Influence of population survey protocol on wood turtle (Glyptemys insculpta) detections

Context The wood turtle (Glyptemys insculpta) is a species of conservation concern and currently being considered for listing under the US Endangered Species Act. Two regional survey protocols were developed to facilitate standardized monitoring across the wood turtle’s geographic distribution due to population declines throughout its range. It is currently unknown whether these survey designs are compatible for broad-scale analyses. Aims We assessed two aspects of the protocols, constrained versus unconstrained surveys and aquatic-focused versus terrestrial-focused surveys, using four survey designs, i.e. aquatic constrained, aquatic unconstrained, terrestrial constrained, and terrestrial unconstrained, to determine whether they result in similar estimates for detection probability and expected count during surveys. Methods Between 2021 and 2023, we completed comparisons at 21 sites in 9 states. We estimated adult detection probability and expected count for aquatic-focused and terrestrial-focused surveys by using N-mixture models and generalized linear mixed models. Key results For aquatic surveys in medium-sized streams, estimated detection probability was 0.08 (95% CI: 0.05–0.12) and 0.05 (95% CI: 0.03–0.08), and expected count was 5.5 (95% CI: 3.6–8.4) and 3.4 (95% CI: 2.2–5.2) for constrained and unconstrained surveys respectively. For terrestrial surveys, estimated detection probability was 0.32 (95% CI: 0.23–0.43) and 0.24 (95% CI: 0.17–0.33), and expected count was 2.0 (95% CI: 1.2–3.5) and 1.6 (95% CI: 0.9–2.7) for constrained and unconstrained surveys respectively, at the mean air temperature (20.3°C). Conclusions Our study results indicate that constrained and unconstrained surveys are both effective population survey techniques for wood turtles, but survey type should be accounted for in count or abundance models. In contrast, mean detection probability substantially differed between aquatic and terrestrial surveys. Thus, restricting all survey replicates within sampling periods at monitoring sites to only aquatic or terrestrial surveys is optimal for use in population models. Implications Our results can be used by agencies to optimize within and across wood turtle monitoring programs, including personnel resources, to meet objectives including continuous monitoring and evaluation of wood turtle populations if the species is listed as threatened under the Endangered Species Act.

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Publication Details

Journal
Wildlife Research
Published
2026-11-05
DOI
https://doi.org/10.1071/wr26021
Primary Topic
Turtle Biology and Conservation
Type
article
Field-Weighted Citation Impact
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article

Influence of population survey protocol on wood turtle (Glyptemys insculpta) detections

Jessica R. Meck, Gaea E. Crozier, Donald J. Brown, Kevin J. Oxenrider et al.
Wildlife Research
Turtle Biology and Conservation
article

Influence of population survey protocol on wood turtle (Glyptemys insculpta) detections

Jessica R. Meck, Gaea E. Crozier, Donald J. Brown, Kevin J. Oxenrider, Christopher M. Lituma, Jennifer A. Moore, Yu Man Lee, Allyson N. Beard, Thomas S. B. Akre, Katharine D. Gipe, Michael T. Jones, Derek Yorks, Andrew F. Badje, Marianne Kelso
article en

Abstract

Context The wood turtle (Glyptemys insculpta) is a species of conservation concern and currently being considered for listing under the US Endangered Species Act. Two regional survey protocols were developed to facilitate standardized monitoring across the wood turtle’s geographic distribution due to population declines throughout its range. It is currently unknown whether these survey designs are compatible for broad-scale analyses. Aims We assessed two aspects of the protocols, constrained versus unconstrained surveys and aquatic-focused versus terrestrial-focused surveys, using four survey designs, i.e. aquatic constrained, aquatic unconstrained, terrestrial constrained, and terrestrial unconstrained, to determine whether they result in similar estimates for detection probability and expected count during surveys. Methods Between 2021 and 2023, we completed comparisons at 21 sites in 9 states. We estimated adult detection probability and expected count for aquatic-focused and terrestrial-focused surveys by using N-mixture models and generalized linear mixed models. Key results For aquatic surveys in medium-sized streams, estimated detection probability was 0.08 (95% CI: 0.05–0.12) and 0.05 (95% CI: 0.03–0.08), and expected count was 5.5 (95% CI: 3.6–8.4) and 3.4 (95% CI: 2.2–5.2) for constrained and unconstrained surveys respectively. For terrestrial surveys, estimated detection probability was 0.32 (95% CI: 0.23–0.43) and 0.24 (95% CI: 0.17–0.33), and expected count was 2.0 (95% CI: 1.2–3.5) and 1.6 (95% CI: 0.9–2.7) for constrained and unconstrained surveys respectively, at the mean air temperature (20.3°C). Conclusions Our study results indicate that constrained and unconstrained surveys are both effective population survey techniques for wood turtles, but survey type should be accounted for in count or abundance models. In contrast, mean detection probability substantially differed between aquatic and terrestrial surveys. Thus, restricting all survey replicates within sampling periods at monitoring sites to only aquatic or terrestrial surveys is optimal for use in population models. Implications Our results can be used by agencies to optimize within and across wood turtle monitoring programs, including personnel resources, to meet objectives including continuous monitoring and evaluation of wood turtle populations if the species is listed as threatened under the Endangered Species Act.

Wildlife ResearchVol. 53(11)
West Virginia University (US), US Forest Service (US), Minnesota Department of Natural Resources (US), Wisconsin Department of Natural Resources (US), Smithsonian Conservation Biology Institute (US), Pennsylvania Fish and Boat Commission (US), National Zoological Park (US), Pacific Northwest Research Station (US), Maine Department of Inland Fisheries and Wildlife (US), Grand Valley State University (US), Michigan State University (US)
Openalex Percentile: Top 18%
Turtle Biology and Conservation
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