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We analysed the wild bee community sampled from 1921 to 2018 at a nature preserve in southern Michigan, USA, to study long-term community shifts in a protected area. During an intensive survey in 1972 and 1973, Francis C. Evans detected 135 bee species. In the most recent intensive surveys conducted in 2017 and 2018, we recorded 90 species. Only 58 species were recorded in both sampling periods, indicating a significant shift in the bee community. We found that the bee community diversity, species richness and evenness were all lower in recent samples. Additionally, 64% of the more common species exhibited a more than 30% decline in relative abundance. Neural network analysis of species traits revealed that extirpation from the reserve was most likely for oligolectic ground-nesting bees and kleptoparasitic bees, whereas polylectic cavity-nesting bees were more likely to persist. Having longer phenological ranges also increased the chance of persistence in polylectic species. Further analysis suggests a climate response as bees in the contemporary sampling period had a more southerly overall distribution compared to the historic community. Results exhibit the utility of both long-term data and machine learning in disentangling complex indicators of bee population trajectories. 

Abstract Sex‐associated differences in behavior can have large ecological consequences, especially in plant–pollinator communities where floral visitor behavior affects plant reproduction. Whether these differences are prevalent enough to impact community‐level processes, however, is unknown. Using 256 plant–pollinator communities, we built networks where the floral interactions of each sex were modeled separately, comparing observations to simulated networks where sex was randomized. We found that (1) in many species the sexes differed in their network roles and visited different partners, with females tending to visit more species and more peripheral species than males; (2) more generalist species differed more in network roles between the sexes; and (3) networks where nodes were separated by sex were more specialized than simulated networks, but were similarly resistant to perturbations. These findings suggest that despite variation among species, sex‐associated differences in behavior are large enough to impact the network roles of male and female pollinators and common enough to influence the interaction patterns of entire plant–pollinator communities. 

Despite their miniature brains, insects exhibit substantial variation in brain size. Although the functional significance of this variation is increasingly recognized, research on whether differences in insect brain sizes are mainly the result of constraints or selective pressures has hardly been performed. Here, we address this gap by combining prospective and retrospective phylogenetic-based analyses of brain size for a major insect group, bees (superfamily Apoidea). Using a brain dataset of 93 species from North America and Europe, we found that body size was the single best predictor of brain size in bees. However, the analyses also revealed that substantial variation in brain size remained even when adjusting for body size. We consequently asked whether such variation in relative brain size might be explained by adaptive hypotheses. We found that ecologically specialized species with single generations have larger brains—relative to their body size—than generalist or multi-generation species, but we did not find an effect of sociality on relative brain size. Phylogenetic reconstruction further supported the existence of different adaptive optima for relative brain size in lineages differing in feeding specialization and reproductive strategy. Our findings shed new light on the evolution of the insect brain, highlighting the importance of ecological pressures over social factors and suggesting that these pressures are different from those previously found to influence brain evolution in other taxa. 

Abstract Climate change is shifting the environmental cues that determine the phenology of interacting species. Plant–pollinator systems may be susceptible to temporal mismatch if bees and flowering plants differ in their phenological responses to warming temperatures. While the cues that trigger flowering are well‐understood, little is known about what determines bee phenology. Using generalised additive models, we analyzed time‐series data representing 67 bee species collected over 9 years in the Colorado Rocky Mountains to perform the first community‐wide quantification of the drivers of bee phenology. Bee emergence was sensitive to climatic variation, advancing with earlier snowmelt timing, whereas later phenophases were best explained by functional traits including overwintering stage and nest location. Comparison of these findings to a long‐term flower study showed that bee phenology is less sensitive than flower phenology to climatic variation, indicating potential for reduced synchrony of flowers and pollinators under climate change.