DOI: 10.5061/dryad.t5b72qv
title: Data from: Spatially explicit abundance estimation of a rare habitat specialist: implications for SECR study design

description: 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.
description: Kristensen_Kovach_empirical cottontail capture historiesCapture histories of New England and eastern cottontails sampled during fecal pellet surveys for spatially explicit genetic mark-recapture abundance estimation. These empirical data were used to generate cottontail density estimates in SECR for six sites in Maine and New Hampshire, USA.Kristensen_Kovach_capture_history_all.xlsxSECR output from simulated data with detection (g0) of 0.1SECR density estimates and other associated output and error measures for simulated survey data with a detection probability at the home range center (g0) of 0.1. Data were simulated and densities estimated for multiple scenarios representing combinations of pellet spacing, transect spacing, and survey occasion. These scenarios represented a range of realistic survey options in the field, from low to high intensity survey effort. Each dataset was simulated for 4 different densities on the landscape: 0.5, 1.0, 2.0, and 3.0 rabbits/ha.Kristensen_Kovach_gpt1_simulation_output.xlsxSECR output from simulated data with detection (g0) of 0.2SECR density estimates and other associated output and error measures for simulated survey data with a detection probability at the home range center (g0) of 0.2. Data were simulated and densities estimated for multiple scenarios representing combinations of pellet spacing, transect spacing, and survey occasion. These scenarios represented a range of realistic survey options in the field, from low to high intensity survey effort. Each dataset was simulated for 4 different densities on the landscape: 0.5, 1.0, 2.0, and 3.0 rabbits/ha.Kristensen_Kovach_gpt2_simluation_output.xlsx