Interspecific competition is notoriously difficult to detect and quantify, especially in species that are wide-ranging or otherwise difficult to track in the wild. Research investigating interspecific competition usually relies on niche overlap measurements despite that this approach alone does not yield rigorous inference. As an illustration, we review published research assessing interspecific competition in mid-sized carnivores in North America (bobcat – Lynx rufus; Canada lynx – Lynx canadensis; coyote – Canis latrans), and report on shortcomings associated with commonly used study designs and types of inference. Niche overlap measurements typically focus on one or two resources (e.g., food, space, habitat), often using non-independent sampling units and inadequate replication. Few studies measure overlap variation through space, time, or resource variability, which is crucial for robust assessment. Niche overlap (or lack thereof) is used as evidence both for and against interspecific competition, reflecting a weak link between competition theory, predicted responses, and observations. Overall, challenges associated with conducting competition research in the field promote over-reliance on simple measurements, flawed study designs and weak inference. Minimally, niche overlap studies should include assessment across multiple niche dimensions and spatial or temporal variation in competitor density or resource availability. Dynamic investigative approaches should include new technologies for tracking inter-individual interactions, study designs that leverage quasi-experiments (e.g., decline in shared resources, biological control of one competitor), and synthetic analyses (e.g., meta-regression). Ultimately, better understanding of competition theory vis-à-vis study design and data needs will promote improved understanding of the role of interspecific competition in nature.

Ecological communities are fundamentally connected through a network of trophic interactions that are often complex and difficult to model. Substantial variation exists in the nature and magnitude of these interactions across various predators and prey and through time. However, the empirical data needed to characterize these relationships are difficult to obtain in natural systems, even for relatively simple food webs. Consequently, prey-dependent relationships and specifically the hyperbolic form (Holling’s Type II), in which prey consumption increases with prey density but ultimately becomes saturated or limited by the time spent handling prey, are most widely used albeit often without knowledge of their appropriateness. Here, we investigate the sensitivity of a simplified food web model for a natural, boreal system in the Kluane region of the Yukon, Canada to the type of functional response used. Intensive study of this community has permitted best-fit functional response relationships to be determined, which comprise linear (type I), hyperbolic (type II), sigmoidal (type III), prey- and ratio-dependent relationships, and inverse relationships where kill rates of alternate prey are driven by densities of the focal prey. We compare node- and network-level properties for a food web where interaction strengths are estimated using best-fit functional responses to one where interaction strengths are estimated exclusively using prey-dependent hyperbolic functional responses. We show that hyperbolic functional responses alone fail to capture important ecological interactions such as prey switching, surplus killing and caching, and predator interference, that in turn affect estimates of cumulative kill rates, vulnerability of prey, generality of predators, and connectance. Exclusive use of hyperbolic functional responses also affected trends observed in these metrics over time and underestimated annual variation in several metrics, which is important given that interaction strengths are typically estimated over relatively short time periods. Our findings highlight the need for more comprehensive research aimed at characterizing functional response relationships when modeling predator-prey interactions and food web structure and function, as we work toward a mechanistic understanding linking food web structure and community dynamics in natural systems.

Abstract The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal‐environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed regional variation in lynx‐environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%–100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well‐validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.

We present a reply to a recent article in Ecology and Evolution ("Measuring agreement among experts in classifying camera images of similar species" by Gooliaff and Hodges) that demonstrated a lack of consistency in expert-based classification of images of similar-looking species. We disagree with several conclusions from the study, and show that with some training, and use of multiple images that is becoming standard practice in camera-trapping studies, even nonexperts can identify similar sympatric species with high consistency.

International political boundaries challenge species conservation because they can hinder coordinated management. Peripheral transboundary species, those with a large portion of their range in one country and a small, peripheral portion in an adjacent country, may be particularly vulnerable to mismatches in management because peripheral populations are likely in greater conservation need than core populations. However, no systematic assessment of peripheral transboundary species or their status across borders has been attempted. We show that numerous species in three vertebrate taxa qualify as peripheral transboundary species in North America, and that these species are often protected differently across US–Canadian and US–Mexican borders. Asymmetries in cross‐border protection may threaten populations through disruption of connectivity between periphery and core regions and are especially relevant given expected impacts of climate change and the US–Mexico border wall. Our results highlight the need for greater international collaboration in management and planning decisions for transboundary species.

The persistence of cold-adapted species along their equatorial range edge (i.e., southern range edge for species in the Northern Hemisphere and northern range edge for species in the Southern Hemisphere) is threatened by climate change. These species will be challenged not just by unfavorable climatic regimes, but also by changing biotic interactions, which may be more intense along equatorial edges. However, we currently have a poor understanding of the nature of biotic interactions at range edges and how climate may mediate those interactions, particularly for cold-adapted mammals. We studied the distribution of threatened Canada lynx (Lynx canadensis) at their southern range edge in northern Washington, United States from 2014 to 2016. Using data collected from 397 camera-trap stations in snow-on and snow-off seasons, and single- and 2-species occupancy models, we investigated seasonal patterns of habitat selection and spatial association of lynx with their primary prey (snowshoe hares, Lepus americanus) and potential competitors (bobcats, Lynx rufus; cougars, Puma concolor). Single-species occupancy models revealed lynx distribution was strongly associated with snowshoe hare abundance and topographic variables related to lower temperatures and increased moisture. In contrast, bobcats and cougars were more generalized in their habitat associations or displayed the reverse response to environmental variables. Spatial overlap of the 3 felid species increased during snow-off seasons. Two-species occupancy models showed a decrease in use of camera sites by lynx when bobcats were present, suggesting lynx were avoiding their warm-adapted competitor. Taken together, these results suggest that biotic interactions are partly shaping large-scale lynx distribution patterns along their southern range edge. Increasing temperatures and loss of snow may result in a combination of habitat isolation and potential for increased competitive interactions for lynx at the margins of their range.

Interspecies foraging associations occur in a wide variety of vertebrate taxa and are maintained through gains in foraging efficiency and (or) predator avoidance. Despite their advantages, foraging associations often are variable in space and time and benefits may not accrue equally to all participants. In mammals, interspecies associations between solitary mammalian carnivores are rare. Coyotes (Canis latrans Say, 1823) and American badgers (Taxidea taxus (Schreber, 1777)) occasionally form hunting associations in pursuit of ground squirrels (Spermophilus armatus Kennicott, 1863), yet spatiotemporal variation in this association may be substantial. Better documentation of coyote–badger interactions across space and time will improve our understanding of the environmental drivers of this relationship and its benefit to both species. We used a broad-scale camera trapping array to document coyote–badger hunting associations. Out of 46 detections of badgers, we found five instances of hunting associations with coyotes, all of which occurred in mid- to late summer when ground squirrels were most active. Given our high rate of detection, these interactions are likely common on our study area. Habitat characteristics of the regions where we document coyote–badger interactions may have increased the likelihood of hunting associations. Our study demonstrates the effectiveness of camera traps for documenting this association and suggests that the coyote–badger system may be ideal for studying drivers of spatiotemporal variation in foraging associations.