Null model analysis of species co‐occurrence patterns has long been used to gain insight into community assembly but is often limited to identifying non‐random patterns without providing clarity about underlying ecological mechanisms. This challenge is especially apparent when sampling units are spread across a heterogeneous landscape or along an environmental gradient because multiple mechanisms can produce similar co‐occurrence patterns. We developed a trait‐based approach for discriminating between environmental filtering and biotic interactions as the probable driver of co‐occurrence patterns across environmentally heterogeneous sites. We demonstrate our framework by analyzing the co‐occurrence of small mammals over elevation in three independent mountain ranges in the Great Basin of the western United States. Our sampling design accounts for landscape scale environmental variability and within‐site habitat heterogeneity. We identified 52 non‐random species pairs, of which 36 were aggregated and 16 were segregated. For each pair, we determined which mechanism was the likely ecological explanation using a hypothesis‐testing framework based on functional trait similarity. Expectations of biotic interactions were based on similarity of diet and body size whereas habitat affinity and geographic range were used for environmental filtering. Only four pairs were consistent with expectations under biotic interactions, including pairs for which competitive exclusion has previously been documented. In addition to analyzing individual pairs, we used binomial tests of observed versus expected totals of intra‐ and inter‐guild pairs to determine assemblage‐wide deviations from random community structure. Signatures of environmental filtering were consistent across mountain ranges and scales. Despite differences in species composition and significant pairs among data sets, our approach revealed consistent mechanistic conclusions, emphasizing the value of trait‐based methods to co‐occurrence and community assembly.

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Aim Understanding how ecological communities are assembled remains a grand challenge in ecology with direct implications for charting the future of biodiversity. Trait‐based methods have emerged as the leading approach for quantifying functional community structure (convergence, divergence) but their potential for inferring assembly processes rests on accurately measuring functional dissimilarity among community members. Here, we argue that trait resolution (from finest‐resolution continuous measurements to coarsest‐resolution binary categories) remains a critically overlooked methodological variable, even though categorical classification is known to mask functional variability and inflate functional redundancy among species or individuals. Innovation We present the first detailed predictions of trait resolution biases and demonstrate, with simulations, how the distortion of signal strength by increasingly coarse‐resolution traits can fundamentally alter functional structure patterns and the interpretation of causative ecological processes (e.g. abiotic filters, biotic interactions). We show that coarser trait data impart different impacts on the signals of divergence and convergence, implying that the role of biotic interactions may be underestimated when using coarser traits. Furthermore, in some systems, coarser traits may overestimate the strength of trait convergence, leading to erroneous support for abiotic processes as the primary drivers of community assembly or change. Main conclusions Inferences of assembly processes must account for trait resolution to ensure robust conclusions, especially for broad‐scale studies of comparative community assembly and biodiversity change. Despite recent improvements in the collection and availability of trait data, great disparities continue to exist among taxa in the number and availability of continuous traits, which are more difficult to acquire for large numbers of species than coarse categorical assignments. Based on our simulations, we urge the consideration of trait resolution in the design and interpretation of community assembly studies and suggest a suite of practical solutions to address the pitfalls of trait resolution biases.

Aim We used the Holarctic northern red-backed vole (Myodes rutilus) as a model organism to improve our understanding of how dynamic, northern high-latitude environments have affected the genetic diversity, demography and distribution of boreal organisms. We tested spatial and temporal hypotheses derived from previous mitochondrial studies, comparative phylogeography, palaeoecology and the fossil record regarding diversification of M. rutilus in the Palaearctic and Beringia.Location High-latitude biomes across the Holarctic.Methods We used a multilocus phylogeographical approach combined with species distribution models to characterize the biogeographical and demographic history of M. rutilus. Our molecular assessment included widespread sampling (more than 100 localities), species tree reconstruction and population genetic analyses.Results Three well-differentiated mitochondrial lineages correspond to geographical regions, but nuclear genes were less structured. Multilocus divergence estimates indicated that diversification of M. rutilus was driven by events occurring before c. 100 ka. Population expansion in all three clades occurred prior to the Last Glacial Maximum (LGM) and presumably led to secondary contact. Species distribution modelling predicted a broad LGM distribution consistent with population and range expansion during this period. Main conclusionsThe biogeographical history of M. rutilus differs from other boreal forest-associated species. Well-differentiated clades and the existence of secondary contact zones indicate prolonged isolation and persistence in Eurasian and Beringian refugia. Dynamic demographic and distributional changes emphasize the impact of pre-LGM glacial-interglacial cycles on contemporary geographical structure. The Bering Strait was not a significant factor in the diversification of northern red-backed voles.