Distribution shifts of tree species are likely to be highly dependent upon population performance at distribution edges. Understanding the drivers of aspects of performance, such as growth, at distribution edges is thus crucial to accurately predicting responses of tree species to climate change. Here, we use a Bayesian model and sensitivity analysis to partition the effects of climate and crowding, as a metric of competition, on radial growth of three dominant conifer species along montane ecotones in the Rocky Mountains. These ecotones represent upper and lower distribution edges of two species, and span the distribution interior of the third species. Our results indicate a greater influence of climate (i.e., temperature and precipitation) than crowding on radial growth. Competition importance appears to increase towards regions of more favorable growing conditions, and precise responses to crowding and climate vary across species. Overall, our results suggest that climate will likely be the most important determinant of changes in tree growth at distribution edges of these montane conifers in the future.

Abstract. Species distributions have often been assumed to represent climatic limitations, yet recent evidence has challenged these assumptions and emphasized the potential importance of biotic interactions, dispersal limitation, and disturbance. Despite significant investigation into these factors, an integrated understanding of where and when they may be important is lacking. Here, we review evidence for the factors underlying the historical and contemporary distributions of North American tree species and argue that a cohesive conceptual framework must be informed by an understanding of species ecological and evolutionary history. We further demonstrate that available evidence offers little indication of a significant, independent influence of biotic interactions or dispersal limitation on species distributions. Disturbance may provide important constraints on distributions in limited contexts. Overall, historic and contemporary evidence suggests that species distributions are strongly influenced by climate, yet examples of disequilibrium with climate abound. We propose that differences among life stages and the impacts of human land use may contribute to explain these inconsistencies and are deserving of greater research attention.

Aim:The rate and magnitude of climate-induced tree range shifts may be influenced by range-wide variation in recruitment, which acts as a bottleneck in tree range dynamics. Here, we compare range predictions made using standard species distribution models (SDMs) and an integrated metamodelling approach that assimilates data on adult occurrence, seedling recruitment dynamics, and seedling survival under both current and future climate, and evaluate the degree to which information provided by seedling data can improve predictions of range dynamics. Location:The interior west region of the United States. Time period: 1990-2015.Major taxa studied: Five widespread conifer tree species. Methods:We used a previously published metamodelling framework to combine information from SDMs of adult tree occurrence and sub-models describing seedling recruitment dynamics and seedling survival into a single set of predictions for the probability of occurrence for each species. The integrated framework links sub-models to a SDM to generate cohesive predictions that consider information and uncertainty contained in all datasets. We then compared predictions from the integrated model to SDM predictions.Results: Integration of seedling information served primarily to improve characterization of model uncertainty, particularly in regions where recruitment may be limited by temperatures that exceed seedling tolerance. Integration constrained response curves very slightly across most climate gradients, particularly across temperature gradients. These differences were primarily attributable to the isolated effects of temperature on seedling survival and not to recruitment dynamics. Main conclusions:Our results indicate that range-wide variation in recruitment both now and in the future is most uncertain along the edges of occupied regions, which increases uncertainty in projections of future species occurrence along range margins. Overall, the broad-scale climatic dependence of the regeneration niche appears weaker than that of the adult climatic niche, and this enhances uncertainty in predicting range-wide responses of these species to climate change. K E Y W O R D SBayesian, climate change, demography, life stage, range dynamics, recruitment, species distribution modelling, tree seedlings, western United States | 103 COPENHAVER-PARRY Et Al.

Aims: Species distributions are hypothesized to be underlain by a complex association of processes that span multiple spatial scales including biotic interactions, dispersal limitation, fine-scale resource gradients and climate. Species disequilibrium with climate may reflect the effects of non-climatic processes on species distributions, yet distribution models have rarely directly considered non-climatic processes. Here, we use a Joint Species Distribution Model (JSDM) to investigate the influence of nonclimatic factors on species co-occurrence patterns and to directly quantify the relative influences of climate and alternative processes that may generate correlated responses in species distributions, such as species interactions, on tree co-occurrence patterns.Location: US Rocky Mountains. Methods:We apply a Bayesian JSDM to simultaneously model the co-occurrence patterns of ten dominant tree species across the Rocky Mountains, and evaluate climatic and residual correlations from the fitted model to determine the relative contribution of each component to observed co-occurrence patterns. We also evaluate predictions generated from the fitted model relative to a single-species modelling approach.Results: For most species, correlation due to climate covariates exceeded residual correlation, indicating an overriding influence of broad-scale climate on co-occurrence patterns. Accounting for covariance among species did not significantly improve predictions relative to a single-species approach, providing limited evidence for a strong independent influence of species interactions on distribution patterns. Conclusions:Overall, our findings indicate that climate is an important driver of regional biodiversity patterns and that interactions between dominant tree species contribute little to explain species co-occurrence patterns among Rocky Mountain trees.

Community-level models (CLMs) aim to improve species distribution modeling (SDM) methods by attempting to explicitly incorporate the influences of interacting species. However, the ability of CLMs to appropriately account for biotic interactions is unclear. We applied CLM and SDM methods to predict the distributions of three dominant conifer tree species in the U.S. Rocky Mountains and compared CLM and SDM predictive accuracy as well as the ability of each approach to accurately reproduce species co-occurrence patterns. We specifically evaluated the performance of two statistical algorithms, MARS and CForest, within both CLM and SDM frameworks. Across all species, differences in SDM and CLM predictive accuracy were slight and can be attributed to differences in model structure rather than accounting for the effects of biotic interactions. In addition, CLMs generally over-predicted species cooccurrence, while SDMs under-predicted co-occurrence. Our results demonstrate no real improvement in the ability of CLMs to account for biotic interactions relative to SDMs. We conclude that alternative modeling approaches are needed in order to accurately account for the effects of biotic interactions on species distributions.