Distance models reveal biases associated with passive trapping methods for measuring wild bee abundance

There is overwhelming evidence of declines in native bee populations and therefore a need for increased monitoring to track these declines and assist in conservation and restoration efforts. Bees can be sampled non-lethally through visual surveys (e.g., distance transects) or lethally through active (e.g., hand netting) or passive (e.g., traps that lure insects from afar) methods. These lethal methods suffer from imperfect detection that is difficult to account for and can confound inferences about habitat characteristics. Additionally, evidence suggests that lethal sampling methods can even invert habitat quality patterns such that high-quality sites yield fewer individuals and low-quality sites yield more individuals.To study potential biases associated with imperfect detection, we used hierarchical density estimation with visual surveys to estimate density of bees within 40 young forest patches across Pennsylvania, USA. We surveyed bee communities non-lethally using visual surveys and lethally using blue-vane traps and bee bowls every two weeks between May and September 2019. We collected data on blooming flowers, vegetation structure, and weather during times of survey.We found that bee densities estimated from distance transects had a positive relationship with floral resource availability. In contrast, abundance measured via bee bowls and blue-vane traps had no relationship, or sometimes even negative trends with habitat quality, including floral resource availability. Raw bee counts within 2-m of the transect always correlated with modeled densities, showing that some methods do not share the biases of attractive traps.Our study demonstrates that failing to account for imperfect detection can impact the interpretation of pollinator surveys and adds to a growing body of literature that acknowledges the value of distance sampling for insects like bees to better understand species’ habitat needs and to monitor populations for conservation.