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Knowledge of habitat suitability (HS) is required for effective conservation planning, yet it can be difficult to obtain. In the absence of local HS information, managers often use studies from other areas to guide their decisions, typically without local validation. We tested the hypothesis that HS is consistent across a species range, and thus reliably extrapolated to understudied sites. We focused on the puma, Puma concolor, a widely distributed large carnivore of conservation and management importance. We conducted a meta-analysis of 41 studies to calculate a mean effect size for six of the most common predictor variables used in mammal HS research. Using the estimated effect sizes in a regression model which included all six variables, we created a new HS model for pumas in an understudied site, the Tumbesian Region (TR). We contrasted predictions from this range-wide model with those from three more regionally specific HS models: a model developed in the Caatinga, Brazil (Caatinga model), a model considering only tropical studies (tropical model), and a model using only studies from the United States and Canada (temperate model). We used puma detection rates from camera trap surveys across the TR to validate model predictions. Although mean effect sizes of habitat predictor variables varied across puma range, all models provided useful predictions of HS for pumas in the TR (area under the receiver operating characteristic curve [AUC] > 0.64). Unexpectedly, the temperate model was best at predicting puma HS in the TR (AUC: 0.77; rs = 0.3), followed by the range-wide model (AUC = 0.73; rs = 0.29). The tropical and Caatinga models had lower predictive accuracy (AUC = 0.68; rs = 0.28 and AUC = 0.64; rs = 0.23, respectively). The accuracy of the tropical model improved when the area of potential recent puma extirpation was excluded from the validation data set. These results highlight that although HS for P. concolor varies across the species range, information collected across a wide range of sites may be better than only locally or regionally specific information for informing HS in understudied sites (e.g., for habitat protection, restoration areas). Given the pressing need for actions to address widespread biodiversity declines, existing knowledge can be used to predict HS to data-poor regions and inform conservation planning while also motivating model validations and targeted data collection.

Land modified for human use alters matrix shape and composition and is a leading contributor to global biodiversity loss. It can also play a key role in facilitating range expansion and ecosystem invasion by anthrophilic species, as it can alter food abundance and distribution while also influencing predation risk; the relative roles of these processes are key to habitat selection theory. We researched these relative influences by examining human footprint, natural habitat, and predator occurrence on seasonal habitat selection by range-expanding boreal white-tailed deer (Odocoileus virginianus) in the oil sands of western Canada. We hypothesized that polygonal industrial features (e.g. cutblocks, well sites) drive deer distributions as sources of early seral forage, while linear features (e.g. roads, trails, and seismic lines) and habitat associated with predators are avoided by deer. We developed seasonal 2nd -order resource selection models from three years of deer GPS-telemetry data, a camera-trap-based model of predator occurrence, and landscape spatial data to weigh evidence for six competing hypotheses. Deer habitat selection was best explained by the combination of polygonal and linear features, intact deciduous forest, and wolf (Canis lupus) occurrence. Deer strongly selected for linear features such as roads and trails, despite a potential increased risk of wolf encounters. Linear features may attract deer by providing high density forage opportunity in heavily exploited landscapes, facilitating expansion into the boreal north.

Despite criticisms, the umbrella species concept remains a fundamental conservation tool for protecting biodiversity in the face of global change, yet it is rarely tested. Food web theory provides a tool to test both umbrella-species' suitability and their ecological function, which we investigate in a large-mammal food web. Using data from 698 camera trap locations in the Canadian Rockies, we develop hierarchical occupancy models to predict the co-occurrence of 16 large mammal species. We draw upon previous diet studies in the Canadian Rockies to describe the meta food-web (meta-web) for these species. Next, we filtered the meta-web using predicted occupancy to estimate realized food webs at each camera location. We tested the umbrella species concept using predicted occupancy across all 698 camera sites. We then tested for carnivore effects using realized food webs on 5 food-web properties: species richness, links, connectance, nestedness and modularity using generalized linear models while accounting for landscape covariates known to affect food web dynamics. Our multispecies occupancy models reflected factors previously demonstrated to affect large mammal occurrence. Our results also demonstrated that grizzly bear (Ursus horribilis), a generalist carnivore, was the best umbrella carivore species, and explained species richness the best. When considering food web properties, however, wolves (Canis lupus) and cougars (Felis concolor) served as better umbrellas that also captured food web properties such as connectance, links and nestedness that better reflect ecological interactions. Our results support the role of large carnivores as umbrella and ecologically interactive species in conservation planning.

Livestock depredation by wild carnivores threatens carnivore populations and livestock-dependent human communities globally. Understanding local attitudes towards carnivores can inform strategies to improve coexistence. In Sri Lanka, the dairy industry is expanding, creating a need for proactive conflict mitigation. Livestock depredation by the Endangered Sri Lankan leopard Panthera pardus kotiya occurs, but little is known about these incidents or the attitudes of those whose livelihoods may be threatened by this. We surveyed people in two rural communities, Palatupana and Maskeliya, that differed in the scale of livestock ownership, livestock management practices and socio-ecological factors, to characterize attitudes towards leopards and understand their determinants. In Palatupana, an area with extensive cattle rearing, depredation incidents were frequent, and attitudes towards leopards were positively related to respondents' age, number of dependants, years spent rearing livestock and a greater overall support for wildlife conservation. Attitudes were negatively related to respondents' knowledge of leopard ecology and awareness of leopard-related tourism, from which cattle owners do not benefit. In Maskeliya, where cattle rearing is secondary to other agricultural work, depredation did not occur. Here, attitudes were positively related to a desire for increased government assistance with cattle rearing. The inability to develop land for cattle husbandry was a common barrier experienced in both communities. Considering local attitudes can inform strategies to improve human–carnivore coexistence. Approaches that could improve attitudes towards leopards include involvement of cattle owners in tourism programmes, exploring potential alternative land ownership schemes, and improving infrastructure and access to veterinary care.

Vegetation phenology and productivity drive resource use by wildlife. Vegetation dynamics also reveal patterns of habitat disturbance and recovery. Monitoring these fine‐scale vegetation patterns over large spatiotemporal extents can be difficult, but camera traps (CTs) commonly used to survey wildlife populations also collect data on local habitat conditions. We used CTs (n = 73) from 2016 to 2019 to assess impacts of habitat change in a boreal landscape of northern Canada, where seismic lines for petroleum exploration disturbed wildlife habitat and prompted vegetation restoration efforts. First, we quantified vegetation dynamics from CTs, comparing them to satellite‐based estimates that are typically used to monitor vegetation at broad spatial scales. We then used understory phenology and productivity estimated from CT time‐lapse images to assess vegetation recovery on seismic lines. Finally, we related vegetation dynamics with the habitat use of three wildlife species: sandhill cranes Grus canadensis, woodland caribou Rangifer tarandus, and white‐tailed deer Odocoileus virginianus. CTs provided unique insight into vegetation dynamics that were different from signals measured by satellites, with temporally inconsistent and even some negative correlations between CT and satellite metrics. We found some indication of vegetation recovery on seismic lines that had received restoration treatment, with understory patterns more similar to undisturbed habitat than to seismic lines that did not receive restoration treatment. CTs also provided inferences about wildlife activity related to vegetation resources, which approaches using satellite data failed to detect. Wildlife habitat use tracked vegetation phenology, but did not always increase with vegetation productivity at weekly, 16‐day, or annual intervals. Instead, associations with vegetation productivity depended on species, temporal scale, and productivity metrics. Given the widespread and growing use of CTs to monitor terrestrial wildlife, we recommend their use to simultaneously monitor habitat conditions to better understand the mechanisms that govern wildlife habitat use in changing environments.

The dual mandate for many protected areas (PAs) to simultaneously promote recreation and conserve biodiversity may be hampered by negative effects of recreation on wildlife. However, reports of these effects are not consistent, presenting a knowledge gap that hinders evidence-based decision-making. We used camera traps to monitor human activity and terrestrial mammals in Golden Ears Provincial Park and the adjacent University of British Columbia Malcolm Knapp Research Forest near Vancouver, Canada, with the objective of discerning relative effects of various forms of recreation on cougars (

Landscape change is a key driver of biodiversity declines due to habitat loss and fragmentation, but spatially shifting resources can also facilitate range expansion and invasion. Invasive populations are reproductively successful, and landscape change may buoy this success.We show how modeling the spatial structure of reproductive success can elucidate the mechanisms of range shifts and sustained invasions for mammalian species with attendant young. We use an example of white‐tailed deer (deer; Odocoileus virginianus) expansion in the Nearctic boreal forest, a North American phenomenon implicated in severe declines of threatened woodland caribou (Rangifer tarandus).We hypothesized that deer reproductive success is linked to forage subsidies provided by extensive landscape change via resource extraction. We measured deer occurrence using data from 62 camera traps in northern Alberta, Canada, over three years. We weighed support for multiple competing hypotheses about deer reproductive success using multistate occupancy models and generalized linear models in an AIC‐based model selection framework.Spatial patterns of reproductive success were best explained by features associated with petroleum exploration and extraction, which offer early‐seral vegetation resource subsidies. Effect sizes of anthropogenic features eclipsed natural heterogeneity by two orders of magnitude. We conclude that anthropogenic early‐seral forage subsidies support high springtime reproductive success, mitigating or exceeding winter losses, maintaining populations. Synthesis and Applications. Modeling spatial structuring in reproductive success can become a key goal of remote camera‐based global networks, yielding ecological insights into mechanisms of invasion and range shifts to inform effective decision‐making for global biodiversity conservation., White‐tailed deer are expanding into the boreal with detrimental effects on the mammal community. Landscape change via resource extraction best explains successful deer reproduction in this boreal landscape.

Human disturbance directly affects animal populations but indirect effects of disturbance on species behaviors are less well understood. Camera traps provide an opportunity to investigate variation in animal behaviors across gradients of disturbance. We used camera trap data to test predictions about predator-sensitive behavior in three ungulate species (caribou Rangifer tarandus; white-tailed deer, Odocoileus virginianus; moose, Alces alces) across two boreal forest landscapes varying in disturbance. We quantified behavior as the number of camera trap photos per detection event and tested its relationship to predation risk between a landscape with greater industrial disturbance and predator abundance (Algar) and a “control” landscape with lower human and predator activity (Richardson). We also assessed the influence of predation risk and habitat on behavior across camera sites within the disturbed Algar landscape. We predicted that animals in areas with greater predation risk (more wolf activity, less cover) would travel faster and generate fewer photos per event, while animals in areas with less predation risk would linger (rest, forage), generating more photos per event. Consistent with predictions, caribou and moose had more photos per event in the landscape where predation risk was reduced. Within the disturbed landscape, no prey species showed a significant behavioral response to wolf activity, but the number of photos per event decreased for white-tailed deer with increasing line of sight (m) along seismic lines (i.e. decreasing visual cover), consistent with a predator-sensitive response. The presence of juveniles was associated with shorter behavioral events for caribou and moose, suggesting greater predator sensitivity for females with calves. Only moose demonstrated a positive association with vegetation productivity (NDVI), suggesting that for other species influences of forage availability were generally weaker than those from predation risk. Behavioral insights can be gleaned from camera trap surveys and provide information about animal responses to predation risk and the indirect impacts of human disturbances.

Climate and landscape change are drivers of species range shifts and biodiversity loss; understanding how they facilitate and sustain invasions has been empirically challenging. Winter severity is decreasing with climate change and is a predicted mechanism of contemporary and future range shifts. For example, white-tailed deer (Odocoileus virginianus) expansion is a continental phenomenon across the Nearctic with ecological consequences for entire biotic communities. We capitalized on recent temporal variation in winter severity to examine spatial and temporal dynamics of invasive deer distribution in the Nearctic boreal forest. We hypothesized deer distribution would decrease in severe winters reflecting historical climate constraints, and remain more static in moderate winters reflecting recent climate. Further, we predicted that regardless of winter severity, deer distribution would persist and be best explained by early seral forage subsidies from extensive landscape change via resource extraction. We applied dynamic occupancy models in time, and species distribution models in space, to data from 62 camera traps sampled over 3 years in northeastern Alberta, Canada. Deer distribution shrank more markedly in severe winters but rebounded each spring regardless of winter severity. Deer distribution was best explained by anthropogenic landscape features assumed to provide early seral vegetation subsidy, accounting for natural landcover. We conclude that deer dynamics in the northern boreal forest are influenced both by landscape change across space and winter severity through time, the latter expected to further decrease with climate change. We contend that the combined influence of these two drivers is likely pervasive for many species, with changing resources offsetting or augmenting physiological limitations.

Interspecific interactions are an integral aspect of ecosystem functioning that may be disrupted in an increasingly anthropocentric world. Industrial landscape change creates a novel playing field on which these interactions take place, and a key question for wildlife managers is whether and how species are able to coexist in such working landscapes. Using camera traps deployed in northern Alberta, we surveyed boreal predators to determine whether interspecific interactions affected occurrences of black bears (Ursus americanus), coyotes (Canis latrans), and lynx (Lynx canadensis) within a landscape disturbed by networks of seismic lines (corridors cut for seismic exploration of oil and gas reserves). We tested hypotheses of species interactions across one spatial‐only and two spatiotemporal (daily and weekly) scales. Specifically, we hypothesized that (1) predators avoid competition with the apex predator, gray wolf (Canis lupus), (2) they avoid competition with each other as intraguild competitors, and (3) they overlap with their prey. All three predators overlapped with wolves on at least one scale, although models at the daily and weekly scale had substantial unexplained variance. None of the predators showed avoidance of intraguild competitors or overlap with prey. These results show patterns in predator space use that are consistent with both facilitative interactions or shared responses to unmeasured ecological cues. Our study provides insight into how predator species use the working boreal landscape in relation to each other, and highlights that predator management may indirectly influence multiple species through their interactions., Interspecific interactions are an integral aspect of ecosystem functioning that may be disrupted in an increasingly anthropocentric world. Using camera traps deployed in northern Alberta, we surveyed boreal predators to determine whether interspecific interactions affected occurrences of black bears (Ursus americanus), coyotes (Canis latrans), and lynx (Lynx canadensis) within a seismic line network. Our results highlight important considerations of the impact of predator management decisions, especially in working landscapes shared between wildlife and industry.

Camera traps (CTs) are an increasingly popular tool for wildlife survey and monitoring. Estimating relative abundance in unmarked species is often done using detection rate as an index of relative abundance, which assumes that detection rate has a positive linear relationship with true abundance. This assumption may be violated if movement behavior varies with density, but the degree to which movement behavior is density‐dependent across taxa is unclear. The potential confounding of population‐level relative abundance indices by movement would depend on how regularly, and by what magnitude, movement rate and home‐range size vary with density. We conducted a systematic review and meta‐analysis to quantify relationships between movement rate, home‐range size, and density, across terrestrial mammalian taxa. We then simulated animal movements and CT sampling to test the effect of contrasting movement scenarios on CT detection rate indices. Overall, movement rate and home‐range size were negatively correlated with density and positively correlated with one another. The strength of the relationships varied significantly between taxa and populations. In simulations, detection rates were related to true abundance but underestimated change, particularly for slower moving species with small home ranges. In situations where animal space use changes markedly with density, we estimate that up to thirty percent of a true change in relative abundance may be missed due to the confounding effect of movement, making trend estimation more difficult. The common assumption that movement remains constant across densities is therefore violated across a wide range of mammal species. When studying unmarked species using CT detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement. Practitioners interpreting changes in camera detection rates should be aware that observed differences may be biased low relative to true changes in abundance. Further information on animal movement, or methods that do not depend on assumptions of density‐independent movement, may be required to make robust inferences on population trends., Animal movement rate and home range size are density‐dependent across a wide range of taxa. This potentially confounds interpretation of detection indices from camera trap surveys. When studying unmarked species using detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement.

Protecting wildlife within areas of resource extraction often involves reducing habitat fragmentation. In Canada, protecting threatened woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) populations requires preserving large areas of intact forest habitat, with some restrictions on industrial forestry activities. We present a linear programming model that assesses the trade-off between achieving an objective of habitat protection for caribou populations while maintaining desired levels of harvest in forest landscapes. The habitat-protection objective maximizes the amount of connected habitat that is accessible by caribou, and the forestry objective maximizes net revenues from timber harvest subject to even harvest flow, a harvest target, and environmental sustainability constraints. We applied the model to explore the habitat protection and harvesting scenarios in the Cold Lake caribou range, a 6726 km2 area of prime caribou habitat in Alberta, Canada. We evaluated harvest scenarios ranging from 0.1 Mm3·year–1 to maximum sustainable harvest levels over 0.7 Mm3·year–1 and assessed the impact of habitat protection measures on timber supply costs. Protecting caribou habitat by deferring or reallocating harvest increases the timber unit cost by Can$1.1–2.0 m–3. However, this impact can be partially mediated by extending the harvest to areas of oil and gas extraction to offset forgone harvest in areas of prime caribou habitat.

AIMS: To model regional vegetation cycles through data fusion methods for creating a 30‐m daily vegetation product from 2000 to 2018 and to analyze annual vegetation trends over this time period. LOCATION: The Yellowhead Bear Management Area, a 31,180‐km² area in west central Alberta, Canada. METHODS: In this paper, we use Dynamic Time Warping (DTW) as a data fusion technique to combine Landsat 5, 7 and 8 satellite data and Moderate Resolution Image Spectroradiometer (MODIS) Aqua and Terra imagery, to quantify daily vegetation using Enhanced Vegetation Index at a 30‐m resolution, for the years 2000–2018. We validated this approach, entitled DRIVE (Daily Remote Inference of VEgetation), using imagery acquired from a network of ground cameras. RESULTS: When DRIVE was compared to start and end of season dates (SOS and EOS respectively) derived from ground cameras, correlations were r = 0.73 at SOS and r = 0.85 at EOS with a mean absolute error of 7.17 days at SOS and 10.76 days at EOS. Results showed that DRIVE accurately increased spatial and temporal resolution of remote‐sensing data. We demonstrated that SOS is advancing at a maximum rate of 0.78 days per year temporally over the 18‐year time period for varying elevation gradients and land cover classes over the region. CONCLUSIONS: With DRIVE, we demonstrate the utility of DTW in quantifying vegetation cycles over a large heterogeneous region and determining how changing climate is affecting regional vegetation. DRIVE may prove to be an important method to determine how carbon sequestration is varying within fine‐scale individual plant communities in response to changing climate and likely will be beneficial to wildlife movement and habitat selection studies examining the varying response of wildlife species to changing vegetation cycles under shifting climatic conditions.

Density estimation is a key goal in ecology but accurate estimates remain elusive, especially for unmarked animals. Data from camera-trap networks combined with new density estimation models can bridge this gap but recent research has shown marked variability in accuracy, precision, and concordance among estimators. We extend this work by comparing estimates from two different classes of models: unmarked spatial capture-recapture (spatial count, SC) models, and Time In Front of Camera (TIFC) models, a class of random encounter model. We estimated density for four large mammal species with different movement rates, behaviours, and sociality, as these traits directly relate to model assumptions. TIFC density estimates were typically higher than SC model estimates for all species. Black bear TIFC estimates were ~ 10-fold greater than SC estimates. Caribou TIFC estimates were 2-10 fold greater than SC estimates. White-tailed deer TIFC estimates were up to 100-fold greater than SC estimates. Differences of 2-5 fold were common for other species in other years. SC estimates were annually stable except for one social species; TIFC estimates were highly annually variable in some cases and consistent in others. Tests against densities obtained from DNA surveys and aerial surveys also showed variable concordance and divergence. For gregarious animals TIFC may outperform SC due to the latter model’s assumption of independent activity centres. For curious animals likely to investigate camera traps, SC may outperform TIFC, which assumes animal behavior is unaffected by cameras. Unmarked models offer great possibilities, but a pragmatic approach employs multiple estimators where possible, considers the ecological plausibility of assumptions, and uses an informed multi-inference approach to seek estimates from models with assumptions best fitting a species’ biology.

British Columbia has the greatest biological diversity of any province or territory in Canada. Yet increasing numbers of species in British Columbia are threatened with extinction. The current patchwork of provincial laws and regulations has not effectively prevented species declines. Recently, the Provincial Government has committed to enacting an endangered species law. Drawing upon our scientific and legal expertise, we offer recommendations for key features of endangered species legislation that build upon strengths and avoid weaknesses observed elsewhere. We recommend striking an independent Oversight Committee to provide recommendations about listing species, organize Recovery Teams, and monitor the efficacy of actions taken. Recovery Teams would evaluate and prioritize potential actions for individual species or groups of species that face common threats or live in a common area, based on best available evidence (including natural and social science and Indigenous Knowledge). Our recommendations focus on implementing an adaptive approach, with ongoing and transparent monitoring and reporting, to reduce delays between determining when a species is at risk and taking effective actions to save it. We urge lawmakers to include this strong evidentiary basis for species recovery as they tackle the scientific and socioeconomic challenges of building an effective species at risk Act. Au Canada, c’est en Colombie-Britannique que la biodiversité est la plus élevée. Pourtant, un nombre croissant de ces espèces sont menacées. L’actuel enchevêtrement de lois et de règlements provinciaux ne parvient pas à en prévenir le déclin. Récemment, le gouvernement provincial s’est engagé à adopter une loi sur les espèces en péril. En nous appuyant sur notre expertise légale et scientifique et sur les succès et échecs connus ailleurs, nous proposons les éléments clés que devrait présenter cette loi. Nous recommandons la formation d’un Comité indépendant de surveillance qui évaluera le statut des espèces, organisera les Équipes de rétablissement et estimera l’efficacité des mesures de protection adoptées. Les Équipes de rétablissement prioriseront les actions possibles pour chaque espèce ou groupe d’espèces subissant les mêmes menaces ou habitant la même région en s’appuyant sur les meilleures informations disponibles (sciences naturelles et sociales et savoirs autochtones). Nos recommandations visent à établir une approche adaptative, incluant un suivi régulier et transparent, afin de réduire les délais entre l’établissement du statut et la mise en œuvre d’actions de rétablissement. Nous exhortons les législateurs et législatrices à tenir compte de cette approche basée sur les éléments probants relatifs au rétablissement des espèces.

Anthropogenic disturbances fragmenting wildlife habitat greatly contribute to extinction risk for many species. In western Canada, four decades of oil and gas exploration have created a network of seismic lines, which are linear disturbances where seismic equipment operates. Seismic lines cause habitat fragmentation and increase predator access to intact forest, leading to declines of some wildlife populations, particularly the threatened woodland caribou, Rangifer tarandus caribou. Restoration of forests within seismic lines is an important activity to reduce habitat fragmentation and recovery caribou. We present an optimization model with the objective of guiding landscape restoration strategies that maximize the area of connected habitat for a caribou population in a fragmented landscape. We use our model to find optimal strategies for seismic line restoration in the Cold Lake Area of Alberta, Canada, a 6726-km2 expanse of boreal forest that represents prime caribou habitat. We formulate mixed integer programming models that depict the landscape as a network of interconnected habitat patches. We develop and compare formulations that emphasize the population's local or long-distance access to habitat. Optimal restoration involves a mix of two strategies: the first establishes short-distance connections between forest patches with large areas of intact habitat and the second establishes corridors between areas with known species locations and large amounts of suitable habitat. Our approach reveals the trade-offs between these strategies and finds the optimal restoration solutions under a limited budget. The approach is generalizable and applicable to other regions and species sensitive to changes in landscape-level habitat connectivity.

Management activities such as law enforcement and community outreach are thought to affect conservation outcomes in protected areas, but their importance relative to intrinsic environmental characteristics of the parks and extrinsic human pressures surrounding the parks have not been explored. Furthermore, it is not clear which is more related to conservation outcomes-the management itself or local people's perceptions of the management. We measured objective (reports by park staff) and subjective (reports by local people) levels of community outreach and law enforcement based on responses to 374 questionnaires. We estimated mammal abundance and diversity of 6 protected areas based on data from 115 camera traps in Xishuangbanna, southwest China, a biodiversity hotspot with high hunting and land-conversion pressures. We then examined correlations among them and found that local people's perception of law enforcement was positively related to the local abundance of 2 large, hunted species, wild boar (Sus scrofa) (β = 15.22) and muntjac (Muntiacus vaginalis) (β = 14.82), but not related to the abundance of smaller mammals or to objective levels of enforcement. The subjective frequency of outreach by park staff to local communities (β = 3.42) and park size (β = 3.28) were significantly and positively related to mammal species richness, whereas elevation, human population density, and subjective frequency of law enforcement were not. We could not conclude that community outreach and law enforcement were directly causing increased mammal abundance and diversity. Nevertheless, the patterns we detected are some of the first empirical evidence consistent with the idea that biodiversity in protected areas may be more positively and strongly related to local perceptions of the intensity of park management than to either intrinsic (e.g., elevation, park size) or extrinsic (e.g., human population density) environmental factors.Efectos de la Aplicación de la Ley y la Participación de la Comunidad sobre la Diversidad de Mamíferos en un Punto Caliente de Biodiversidad Resumen Las actividades de manejo como la aplicación de la ley y la participación de la comunidad afectan los resultados de conservación dentro de las áreas protegidas, pero su importancia en relación con las características ambientales intrínsecas de los parques y las presiones humanas extrínsecas que rodean a los parques no han sido exploradas. Además, no está claro cuál está más relacionado con los resultados de conservación - el manejo en sí o las percepciones que las personas locales tienen sobre el manejo. Medimos los niveles objetivos (reportes dados por el personal del parque) y subjetivos (reportes dados por los locales) de la participación de la comunidad y la aplicación de la ley con base en las respuestas a 347 cuestionarios. Estimamos la abundancia y diversidad de mamíferos de seis áreas protegidas con base en datos de 115 cámaras trampa en Xishuangbann, al suroeste de China, un punto caliente de biodiversidad con altas presiones causadas por la caza y la conversión del uso de suelo. Después examinamos la correlación entre ellos y encontramos que la percepción que los locales tienen sobre la aplicación de la ley estuvo relacionada positivamente con la abundancia local de dos grandes especies que son cazadas, el jabalí (Sus scrofa) (β = 15.22) y el muntíaco (Muntiacus vaginalis) (β = 14.82), pero no estuvo relacionada con la abundancia de mamíferos más pequeños o con los niveles objetivos de la aplicación de la ley. La frecuencia subjetiva del alcance del personal del parque hacia las comunidades locales (β = 3.42) y el tamaño del parque and (β = 3.28) estuvieron relacionadas significativa y positivamente con la riqueza de las especies de mamíferos, mientras que la elevación, la densidad de la población humana, y la frecuencia subjetiva de la aplicación de la ley no lo estuvieron. No pudimos concluir que la participación de la comunidad y la aplicación de la ley estuvieran causando directamente una abundancia y diversidad aumentada de mamíferos. Sin embargo, los patrones que detectamos son de las primeras evidencias empíricas consistentes con la idea de que la biodiversidad en las áreas protegidas podría estar relacionada positiva y fuertemente con la percepción que tienen los locales de la intensidad del manejo del parque y no con los factores ambientales intrínsecos (p. ej.: elevación, tamaño del parque) o extrínsecos (p.ej.: densidad de la población humana).保护区执法 和社区宣传 等管理活动被认为会影响保护区的保护成果, 但其相对于保护区内在环境特征因素以及保护区周边的外在人类活动因素的重要性尚未得到探索。此外, 尚不清楚哪个与保护结果更相关 - 管理本身或当地人对管理行为的感知。我们通过 374 份问卷测量了客观 (由保护区工作人员报告的) 和主观 (由当地人报告的) 执法和社区宣传水平。我们通过 115 个相机陷阱估算了西双版纳的 6 个保护区的哺乳动物丰度和多样性, 西双版纳是一个具有高狩猎压力和土地流转压力的生物多样性热点地区。我们接下来验证了管理活动和生物多样性指标的相关性, 发现当地居民对执法行为的感知与 2 种大型猎物, 野猪 (Sus scrofa) (β = 15.22) 和赤麂 (Muntiacus vaginalis) (β = 14.82) 的相对多度呈正相关, 但与较小的哺乳动物的相对多度无相关性关, 且客观的执法水平猎物丰富度也无相关性。当地居民感知的保护区宣传频率 (β = 3.42) 和保护区面积 (β = 3.28) 与哺乳动物物种丰富度显著正相关, 而与海拔, 保护区周边人口密度和保护区汇报的宣传频率无相关性。虽然, 相关性不等于因果关系, 我们无法得出是保护区执法和社区宣传直接导致了保护区哺乳动物多度和多样性地增加。不过, 我们发现的结果可能是第一个与平时推测相一致的实验性证据:保护区周边居民对保护区管理的感知与保护区内的生物多样性的相关性高于保护区内在环境特征 (例如保护区海拔和面积) 以及保护区周边的外在人类活动因素 (例如保护区周边的人口密度) 与保护区内的生物多样性的相关性。.

Camera traps are increasingly used to answer complex ecological questions. However, the rapidly growing number of images collected presents technical challenges. Each image must be classified to extract data, requiring significant labour, and potentially creating an information bottleneck. We applied an object-detection model (MegaDetector) to camera trap data from a study of recreation ecology in British Columbia, Canada. We tested its performance in detecting humans and animals relative to manual image classifications, and assessed efficiency by comparing the time required for manual classification versus a modified workflow integrating object-detection with manual classification. We also evaluated the reliability of using MegaDetector to create an index of human activity for application to the study of recreation impacts to wildlife. In our application, MegaDetector detected human and animal images with 99% and 82% precision, and 95% and 92% recall respectively, at a confidence threshold of 90%. The overall time required to process the dataset was reduced by over 500%, and the manual processing component was reduced by 840%. The index of human detection events from MegaDetector matched the output from manual classification, with a mean 0.45% difference in estimated human detections across site-weeks. Our test of an open-source object-detection model showed it performed well in partially classifying a camera trap dataset, significantly increasing processing efficiency. We suggest that this tool could be integrated into existing camera trap workflows to accelerate research and application by alleviating data bottlenecks, particularly for surveys processing large volumes of human images. We also show how the model and workflow can be used to anonymize human images prior to classification, protecting individual privacy.Impact StatementWe developed and tested a workflow for classifying camera trap images that integrated an existing object-detection model with manual image classification. Our workflow demonstrates an increase in efficiency of 500% over manual labelling, and additionally includes a method to anonymize human images prior to archiving and classification. We provide an example of the application of these tools to ease data processing, particularly for studies focused on recreation ecology which record high volumes of human images. Data lags due to processing delays have the potential to result in sub-optimal conservation decisions, which may be alleviated by accelerated processing. To our knowledge, this is the first in-depth assessment of the practical application of such technology to real world workflows focused on human detections.

Land-use change is a root cause of the extinction crisis, but links between habitat change and biodiversity loss are not fully understood. While there is evidence that habitat loss is an important extinction driver, the relevance of habitat fragmentation remains debated. Moreover, while time delays of biodiversity responses to habitat transformation are well-documented, time-delayed effects have been ignored in the habitat loss versus fragmentation debate. Here, using a hierarchical Bayesian multi-species occupancy framework, we systematically tested for time-delayed responses of bird and mammal communities to habitat loss and to habitat fragmentation. We focused on the Argentine Chaco, where deforestation has been widespread recently. We used an extensive field dataset on birds and mammals, along with a time series of annual woodland maps from 1985 to 2016 covering recent and historical habitat transformations. Contemporary habitat amount explained bird and mammal occupancy better than past habitat amount. However, occupancy was affected more by the past rather than recent fragmentation, indicating a time-delayed response to fragmentation. Considering past landscape patterns is therefore crucial for understanding current biodiversity patterns. Not accounting for land-use history ignores the possibility of extinction debt and can thus obscure impacts of fragmentation, potentially explaining contrasting findings of habitat loss versus fragmentation studies.

A major threat to mammalian carnivores is death due to human conflict, including carnivore use of anthropogenic food sources, predation of livestock, or car accidents. To reduce conflicts, it is critical to target proactive mitigations using reliable evidence on where conflict is likely to occur. We tested hypotheses about the importance of anthropogenic and environmental predictors in explaining the timing and distribution of human conflict with black bears (Ursus americanus) and cougars (Puma concolor) in a North American hotspot of human-carnivore conflict. Using reported conflict locations and spatial data in use-availability models, we estimated and mapped the probability of conflict for both species, including seasonally for bears, between 2011 and 2017. We found conflict increased for both species along the urban-wildland interface. Conflict with black bears was present in all seasons and increased with intermediate human density (i.e. suburban neighbourhoods). However, in autumn, bear conflict was more common in agricultural areas. Conversely, cougar conflict was primarily in rural areas, as their main attractant was livestock. We recommend targeting areas and times of expected conflict with proactive mitigations, such as bear-resistant garbage bins in communities adjacent to forests, electric fences that deter both carnivore species, and elimination of rural food attractants in autumn.

Outdoor recreation is one of the fastest growing economic sectors in the world and provides many benefits to people. Assessing possible negative impacts of recreation is nevertheless important for sustainable management. Here, we used camera traps to assess relative effects of various recreational activities—as compared to each other and to environmental conditions—on a terrestrial wildlife assemblage in British Columbia, Canada. Across 13 species, only two negative associations between recreational activities and wildlife detections were observed at weekly scales: mountain biking on moose and grizzly bears. However, finer‐scale analysis showed that all species avoided humans on trails, with avoidance strongest for mountain biking and motorized vehicles. Our results imply that environmental factors generally shaped broad‐scale patterns of wildlife use, but highlight that recreational activities also have detectable impacts. These impacts can be monitored using the same camera‐trapping techniques that are commonly used to monitor wildlife assemblages.

Camera traps (CTs) are an increasingly popular method of studying animal behavior. However, the impact of cameras on detected individuals—such as from mechanical noise, odor, and emitted light—has received relatively little attention. These impacts are particularly important in behavioral studies in conservation that seek to ascribe changes in behavior to relevant environmental factors. In this article, we discuss three sources of bias that are relevant to conservation behavior studies using CTs: (a) disturbance caused by cameras; (b) variation in animal‐detection parameters across camera models; and (c) biased detection across individuals and age, sex, and behavioral classes. We propose several recommendations aimed at mitigating responses to CTs by wildlife. Our recommendations offer a platform for the development of more rigorous and robust behavioral studies using CT technology and, if adopted, would result in greater applied benefits for conservation and management. Publisher PDF

To monitor the extent and impact of human disturbances on landscapes and wildlife, managers often estimate zones of influence. Traditionally, zones of influence have been defined with constant width buffers around a disturbance; however, the importance of incorporating variation in landscape contexts and species responses is increasingly recognized. One way to better develop and apply these zones of influence is to understand the mechanisms of animal response to disturbance by examining their sensory detection. We explored the role of perception in wildlife responses to disturbances using a case study with grizzly bears (Ursus arctos) and roads in Alberta, Canada. Our objectives were, first, to model viewsheds and soundscapes around roads and, second, to determine the effect of road perception on grizzly bear movement patterns and build context-specific zones of influence for grizzly bears around roads. Results indicate that zones of influence varied widely between the standard buffer approach and our novel approach based on animal perception. In addition, response distances of bears to roads were greater in areas where roads were perceptible than areas where roads were imperceptible. Estimating a perceptual zone of influence allows managers to prioritize areas for mitigating human disturbances. Our methods may be applied to new disturbances, areas, and species. We recommend measures of perception be used to create more biologically and geographically relevant zones of influence for wildlife.

Anthropogenic landscape disturbances are known to alter, destroy, and fragment habitat, which typically leads to biodiversity loss. The effects of landscape disturbance generally vary among species and depend on the nature of the disturbances, which may interact and result in synergistic effects. Western Canada's oil sands region experiences disturbances from forestry and energy sector activities as well as municipal and transportation infrastructure. The effects of those disturbances on single species have been studied and have been implicated in declines of the boreal woodland caribou (Rangifer tarandus caribou). Yet, the specific responses of the mammal community, and of functional groups such as prey and predators, to those interacting disturbances are still poorly known. We investigated the responses of black bear, grey wolf, coyote, fisher, lynx, red fox, American red squirrel, white-tailed deer, moose, caribou, and snowshoe hare to both natural habitat and disturbance associated with anthropogenic features within Alberta's northeast boreal forest. We used a novel community-level modelling framework on three years of camera-trap data collected in an oil sands landscape. This framework allowed us to identify the natural and anthropogenic features which explained the most variation in occurrence frequency among functional groups, as well as compare responses to linear and non-linear anthropogenic disturbance. Occurrence frequency by predators was better explained by anthropogenic features than by natural habitat. Both linear and non-linear anthropogenic features helped explain occurrence frequency by prey and predators, although the effects differed in magnitude and spatial scale. To better conserve boreal biodiversity, management actions should extend beyond a focus on caribou and wolves and aim to restore habitat across a diversity of anthropogenic disturbances and monitor the dynamics of the entire mammal community.

Population declines and extirpations of large mammalian carnivores are major concerns for global biodiversity conservation. Many large carnivores are vulnerable to conflict with humans and attract conservation attention for their flagship appeal and ecological importance. Coexisting with carnivores requires an understanding of carnivore distribution and abundance relative to human activities and disturbances. Such knowledge is often hindered by the rare and elusive nature of carnivores and the lack of systematic ecological surveys in biodiverse regions facing high levels of threat. The Caucasus Ecoregion is one such biodiversity hotspot harboring several threatened mammal species for which there is a paucity of reliable data, including brown bears (Ursus arctos). Caucasus brown bear populations have declined significantly from historical times and may be isolated and vulnerable to disturbance from development activities such as mining, as well as increasing hunting pressure. To inform land-use planning and bear conservation in the Caucasus Ecoregion, we conducted systematic surveys in May–October 2015 in the foothills of the Caucasus Mountains within the Vayots Dzor region of Armenia. We used noninvasive genetic sampling, camera trapping, and statistical models that account for imperfect detection to estimate density and distribution of the bear population in the 1,000-km2 study area. Across 34 sampling sites, we obtained 3,163 camera-trap photos of brown bears and genotyped 28 individual bears (7 males and 21 females). Spatially explicit capture-recapture models revealed an unexpectedly high density of bears (59.4/1,000 km2; females = 44.6, 95% confidence interval, CI = 25.4–78.4; males = 14.8, 95% CI = 6.6–34.0), and multi-method occupancy models indicated that bears were distributed across most of the study area (ψ = 0.85; SE = 0.07). These results provide robust evidence that a significant population of brown bears persists in Armenia's Vayots Dzor region, despite a history of hunting and habitat loss that have driven declines in brown bear populations throughout much of the Caucasus Ecoregion. Continued persistence of this flagship species may be threatened by mining, poaching, and other anthropogenic pressures in the region, underscoring the urgent need for strategic conservation planning, impact mitigation, and expanded ecological monitoring within this biodiversity hotspot.

A rapidly expanding human footprint - comprised of anthropogenic land-use change and infrastructure - is profoundly affecting wildlife distributions worldwide. Cumulative effects management (CEM) is a regional approach that seeks to manage combined effects of the human footprint on biodiversity across large spatial scales. Challenges to implementing this approach include a lack of ecological data at large spatial scales, the high cost of monitoring multiple indicators, and the need to manage multiple footprints across industries. To inform development of effective CEM, we used large mammals as indicators to address the following questions: a) do species respond more strongly to individual footprint features or to cumulative effects (combined area of all footprint types, measured as total footprint), b) which features elicit the strongest responses across species, and c) are the direction of responses to footprint consistent? We used data from 12 years of snowtrack surveys (2001-2013) in the boreal forest of Alberta, coupled with regional footprint and landcover data, to develop generalized linear mixed-effects models relating the relative abundance of five boreal mammals [gray wolf (Canis lupus), Canada lynx (Lynx canadensis), coyote (Canis latrans), white-tailed deer (Odocoileus virginianus) and moose (Alces alces)] to individual and cumulative effects of the human footprint. We found that across species the strongest responses were to agriculture, roads, and young cutblocks (

Energy development and consumption drive changes in global climate, landscapes, and biodiversity. The oil sands of western Canada are an epicenter of oil production, creating landscapes without current or historical analogs. Science and policy often focus on pipelines and species‐at‐risk declines, but we hypothesized that differential responses to anthropogenic disturbances shift the entire mammal community. Analysis of data collected from 3 years of camera trapping and species distribution models indicated that anthropogenic features best explained the distributions of the ten mammal species included in the study. Relative abundances of some mammals were positively correlated with anthropogenic feature density, and others were negatively correlated. Effect sizes were often larger than for natural features. Increasing anthropogenic spatial complexity, access to multiple habitats, and new forage sources favor generalist predators and browsers, to the detriment of specialists, likely altering ecological processes. This issue has far‐reaching implications: as the oil sands landscape changes so too does its mammal community, serving as a bellwether of future change for energy landscapes worldwide.

Active forest management for timber production, through the harvesting of forest stands using cut blocks, frequently overlaps grizzly bear (Ursus arctos) habitat on multi-use landscapes in North America, making it critical to understand how forest harvest management can effectively support grizzly bear conservation efforts. While many localised studies have investigated the relationships between forest harvest and grizzly bear habitat use, a synthesis of our current understanding of these complex interactions is warranted. We reviewed publications that empirically assessed grizzly bear use of recently harvested forest stands (

Time-stamped camera data are increasingly used to study temporal patterns in species and community ecology, including species’ activity patterns and niche partitioning. Given the importance of niche partitioning for facilitating coexistence between sympatric species, understanding how emerging environmental stressors – climate and landscape change, biodiversity loss and concomitant changes to community composition – affect temporal niche partitioning is of immediate importance for advancing ecological theory and informing management decisions. A large variety of analytical approaches have been applied to camera-trap data to ask key questions about species activity patterns and temporal overlap among heterospecifics. Despite the many advances for describing and quantifying these temporal patterns, few studies have explicitly tested how interacting biotic and abiotic variables influence species’ activity and capacity to segregate along the temporal niche axis. To address this gap, we suggest coordinated distributed experiments to capture sufficient camera-trap data across a range of anthropogenic stressors and community compositions. This will facilitate a standardized approach to assessing the impacts of multiple variables on species’ behaviours and interactions. Ultimately, further integration of spatial and temporal analyses of camera-trap data is critical for improving our understanding of how anthropogenic activities and landscape changes are altering competitive interactions and the dynamics of animal communities.