A flexible framework for spatial capture-recapture with unknown identities.

Camera traps or acoustic recorders are often used to sample wildlife populations. When animals can be individually identified, these data can be used with spatial capture-recapture (SCR) methods to assess populations. However, obtaining animal identities is often labor-intensive and not always possible for all detected animals. To address this problem, we formulate SCR, including acoustic SCR, as a marked Poisson process, comprising a single counting process for the detections of all animals and a mark distribution for what is observed (eg, animal identity, detector location). The counting process applies equally when it is animals appearing in front of camera traps and when vocalizations are captured by microphones, although the definition of a mark changes. When animals cannot be uniquely identified, the observed marks arise from a mixture of mark distributions defined by the animal activity centers and additional characteristics. Our method generalizes existing latent identity SCR models and provides an integrated framework that includes acoustic SCR. We apply our method to estimate density from a camera trap study of fisher (Pekania pennanti) and an acoustic survey of Cape Peninsula moss frog (Arthroleptella lightfooti). We also test it through simulation. We find latent identity SCR with additional marks such as sex or time of arrival to be a reliable method for estimating animal density.

How landscape traits affect boreal mammal responses to anthropogenic disturbance.

Understanding mammalian responses to anthropogenic disturbance is challenging, as ecological processes and the patterns arising therefrom notoriously change across spatial and temporal scales, and among different landscape contexts. Responses to local scale disturbances are likely influenced by landscape context (e.g., overall landscape-level disturbance, landscape-level productivity). Hierarchical approaches considering small-scale sampling sites as nested holons within larger-scale landscapes, which constrain processes in lower-level holons, can potentially explain differences in ecological processes between multiple locations. We tested hypotheses about mammal responses to disturbance and interactions among holons using collected images from 957 camera sites across 9 landscapes in Alberta from 2007 to 2020 and examined occurrence for 11 mammal species using generalized linear mixed models. White-tailed deer occurred more in higher disturbed sites within lower disturbed landscapes (ß = -0.30 [-0.4 to -0.15]), whereas occurrence was greater in highly disturbed sites within highly disturbed landscapes for moose (ß = 0.20 [0.09-0.31]), coyote (ß = 0.20 [0.08-0.26]), and lynx (ß = 0.20 [0.07-0.26]). High disturbance sites in high productivity landscapes had higher occurrence of black bears (ß = -0.20 [-0.46 to -0.01]), lynx (ß = -0.70 [-0.97 to -0.34]), and wolves (ß = -0.50 [-0.73 to -0.21]). Conversely, we found higher probability of occurrence in low productivity landscapes with increasing site disturbance for mule deer (ß = 0.80 [0.39-1.14]), and white-tailed deer (ß = 0.20 [0.01-0.47]). We found the ecological context created by aggregate sums (high overall landscape disturbance), and by subcontinental hydrogeological processes in which that landscape is embedded (high landscape productivity), alter mammalian responses to anthropogenic disturbance at local scales. These responses also vary by species, which has implications for large-scale conservation planning. Management interventions must consider large-scale geoclimatic processes and geographic location of a landscape when assessing wildlife responses to disturbance.