If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact us at firstname.lastname@example.org.
Desert Tortoises, Density, and Violated Assumptions: Improving Estimates with Spatial Information
AuthorMitchell, Corey I
AdvisorNussear, Kenneth E
AltmetricsView Usage Statistics
Accurate population estimates are essential for monitoring the recovery of the federally listed Mojave desert tortoise (Gopherus agassizii), however, desert tortoise populations are difficult to accurately quantify due to a number of factors. Mark-recapture sampling methods have regularly been used to monitor this species, but the methods employed are often plagued by the violation of statistical assumptions, which have the potential to bias density estimates. By incorporating spatial information into conventional density estimation models, spatial capture-recapture (SCR) models can account for common assumption violations such as spatially heterogeneous detection probabilities and temporary emigration when animals leave plots during surveys. We conducted mark-recapture surveys separated by three years at 10 1-km2 plots in and adjacent to the Ivanpah Valley of CA and NV from 2015-2019. Movement data were collected concurrently using radio-telemetry and GPS data loggers. GPS data demonstrated that desert tortoises frequently exhibited temporary emigration outside the plot during the three-day survey periods; thereby, complicating standard approaches for closed-model density estimation. We integrated mark-recapture survey data for adults (>160 mm MCL) at each plot with corresponding spatial capture locations and supplementary spatial data using a modified SCR model fitted in a Bayesian framework. We compared density estimates modeled with conventional non-spatial methods, as well as three standard SCR models based on symmetrical usage areas described by various levels of supplementary spatial data, and a novel SCR model that integrates daily movement displacement quantified from fine-scale GPS data to define movement between sampling periods. The conventional model consistently resulted in inflated estimates of density while the standard SCR models allowed us to generate spatially corrected estimates for a species where detectability and abundance are low. However, we found that if not properly specified, the temporal scale of supplementary data may result in an unintended source of bias. Our results demonstrate the importance of accounting for spatial information as well was the value of understanding model specification when estimating density for the desert tortoise and have the potential to enhance the efficacy of long-term efforts to monitor population trends and inform recovery efforts.