Plant-pollinator mutualisms rely upon the synchrony of interacting taxa. Climate change can disrupt this synchrony as phenological responses to climate vary within and across species. However, intra-and interspecific variation in phenological responses is seldom considered simultaneously, limiting our understanding of climate change impacts on interactions among taxa across their ranges.We investigated how variation in phenological sensitivity to climate can alter ecological interactions simultaneously within and among species using natural history collections and citizen science data. We focus on a unique system, comprising a wide-ranged spring ephemeral with varying color morphs (Claytonia virginica) and its specialist bee pollinator (Andrena erigeniae).We found strongly opposing trends in the phenological sensitivities of plants vs their pollinators. Flowering phenology was more sensitive to temperature in warmer regions, whereas bee phenology was more responsive in colder regions. Phenological sensitivity varied across flower color morphs. Temporal synchrony between flowering and pollinator activity was predicted to change heterogeneously across the species' ranges in the future.Our work demonstrates the complexity and fragility of ecological interactions in time and the necessity of incorporating variation in phenological responses across multiple axes to understand how such interactions will change in the future.
Aim: Species occurrence records are essential to understanding Earth's biodiversity and addressing global environmental issues, but do not always reflect actual locations of occurrence. Certain geographical coordinates are assigned repeatedly to thousands of observation/collection records. This may result from imperfect data management and georeferencing practices, and can greatly bias the inferred distribution of biodiversity and associated environmental conditions. Nonetheless, these 'biodiverse' coordinates are often overlooked in taxon-centric studies, as they are identifiable only in aggregate across taxa and datasets, and it is difficult to determine their true circumstance without in-depth, focused investigation. Here we assess highly recurring coordinates in biodiversity data to determine artificial hotspots of occurrences.Location: Global.
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