Geology topics

Jessica J. Stocking

Publications and source records attributed to Jessica J. Stocking.

3 recordsLinked to original sources

USGS2017

Managing native predators: Evidence from a partial removal of raccoons ( Procyon lotor ) on the Outer Banks of North Carolina, USA

Raccoons ( Procyon lotor ) are important predators of ground-nesting species in coastal systems. They have been identified as a primary cause of nest failure for the American Oystercatcher ( Haematopus palliatus ) throughout its range. Concerns over the long-term effects of raccoon predation and increased nest success following a hurricane inspired a mark-resight study of the raccoon population on a barrier island off North Carolina, USA. Approximately half of the raccoons were experimentally removed in 2008. Nests ( n = 700) were monitored on two adjacent barrier islands during 2004–2013. Daily nest survival estimates were highest for 2004 (0.974 ± 0.005) and lowest for 2007 and 2008 (0.925 ± 0.009 and 0.925 ± 0.010, respectively). The only model in our candidate set that received any support included island and time of season, along with a diminishing effect of the hurricane and a constant, 5-year effect of the raccoon removal. For both hurricane and raccoon removal, however, the support for island-specific effects was weak (β = -0.204 ± 0.116 and 0.146 ± 0.349, respectively). We conclude that either the raccoon reduction was inadequate, or factors other than predation cause more variation in nest success than previously recognized. A multi-faceted approach to management aimed at reducing nest losses to storm overwash, predation, and human disturbance is likely to yield the largest population level benefits.

North Carolina↗

USGS2015

Camera traps and mark-resight models: The value of ancillary data for evaluating assumptions

Unbiased estimators of abundance and density are fundamental to the study of animal ecology and critical for making sound management decisions. Capture–recapture models are generally considered the most robust approach for estimating these parameters but rely on a number of assumptions that are often violated but rarely validated. Mark-resight models, a form of capture–recapture, are well suited for use with noninvasive sampling methods and allow for a number of assumptions to be relaxed. We used ancillary data from continuous video and radio telemetry to evaluate the assumptions of mark-resight models for abundance estimation on a barrier island raccoon (Procyon lotor) population using camera traps. Our island study site was geographically closed, allowing us to estimate real survival and in situ recruitment in addition to population size. We found several sources of bias due to heterogeneity of capture probabilities in our study, including camera placement, animal movement, island physiography, and animal behavior. Almost all sources of heterogeneity could be accounted for using the sophisticated mark-resight models developed by McClintock et al. (2009b) and this model generated estimates similar to a spatially explicit mark-resight model previously developed for this population during our study. Spatially explicit capture–recapture models have become an important tool in ecology and confer a number of advantages; however, non-spatial models that account for inherent individual heterogeneity may perform nearly as well, especially where immigration and emigration are limited. Non-spatial models are computationally less demanding, do not make implicit assumptions related to the isotropy of home ranges, and can provide insights with respect to the biological traits of the local population.

North Carolina↗

USGS2013

A spatial mark–resight model augmented with telemetry data

Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark-resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark-recapture. However, density estimation using mark-resight is difficult because the area sampled must be explicitly defined, historically using ad-hoc approaches. We develop a spatial mark-resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows <100% individual identification of marked individuals. We implemented the model in a Bayesian framework, using a custom-made Metropolis-within-Gibbs Markov chain Monte Carlo algorithm. As an example, we applied this model to a mark-resight study of raccoons on South Core Banks, a barrier island in Cape Lookout National Seashore, North Carolina. We estimated a population of 186.71 ± 14.81 individuals, which translated to a density of 8.29 ± 0.66 individuals per km 2 . The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.

Ecology↗