Many populations near low-latitude range margins are declining in response to climate change, but most studies of trailing-edge populations have focused on single species. Using ten years (2014–2023) of avian survey data from a trailing-edge population hotspot in the Appalachian Mountains, USA, we tested the hypothesis that high-elevation communities would experience turnover through thermophilisation, as warm-adapted species near the center of their geographic ranges expand into regions formerly dominated by peripheral populations of cool-adapted species. Three of the nine cool-adapted populations decreased in abundance whereas six species exhibited little change. For warm-adapted populations, one of 16 decreased in abundance, 11 increased, and four exhibited no change. Our results indicate that warm-adapted species are expanding their ranges faster than the rate at which ranges of cool-adapted species are contracting, suggesting that community turnover will lag behind encroachment by warm-adapted species.

Species interactions and abiotic factors are important determinants of abundance and distribution, but accounting for biotic interactions is complicated by the fact that interactions occur at the individual-level at unknown spatial scales. Ignoring individual-level interactions can yield incorrect conclusions about biotic interactions when analyzing aggregated count data or presence-absence data. We present a hierarchical species distribution model that includes a Markov point process in which an individual’s location is dependent upon both abiotic variables and the locations of individuals of another species. The model can be regarded as a thinned point process in which encounter probability is a function of the distance between individual activity centers and survey locations. We applied the model to spatial capture-recapture data on two ecologically similar songbird species – hooded warbler (Setophaga citrina) and black-throated blue warbler (Setophaga caerulescens) – that segregate over a climate gradient in the southern Appalachian Mountains, USA. In spite of coarse spatial segregation and many ecological similarities between the two species, we found minimal evidence of spatial competition. There were strong, and opposing effects of climate on spatial variation in population densities, but spatial competition did not influence their distributions. A small simulation study indicated that the model can identify the distinct effects of environmental variation and biotic interactions on co-occurring species distributions. Unlike previous statistical models that attempt to infer competition from species-level co-occurrence data, the framework proposed here can be used to investigate how population-level patterns emerge from individual-level processes, while also allowing for inference on the spatial scale of biotic interactions. Our finding of minimal spatial competition between black-throated blue warbler and hooded warbler adds to the growing body of literature suggesting that, contrary to early theory from biogeography, abiotic factors may be more important than competition at low-latitude range margins.

Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for rigorous CU identification in the Canada Warbler (Cardellina canadensis), a highly mobile migratory bird species of conservation concern, and then integrate demographic modeling and genomic offset within a CU framework to guide conservation decisions. We find that whole-genome structure in this highly mobile species is primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two Evolutionarily Significant Units (ESU), and three putative Adaptive Units (AUs) in the South, East and Northwest. Quantification of genomic offset within each AU reveals significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change based on genomic offset predictions. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics-informed CUs provide a strong foundation for identifying current and potential future regional threats that can be used to manage highly mobile species in a rapidly changing world.