Understanding the timing of native bee activity is a critical underpinning of predicting changes in their abundance, biodiversity, and ecosystem service potential. Though most native bee species are active only a few weeks out of the year, together they comprise a fleet of important pollinators that span the flowering seasons of diverse ecosystems worldwide. Knowledge of how native bee species vary in phenology across their range, however, remains extremely limited. Adequate data to answer questions about trends in bee species phenology across spatiotemporal gradients is available for only a few groups of charismatic (e.g. Bombus) or agriculturally-relevant (e.g. Osmia lignaria) species. Instead, museum records are often used to estimate native bee declines without evaluating their suitability for this purpose or how methodological biases may influence results. By combining results from six systematic bee inventory efforts across the U.S. with data from museum specimens collected in the same regions, we compiled a dataset of over half a million records to test whether opportunistic data can portray native bee species activity as well as intensive inventory efforts. To assess the generalizability of our results beyond common species, we also evaluated the influence of functional traits and ecoregion on phenological patterns.
Results/Conclusions
From our compiled dataset, we selected 45 bee species for study based on a minimum number of records in both inventory and opportunistic data types, and a diversity of traits and ecoregions represented. Species were classified into one of five North American regions and categories of five functional traits: sociality (solitary or social), nesting habits (above or below ground), foraging preferences (specialist or generalist), voltinism (one or multiple generations per year), and body size (continuous). Permutation tests revealed that museum and inventory data often produce statistically different results for the flight duration of a native bee species, the number of peaks in abundance during a season, and the date of the highest peak. As these are all metrics that may be used to estimate changes in native bee activity, our results have broad, cautionary implications for how we monitor and assess trends among native bees, and how we talk about this hot-button issue both publicly and within the scientific community. Our findings also illustrate the need for expanded native bee species monitoring and consideration of data source limitations when asking questions about these important pollinators.