Understanding how organisms distribute themselves in response to interacting species, ecosystems, climate, human development and time is fundamental to ecological study and practice. A measure to quantify the relationship among organisms and their environments is intensity of use: the rate of use of a specific resource in a defined unit of time. Estimating the intensity of use differs from estimating probabilities of occupancy or selection, which can remain constant even when the intensity of use varies. We describe a method to evaluate the intensity of use across conditions that vary in both space and time. We demonstrate its application on a large mammal community where linear developments and human activity are conjectured to influence the interactions between white‐tailed deer (Odocoileus virginianus) and wolves (Canis lupus) with possible consequences on threatened woodland caribou (Rangifer tarandus caribou). We collect and quantify intensity of use data for multiple, interacting species with the goal of assessing management efficacy, including a habitat restoration strategy for linear developments. We test whether blocking linear developments by spreading logs across a 200‐m interval can be applied as an immediate mitigation to reduce the intensities of use by humans, predator and prey species in a boreal caribou range. We deployed camera traps on linear developments with and without restoration treatments in a landscape exposed to both timber and oil development. We collected a three‐year dataset and employed spatial recurrent event models to analyse intensity of use by an interacting human and large mammal community across a range of environmental and climatic conditions. Spatial recurrent event models revealed that intensity of use by humans influenced the intensity of use by all five large mammal species evaluated, and the intensities of use by wolves and deer were inextricably linked in space and time. Conditions that resist travel on linear developments had a strong negative effect on the intensity of human and large mammal use. Mitigation strategies that resist, or redirect, animal travel on linear developments can reduce the effects of resource development on interacting human and predator–prey interactions. Our approach is easily applied to other continuous time point‐based survey methodologies and shows that measuring the intensity of use within animal communities can help scientists monitor, mitigate and understand ecological states and processes.

Animal populations are regulated by the combined effects of top-down, bottom-up and abiotic processes. Ecologists have struggled to isolate these mechanisms because their effects on prey behaviour, nutrition, security and fitness are often interrelated. We monitored how forage, non-consumptive effects (NCEs), consumptive predation and climatic conditions influenced the demography and nutritional state of a wild prey population during predator recolonization. Combined measures of nutrition, survival and population growth reveal that predators imposed strong effects on the prey population through interacting non-consumptive and consumptive effects, and forage mechanisms. Predation was directly responsible for adult survival, while declining recruitment was attributed to predation risk-sensitive foraging, manifested in poor female nutrition and juvenile recruitment. Substituting nutritional state into the recruitment model through a shared term reveals that predation risk-sensitive foraging was nearly twice as influential as summer forage conditions. Our findings provide a novel, mechanistic insight into the complex means by which predators and forage conditions affect prey populations, and point to a need for more ecological studies that integrate behaviour, nutrition and demography. This line of inquiry can provide further insight into how NCEs interactively contribute to the dynamics of terrestrial prey populations; particularly, how predation risk-sensitive foraging has the potential to stabilize predator–prey coexistence.

Camera trap data are biased when an animal passes through a camera’s field of view but is not recorded. Cameras that operate using passive infrared sensors rely on their ability to detect thermal energy from the surface of an object. Optimal camera deployment consequently depends on the relationship between a sensor array and an animal. Here, we describe a general, experimental approach to evaluate detection errors that arise from the interaction between cameras and animals. We adapted distance sampling models and estimated the combined effects of distance, camera model, lens height, and vertical angle on the probability of detecting three different body sizes representing mammals that inhabit temperate, boreal, and arctic ecosystems. Detection probabilities were best explained by a half-normal-logistic mixture and were influenced by all experimental covariates. Detection monotonically declined when proxies were ≥6 m from the camera; however, models show that body size and camera model mediated the effect of distance on detection. Although not a focus of our study, we found that unmodeled heterogeneity arising from solar position has the potential to bias inferences where animal movements vary over time. Understanding heterogeneous detection probabilities is valuable when designing and analyzing camera trap studies. We provide a general experimental and analytical framework that ecologists, citizen scientists, and others can use and adapt to optimize camera protocols for various wildlife species and communities. Applying our framework can help ecologists assess trade-offs that arise from interactions among distance, cameras, and body sizes before committing resources to field data collection.

Gray Wolf (Canis lupus) uses scent-marking to communicate breeding status, dominance, and territorial boundaries. Despite its importance for reproduction and pack dynamics, information on scent-marking and proestrus in wild wolf populations is limited to a handful of locations. We estimated the rate of territorial scent-marking and the probability of proestrus in a recolonizing Gray Wolf population near the species southern range extent in eastern North America. An analysis of 221 pack-winters of tracking data show that the incremental addition of one wolf pack increased marking rates by 3.4%, whereas increasing the number of wolves in a pack decreased marking rates by 12.1%. Scent-marking rates subsequently increased from 1.9 times/km during recolonization to 3.0 times/km once the population was saturated. We observed evidence of proestrus from 19 December to 14 March with the highest probability of proestrus occurring around 6 February, after peak marking rates around 26 January. Repeated observations of bloody urinations within individual packs suggest proestrus averages 27.9 days. Our study reveals the role of population growth on territorial behaviours and provides a foundation for studies exploring the role of geographic and temporal variation on territorial and reproductive behaviours in wolves.