Location: Invasive Species and Pollinator Health2021 Annual Report
As pollinators, honey bees (Apis mellifera) are the third most important agricultural livestock after cattle and pork, indispensable for crop production and global food security. Despite their significant economic importance, honey bees continue to face debilitating challenges from several interactive factors including poor nutrition, exposure to agrochemicals, reduced genetic diversity, devastating pests and pathogens and ongoing changes to climatic conditions. A common underlying thread is that these factors vary across seasons and across years, and their build-up leads to compounding impacts that result in patterns not easily discerned with short-term datasets. Depending on agricultural practices, some of the factors may go through cyclical trends that affect long-term performance of apiaries. To get a comprehensive understanding of factors determining honey bee health, it is necessary to obtain continuous recording of data on colony performance, survivorship, environmental factors surrounding the apiaries, agrochemical residues, and availability of nutritional forage, over long periods of time. This project will establish a Long-Term Honey Bee Research (LTHBR) system in California at the Davis ARS location, associated with the Invasive Species and Pollinator Health Research (ISPHR) unit. This LTHBR system will elucidate how key components involved in honey bee health and pollinator sustainability interact with the demand for pollination and agricultural practices. The data collected will generate insights into whether sustainable intensification of beekeeping can occur through better mitigation of stress-induced hive declines. This LTHBR system will also support the development of research projects that monitor a range of environmental conditions and correlated episodic events such as changes to nutrient flow, pest-pathogen cycles, and changing weather patterns affecting hive performance. The data collected over several years will enable the development and validation of theoretical and empirical models to forecast colony performance across various scenarios, allowing for strategies to improve pollinator health and sustainability. The following are the objectives and sub-objectives of the project plan: Objective 1: Establish longitudinal monitoring of apiaries to collect long-term data on colony performance and evaluate relative benefits of new management discoveries to improve honey bee health. Sub-objective 1A: Establish a Long-Term Honey Bee Research (LTHBR) system in California. Sub-objective 1B: Quantify the expression of hygienic behavior across the cooperator apiaries in the LTHBR system. Objective 2: Understand the effects of nutritional and agrochemical stressors on honey bee health and develop hive management strategies. Sub-objective 2A: Determine performance of honey bees under nutrient conditions relevant to California agriculture. Sub-objective 2B: Characterize how exposure to agrochemical stressors like IGRs affect honey bee reproduction, development and long-term colony stability to help beekeepers predict and mitigate the long-term consequences of agrochemical exposure.
The primary objective of this project plan is to conduct longitudinal monitoring of apiaries and collect long-term data on colony performance. As a part of Sub-objective 1A, the LTHBR system will be established in California in collaboration with commercial beekeepers, such that the different monitoring locations will be spread over the different beekeeping regions within the state. Research colonies will be established in cooperator apiaries and monitored by the Davis, California, ARS Bee lab scientists. Using a combination of laboratory and field methods, the following parameters will be recorded over the entire duration of the project plan: (1) colony performance parameters including weight, brood and food storage areas, adult bee population, queen laying patterns, honey and pollen storage areas, and prevalence of pests and pathogens including viruses, (2) reproductive performance parameters measured on queens and drones including viability of the sperm in the spermathecae of queens and in the semen of drones and (3) apiary parameters including beekeeper operating costs, their profit margins and available floral resources and their bloom time in the vicinity of the apiaries. To determine the efficacy of automated hive monitoring technologies, inhive sensors will be installed in the experimental hives. Hive performance measures recorded by the automated devices will be compared with the parameters recorded by researchers during the same time periods in the same apiaries. As a part of Sub-objective 1B, the expression of hygienic behavior, an important a form of behavioral resistance to American Foul Brood (AFB) and a behavioral defense against chalkbrood, will be quantified in the colonies of the participating stakeholder apiaries and the impact of nutrition on behavioral expression will be determined using the established Freeze Killed Brood assay. The second objective of the project plan is to determine the effects of nutritional and agrochemical stressors on honey bee health. Towards this goal, field and laboratory studies in Sub-objective 2A will determine the impact of monocrop and multi-floral pollen diets on colony-level performance measures and individual bee-level behavioral parameters. To determine the effects of agrochemical stressors on honey bee reproduction and development, laboratory studies in Sub-objective 2B will explore how Insect Growth Regulators used in almond orchards affect honey bee queen fecundity and the survival and performance of offspring.
This is the replacement project for project 2030-21000-001-00D, which was bridged by 2030-21000-053-00D. In support of Sub-objective 1A, colonies in the three apiaries are being monitored. Efforts to establish automated hive monitoring systems are in progress. Automated temperature monitoring sensors have been deployed in each of the experimental hives. The sensors are further being standardized for data recording and transferring the recorded data into the computers. The temperature monitors are being calibrated to adjust the frequency of data reporting to reflect a meaningful pattern that can be integrated with hive performance data. In-person monitoring of colonies recording the frame of bees, egg laying, colony growth and other health parameters will continue through the year. Two collaborative experiments with scientists from University of California, Davis, have been initiated. The first one aims to determine the impact of deteriorating air quality resulting from climate change-mediated increases in wildfire frequency and intensity. The second will determine the impact of nutritional supplements on the expression of hygienic behavior. In support of Sub-objective 2A, pollen traps were deployed to collect pollen from flowering almond trees, mustard fields and sunflower fields. These are three crops representative of California agriculture. Nucleus colonies with a laying queen, four frames of brood, and 3,000-5,000 adult worker bees were set up in individual enclosures (tents). Workers were trained to feed on pollen provided in a petri dish placed within the tents. After a day of training, the diet was replaced with a choice of pollen from the three different crops and forager choice was noted manually and through video recordings. Transitions between dishes and amount of experimental diet consumed was also noted. Data measuring bee preferences is being analyzed. Experiment 2 of Sub-objective 2B aims to characterize the behavioral effects of embryonic exposure to insect growth disruptors (IGDs). Based on initial experimental results, we have conducted an experiment to examine the effects of substantially lower doses of IGDs on honey bee embryos following maternal exposure. We have collected behavioral data on queens and workers under IGD exposure, reared embryos to adulthood using foster colonies, and collected behavioral data on the resultant adult insects and their interactions with new queens. We will begin analyzing data and processing samples.