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Communities that occupy similar environments but vary in the richness of closely related species can illuminate how functional variation and species richness interact to fill ecological space in the absence of abiotic filtering, though this has yet to be explored on an oceanic island where the processes of community assembly may differ from continental settings. In discrete montane communities on the island of Sulawesi, local murine rodent (rats and mice) richness ranges from 7 to 23 species. We measured 17 morphological, ecological, and isotopic traits – both individually and as five multivariate traits – in 40 species to test for the expansion or packing of functional space among nine murine communities. We employed a novel probabilistic approach for integrating intraspecific and community‐level trait variance into functional richness. Trait‐specific and phylogenetic diversity patterns indicate dynamic community assembly due to variable niche expansion and packing on multiple niche axes. Locomotion and covarying traits such as tail length emerged as a fundamental axis of ecological variation, expanding functional space and enabling the niche packing of other traits such as diet and body size. Though trait divergence often explains functional diversity in island communities, we found that phylogenetic diversity facilitates functional space expansion in some conserved traits such as cranial shape, while more labile traits are overdispersed both within and between island clades, suggesting a role of niche complementarity. Our results evoke interspecific interactions, differences in trait lability, and the independent evolutionary trajectories of each of Sulawesi's six murine clades as central to generating the exceptional functional diversity and species richness in this exceptional, insular radiation. 

Abstract While museum voucher specimens continue to be the standard for species identifications, biodiversity data are increasingly represented by photographic records from camera traps and amateur naturalists. Some species are easily recognized in these pictures, others are impossible to distinguish. Here we quantify the extent to which 335 terrestrial nonvolant North American mammals can be identified in typical photographs, with and without considering species range maps. We evaluated all pairwise comparisons of species and judged, based on professional opinion, whether they are visually distinguishable in typical pictures from camera traps or the iNaturalist crowdsourced platform on a 4-point scale: (1) always, (2) usually, (3) rarely, or (4) never. Most (96.5%) of the 55,944 pairwise comparisons were ranked as always or usually distinguishable in a photograph, leaving exactly 2,000 pairs of species that can rarely or never be distinguished from typical pictures, primarily within clades such as shrews and small-bodied rodents. Accounting for a species geographic range eliminates many problematic comparisons, such that the average number of difficult or impossible-to-distinguish species pairs from any location was 7.3 when considering all species, or 0.37 when considering only those typically surveyed with camera traps. The greatest diversity of difficult-to-distinguish species was in Arizona and New Mexico, with 57 difficult pairs of species, suggesting the problem scales with overall species diversity. Our results show which species are most readily differentiated by photographic data and which taxa should be identified only to higher taxonomic levels (e.g., genus). Our results are relevant to ecologists, as well as those using artificial intelligence to identify species in photographs, but also serve as a reminder that continued study of mammals through museum vouchers is critical since it is the only way to accurately identify many smaller species, provides a wealth of data unattainable from photographs, and constrains photographic records via accurate range maps. Ongoing specimen voucher collection, in addition to photographs, will become even more important as species ranges change, and photographic evidence alone will not be sufficient to document these dynamics for many species. 

Abstract AimUnderstanding 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. InnovationWe 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 conclusionsInferences 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.