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Different models of speciation predict contrasting patterns in the relationship between the dispersal ability of lineages and their diversification rates. This relationship is expected to be negative in isolation-limited models and positive in founder-event models. In addition, the combination of negative and positive effects of dispersal on speciation can result in higher diversification rates at intermediate levels of dispersal ability. Using molecular phylogenies to estimate diversification rates, and wing morphology to estimate dispersal ability, we analysed the influence of dispersal on diversification in the avifauna of Australasian archipelagoes. Contrary to expectations given the fragmented nature of island systems, the relationship between dispersal ability and diversification rate was monotonically negative. While multiple mechanisms could generate this pattern, they all share a phase of range expansion that is decoupled from speciation.

Background Rapid morphological change is emerging as a consequence of climate change in many systems. It is intuitive to hypothesize that temporal morphological trends are driven by the same selective pressures that have established well-known ecogeographic patterns over spatial environmental gradients (e.g., Bergman’s and Allen’s rules). However, mechanistic understanding of contemporary morphological shifts is lacking. Results We combine morphological data and whole genome sequencing from a four-decade dataset in the migratory bird hermit thrush ( Catharus guttatus ) to test whether morphological shifts over time are accompanied by genetic change. Using genome-wide association, we identify alleles associated with body size, bill length, and wing length. Shifts in morphology and concordant shifts in morphology-associated alleles over time would support a genetic basis for the observed changes in morphology over recent decades, potentially an adaptive response to climate change. In our data, bill size decreases were paralleled by genetic shifts in bill size-associated alleles. On the other hand, alleles associated with body size showed no shift in frequency over time. Conclusions Together, our results show mixed support for evolutionary explanations of morphological response to climate change. Temporal shifts in alleles associated with bill size support the hypothesis that selection is driving temporal morphological trends. The lack of evidence for genetic shifts in body size alleles could be explained by a large role of plasticity or technical limitations associated with the likely polygenic architecture of body size, or both. Disentangling the mechanisms responsible for observed morphological response to changing environments will be vital for predicting future organismal and population responses to climate change.

Increasingly, natural history museum collections are being used to generate large‐scale morphological datasets to address a range of macroecological and macroevolutionary questions. One challenge to this approach is that large numbers of individuals either from a single species or from taxonomically broad sets of species may be necessary to characterize morphology at the relevant spatial, phylogenetic or temporal scales. We present ‘Skelevision’, a method for rapidly handling, photographing and measuring skeletal specimens with a computer vision approach that uses a deep neural network to segment the photographs of specimens into individual bones, and identify and measure functional aspects of those bones. We demonstrate the scale of what is feasible with Skelevision by estimating 11 functional traits from 11 different bones for 12,450 bird skeletal specimens spanning 1,882 species of passerines (~32% of all passerine diversity). We quantify the accuracy of Skelevision estimates by comparing them to handmade measurements for 174 specimens from 115 species across 79 genera that span 59 families. Skelevision is precise, with a mean standard deviation of 0.86 mm for repeated independent measurements of individual bones, and is extremely accurate, with a mean RMSE of 0.89 mm across all traits when compared to handmade measurements. There is minimal phylogenetic signal in the measurement error (mean Pagel's λ across traits = 0.13), and Skelevision estimates are robust to variation in the degree to which specimens remain articulated. This approach has several important advantages over traditional methods for building large‐scale morphological datasets (e.g. measurements from long‐term field‐based operations or handmade measurements of museum specimens). First, measuring new specimens only requires the collection of photographs, which can then be measured automatically, and effectively instantaneously, with the neural network. This is a significant departure from the time and skill required to measure skeletal specimens by hand. Second, the measurements are repeatable. Third, even as the dataset of photographed specimens expands, the amount of annotation data needed to measure new traits on all of the photographed specimens using the neural network will remain fixed and can be done without re‐capturing images.

The relative importance of evolutionary history and ecology for traits that drive ecosystem processes is poorly understood. Consumers are essential drivers of nutrient cycling on coral reefs, and thus ecosystem productivity. We use nine consumer “chemical traits” associated with nutrient cycling, collected from 1,572 individual coral reef fishes (178 species spanning 41 families) in two biogeographic regions, the Caribbean and Polynesia, to quantify the relative importance of phylogenetic history and ecological context as drivers of chemical trait variation on coral reefs. We find: ( 1 ) phylogenetic relatedness is the best predictor of all chemical traits, substantially outweighing the importance of ecological factors thought to be key drivers of these traits, ( 2 ) phylogenetic conservatism in chemical traits is greater in the Caribbean than Polynesia, where our data suggests that ecological forces have a greater influence on chemical trait variation, and ( 3 ) differences in chemical traits between regions can be explained by differences in nutrient limitation associated with the geologic context of our study locations. Our study provides multiple lines of evidence that phylogeny is a critical determinant of contemporary nutrient dynamics on coral reefs. More broadly our findings highlight the utility of evolutionary history to improve prediction in ecosystem ecology. The relative importance of evolutionary history and ecology for traits that drive ecosystem processes is poorly understood. Analyzing nine traits associated with fish stoichiometry from 1,572 individuals yields multiple lines of evidence that phylogeny is a critical determinant of nutrient cycling in coral reefs.

Migratory birds have the capacity to shift their migration phenology in response to climatic change. Yet the mechanistic underpinning of changes in migratory timing remain poorly understood. We employed newly developed global positioning system (GPS) tracking devices and long-term dataset of migration passage timing to investigate how behavioral responses to environmental conditions relate to phenological shifts in American robins (Turdus migratorius) during spring migration to Arctic-boreal breeding grounds. We found that over the past quarter-century (1994-2018), robins have migrated ca. 5 d/decade earlier. Based on GPS data collected for 55 robins over three springs (2016-2018), we found the arrival timing and likelihood of stopovers, and timing of arrival to breeding grounds, were strongly influenced by dynamics in snow conditions along migratory paths. These findings suggest plasticity in migratory behavior may be an important mechanism for how long-distance migrants adjust their breeding phenology to keep pace with advancement of spring on breeding grounds.

Understanding how co‐occurring species divide ecological space is a central issue in ecology. Functional traits have the potential to serve as a means for quantitatively assessing niche partitioning by different species based on their ecological attributes, such as morphology, behavior, or trophic habit. This enables testing ecological and evolutionary questions using functional traits at spatio‐temporal scales that are not feasible using traditional field methods. Both rapid evolutionary change and inter‐ and intraspecific competition, however, may limit the utility of morphological functional traits as indicators of how niches are partitioned. To address how behavior and morphology interact, we quantified foraging behavior of mixed‐species flocks of birds in the Solomon Islands to test whether behavior and morphology are correlated in these flocks. We find that foraging behavior is significantly correlated with morphological traits (p = .05), but this correlation breaks down after correcting for phylogenetic relatedness (p = .66). These results suggest that there are consistent correlations between aspects of behavior and morphology at large taxonomic scales (e.g., across genera), but the relationship between behavior and morphology depends largely on among‐clade differences and may be idiosyncratic at shallower scales (e.g., within genera). As a result, general relationships between behaviors and morphology may not be applicable when comparing close relatives. Understanding how co‐occurring species divide ecological space is a central issue in ecology. We demonstrate that morphology may reflect behavioral niche partitioning at large scales, but among islands in the Solomon Archipelago, shifts in avian morphology and behavior are decoupled. General relationships between behaviors and morphology may not be applicable when comparing close relatives.

Plant diversity has a positive influence on the number of ecosystem functions maintained simultaneously by a community, or multifunctionality. While the presence of multiple trophic levels beyond plants, or trophic complexity, affects individual functions, the effect of trophic complexity on the diversity–multifunctionality relationship is less well known. To address this issue, we tested whether the independent or simultaneous manipulation of both plant diversity and trophic complexity impacted multifunctionality using a mesocosm experiment from Cedar Creek, Minnesota, USA. Our analyses revealed that neither plant diversity nor trophic complexity had significant effects on single functions, but trophic complexity altered the diversity–multifunctionality relationship in two key ways: It lowered the maximum strength of the diversity–multifunctionality effect, and it shifted the relationship between increasing diversity and multifunctionality from positive to negative at lower function thresholds. Our findings highlight the importance to account for interactions with higher trophic levels, as they can alter the biodiversity effect on multifunctionality. We used a manipulated grassland mesocosm experiment to test the effects of higher trophic levels on ecosystem multifunctionality. We find that the number and identity of trophic levels affect the jack‐of‐all‐trades relationship between biodiversity and ecosystem multifunctionality. Our findings have implications in refining predictions for ecosystem multifunctionality in the face of ongoing biodiversity loss.

Large comparative datasets of avian functional traits have been used to address a wide range of questions in ecology and evolution. To date, this work has been constrained by the limited availability of skeletal trait datasets that include extensive inter- and intra-specific sampling. We use computer vision to identify and measure bones from photographs of museum skeletal specimens to assemble an extensive dataset of functionally important skeletal elements in birds. The dataset spans 2,057 species of birds (Aves: Passeriformes) and includes measurements of 12 skeletal elements from 14,419 individuals. In addition to the trait values directly measured from photographs, we leverage the multi-dimensional nature of our dataset and known phylogenetic relationships of the species to impute missing data under an evolutionary model. To facilitate use of the dataset, the taxonomy has been reconciled with an existing comprehensive avian phylogeny and an additional dataset of external functional traits for all birds.

Island systems have long played a central role in the development of ecology and evolutionary biology. However, while many empirical studies suggest species differ in vital biogeographic rates, such as dispersal abilities, quantitative methods have had difficulty incorporating such differences into analyses of whole-assemblages. In particular, differences in dispersal abilities among species can cause variation in the spatial clustering and localization of species distributions. Here, we develop a single, hierarchical Bayes, assemblage-wide model of 252 bird species distributions on the islands of northern Melanesia and use it to investigate a) whether dispersal limitation structures bird assemblages across the archipelago, b) whether species differ in dispersal ability, and c) test the hypothesis that wing aspect ratio, a trait linked to flight efficiency, predicts differences inferred by the model. Consistent with island biogeographic theory, we found that individual species were more likely to occur on islands with greater area, and on islands near to other islands where the species also occurred. However, species showed wide variation in the importance and spatial scale of these clustering effects. The importance of clustering in distributions was greater for species with low wing aspect ratios, and the spatial scale of clustering was also smaller for low aspect ratio species. These findings suggest that the spatial configuration of islands interacts with species dispersal ability to affect contemporary distributions, and that these species differences are detectable in occurrence patterns. More generally, our study demonstrates a quantitative, hierarchical approach that can be used to model the influence of dispersal heterogeneity in diverse assemblages and test hypotheses for how traits drive dispersal differences, providing a framework for deconstructing ecological assemblages and their drivers.

Ecosystems vary widely in their responses to biodiversity change, with some losing function dramatically while others are highly resilient. However, generalizations about how species- and community-level properties determine these divergent ecosystem responses have been elusive because potential sources of variation (e.g., trophic structure, compensation, functional trait diversity) are rarely evaluated in conjunction. Ecosystem vulnerability, or the likely change in ecosystem function following biodiversity change, is influenced by two types of species traits: response traits that determine species’ individual sensitivities to environmental change, and effect traits that determine a species’ contribution to ecosystem function. Here we extend the response-effect trait framework to quantify ecosystem vulnerability and show how trophic structure, within-trait variance, and among-trait covariance affect ecosystem vulnerability by linking extinction order and functional compensation. Using in silico trait-based simulations we found that ecosystem vulnerability increased when response and effect traits positively covaried, but this increase was attenuated by decreasing trait variance. Contrary to expectations, in these communities, both functional diversity and trophic structure increased ecosystem vulnerability. In contrast, ecosystem functions were resilient when response and effect traits covaried negatively, and variance had a positive effect on resiliency. Our results suggest that although biodiversity loss is often associated with decreases in ecosystem functions, such effects are conditional on trophic structure, and the variation within and covariation among response and effect traits. Taken together, these three factors can predict when ecosystems are poised to lose or gain function with ongoing biodiversity change.