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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. 

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap‐derived Big Data are becoming increasingly solvable with the help of scalable cyber‐infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media‐based and event‐based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in‐depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard.

 

As the quality and quantity of natural habitats decrease, pressure increases to better understand species–habitat interactions and how animal communities respond to habitat changes. We assessed the relative importance of local habitat heterogeneity and productivity measures as predictors of avian species richness and compared these results to models for species of conservation concern (SCC). We derived three‐dimensional habitat heterogeneity and productivity measures from light detection and ranging data and hyperspectral imagery, and then used a Bayesian multi‐species hierarchical framework to model avian species richness and occupancy. We found both habitat heterogeneity and productivity were important factors for determining avian community richness. Three‐dimensional habitat heterogeneity and productivity metrics accurately predicted species richness at a local scale and were especially important to use within habitat guilds (i.e., alpha diversity). When scaling up to community richness across multiple habitat types (i.e., gamma diversity), two‐dimensional (surface level) productivity and heterogeneity metrics became important additions to the three‐dimensional metrics when estimating total avian richness. We also tested the utility of these metrics for predicting occupancy of SCC and compared community‐level relationships to species‐specific relationships. Species of conservation concern differed from the broader avian community with regard to local habitat heterogeneity and productivity measures. Species of conservation concern had different relationship habitat metrics than the greater avian community. Three‐dimensional measures of habitat heterogeneity and productivity predicted avian richness across the landscape, yet also highlighted the different habitat structure needs of SCC compared with the greater avian community.

 

Interspecific interactions can provoke temporal and spatial avoidance, ultimately affecting population densities and spatial distribution patterns. The ability (or inability) of species to coexist has consequences for diversity and ultimately ecosystem stability. Urbanization is predicted to change species interactions but its relative impact is not well known. Urbanization gradients offer the opportunity to evaluate the effect of humans on species interactions by comparing community dynamics across levels of disturbance.

We used camera traps deployed by citizen scientists to survey mammals along urbanization gradients of two cities (Washington, DC and Raleigh, NC, USA). We used a multispecies occupancy model with four competing predator species to test whether forest fragmentation, interspecific interactions, humans or prey had the greatest influence on carnivore distribution.

Our study produced 6,413 carnivore detections from 1,260 sites in two cities, sampling both private and public lands. All species used all levels of the urbanization gradient to a similar extent, but co‐occurrence of urban‐adapted foxes with less urban‐adapted bobcats and coyotes was dependent on the availability of green space, especially as urbanization increased. This suggests green space allows less urban‐adapted species to occupy suburban areas, but focuses their movements through remaining forest patches, leading to more species interactions.

Synthesis and applications. Species interactions, forest fragmentation and human‐related covariates were important determinants of carnivore occupancy across a gradient of urbanization with the relative importance of forest fragmentation being highest. We found evidence of both positive and negative interactions across the gradient with some dependent on available green space, suggesting that fragmentation leads to higher levels of spatial interaction. Where green space is adequate, there appears to be sufficient opportunity for coexistence between carnivore species in an urban landscape.