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Reliable maps of species distributions are fundamental for biodiversity research and conservation. The International Union for Conservation of Nature (IUCN) range maps are widely recognized as authoritative representations of species' geographic limits, yet they might not always align with actual occurrence data. In recent area of habitat (AOH) maps, areas that are not habitat have been removed from IUCN ranges to reduce commission errors, but their concordance with actual species occurrence also remains untested. We tested concordance between occurrences recorded in camera trap surveys and predicted occurrences from the IUCN and AOH maps for 510 medium- to large-bodied mammalian species in 80 camera trap sampling areas. Across all areas, cameras detected only 39% of species expected to occur based on IUCN ranges and AOH maps; 85% of the IUCN only mismatches occurred within 200 km of range edges. Only 4% of species occurrences were detected by cameras outside IUCN ranges. The probability of mismatches between cameras and the IUCN range was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya and in areas with shorter canopy forests. Our findings suggest that range and AOH maps rarely underrepresent areas where species occur, but they may more often overrepresent ranges by including areas where a species may be absent, particularly at range edges. We suggest that combining range maps with data from ground-based biodiversity sensors, such as camera traps, provides a richer knowledge base for conservation mapping and planning., (© 2024 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human-wildlife interactions along gradients of human influence., (© 2024. The Author(s).)

Addressing the ongoing biodiversity crisis requires identifying the winners and losers of global change. Species are often categorized based on how they respond to habitat loss; for example, species restricted to natural environments, those that most often occur in anthropogenic habitats, and generalists that do well in both. However, species might switch habitat affiliations across time and space: an organism may venture into human-modified areas in benign regions but retreat into thermally buffered forested habitats in areas with high temperatures. Here, we apply community occupancy models to a large-scale camera trapping dataset with 29 mammal species distributed over 2,485 sites across the continental United States, to ask three questions. First, are species' responses to forest and anthropogenic habitats consistent across continental scales? Second, do macroclimatic conditions explain spatial variation in species responses to land use? Third, can species traits elucidate which taxa are most likely to show climate-dependent habitat associations? We found that all species exhibited significant spatial variation in how they respond to land-use, tending to avoid anthropogenic areas and increasingly use forests in hotter regions. In the hottest regions, species occupancy was 50% higher in forested compared to open habitats, whereas in the coldest regions, the trend reversed. Larger species with larger ranges, herbivores, and primary predators were more likely to change their habitat affiliations than top predators, which consistently affiliated with high forest cover. Our findings suggest that climatic conditions influence species' space-use and that maintaining forest cover can help protect mammals from warming climates., Competing Interests: Competing interests statement:The authors declare no competing interest.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August-24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication., (© 2021 The Authors. Ecology © 2021 The Ecological Society of America.)

Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum., (© 2020 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

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., Competing Interests: AP, TF, MB, WM, CR, SS, JM, RK No competing interests declared, (© 2018, Parsons et al.)

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission., (Copyright © 2018, The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Aim: Synthesize literature on genetic structure within species to understand how geographic features and species traits influence past responses to climate change. Location: North America. Time Period: We synthesized phylogeographic studies from 1978 to 2023, which describe genetic lineages that diverged during the Pleistocene (≥11,700 years ago). Major Taxa Studied: Mammals. Methods: We conducted a literature review to map genetic breaks in species distributions, then tested a set of geographic hypotheses (e.g., mountains, rivers) to explain their position by comparing break locations to a grid within each species' sampled range using logistic regression. We then conducted a meta‐analysis using species‐specific model estimates to ask if life‐history traits explained variation in which barriers were most important in species' past response to climate change. Results: Our findings reveal heterogeneity in both where North American mammal phylogeography has been studied and the density of genetic breaks across 229 species. We found relatively high concordance among carnivores, ungulates and lagomorphs, where breaks were associated with mountains, major water bodies and relatively even terrain. In contrast, we found high variability within rodents and shrews, and no evidence that intrinsic factors related to dispersal ability explained the importance of hypothesized barriers across all species. Main Conclusions: Southern Mexico is a hotspot for genetic breaks that has yet to be integrated into the broader story of North American phylogeography. We show that mountains and major water bodies play particularly important roles as barriers, but substantial variation across species within orders suggests that there is more to the story besides shared climatic or phylogenetic histories. Thus, understanding the phylogeography of individual species will continue to be important given that our results suggest high variability in how species may respond to future global change. [ABSTRACT FROM AUTHOR]

SNAPSHOT USA is a multicontributor, long‐term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22–5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. [ABSTRACT FROM AUTHOR]

A leading hypothesis for the evolution of large brains in humans and other species is that a feedback loop exists whereby intelligent animals forage more efficiently, which results in increased energy intake that fuels the growth and maintenance of large brains. We test this hypothesis for the first time with high-resolution tracking data from four sympatric, frugivorous rainforest mammal species (42 individuals) and drone-based maps of their predominant feeding trees. We found no evidence that larger-brained primates had more efficient foraging paths than smaller brained procyonids. This refutes a key assumption of the fruit-diet hypothesis for brain evolution, suggesting that other factors such as temporal cognition, extractive foraging or sociality have been more important for brain evolution. [ABSTRACT FROM AUTHOR]

Small mammals are important to the functioning of ecological communities with changes to their abundances used to track impacts of environmental change. While capture–recapture estimates of absolute abundance are preferred, indices of abundance continue to be used in cases of limited sampling, rare species with little data, or unmarked individuals. Improvement to indices can be achieved by calibrating them to absolute abundance but their reliability across years, sites, or species is unclear. To evaluate this, we used the US National Ecological Observatory Network capture–recapture data for 63 small mammal species over 46 sites from 2013 to 2019. We generated 17,155 absolute abundance estimates using capture–recapture analyses and compared these to two standard abundance indices, and three types of calibrated indices. We found that neither raw abundance indices nor index calibrations were reliable approximations of absolute abundance, with raw indices less correlated with absolute abundance than index calibrations (raw indices overall R 2 < 0.5, index calibration overall R 2 > 0.6). Performance of indices and index calibrations varied by species, with those having higher and less variable capture probabilities performing best. We conclude that indices and index calibration methods should be used with caution with a count of individuals being the best index to use, especially if it can be calibrated with capture probability. None of the indices we tested should be used for comparing different species due to high variation in capture probabilities. Hierarchical models that allow for sharing of capture probabilities over species or plots (i.e. joint-likelihood models) may offer a better solution to mitigate the cost and effort of large-scale small mammal sampling while still providing robust estimates of abundance. [ABSTRACT FROM AUTHOR]

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap‐nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID‐19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site‐level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication. [ABSTRACT FROM AUTHOR]

While museum voucher specimens continue to be the standard for species identifications, biodiversity data are increasingly represented by photographic records from camera traps and amateur naturalists. Some species are easily recognized in these pictures, others are impossible to distinguish. Here we quantify the extent to which 335 terrestrial nonvolant North American mammals can be identified in typical photographs, with and without considering species range maps. We evaluated all pairwise comparisons of species and judged, based on professional opinion, whether they are visually distinguishable in typical pictures from camera traps or the iNaturalist crowdsourced platform on a 4-point scale: (1) always, (2) usually, (3) rarely, or (4) never. Most (96.5%) of the 55,944 pairwise comparisons were ranked as always or usually distinguishable in a photograph, leaving exactly 2,000 pairs of species that can rarely or never be distinguished from typical pictures, primarily within clades such as shrews and small-bodied rodents. Accounting for a species geographic range eliminates many problematic comparisons, such that the average number of difficult or impossible-to-distinguish species pairs from any location was 7.3 when considering all species, or 0.37 when considering only those typically surveyed with camera traps. The greatest diversity of difficult-to-distinguish species was in Arizona and New Mexico, with 57 difficult pairs of species, suggesting the problem scales with overall species diversity. Our results show which species are most readily differentiated by photographic data and which taxa should be identified only to higher taxonomic levels (e.g., genus). Our results are relevant to ecologists, as well as those using artificial intelligence to identify species in photographs, but also serve as a reminder that continued study of mammals through museum vouchers is critical since it is the only way to accurately identify many smaller species, provides a wealth of data unattainable from photographs, and constrains photographic records via accurate range maps. Ongoing specimen voucher collection, in addition to photographs, will become even more important as species ranges change, and photographic evidence alone will not be sufficient to document these dynamics for many species. [ABSTRACT FROM AUTHOR]

Broad‐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. [ABSTRACT FROM AUTHOR]

Human activity and land use change impact every landscape on Earth, driving declines in many animal species while benefiting others. Species ecological and life history traits may predict success in human‐dominated landscapes such that only species with "winning" combinations of traits will persist in disturbed environments. However, this link between species traits and successful coexistence with humans remains obscured by the complexity of anthropogenic disturbances and variability among study systems. We compiled detection data for 24 mammal species from 61 populations across North America to quantify the effects of (1) the direct presence of people and (2) the human footprint (landscape modification) on mammal occurrence and activity levels. Thirty‐three percent of mammal species exhibited a net negative response (i.e., reduced occurrence or activity) to increasing human presence and/or footprint across populations, whereas 58% of species were positively associated with increasing disturbance. However, apparent benefits of human presence and footprint tended to decrease or disappear at higher disturbance levels, indicative of thresholds in mammal species' capacity to tolerate disturbance or exploit human‐dominated landscapes. Species ecological and life history traits were strong predictors of their responses to human footprint, with increasing footprint favoring smaller, less carnivorous, faster‐reproducing species. The positive and negative effects of human presence were distributed more randomly with respect to species trait values, with apparent winners and losers across a range of body sizes and dietary guilds. Differential responses by some species to human presence and human footprint highlight the importance of considering these two forms of human disturbance separately when estimating anthropogenic impacts on wildlife. Our approach provides insights into the complex mechanisms through which human activities shape mammal communities globally, revealing the drivers of the loss of larger predators in human‐modified landscapes. [ABSTRACT FROM AUTHOR]

Background: Camera traps present a valuable tool for monitoring animals but detect species imperfectly. Occupancy models are frequently used to address this, but it is unclear what spatial scale the data represent. Although individual cameras monitor animal activity within a small target window in front of the device, many practitioners use these data to infer animal presence over larger, vaguely-defined areas. Animal movement is generally presumed to link these scales, but fine-scale heterogeneity in animal space use could disrupt this relationship. Methods: We deployed cameras at 10 m intervals across a 0.6 ha forest plot to create an unprecedentedly dense sensor array that allows us to compare animal detections at these two scales. Using time-stamped camera detections we reconstructed fine-scale movement paths of four mammal species and characterized (a) how well animal use of a single camera represented use of the surrounding plot, (b) how well cameras detected animals, and (c) how these processes affected overall detection probability, p. We used these observations to parameterize simulations that test the performance of occupancy models in realistic scenarios. Results: We document two important aspects of animal movement and how it affects sampling with passive detectors. First, animal space use is heterogeneous at the camera-trap scale, and data from a single camera may poorly represent activity in its surroundings. Second, cameras frequently (14–71%) fail to record passing animals. Our simulations show how this heterogeneity can introduce unmodeled variation into detection probability, biasing occupancy estimates for species with low p. Conclusions: Occupancy or population estimates with camera traps could be improved by increasing camera reliability to reduce missed detections, adding covariates to model heterogeneity in p, or increasing the area sampled by each camera through different sampling designs or technologies. [ABSTRACT FROM AUTHOR]

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Citizen science has been touted as an effective means to collect large-scale data while engaging the public. We demonstrate that children as young as 9 years old can collect valuable mammal monitoring data using camera traps while connecting with nature and learning through their own scientific discoveries. Indian, Kenyan, Mexican, and American students used camera traps near their schools and detected 13–37 species, all of which were verified by professionals. These data describe rich mammal faunas near schools, sometimes surpassing nearby protected areas, and included five endangered species. Ninety-four percent of the camera traps were set in accordance with scientific protocols, and the teachers reported the experience as highly engaging for their students. Furthermore, the generated photos and results had community-wide impacts involving local politicians, community members, and the media. We show that children can run sensors to contribute valid scientific data important for conservation and research. [ABSTRACT FROM AUTHOR]

Managed public wild areas have dual mandates to protect biodiversity and provide recreational opportunities for people. These goals could be at odds if recreation, ranging from hiking to legal hunting, disrupts wildlife enough to alter their space use or community structure., We evaluated the effect of managed hunting and recreation on 12 terrestrial wildlife species by employing a large citizen science camera trapping survey at 1947 sites stratified across different levels of human activities in 32 protected forests in the eastern USA., Habitat covariates, especially the amount of large continuous forest and local housing density, were more important than recreation for affecting the distribution of most species. The four most hunted species (white-tailed deer, raccoons, eastern grey and fox squirrels) were commonly detected throughout the region, but relatively less so at hunted sites. Recreation was most important for affecting the distribution of coyotes, which used hunted areas more compared with unhunted control areas, and did not avoid areas used by hikers., Most species did not avoid human-made trails, and many predators positively selected them. Bears and bobcats were more likely to avoid people in hunted areas than unhunted preserves, suggesting that they perceive the risk of humans differently depending on local hunting regulations. However, this effect was not found for the most heavily hunted species, suggesting that human hunters are not broadly creating 'fear' effects to the wildlife community as would be expected for apex predators., Synthesis and applications. Although we found that hiking and managed hunting have measureable effects on the distribution of some species, these were relatively minor in comparison with the importance of habitat covariates associated with land use and habitat fragmentation. These patterns of wildlife distribution suggest that the present practices for regulating recreation in the region are sustainable and in balance with the goal of protecting wildlife populations and may be facilitated by decades of animal habituation to humans. The citizen science monitoring approach we developed could offer a long-term monitoring protocol for protected areas, which would help managers to detect where and when the balance between recreation and wildlife has tipped. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Hybrid zones typically contain novel gene combinations that can be tested by natural selection in a unique genetic context. Parental haplotypes that increase fitness can introgress beyond the hybrid zone, into the range of parental species. We used the Affymetrix canine SNP genotyping array to identify genomic regions tagged by multiple ancestry informative markers that are more frequent in an admixed population than expected. We surveyed a hybrid zone formed in the last 100 years as coyotes expanded their range into eastern North America. Concomitant with expansion, coyotes hybridized with wolves and some populations became more wolflike, such that coyotes in the northeast have the largest body size of any coyote population. Using a set of 3102 ancestry informative markers, we identified 60 differentially introgressed regions in 44 canines across this admixture zone. These regions are characterized by an excess of exogenous ancestry and, in northeastern coyotes, are enriched for genes affecting body size and skeletal proportions. Further, introgressed wolf-derived alleles have penetrated into Southern US coyote populations. Because no wolves currently exist in this area, these alleles are unlikely to have originated from recent hybridization. Instead, they probably originated from intraspecific gene flow or ancient admixture. We show that grey wolf and coyote admixture has far-reaching effects and, in addition to phenotypically transforming admixed populations, allows for the differential movement of alleles from different parental species to be tested in new genomic backgrounds. [ABSTRACT FROM AUTHOR]

Understanding causes of mortality in a population provides information about the selection pressures acting on individuals in that population. To obtain unbiased estimates of mortality, researchers must track individual animals until they die, retrieve dead animals, and make a forensic estimation to determine the cause. Given the limitations of traditional radio-tracking technology and the biases inherent in other methods of estimating mortality causes, little is known about causes of mortality in small mammals (<1 kg). Here we used an automated radio telemetry system to record activity patterns and detect mortality events in a wild population of Peromyscus leucopus (White-footed Mouse). Mice (n = 32) were fitted with small (1 g) radio-collars. Daily survival rate was 0.98 ± 0.01, which translates to a 50% chance of survival over a 29-day period. Although the species is well known as a vector for various diseases, we found only one death attributable to disease. Most mouse mortality (93%) was caused by predators, primarily Mustela spp. (weasels ). We found a significant relationship between Borrelia infection (the bacterium that causes Lyme disease in humans), and increased mortality (χ²= 6.92, df = 1,P = 0.008); there was no detectable effect of sex on survival. Our results suggest that, to the extent that predation risk is dependent on heritable phenotypes, predation risk is the most important evolutionary force acting on mortality in the population we studied. [ABSTRACT FROM AUTHOR]

1. The distance travelled by animals is an important ecological variable that links behaviour, energetics and demography. It is usually measured by summing straight-line distances between intermittently sampled locations along continuous animal movement paths. The extent to which this approach underestimates travel distance remains a rarely addressed and unsolved problem, largely because true movement paths are rarely, if ever, available for comparison. Here, we use simulated movement paths parameterized with empirical movement data to study how estimates of distance travelled are affected by sampling frequency. 2. We used a novel method to obtain fine-scale characteristics of animal movement from camera trap videos for a set of tropical forest mammals and used these characteristics to generate detailed movement paths. We then sampled these paths at different frequencies, simulating telemetry studies, and quantified the accuracy of sampled travel distance estimation. 3. For our focal species, typical telemetry studies would underestimate distances travelled by 67-93%, and extremely high sampling frequencies (several fixes per minute) would be required to get tolerably accurate estimates. The form of the relationship between tortuosity, sample frequency, and distance travelled was such that absolute distance cannot accurately be estimated by the infrequent samples used in typical tracking studies. 4. We conclude that the underestimation of distance travelled is a serious but underappreciated problem. Currently, there is no reliable, widely applicable method to obtain approximately unbiased estimates of distance travelled by animals. Further research on this problem is needed. [ABSTRACT FROM AUTHOR]

Carnivores are difficult to survey due, in large pert, to their relative rarity across the landscape and wariness toward humans. Several noninvasive methods may aid in overcoming these difficulties, but there has been little discussion of the relative merits and biases of these techniques. We assess the value of 5 noninvasive techniques based on results from 2 multiyear studies of carnivores (including members of Carnivora and Didelphidae) in New York forests. Two metrics were particularly valuable in assessing the species-specific value of any particular survey technique: latency to initial detection (LTD) and probability of detection (POD). We found differences in the value of techniques in detecting different species. For midsized species (raccoon [Procyon lotor], fisher [Martes pennanti], opossum [Didelphis virginiana], and domestic cat [Felis catus]), camera traps and track-plates were approximately equivalent in detection efficiency, but the potential for wariness toward the survey apparatus resulted in higher LTD for track-plates than for cameras. On the other hand, track-plates detected small carnivores (marten [M. americana] and weasels [Mustela spp.]) more often than cameras and had higher PODs for small and midsized species than did cameras. Cameras were efficient mechanisms for surveying bears (Ursus americanus; low LTD, high POD) but functioned poorly for discerning presence of coyotes (Canis latrans; high LTD, low POD). Scat surveys and snowtracking were the best methods for coyotes, which avoided camera traps and artificial tracking surfaces. Our analysis of fecal DNA revealed that trail-based fecal surveys were inefficient at detecting species other than coyotes, with the possible exception of red foxes (Vulpes vulpes). Genetic analyses of feces and snowtracking revealed the presence of foxes at sites where other techniques failed to discern these species, suggesting that cameras and track-plates are inefficient for surveying small canids in this region. The LTD of coyotes by camera traps was not correlated with their abundance as indexed by scat counts, but for other species this metric may offer an opportunity to assess relative abundance across sites. Snowtracking surveys were particularly robust (high POD) for detecting species active in winter and may be more effective than both cameras and track-plates where conditions are suitable. We recommend that survey efforts targeting multiple members of the carnivore community use multiple independent techniques and incorporate mechanisms to truth their relative value. [ABSTRACT FROM AUTHOR]

We used fecal analyses to document the diet of ocelots (Leopardus pardalis) and puma (Puma concolor) at 2 sites in central Panama. We detected puma on Barro Colorado Island (BCI) nearly every month during the study but never found evidence of jaguars (Punthera onca) at either site. Both ocelots and puma fed predominantly on mammalian prey, but consumed a diversity of species. Collared peccaries (Pecari tajacu) and Central American red brocket (Mazama temama) were the most important food items for puma, whereas Central American agoutis (Dasyprocta punctata) and sloths (Choloepus hoffmanni and Bradypus variegatus) were the most important for ocelots. Considerable overlap in diet was found between populations and species, but the diet of puma on BCI was significantly different from the 2 ocelot populations in containing more large prey, suggesting that dietary differences between these predator species are chiefly related to their relative body size. Comparing across larger scales, both populations of ocelots in our study ate larger prey than elsewhere in their range, suggesting that their fundamental niche includes more medium-sized prey than their realized niche in other sites. Puma on BCI ate proportionally more peccaries and deer than in most other populations. These unusual diets in the wake of a recent decline or local extinction of jaguars are consistent with a prey shift in response to competitive release. [ABSTRACT FROM AUTHOR]