|KAZENEL, MELANIE - University Of New Mexico|
|WRIGHT, KAREN - Texas A&M University|
|BETTINELLI, JULIETA - University Of New Mexico|
|WHITNEY, KENNETH - University Of New Mexico|
Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/26/2019
Publication Date: 1/20/2020
Citation: Kazenel, M.R., Wright, K.W., Bettinelli, J., Griswold, T.L., Whitney, K.D. 2020. Predicting changes in bee assemblages following state transitions at North American dryland ecotones. Scientific Reports. 10. https://doi.org/10.1038/s41598-020-57553-2.
Interpretive Summary: Across the globe drylands changes in the relationships among their plants and animals. Bees are especially diverse in drylands. They vary not only in overall diversity and in the kinds of species present, they also vary across the flowering season. This variability could have implications for shifts in the timing of bee activity, and thus effect pollination. We compared bee communities and their seasonality among three dryland ecosystem types of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland) to better understand how future changes may influence bee communities. Samples were taken at two week intervals across the flowering season (March – October) for thirteen years (2002-2014) resulting in more than 70,000 specimens. Bee abundance, composition, and diversity differed among the three ecosystem type. But surprisingly, seasonal differences were an much greater than these ecosystem differences. This suggests the potential for future environmental change to alter the timing of bee activity both within and across dryland ecosystem types.Common rather than rare species were responsible for these trends. We were able to identify both specialist and generalist bee species that are indicators for each ecosystem type and for each month. These abundant species could be particularly helpful as sentinels of future change. The work also suggests that shifts in timing of bee activity, along with changes in the ecosystems, may bring about altered dynamics in these communities.
Technical Abstract: Drylands worldwide are experiencing ecosystem state transitions: the expansion of some ecosystem types at the expense of others. Bees in drylands are particularly abundant and diverse, with potential for large variation across dryland ecotones. Among ecosystem types, bees may not only vary in diversity or composition, but also in their seasonality, which could have implications for bee phenological shifts under global change and for the future of ecosystem services provided by bees. We compared bee communities and their seasonality among three dryland ecosystem types of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland) to better understand how future ecosystem state transitions may influence bee communities. Using passive funnel traps, we caught bees during two-week intervals from March to October over the period of 2002 – 2014. The resulting dataset included 302 bee species and >70,500 individuals. Our analyses focused on bee assemblage variation among ecosystem types and intra-annually. Bee abundance, composition, and diversity differed among ecosystem types, but seasonal differences were an order of magnitude larger than ecosystem differences, suggesting the potential for future global environmental change to alter bee phenology both within and across dryland ecosystem types. Common rather than rare species drove the observed bee assemblage trends, and we identified both specialist and generalist bee species as indicators of each ecosystem type or month. These abundant species and indicator species could be particularly informative as sentinels of community-wide responses to future change. Our work suggests that shifts in bee phenology, along with ecosystem state transitions, may bring about altered community dynamics, and that predicting the consequences of global change for bee assemblages will require accounting for both within-year and among-habitat variation.