%0 Journal Article
%T A century of wild bee sampling: historical data and neural network analysis reveal ecological traits associated with species loss.
%A Graham KK
%A Glaum P
%A Hartert J
%A Gibbs J
%A Tucker E
%A Isaacs R
%A Valdovinos FS
%J Proc Biol Sci
%V 291
%N 2028
%D 2024 Aug
%M 39137885
%F 5.53
%R 10.1098/rspb.2023.2837
%X 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.