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Data from: Spatially explicit abundance estimation of a rare habitat specialist: implications for SECR study design

Citation

Kristensen, Thea V.; Kovach, Adrienne I. (2019), Data from: Spatially explicit abundance estimation of a rare habitat specialist: implications for SECR study design, Dryad, Dataset, https://doi.org/10.5061/dryad.t5b72qv

Abstract

Estimating abundance is an essential component of monitoring and recovery of rare species and spatially explicit capture-recapture (SECR) models provide the means for robust density estimation. Previous work has elucidated principles of SECR study design for large, generalist carnivores, but less attention has been paid to study design considerations for smaller species, with less extensive home ranges. Here we integrated data from an intensive pilot study with simulation modeling to evaluate the influence of survey sampling intensity on precision and accuracy in SECR abundance estimation for a rare lagomorph that specializes on patchily distributed early successional habitats. Doing so, we obtained the first mark-recapture density estimates for the New England cottontail (Sylvilagus transitionalis). Capture probability and density on the landscape both impacted the required intensity of the sampling design. The optimal study design for robust estimation also required a greater number of traps relative to home range size or spatial extent than those recommended in prior SECR studies. This divergence emphasizes that SECR study design considerations will differ among organisms with varying spatial extent and habitat use. Demonstrating the appropriate sampling design for a study system is important prior to embarking in a SECR study. Integrating pilot empirical data with simulations provides a powerful means for optimizing SECR study design and for facilitating applicability of SECR approaches to a wider array of organisms with varying habitat and space use. This methodology may be employed in planning a monitoring program that maximizes effectiveness while minimizing cost and effort, as part of the adaptive management approach to monitor and recover rare or endangered species.

Usage Notes

Location

northeastern USA