Data from: Spatially explicit abundance estimation of a rare habitat specialist: implications for SECR study design - Kristensen, Thea V.; Kovach, Adrienne I. (Dryad, 2019)
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.
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
Keywords: population estimation: shrubland; eastern cottontail; Sylvilagus transitionalis; Holocene; New England cottontail; spatially explicit capture-recapture; Sylvilagus floridanus