Performing Department
Entomology, Riverside
Non Technical Summary
Pollinating insects are an integral component of the production, security, and stability of more than 70% of the world's top food crops. In the US, bumble bees are the single most economically important group of native pollinators and are particularly important in the production of greenhouse crops, early blooming fruit crops, and field crops grown in cooler climates. Despite their importance, many wild bumble bee populations are in decline and some local and large-scale extinctions have occurred. Because of their role in crop production, the decline of wild bumble bees poses a serious threat to national food security. Many factors are involved in the decline of wild bumble bees (e.g., pesticides, pathogens), but habitat loss and unavailability of food resources appear to be recurring, driving factors. Unfortunately, the current state of knowledge about bumble bee nutrition is relatively poor, with significant gaps in three key areas. First, it is not known how foraging behavior and pollination services are influenced by nutritional state in bumble bees (Objective 1). This information gap precludes our ability to predict pollination services provided by bumble bees and anticipate how these services will be altered by ongoing global change. Second, little is known about the impacts of nutrition on bumble bee physiology, in particular for processes that are fundamental to bee health and fitness (Objective 2). Third, it is unclear how nutritional resource availability at the landscape scale impacts the long-term health and stability of bumble bee populations (Objective 3). This information is critical for managing foraging habitat to best support wild bumble bee populations. This project addresses these three knowledge gaps about the nutritional health of bumble bees using a combination of approaches from genomics and molecular biology, experimental biology, animal behavior, and field ecology. Expected outcomes include (i) an improved understanding of the mechanistic basis of bumble bee nutrition; (ii) a predictive framework for modeling bumble bee pollination services in unique nutritional environments; and (iii) management recommendations for optimally supporting bumble bee populations and pollination services.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
0%
Developmental
0%
Goals / Objectives
Research in the Woodard lab uses experimental and molecular approaches to advance our fundamental understanding of bumble bees. Our research program is particularly focused on how the nutritional environment shapes behavior, physiology, and population dynamic processes in this group of bees across both ecological and evolutionary timescales. The overarching goal of this research is to understand and conserve bumble bees for improved human food production and security.OBJECTIVES(1) Nutritional drivers of bumble bee pollination services(2) Physiological basis of bumble bee nutritional health(3) Nutritional landscapes and bumble bee population health
Project Methods
Objective 1:Greenhouse Experiments: Colonies of the bumble bee B. vosnesenksii will be maintained at UCR's Insectary and Quarantine Facility in greenhouses provided with tomato (Solanum lycopersicum; multiple varieties) and pepper (Capsicum annuum; multiple varieties). Individual bees will be provided with diets manipulated in the following ways: pollen diversity (number of source plants), pollen quality (% content of lipid, protein, and micronutrients), and nectar quality (% sucrose). Bees will be released and the followingwill be monitored: pollination activity (using RFID technology as in (Stanley & Raine, 2016)); foraging decision making (floral resource choice); buzz pollination behavior (frequency, duration); and pollen collection (number pollen grains brought back to hive). Total colony foraging activity will be recorded using an automated hive monitoring system (EyesOnHive, Keltronix Inc.). Nutritional treatments will vary across greenhouses and pollination efficacy as a function of diet treatment will be estimated byfruit set and seed production (as in (Garratt et al., 2015)).Open Field Experiments: Young B. vosnesenksii colonies will be placed at sites within the Sierra Foothill Research and Extension Center (UC ANR) that naturally vary in floral resource availability and are spatially independent at > 10 km apart. Across a two month period, foraging behavior will be continuously monitored using methods similar to greenhouse experiments (above) but individual foraging activity will also be monitored for a subset of individuals using radio tracking (as in (Hagen, Wikelski, & Kissling, 2011)). Workers and their pollen loads will be sampled from colonies weekly for analysis of bee nutritional state and floral resource utilization. After two months colonies will be dissected and number of workers andlarvae will be recorded. Spectrophotometric analyses will be used to quantify whole body macronutrients levels; following (Judd, Magnus, & Fasnacht, 2010)). Generalized linear models will be used to examine how metrics of colony development, nesting success, and nutrient levels vary as a function of floral resources around the nest at larger and smaller spatial scales, as well as foraging activity.Objective 2:Laboratory Experiment 1: Queen (B. impatiens) nectar diet quality will be manipulated (sucrose concentrations of 0%, 25%, 50%, or 75% w/v; fed ad libitum) during the first 12 days of adult life and queens from each diet treatment group will be collected at ages 0, 3, 6, 9, and 12d. Complete sets of age x diet queens will be replicated across 10 colonies. All queens will be collected directly into liquid Nitrogen and stored at -80°C. Queens from 5 colonies will be used for spectrophotometric quantitation of abdominal macronutrients (total carbohydrate, lipid, and protein); methods will follow Judd et al. (2010). Queens from additional colonies will be used for fat body transcriptomic analyses to identify molecular processes that change in response to diet quality. RNA-seq will be used to measure levels of transcript abundance and qRT-PCR will be used for a more targeted analysis of transcriptional responses of a subset of genes involved in carbohydrate sequestration (e.g., glucokinases, glycogen synthases). A multivariate analysis of variance (MANOVA) will be used to examine effects of diet and age on nutrient levels.Laboratory Experiment 2: Queen (B. impatiens) pollen and nectar diet quality will be manipulated (6 treatment groups: i-iv, sucrose concentrations of 0%, 25%, 50%, 75% w/v and control pollen; v, pollen starvation; vi, low quality pollen; fed ad libitum) during the first 12 days of adult life, which is the critical period during which queens sequester nutrients for overwintering. Following treatment administration, queens will be assigned to one of three overwintering temperature groups: 0°C, 5°C, 10 °C. Complete sets of diet x overwintering temperature queens will be replicated across 20 colonies. At age 13 d queens will be artificially overwintered in incubators (set to treatment temperatures and 75% RH) for a 2-month period, during which they will be monitored biweekly for mortality. An ANOVA will be used to examine the effects of diet and overwintering temperature on queen survival.Laboratory Experiment 3: Lab-reared, overwintered queens (B. impatiens) will be housed in small nesting boxes in the laboratory at 28°C and 70% RH for 1 month. During the 1-month period they will be fed ad libitum control nectar (40% w/v sucrose solution) and administered one of four pollen diet treatments: i) pollen starvation, ii) monofloral diet A (apricot pollen), iii) monofloral diet B (apple pollen), iv) monofloral diet C (almond pollen), or v) mixed diet (combined apricot, apple, and almond pollen); pollen fed ad libitum. Throughout the 1-month period egg production and brood development will be monitored twice weekly. At the end of the 1-month period all bees will be collected onto dry ice. Queen ovaries will be dissected to determine reproductive status (ovary development score 1-4) using methods in (Woodard, Bloch, Band, & Robinson, 2014). An ANOVA will be used to examine the effect of diet on the following response variables: queen reproductive status, brood quantities (total number of eggs, larvae, pupae, and workers in nest at collection), and larval weights.Field Cage Experiment: Lab-reared queens (B. impatiens) will be removed from their natal colonies, mated, overwintered, then emerged from diapause in spring and housed in small nesting boxes placed within a field cage (area 10 m2) supplemented with floral resources (potted flowers, including California poppy, Eschscholzia californica, flowering sage, Salvia leucophylla, California bluebells, Phacelia companularia, and globe gilia, Gilia capitata). During a 1-month period the nest boxes will be supplemented ad libitum with mixed floral pollen and nectar (40% w/v sucrose solution) that is untreated (control group) or treated with 10 μg l−1 (10 ppb; high dose group) or 2.4 μg l−1 (2.4 ppb; low dose group) thiamethoxam (PESTANAL, Analytical Standard, Sigma Aldrich), an imidicloprid pesticide known to have detrimental effects on bumble bee health(Garratt et al., 2015). Daily foraging activity and colony development will be monitored across the 1-month period. ANOVA will be used to examine the effect of pesticide exposure on the following response variables: daily foraging activity, time to egg production, and total number of workers produced.Objective 3We will explore the hypothesis that food resource availability is a major driver of wild bumble bee population dynamics, in particular during the early nesting period of the bumble bee life cycle. Bumble bees (multiple species) will be surveyed at 30 mid- to high-elevation (1750 - 2300 m) field sites in the Sierra Nevada Mountains around the Sierra Nevada Research Station (SNRS, UC Reserve System) over the course of two consecutive summers. Data collected will include bee abundance and diversity, and tissue samples (non-destructive tarsal snips). Sites will be >10 km apart and will be sampled biweekly from June-July. Each following day, floral resources within sites will be surveyed along transects using an extensive quadrat-based plant inventory system (Jha & Kremen, 2013) where within each quadrat sampled, the number of flowering plant species, number of flowering heads (inflorescences) per species, and the average per species diameter of flowering heads will be counted. From bee tissue samples, double digest RADseq (Peterson et al., 2012) will be used to generate genomic data for estimating population parameters. Generalized linear models will be used to examine how estimates of population health (e.g., bee abundance, diversity, effective population sizes) vary as a function of site-wide total floral resource availability.