Arielle Waldstein Parsons

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 developed 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 (Procyon lotor) on South Core Banks, a barrier island in Cape Lookout National Seashore, North Carolina, USA. We estimated a population of 186.71 +/- 14.81 individuals, which translated to a density of 8.29 +/- 0.66 individuals/km2 (mean +/- SD). The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.

Cats are Rare Where Coyotes Roam

Domestic cats (Felis catus) have caused the extinction of many island species and are thought to kill many billions of birds and mammals in the continental United States each year. However, the spatial distribution and abundance of cats and their risk to our protected areas remains unknown. We worked with citizen scientists to survey the mammals at 2,117 sites in 32 protected areas and one urban area across 6 states in the eastern United States using camera traps. We found that most protected areas had high levels of coyote (Canis latrans) activity, but few or no domestic cats. The relative abundance of domestic cats in residential yards, where coyotes were rare, was 300 times higher than in the protected areas. Our spatial models of cat distribution show the amount of coyote activity and housing density are the best predictors of cat activity, and that coyotes and cats overlap the most in small urban forests. Coyotes were nocturnal at all sites, while cats were nocturnal in protected areas, but significantly more diurnal in urban sites. We suggest that the ecological impact of free-ranging cats in the region is concentrated in urban areas or other sites, such as islands, with few coyotes. Our study also shows the value of citizen science for conducting broadscale mammal surveys using photo-vouchered locations that ensure high data quality.

A two-species occupancy model accommodating simultaneous spatial and interspecific dependence

Occupancy models are popular for estimating the probability a site is occupied by a species of interest when detection is imperfect. Occupancy models have been extended to account for interacting species and spatial dependence but cannot presently allow both factors to act simultaneously. We propose a two-species occupancy model that accommodates both interspecific and spatial dependence. We use a point-referenced multivariate hierarchical spatial model to account for both spatial and interspecific dependence. We model spatial random effects with predictive process models and use probit regression to improve efficiency of posterior sampling. We model occupancy probabilities of red fox (Vulpes vulpes) and coyote (Canis latrans) with camera trap data collected from six mid-Atlantic states in the eastern United States. We fit four models comprising a fully factorial combination of spatial and interspecific dependence to two-thirds of camera trapping sites and validated models with the remaining data. Red fox and coyotes each exhibited spatial dependence at distances > 0.8 and 0.4 km, respectively, and exhibited geographic variation in interspecific dependence. Consequently, predictions from the model assuming simultaneous spatial and interspecific dependence best matched test data observations. This application highlights the utility of simultaneously accounting for spatial and interspecific dependence.

A multispecies occupancy model for two or more interacting species

Summary Species occurrence is influenced by environmental conditions and the presence of other species. Current approaches for multispecies occupancy modelling are practically limited to two interacting species and often require the assumption of asymmetric interactions. We propose a multispecies occupancy model that can accommodate two or more interacting species. We generalize the single-species occupancy model to two or more interacting species by assuming the latent occupancy state is a multivariate Bernoulli random variable. We propose modelling the probability of each potential latent occupancy state with both a multinomial logit and a multinomial probit model and present details of a Gibbs sampler for the latter. As an example, we model co-occurrence probabilities of bobcat (Lynx rufus), coyote (Canis latrans), grey fox (Urocyon cinereoargenteus) and red fox (Vulpes vulpes) as a function of human disturbance variables throughout 6 Mid-Atlantic states in the eastern United States. We found evidence for pairwise interactions among most species, and the probability of some pairs of species occupying the same site varied along environmental gradients; for example, occupancy probabilities of coyote and grey fox were independent at sites with little human disturbance, but these two species were more likely to occur together at sites with high human disturbance. Ecological communities are composed of multiple interacting species. Our proposed method improves our ability to draw inference from such communities by permitting modelling of detection/non-detection data from an arbitrary number of species, without assuming asymmetric interactions. Additionally, our proposed method permits modelling the probability two or more species occur together as a function of environmental variables. These advancements represent an important improvement in our ability to draw community-level inference from multiple interacting species that are subject to imperfect detection.

Do occupancy or detection rates from camera traps reflect deer density

Camera trapping is a powerful tool for studying mammal populations over large spatial scales. Density estimation using camera-trap data is a commonly desired outcome, but most approaches only work for species that can be individually recognized, and researchers studying most mammals are typically constrained to measures of site occupancy or detection rate. These 2 metrics are often used as measures of relative abundance and presumed to be related directly to animal density. To test this relationship, we estimated density, occupancy, and detection rate of male white-tailed deer (Odocoileus virginianus) using camera-trap data collected from 1,199 cameras across 20 study sites. Detection rate and density exhibited stronger positive linear correlation (r2 = 0.80) than occupancy and density (r2 = 0.27). When hunted and unhunted paired areas were compared, detection rate and density showed the same trend between paired sites 62.5% of the time compared to 87.5% for occupancy and density. In particular, agreement between estimates was lowest for pairs of sites that had the largest differences in surrounding housing density. Although it is clear occupancy and detection rate contain some information about density, models suggested different ecological relationships associated with the metrics. Using occupancy or detection rate as proxies for density may be particularly problematic when comparing between areas where animals might to move or behave differently, such as urban–wild interfaces. In such cases, alternate methods of density approximation are recommended.

Demographics, diet, movements, and survival of an isolated, unmanaged raccoon Procyon lotor (Procyonidae, Carnivora) population on the Outer Banks of North Carolina

Abstract Raccoons (Procyon lotor) are highly adaptable meso-carnivores that inhabit many environments, including the Atlantic barrier islands, where their role as predators of declining, beach-nesting bird and turtle species is of particular interest. Population models that improve our understanding of predator-prey dynamics are receiving increasing attention in the literature; however, their effective application requires site-specific information on population parameters. We studied an unharvested raccoon population on the Outer Banks of North Carolina and evaluated spatial and seasonal differences in a number of population/demographic factors of raccoons inhabiting areas of high and low human activity. Raccoons denned and foraged primarily in salt marsh habitats but shifted their movements in response to changes in seasonal resource conditions. The population was skewed toward older animals and exhibited delayed breeding, typical of populations at high density with few sources of mortality. Diet and movement analysis indicated shorebird and turtle predation was attributed to a small number of individual raccoons. Although seasonal resources appeared adequate to sustain a high population density of raccoons, poor body condition and low recruitment suggested a population near carrying capacity.

Mammal communities are larger and more diverse in moderately developed areas

Developed areas are thought to have low species diversity, low animal abundance, few native predators, and thus low resilience and ecological function. Working with citizen scientist volunteers to survey mammals at 1427 sites across two development gradients (wild-rural-exurban-suburban-urban) and four plot types (large forests, small forest fragments, open areas and residential yards) in the eastern US, we show that developed areas actually had significantly higher or statistically similar mammalian occupancy, relative abundance, richness and diversity compared to wild areas. However, although some animals can thrive in suburbia, conservation of wild areas and preservation of green space within cities are needed to protect sensitive species and to give all species the chance to adapt and persist in the Anthropocene.

The value of citizen science for ecological monitoring of mammals

Citizen science approaches are of great interest for their potential to efficiently and sustainably monitor wildlife populations on both public and private lands. Here we present two studies that worked with volunteers to set camera traps for ecological surveys. The photographs recorded by these citizen scientists were archived and verified using the eMammal software platform, providing a professional grade, vouchered database of biodiversity records. Motivated by managers’ concern with perceived high bear activity, our first example enlisted the help of homeowners in a short-term study to compare black bear activity inside a National Historic Site with surrounding private land. We found similar levels of bear activity inside and outside the NHS, and regional comparisons suggest the bear population is typical. Participants benefited from knowing their local bear population was normal and managers refocused bear management given this new information. Our second example is a continuous survey of wildlife using the grounds of a nature education center that actively manages habitat to maintain a grassland prairie. Center staff incorporated the camera traps into educational programs, involving visitors with camera setup and picture review. Over two years and 5,968 camera-nights this survey has collected 41,393 detections of 14 wildlife species. Detection rates and occupancy were higher in open habitats compared to forest, suggesting that the maintenance of prairie habitat is beneficial to some species. Over 500 volunteers of all ages participated in this project over two years. Some of the greatest benefits have been to high school students, exemplified by a student with autism who increased his communication and comfort level with others through field work with the cameras. These examples show how, with the right tools, training and survey design protocols, citizen science can be used to answer a variety of applied management questions while connecting participants with their secretive mammal neighbors.

Managing Native Predators: Evidence from a Partial Removal of Raccoons (Procyon lotor) on the Outer Banks of North Carolina, USA

Abstract. 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.