.com/journal/10661
Publisher PageOpen Publisher Page
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