Summary1. Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. 2. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. 3. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence-absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. 4. Most studies estimating density used capture-recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). 5. Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.

Countries committed to implementing the Convention on Biological Diversity's 2011–2020 strategic plan need effective tools to monitor global trends in biodiversity. Remote cameras are a rapidly growing technology that has great potential to transform global monitoring for terrestrial biodiversity and can be an important contributor to the call for measuring Essential Biodiversity Variables. Recent advances in camera technology and methods enable researchers to estimate changes in abundance and distribution for entire communities of animals and to identify global drivers of biodiversity trends. We suggest that interconnected networks of remote cameras will soon monitor biodiversity at a global scale, help answer pressing ecological questions, and guide conservation policy. This global network will require greater collaboration among remote‐camera studies and citizen scientists, including standardized metadata, shared protocols, and security measures to protect records about sensitive species. With modest investment in infrastructure, and continued innovation, synthesis, and collaboration, we envision a global network of remote cameras that not only provides real‐time biodiversity data but also serves to connect people with nature.

1. This paper reviews and compares the effects of forest fire and timber harvest on mammalian abundance and diversity, throughout successional time in the boreal forest of North America. 2. Temporal trends in mammal abundance and diversity are generally similar for both harvested and burned stands, with some differences occurring in the initiation stage (0-10 years post disturbance). 3. Small mammals and ungulates are most abundant immediately post disturbance, and decrease as stands age. Lynxes and hares utilize mid-successional stands, but are rare in young and old stands. Bats, arboreal sciurids and mustelids increase in abundance with stand age, and are most abundant in old growth. 4. Substantial gaps in the data exist for carnivores; the response of these species to fire and harvest requires research, as predator-prey interactions can affect mammal community structure in both early and late successional stages. 5. The lack of explicit treatment of in-stand forest structure post disturbance, in the reviewed literature made comparisons difficult. Where forest structure was considered, the presence of downed woody material, live residual trees and standing dead wood were shown to facilitate convergence of mammal communities to a pre-disturbance state for both disturbance types. 6. Mammalian assemblages differed considerably between successional stages, emphasizing the importance of maintaining stands of each successional stage on the landscape when implementing forest management strategies.

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.

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.

Niche theory in its various forms is based on those environmental factors that permit species persistence, but less work has focused on defining the extent, or size, of a species’ environment: the area that explains a species’ presence at a point in space. We proposed that this habitat extent is identifiable from a characteristic scale of habitat selection, the spatial scale at which habitat best explains species’ occurrence. We hypothesized that this scale is predicted by body size. We tested this hypothesis on 12 sympatric terrestrial mammal species in the Canadian Rocky Mountains. For each species, habitat models varied across the 20 spatial scales tested. For six species, we found a characteristic scale; this scale was explained by species’ body mass in a quadratic relationship. Habitat measured at large scales best-predicted habitat selection in both large and small species, and small scales predict habitat extent in medium-sized species. The relationship between body size and habitat selection scale implies evolutionary adaptation to landscape heterogeneity as the driver of scale-dependent habitat selection.

Co-occurring species are rarely considered as a factor infl uencing habitat selection. However, niche theory predicts that sharing resources, predators, and other interspecifi c interactions can limit the environmental conditions under which a species may exist. How does the spatial distribution of one species aff ect that of another within shared landscapes? We tested whether sympatric marten Martes americana and fi shers M. pennanti in a mountain landscape in Alberta, Canada exhibit local-scale spatial segregation, beyond diff erential habitat selection. We modelled marten and fi sher distribution in relation to remotely-sensed habitat data and species co-occurrence, using generalized linear models and informationtheoretic model selection. Marten and fi shers selected diff erent habitat types and showed diff erent responses to habitat fragmentation. Even after accounting for these diff erences, the absence of one species signifi cantly explained the occurrence of the other. We conclude that the spatial distribution of marten and fi shers infl uences habitat selection by each other at landscape scales, and hypothesize that this pattern may result from competition in a spatially heterogeneous environment. Species-habitat models that consider only resources may fail to capture key predictors of species ' occurrence. Reliable prediction and inference requires that ecologists expand from landscapes to also include species-scapes: a spatial plane of species interactions that combines with resources to drive species ' distributions.

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