@article{pease_pacifici_kays_2022, title={Exploring spatial nonstationarity for four mammal species reveals regional variation in environmental relationships}, volume={13}, ISSN={["2150-8925"]}, url={https://doi.org/10.1002/ecs2.4166}, DOI={10.1002/ecs2.4166}, abstractNote={AbstractBroad‐scale ecological research on species distributions commonly presumes that the correlative relationships discovered are stationary over space. This is an assumption of most species distribution models (SDMs) that combine observations of species occurrence with environmental characteristics to understand current ecological correlates and to predict distributions based on those relationships. However, ecological relationships may vary spatially because of changes in the environment (i.e., resource availability) or the organism itself (i.e., local adaptation). Discovering this within‐species variation typically requires dense datasets over large geographic areas, which are now being provided by the recent proliferation of open‐access biodiversity occurrence records. Using nearly 4000 sampling locations from an open‐access, state‐wide camera‐trapping project, we explore the space‐varying effects of covariates on the distribution of four mammal species at two scales: region‐specific and fine resolution, with the latter estimated using spatially varying coefficients (SVC) models, to understand the scale of spatial variation in ecological relationships. Among the four species tested, the ecological relationships for two were best explained with the regional models, equivocal results for one species, while the SVC model had superior fit and predictive performance for the final species (white‐tailed deer, Odocoileus virginianus). Spatial nonstationarity was more common in relationships with landscape composition characteristics, such as housing density, than in landscape configuration metrics, such as patch richness density. One of the most appealing results of an SVC approach is not only the improved predictions across large landscapes but also understanding how animals are responding to the environment differently at the management unit level. For example, we found that deer's spatially varying relationship with forest cover was best explained by an interactive effect of deer management units (i.e., differences in deer populations) and predator pressure. These findings lead to a new hypothesis about how deer may be differentially using forested environments across space and could be a promising area of future research. Given sufficient data, accounting for nonstationarity in SDMs can show large‐scale ecological patterns while also detecting local level changes in animal ecology in areas small enough that management or protection can be readily implemented.}, number={8}, journal={ECOSPHERE}, publisher={Wiley}, author={Pease, Brent S. and Pacifici, Krishna and Kays, Roland}, year={2022}, month={Aug} }
 @article{pease_pacifici_kays_reich_2022, title={What drives spatially varying ecological relationships in a wide-ranging species?}, volume={7}, ISSN={["1472-4642"]}, url={https://doi.org/10.1111/ddi.13594}, DOI={10.1111/ddi.13594}, abstractNote={AbstractAimDecades 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.LocationNorth America.MethodsWe 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.ResultsWe documented considerable spatial non‐stationarity in all eight environmental relationships, with the greatest spatial variation occurring in bear's relationship to climatic factors. Notably, the greatest variation in environmental relationships tended to occur along the current boundaries of the species' range, potentially representing the ecological limits to the species geographic range. We additionally documented that spatial variation in relationships with land cover and anthropogenic factors were best explained by niche conservatism at the subspecies level, whereas climatic relationships were better explained by local adaptation.Main ConclusionsBased on these results, we propose that the current distribution of American black bear is determined by an evolutionary legacy of habitat relationships unique to each subspecies combined with more fine‐scale local adaptation to climatic conditions. This result suggests that black bears should be adaptable to climatic changes over the 21st century and that management of habitat and human‐bear relationships could be considered at the subspecies level.}, journal={DIVERSITY AND DISTRIBUTIONS}, publisher={Wiley}, author={Pease, Brent S. and Pacifici, Krishna and Kays, Roland and Reich, Brian}, year={2022}, month={Jul} }
 @article{gilbert_pease_anhalt-depies_clare_stenglein_townsend_van deelen_zuckerberg_2021, title={Integrating harvest and camera trap data in species distribution models}, volume={258}, ISSN={["1873-2917"]}, DOI={10.1016/j.biocon.2021.109147}, abstractNote={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. We expected that iSDMs would more precisely estimate species-environment relationships and predict spatial abundance patterns intermediate between camera- and harvest-only SDMs. We also conducted simulations to explore the consequences of incomplete knowledge of harvest effort for estimates of abundance and species-environment relationships. Integrated models produced more precise species-environment relationships than camera-only models in 53% of the relationships we tested; all harvest-only models failed to converge. Moreover, integrated and camera-only models showed low agreement (mean: 19.67%) in identifying abundance “hotspots” but considerably higher agreement (mean: 45.17%) in identifying abundance “cold spots”. Our simulations showed that abundance patterns estimated by iSDMs may suffer from imprecision if harvest effort is poorly measured. We recommend that harvest records be collected at finer spatial resolutions and be paired with in-depth effort reporting. Our work demonstrates the potential for integrating an existing datastream (harvest records) with an emerging one (citizen-science camera-trap monitoring) for modeling species distributions and providing support for wildlife management decisions.}, journal={BIOLOGICAL CONSERVATION}, author={Gilbert, Neil A. and Pease, Brent S. and Anhalt-Depies, Christine M. and Clare, John D. J. and Stenglein, Jennifer L. and Townsend, Philip A. and Van Deelen, Timothy R. and Zuckerberg, Benjamin}, year={2021}, month={Jun} }
 @article{casola_peterson_wu_sills_pease_pacifici_2021, title={Measuring the value of public hunting land using a hedonic approach}, volume={8}, ISSN={["1533-158X"]}, DOI={10.1080/10871209.2021.1953196}, abstractNote={ABSTRACT 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.}, journal={HUMAN DIMENSIONS OF WILDLIFE}, author={Casola, William R. and Peterson, M. Nils and Wu, Yu and Sills, Erin O. and Pease, Brent S. and Pacifici, Krishna}, year={2021}, month={Aug} }
 @article{pease_pacifici_collazo_2021, title={Survey design optimization for monitoring wildlife communities in areas managed for federally endangered species}, volume={24}, ISSN={["1469-1795"]}, DOI={10.1111/acv.12681}, abstractNote={AbstractIn wildlife communities composed of federally endangered species, there are often several species of conservation concern that have not yet warranted federally mandated protection. These species often need continued monitoring to inform the direction of future management. While recovering endangered species is an important conservation goal, practitioners are challenged by balancing federally mandated protocols with actions that promote non‐listed priority species. Practitioners need an understanding of how focused, single‐species management actions may affect non‐listed priority species, but developing a monitoring protocol that can detect such effects with limited resources is a challenge. Here we use constrained optimization as a path to identifying a sampling scheme that overcomes these logistical challenges and then illustrate its potential in the Sandhills region of North Carolina, USA. Using empirical results from multi‐year avian community monitoring, we parameterized simulations to understand how varying the number of sampling locations and site visits affected the optimal monitoring protocol across three different avian community composition scenarios: a community with (1) 10 percent, (2) 25 percent, or (3) 50 percent non‐listed priority species. We found the greatest rate of change in precision of community‐level metrics, such as species richness, by increasing sampling replicates when surveying up to 50 sites. Importantly, this trend was apparent across all three community scenarios, indicating relatively predictable changes in uncertainty regardless of community composition. In contrast, increasing the sampling frequency did not consistently reduce uncertainty in species‐level parameters such as occupancy probability. Concerningly, we saw the greatest variation when communities were comprised of 50 percent non‐listed species suggesting increasingly complex monitoring protocols may be required if the number of non‐listed priority species continues to increase. Practitioners could consider reducing detection error of priority species through increasing sampling frequency, as this can strongly affect optimization study designs.}, number={5}, journal={ANIMAL CONSERVATION}, author={Pease, B. S. and Pacifici, K. and Collazo, J. A.}, year={2021}, month={Oct}, pages={756–769} }
 @article{kays_arbogast_baker‐whatton_beirne_boone_bowler_burneo_cove_ding_espinosa_et al._2020, title={An empirical evaluation of camera trap study design: How many, how long and when?}, volume={11}, ISSN={2041-210X 2041-210X}, url={http://dx.doi.org/10.1111/2041-210X.13370}, DOI={10.1111/2041-210X.13370}, abstractNote={Abstract


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 (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy and detection rate) for mammals.

We found that 25–35 camera sites were needed for precise estimates of species richness, depending on scale of the study. The precision of species‐level estimates of occupancy (ψ) was highly sensitive to occupancy level, with <20 camera sites needed for precise estimates of common (ψ > 0.75) species, but more than 150 camera sites likely needed for rare (ψ < 0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted habitat variability factors within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3–4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37%–50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4–5, and some species were completely absent in one season due to hibernation or migration.

We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3–5 weeks across 40–60 sites per array. We recommend comparisons of detection rates be model based and include local covariates to help account for small‐scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which could have strong impacts on mammal communities in both tropical and temperate sites.

}, number={6}, journal={Methods in Ecology and Evolution}, publisher={Wiley}, author={Kays, Roland and Arbogast, Brian S. and Baker‐Whatton, Megan and Beirne, Chris and Boone, Hailey M. and Bowler, Mark and Burneo, Santiago F. and Cove, Michael V. and Ding, Ping and Espinosa, Santiago and et al.}, editor={Fisher, DianaEditor}, year={2020}, month={Apr}, pages={700–713} }
 @article{larue_nielsen_pease_2019, title={Increases in Midwestern cougars despite harvest in a source population}, volume={83}, ISSN={["1937-2817"]}, DOI={10.1002/jwmg.21693}, abstractNote={ABSTRACTAlthough cougars (Puma concolor) appear to be recolonizing the midwestern United States, there is concern that hunting in source populations (primarily the Black Hills, SD and WY, USA) may prevent cougars from dispersing eastward. We use carcass data of cougars (n =147 carcasses at known locations, of which 111 were of known sex) in the Midwest collected during 1990–2015 to quantify whether cougar hunting in the Black Hills affected cougar distribution and presence in the Midwest. We separated carcass data into 2 time periods: before hunting in the Black Hills (i.e., pre‐hunt; 1990–2004) and after hunting (i.e., post‐hunt; 2005–2015). We hypothesized that if hunting prevented dispersal into the Midwest, cougar distribution would be random and their presence less, relative to the pre‐hunt period. We also were interested in sex ratios of carcasses over time, given the importance of that demographic metric to the potential establishment of viable populations. During the pre‐hunt period, 25 carcasses were dispersed randomly in the Midwest. During the post‐hunt period, we found nearly 4 times the number of carcasses in the Midwest (n = 86), carcasses were significantly clustered, and a greater percentage of carcasses were female (pre‐hunt n = 6 [24%]; post‐hunt n = 27 [31%]). Relative to the pre‐hunt period, we observed a 460‐km northward shift in the directional distribution of carcass locations during the post‐hunt period. These findings do not support the idea that hunting in the Black Hills has prevented cougar presence from increasing in the Midwest. Alternatively, we suggest the potential for immigration from cougar populations farther to the west as an explanation for the increase in cougar presence (particularly females) confirmed after the initiation of cougar hunting in the Black Hills. © 2019 The Wildlife Society.}, number={6}, journal={JOURNAL OF WILDLIFE MANAGEMENT}, author={Larue, Michelle A. and Nielsen, Clayton K. and Pease, Brent S.}, year={2019}, month={Aug}, pages={1306–1313} }
 @article{pease_holzmueller_nielsen_2019, title={Influence of Forest Structure and Composition on Summer Habitat Use of Wildlife in an Upland Hardwood Forest}, volume={11}, ISSN={["1424-2818"]}, DOI={10.3390/d11090160}, abstractNote={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. With nearly 4000 camera days of effort, we modeled occupancy patterns for white-tailed deer (Odocoileus virginianus), raccoon (Procyon lotor), and eastern gray squirrel (Sciurus canadensis). Forest composition models outcompeted forest structure models for white-tailed deer, where we observed a statistically significant negative relationship between white-tailed deer habitat use and beech dominance. Further, we found a strong, positive association between deer and oak dominance. Model selection indicated little support for within-stand forest structure or composition characteristics influencing habitat use for raccoons. Eastern gray squirrel occurrence was best described by forest composition, revealing a positive relationship with beech–maple importance values. Our predictive models indicated that the impact of forest changes underway will have varying impacts on wildlife species. We can expect changes in habitat use patterns to be more pronounced with time barring revised forest management practices, and these changes are likely to be most influential at the landscape-scale. We conclude that a patchwork mosaic of forest conditions will likely best support a diverse and abundant mammal community across the region. }, number={9}, journal={DIVERSITY-BASEL}, author={Pease, Brent S. and Holzmueller, Eric J. and Nielsen, Clayton K.}, year={2019}, month={Sep} }