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Exploring spatial nonstationarity for four mammal species reveals regional variation in environmental relationships

What drives spatially varying ecological relationships in a wide-ranging species?

Decades of research on species distributions has revealed geographic variation in species-environment relationships for a given species. That is, the way a species uses the local environment varies across geographic space. However, the drivers underlying this variation are contested and still largely unexplored. Niche traits that are conserved should reflect the evolutionary history of a species whereas more flexible ecological traits could vary at finer scales, reflecting local adaptation. We used mammal observations during a 5-year period from the iNaturalist biodiversity database and a local ensemble modelling approach to explore spatial variation in American black bear (Ursus americanus) relationships with eight ecological correlates. We tested four biologically driven hypotheses to explain the patterns of local adaptation. We evaluated non-stationarity in ecological relationships using a Stationarity Index and tested predictive performance using an independent, national-level animal occurrence data set.

Evaluation of the Spatial Biases and Sample Size of a Statewide Citizen Science Project

Although quality control for accuracy is increasingly common in citizen science projects, there is still a risk that spatial biases of opportunistic data could affect results, especially if sample size is low. Here we evaluate how well the sampling locations of North Carolina Candid Critters citizen science camera trapping project represented available land cover types in the state and whether the sample size was sufficient to estimate ecological parameters with low bias and error.

Is it an omnivore's world? A comment on dietary traits in multispecies hierarchical models

Measuring the value of public hunting land using a hedonic approach

Acquisition of public land is critical for wildlife conservation and can impact local tax bases and property values. Those impacts reflect the capitalized value of benefits (e.g., recreational opportunities) and costs (e.g., nuisance wildlife) of living near protected areas. We employed the hedonic price framework to determine how proximity and adjacency to public hunting land in North Carolina were capitalized into housing prices. We modeled sale price as the composite value of structural, neighborhood, and environmental characteristics. Proximity to public hunting land had positive effects on sale price in some locations, whereas adjacency had negative effects in some locations. These relationships were dependent on the sociocultural context of the public hunting land, including proximity to other forms of public land. This research may help facilitate negotiations among stakeholders impacted by protected areas, including land dedicated to wildlife-based recreation.

Integrating harvest and camera trap data in species distribution models

Wildlife managers need reliable information on species distributions (i.e. patterns of occurrence and abundance) to make effective decisions. Historically, managers have relied on harvest records (collected at broad spatial extents but coarse resolution) to monitor wildlife populations. However, emerging citizen-science datastreams can potentially supplement harvest-based monitoring by providing fine-resolution data that permit identification of species-environment relationships needed to predict occurrence and abundance. We combined harvest records and citizen-science camera-trap data in integrated species distribution models (iSDMs) to estimate species-environment relationships and distribution patterns of six wildlife species in Wisconsin, USA.

Survey design optimization for monitoring wildlife communities in areas managed for federally endangered species

Camera traps deployed in grids or stratified random designs are a well‐established survey tool for wildlife but there has been little evaluation of study design parameters. We used an empirical subsampling approach involving 2,225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design and their influence on the estimation of three ecological metrics for mammals.

Candid Critters: Challenges and Solutions in a Large-Scale Citizen Science Camera Trap Project

Citizen science projects that use camera traps to collect data can collect large-scale data without compromising information quality. However, project management challenges are increased when data collection is scaled up. Here, we provide an overview of our efforts to conduct a large-scale citizen science project using camera traps — North Carolina’s Candid Critters.

An empirical evaluation of camera trap study design: How many, how long and when?

Camera traps deployed in grids or stratified random designs are a well‐established survey tool for wildlife but there has been little evaluation of study design parameters. We used an empirical subsampling approach involving 2,225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design and their influence on the estimation of three ecological metrics for mammals.

Influence of Forest Structure and Composition on Summer Habitat Use of Wildlife in an Upland Hardwood Forest

Oak-hickory (Quercus-Carya spp.) forest types are widespread across the midwestern United States, but changes in forest disturbance regimes are resulting in little to no oak recruitment and a compositional shift to shade-tolerant, mesophytic species, such as American beech (Fagus grandifolia) and sugar maple (Acer saccharum). We conducted camera trap surveys in a mature upland hardwood forest of southern Illinois, USA during May to August 2015–2016 to document mammal summer habitat use in relation to forest structure and composition to further understand how regional shifts in forests may affect mammal communities.