Effects of study design parameters on estimates of bee abundance and richness in agroecosystems: a meta-analysis.

Pollinators are critical for agricultural production and food security, leading to many ongoing surveys of pollinators (especially bees) in crop and adjacent landscapes. These surveys have become increasingly important to better understand the community of potential pollinators, quantify relative insect abundance, and secure crop ecosystem services. However, as some bee populations are declining, there is a need to align and improve bee survey efforts, so that they can best meet research and conservation goals, particularly in light of the logistical and financial constraints of conducting such studies. Here, we mined the existing literature on bee surveys in or around agricultural lands to better understand how sampling methods can be optimized to maximize estimates of 2 key measures of bee communities (abundance and richness). After reviewing 72 papers spanning 20 yr of publication, we found that study duration, number of sites, sampling time, and sampling method most significantly influenced abundance, while the number of trips per year and collection method significantly influenced richness. Our analysis helps to derive thresholds, priorities, and recommendations that can be applied to future studies describing bee communities in agroecosystems.

Bee species richness through time in an urbanizing landscape of the southeastern United States.

Compared to non-urban environments, cities host ecological communities with altered taxonomic diversity and functional trait composition. However, we know little about how these urban changes take shape over time. Using historical bee (Apoidea: Anthophila) museum specimens supplemented with online repositories and researcher collections, we investigated whether bee species richness tracked urban and human population growth over the past 118 years. We also determined which species were no longer collected, whether those species shared certain traits, and if collector behavior changed over time. We focused on Wake County, North Carolina, United States where human population size has increased over 16 times over the last century along with the urban area within its largest city, Raleigh, which has increased over four times. We estimated bee species richness with occupancy models, and rarefaction and extrapolation curves to account for imperfect detection and sample coverage. To determine if bee traits correlated with when species were collected, we compiled information on native status, nesting habits, diet breadth, and sociality. We used non-metric multidimensional scaling to determine if individual collectors contributed different bee assemblages over time. In total, there were 328 species collected in Wake County. We found that although bee species richness varied, there was no clear trend in bee species richness over time. However, recent collections (since 2003) were missing 195 species, and there was a shift in trait composition, particularly lost species were below-ground nesters. The top collectors in the dataset differed in how often they collected bee species, but this was not consistent between historic and contemporary time periods; some contemporary collectors grouped closer together than others, potentially due to focusing on urban habitats. Use of historical collections and complimentary analyses can fill knowledge gaps to help understand temporal patterns of species richness in taxonomic groups that may not have planned long-term data.

Effects of planted pollinator habitat on pathogen prevalence and interspecific detection between bee species.

Shared resources can instigate pathogen spread due to large congregations of individuals in both natural and human modified resources. Of current concern is the addition of pollinator habitat in conservation efforts as it attracts bees of various species, potentially instigating interspecific sharing of pathogens. Common pathogens have been documented across a wide variety of pollinators with shared floral resources instigating their spread in some, but not all, cases. To evaluate the impact of augmented pollinator habitat on pathogen prevalence, we extracted RNA from samples of eight bee species across three families and screened these samples for nine pathogens using RT-qPCR. We found that some habitat characteristics influenced pathogen detection; however, we found no evidence that pathogen detection in one bee species was correlated with pathogen detection in another. In fact, pathogen detection was rare in wild bees. While gut parasites were detected in 6 out of the 8 species included in this study, viruses were only detected in honey bees. Further, virus detection in honey bees was low with a maximum 21% of samples testing positive for BQCV, for example. These findings suggest factors other than the habitat itself may be more critical in the dissemination of pathogens among bee species. However, we found high relative prevalence and copy number of gut parasites in some bee species which may be of concern, such as Bombus pensylvanicus. Long-term monitoring of pathogens in different bee species at augmented pollinator habitat is needed to evaluate if these patterns will change over time.