Assessing impacts of pesticides and other stressors on honey bee colony health: Experimental and modeling approaches

A healthy honey bee colony is a population of closely interacting individuals that form a highly complex society. However, the combinational energy-draining stresses of illness from environment, nutrition, and human migratory and cultural practices strike honey bee populations day after day, depriving them of long-term health. The possibility of a multi-factorial cause is one of the problems that make investigating colony declines especially complex. Pesticides are a major concern due to their widespread distribution within the hive. Beyond the effects of acute toxicity, pesticides are also likely to cause sublethal effects that result in behavior alteration or disorder of individual bees, together with the synergistic interactions among various pesticides in hive matrices, which eventually trigger serious harm to colony health. Therefore, a combination of mathematical modeling and experimental approaches were proposed to study the honey bee colony dynamics and quantify the colony-level effects of nutritional disturbance due to pesticides.;First, a larval rearing method was adapted to assess experimentally the chronic oral toxicity to honey bee larvae of the four most common pesticides detected in pollen and wax - fluvalinate, coumaphos, chlorothalonil, and chlorpyrifos - tested alone and in all combinations. All individual or combined pesticides at hive-residue levels triggered a significant increase in larval mortality compared to untreated larvae by over two fold, with a strong increase after 3 days of exposure. Among these four pesticides, honey bee larvae were most sensitive to chlorothalonil compared to adults.;We explored the potential hazard to honey bee larvae of frequently-found fungicides at environmentally relevant levels. Bravo®, its active ingredient (AI) chlorothalonil, and the formulations Nova ® and Pristine® at environmentally realistic levels all triggered a significant increase in larval mortality through 6-d continuous dietary exposure. We also found a significant difference in larval toxicity of the fungicide formulation and its AI. Bravo® exhibited a monotonic and positive dose response for larval mortality, with hazard ratios increasing with concentrations; however, chlorothalonil showed a complex nonmonotonic dose response for larval mortality. This is the first study to report synergism for developing honey bee larvae between the non-systemic fungicide chlorothalonil and systemic EBI fungicide myclobutanil at environmentally relevant dietary levels.;For further testing of pesticide impacts at the colony level, and linking of larval responses to effects on later honey bee life stages and colony health, we developed a worker-based, stage-structured model of honey bee population dynamics. This model was formulated with combined difference and differential equations, consisting of six discrete stages based on honey bee temporal polyethism: egg, larva, pupa, nurse, house bee and forager stage. It is unique in capturing the adaptive feedback mechanisms in the population and resource dynamics in a healthy bee colony, including the comb pattern formation, brood maintenance and collective foraging behavior. By validating with independent data sets for colony numbers at different latitudes and under different conditions, our model represents the most advanced population model for integrating the top-down differential model and bottom-up difference model that gives the most refined and realistic details of colony population and resource dynamics to date.;Lastly, as a further step to extend our current modeling efforts, a decision support system (DSS) model (also called knowledge-based system model, expert system) was developed using the NetWeaver™ software, as a new and innovative method of transferring timely, up-to-date decision support to non-specialists and stakeholders for colony management and conservation. This system will offer effective directions for beekeepers and other stakeholders to determine the condition of honey bee colony, diagnose the potential stressors affecting colony health, and prioritize management plans based on relevance to colony health. (Abstract shortened by UMI.).