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Abstract Climate is a fundamental driver of macroecological patterns in functional trait variation. However, many of the traits that have outsized effects on thermal performance are complex, multi‐dimensional, and challenging to quantify at scale.To overcome this challenge, we leveraged techniques in deep learning and computer vision to quantify hair coverage and lightness of bees, using images of a diverse and widely distributed sample of museum specimens.We demonstrate that climate shapes variation in these traits at a global scale, with bee lightness increasing with maximum environmental temperatures (thermal melanism hypothesis) and decreasing with annual precipitation (Gloger's Rule).We found that deserts are hotspots for bees covered in light‐coloured hairs, adaptations that may mitigate heat stress and represent convergent evolution with other desert organisms.These results support major ecogeographical rules in functional trait variation and emphasize the role of climate in shaping bee phenotypic diversity. Read the freePlain Language Summaryfor this article on the Journal blog. 

Abstract Climatic factors are known to shape the expression of social behaviours. Likewise, variation in social behaviour can dictate climate responses. Understanding interactions between climate and sociality is crucial for forecasting vulnerability and resilience to climate change across animal taxa.These interactions are particularly relevant for taxa like bees that exhibit a broad diversity of social states. An emerging body of literature aims to quantify bee responses to environmental change with respect to variation in key functional traits, including sociality. Additionally, decades of research on environmental drivers of social evolution may prove fruitful for predicting shifts in the costs and benefits of social strategies under climate change.In this review, we explore these findings to ask two interconnected questions: (a) how does sociality mediate vulnerability to climate change, and (b) how might climate change impact social organisation in bees? We highlight traits that intersect with bee sociality that may confer resilience to climate change (e.g. extended activity periods, diet breadth, behavioural thermoregulation) and we generate predictions about the impacts of climate change on the expression and distribution of social phenotypes in bees.The social evolutionary consequences of climate change will be complex and heterogeneous, depending on such factors as local climate and plasticity of social traits. Many contexts will see an increase in the frequency of eusocial nesting as warming temperatures accelerate development and expand the temporal window for rearing a worker brood. More broadly, climate‐mediated shifts in the abiotic and biotic selective environments will alter the costs and benefits of social living in different contexts, with cascading impacts at the population, community and ecosystem levels. 

ABSTRACT Community or volunteer participation in research has the potential to significantly help mobilize the wealth of biodiversity and functional ecological data housed in natural history collections. Many such projects recruit community scientists to transcribe specimen label data from images; a next step is to task community scientists with conducting straightforward morphological measurements (e.g., body size) from specimen images. We investigated whether community science could be an effective approach to generating significant body size datasets from specimen images generated by museum digitization initiatives. Using the community science platform Notes from Nature, we engaged community scientists in a specimen measurement task to estimate body size (i.e., intertegular distance) from images of bee specimens. Community scientists showed high engagement and completion of this task, with each user measuring 43.6 specimens on average and self‐reporting successful measurement of 98.0% of the images. Community scientist measurements were significantly larger than measurements conducted by trained researchers, though the average measurement error was only 2.3%. These results suggest that community science participation could be an effective approach for bee body size measurement, for descriptive studies or for research questions where this degree of expected error is deemed acceptable. For larger‐bodied organisms (e.g., vertebrates), where modest measurement errors represent a smaller proportion of body size, community science approaches may be particularly effective. Methods we present here may serve as a blueprint for future projects aimed at engaging the public in biodiversity and collections‐based research efforts.