Performing Department
Entomology
Non Technical Summary
Honey bees are the most important agricultural pollinators and generate commercial products such as honey and wax that contribute over $300 million to the US economy annually. Despite their higher market value, organic products are currently not produced in the continental United States because meeting recommendations for certification is not feasible. Specifically, beekeepers cannot meet the pesticide-free zoning requirements (at least a 3 km radius around the colonies) that were established based on maximum foraging distance of honey bees. Our preliminary data and published research indicate that honey bee foraging is context-dependent and can be significantly smaller in colonies of smaller size and surrounded by high-quality landscapes. Here, we propose integrating data from automated tag readers, harmonic radars, and waggle dance decoding to characterize honey bee foraging patterns in colonies of different population sizes and placed in landscapes with varying floral quality. We will develop high-quality floral maps around the apiaries based on satellite imagery, ground observations, and pollen metabarcoding to develop a seasonal landscape quality index that will be used as a predictor of the estimated average foraging distances of the colonies in different landscapes. Our goal is to assess whether the recommendations for pesticide-free zones can be reduced based on empirical data that incorporates information about landscape quality and colony size. The project will count with the input of an advisory panel composed of scientists, beekeepers, farmers and policy makers. The extension teams will disseminate our results to stakeholder groups and the national organic program.
Animal Health Component
0%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Objective 1: Assess the role of temporal variation in landscape quality on the foraging distances of honey bees.Objective 2: Determine the impact of colony size on foraging distances of honey bee colonies placed on organic farms.Objective 3: Develop extension materials and education programs to disseminate the outcomes of this study to beekeepers, organic farmers, and advisory boards.
Project Methods
A. Landscape quality estimation:To generate a spatial prediction of the density of honey bee foraging and landscape quality, we will utilize data from pollen metabarcoding to adjust seasonal forage maps to reflect visitation preferences of honey bees. Specifically, we will re-generate forage maps excluding species that were not detected in pollen samples and apply a distance-weighting algorithm (Lonsdorf et al. 2009) to develop a foraging quality index based on these weighted average distances. Floral resources closer to the colony will have greater weight, thus the floral index will be positively correlated with the proximity and the floral availability in the landscape.B. Honey bee foraging estimation: We will integrate data from QR code automated readers, harmonic radars, and waggle dance decoding to describe the distance, duration, and direction of foraging flights in honey bees. Data sets from QR code tags, harmonic radar and waggle dances will be analyzed to ascertain whether bees mainly forage within the radius of the organic farms throughout the year. We will develop foraging kernels from each of these three methods to determine the percent of the foraging trips that occur outside of the boundaries of organic farms. Radar data will be analyzed to determine bee flight direction, length of each step bees take, outbound and inbound bee flying patterns, and length of time for each trip bees can take over the course of a given day. The resulting data sets will be used to develop a numerical model (to be improved from previous formulations as, for example, outlined in Fuentes et al. 2016, see Equation 5) to determine the foraging patterns of bees as a function of meteorological conditions (e.g., wind speed) and floral resources distributed throughout the landscape. Data collected from the QR code automated readers will include flight length for 100 individuals per colony to robust distribution of the foraging distances in each colony. The QR code data sets will serve as the basis to generate a numerical model to estimate the distances bees travel based on the duration of the foraging per individual. These numerical models will be calibrated with the more accurate data collected from harmonic radars and waggle dance decoding. Radar data will provide the necessary parameters (e.g., minimum step lengths taken by bees, ensemble range distances traveled from hives, etc.). We will compare the results of the waggle dance data (distance and forage location, as per Schürch et al. 2013; 2019) with the data obtained through the automated methods. Specifically, we will convert dance duration into distances and correlate individual flight distance with flight duration, as determined by QR code surveillance. A highly significant positive correlation between the different methods (r2 > 0.9) would indicate that QR code methods can provide a cost-effective and automated methodology to study foraging distances of honey bee foragers. The verification of this method would also provide a technology that could be easily incorporated to determine whether the organic certification of honey bee products is possible in different organic farms.C. Pesticide residue analysis: In addition to quantitatively assessing honey bee foraging distances with three methods, we will validate the feasibility of the development of organic beekeeping certification protocols through the quantification of pesticide residues in honey, pollen, and wax from the experimental colonies. We will collect pollen samples in May, June, and September (as described in Obj 1). Honey and wax samples will be collected each fall in years 1 and 2. During the honey extraction procedure, containers of 50 ml of honey will be collected from each selected hive. Wax samples (15g) will be scraped from a frame in the center of each hive and placed in a 50 ml container for storage. All samples will be collected on dry ice and stored at -80ºC until analysis. These samples will be sent to Cornell University for analysis of the quantities of 93 pesticides by LCMS (https://blogs.cornell.edu/ccecf/). Results of pesticide residues from all bee products will be used to indicate the presence of chemical contaminants and whether they contain levels that would be acceptable to qualify them for organic certification. We will calculate the total abundance and the total number of compounds to generate summary statistics for the diversity of pesticides in all samples. We will use a GLM to statistically test whether the diversity of pesticides in honey, wax, and pollen is significantly different in colonies foraging on different organic farms. All statistical analyses will be done in R (R project 2021).