Gut parasite infection and pesticide exposure affect bumble bee health and pollination behavior. These stressors are common in commercial tomato greenhouses, where growers deploy bumble bees for pollination. To investigate the effects of these stressors on bumble bee pollination in greenhouses, we sampled commercial bumble bee colonies for the presence of three common gut-parasites (Crithidia, Apicystis, Nosema) within three commercial tomato greenhouses that were sampled during 12-week periods of two growing seasons. We then sampled the nest material of these same colonies to detect and quantify compounds that are active ingredients in pesticides. Using grower-collected data, we monitored tomato anther bruising as a proxy for bee pollination activity, and recorded pesticide applications within the greenhouses. We found that parasite infection prevalence was correlated with total pesticide application and bumble bee colony density, but these relationships were parasite-specific. Crithidia prevalence increased with total pesticide use and decreased with bumble bee colony density. Crithidia infection was also negatively associated correlated with decreased pollination activity. In contrast, Apicystis infection decreased with total pesticide use, but increased with colony density, and was positively associated with pollination activity. We never detected Nosema in any colony. Pollination activity was not directly predicted by pesticide quantity. Nest-compound exposure revealed frequent detection of multiple pesticide compounds. We further found compound-specific associations with pathogen infection probability. Our results highlight that gut parasites, as mediated through pesticide exposure, have important effects on bumble bee pollination, but these effects are pathogen- and pesticide-specific.

Bumble bees face numerous environmental stressors, including gut-parasite infection and exposure to agricultural fungicides. This study evaluates the interactive effects of these stressors on bumble bee (Bombus impatiens) microcolonies, focusing on colony development, worker survival, and parasite infection dynamics. Our aim in evaluating these interactions, was to determine if bees would experience synergistic negative health outcomes compared to single stressor exposures. We reared forty queenless bumble bee microcolonies, and treated them with either fungicide-contaminated pollen, inoculation with a gut parasite, both, or neither. Contrary to original expectations, we did not observe significant synergistic interactions between the two stressors, however we found that consumption of fungicide was associated with higher likelihood of gut-parasite infection, and delayed recovery from infection. Fungicide consumption was also connected to smaller workers, and smaller male offspring. We also found that gut-parasite infection was correlated with decreased pollen consumption overall, decreased worker survival, and fewer developed pupae. This study provides insights into the complexities of stressor interactions affecting bumble bees and emphasizes the importance of sublethal effects on pollinator health.

Analyses performed: Repeated measures modeling time as a quadratic predictor of pollen comsumption, with the interaction of fungicide and crithidia

Analyses run: Linear mixed effects (Guassian and Negative Binomial Distributions) Cox Proportional Hazards Analysis Generalized linear models (Binomial distribution; logit link function) Post-Hoc analysis ANOVA

LM.fit <- lmer(whole_dif~crithidia*fungicide*poly(pollen.ball.id,2)+(1|colony), data = df) LM.fit2 <- lmer(whole_dif~(crithidia+fungicide+poly(pollen.ball.id,2))^2+(1|colony), data = df) summary(LM.fit2) anova(LM.fit2, LM.fit, test = "Chi") #LM.fit2 fits better emtrends(LM.fit2,pairwise~crithidia, var = "pollen.ball.id", max.degree = 2) emtrends(LM.fit2,pairwise~fungicide, var = "pollen.ball.id", max.degree = 2) pollen.emm <- emmeans(time.quad3, ~crithidia*fungicide*time2) pollen.emm

Synergism microcolony data analysis looking at brood production worker size and survival adult male health metrics and pollen consumption.

Bumble bees are declining across the globe. Causes of this decline have been attributed to a variety of stressors, most notably, pesticides. Fungicides are a type of pesticide generally long considered to not affect bumble bees, and as a result, are often applied to flowering plants without consideration of pollinator exposure. Recent work demonstrates that fungicides have sublethal effects in bumble bees, but little is known about how much fungicide it takes to cause these sublethal effects. To address this gap in the literature, we fed microcolonies of the common eastern bumble bee (Bombus impatiens) pollen contaminated with a range of fungicide concentrations. We chose these concentrations based on the range of fungicide concentrations in pollen and nectar that were reported in the literature. We found that intermediate levels (1,500 ppb) of fungicide led to smaller adult males overall, measured by their dry weights and their relative fat values. Higher doses of fungicide (15,000 ppb) were also associated with shorter times until the first adult male emergence. Because body size and emergence timing are important aspects of bumble bee reproduction behavior, results have implications for mating success and altered life history events in bumble bees exposed to fungicide. E. N. Runnion1, J.P. Strange2, F. S. Sivakoff1 1Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, Ohio, USA 2Department of Entomology, The Ohio State University, 2021 Columbus, OH USA

Pollen consumption does not differ by treatment

drones updated with censored data

Drone metrics. Need to fix colony duration to be emergence time while accounting for the colonies in which no drones emerged.

Final analysis with organized steps for brood production of Pristine microcolonies from 2022

Updated data analysis based on meeting with Frances at bee lab 6/8/2023 with the list of steps for organizing the analysis. Drone metrics.

Emerge time and drone counts with artificially ended colonies and colonies with all workers dead cut out

Pollen consumption without round 1

Brood data and counts of drones without round 1 data

Worker mortality and dry weights without round 1 data

Drone emergence time, radial length, relative fat, and dry weights without round 1 data

Colony weight changes over time

Pollen consumption per treatment (means)

Drone radial cell, relative fat, and dry weight

Brood metric counts

worker mortality as counts of workers alive at end of experiment and as proportion of time each worker survived. worker dry weights.

Drone radial length and relative fat analysis

Average drone dry weights per treatment, with average pollen consumption per colony held as an explanatory variable.

A short introduction to the basics of rmd files and a few tools yo can use to begin to understand them.

Reflection from HCS 7806, 9/06/2022. How to use R Markdown.