Vanderplanck M., Michez D., Albrecht M., Attridge E., Babin A., Bottero I., Breeze T., Brown M., Chauzat M.-P., Cini E., Costa C., De la Rua P., de Miranda J. R., Di Prisco G., Dominik C., Dzul D., Fiordaliso W., Gennaux S., Ghisbain G., Hodge S., Klein A.-M., Knapp J., Knauer A., Laurent M., Lefebvre V., Mänd M., Martinet B., Martinez-Lopez V., Medrzycki P., Pereira Peixa M. H., Potts S. G., Przybyla K., Raimets R., Rundlöf M., Schweiger O., Senapathi D., Serrano J., Stout J. C., Straw E. A., Tamburini G., Toktas Y., Gérard M.
Monitoring bee health in European agroecosystems using wing morphology and fat bodies.
Current global change substantially threatens pollinators, which directly impacts the pollination services underpinning the stability, structure and functioning of ecosystems. Amongst these threats, many synergistic drivers, such as habitat destruction and fragmentation, increasing use of agrochemicals, decreasing resource diversity, as well as climate change, are known to affect wild and managed bees. Therefore, reliable indicators for pollinator sensitivity to such threats are needed. Biological traits, such as phenotype (e.g. shape, size and asymmetry) and storage reserves (e.g. fat body size), are important pollinator traits linked to reproductive success, immunity, resilience and foraging efficiency and, therefore, could serve as valuable markers of bee health and pollination service potential. This data paper contains an extensive dataset of wing morphology and fat body content for the European honeybee (Apis mellifera) and the buff-tailed bumblebee (Bombus terrestris) sampled at 128 sites across eight European countries in landscape gradients dominated by two major bee-pollinated crops (apple and oilseed rape), before and after focal crop bloom and potential pesticide exposure. The dataset also includes environmental metrics of each sampling site, namely landscape structure and pesticide use. The data offer the opportunity to test whether variation in the phenotype and fat bodies of bees is structured by environmental factors and drivers of global change. Overall, the dataset provides valuable information to identify which environmental threats predominantly contribute to the modification of these traits.
