Community diversity can reduce the prevalence and spread of disease, but certain species may play a disproportionate role in diluting or amplifying pathogens. Flowers act as both sources of nutrition and sites of pathogen transmission, but the effects of specific plant species in shaping bee disease dynamics are not well understood. We evaluated whether plantings of sunflower (Helianthus annuus), whose pollen reduces infection by some pathogens when fed to bees in captivity, lowered pathogen levels and increased reproduction in free-foraging bumblebee colonies (Bombus impatiens). Sunflower abundance reduced the prevalence of a common gut pathogen, Crithidia bombi, and reduced infection intensity, with an order of magnitude lower infection intensity at high sunflower sites compared with sites with little to no sunflower. Sunflower abundance was also positively associated with greater queen production in colonies. Sunflower did not affect prevalence of other detected pathogens. This work demonstrates that a single plant species can drive disease dynamics in foraging B. impatiens, and that sunflower plantings can be used as a tool for mitigating a prevalent pathogen while also increasing reproduction of an agriculturally important bee species.

Behavior and organization of social groups is thought to be vital to the functioning of societies, yet the contributions of various roles within social groups toward population growth and dynamics have been difficult to quantify. A common approach to quantifying these role-based contributions is evaluating the number of individuals conducting certain roles, which ignores how behavior might scale up to effects at the population-level. Manipulative experiments are another common approach to determine population-level effects, but they often ignore potential feedbacks associated with these various roles.Here, we evaluate the effects of worker size distribution in bumblebee colonies on worker production in 24 observational colonies across three environments, using functional linear models. Functional linear models are an underused correlative technique that has been used to assess lag effects of environmental drivers on plant performance. We demonstrate potential applications of this technique for exploring high-dimensional ecological systems, such as the contributions of individuals with different traits to colony dynamics.We found that more larger workers had mostly positive effects and more smaller workers had negative effects on worker production. Most of these effects were only detected under low or fluctuating resource environments suggesting that the advantage of colonies with larger-bodied workers becomes more apparent under stressful conditions.We also demonstrate the wider ecological application of functional linear models. We highlight the advantages and limitations when considering these models, and how they are a valuable complement to many of these performance-based and manipulative experiments.