Pollinators, including honey bees, are responsible for the successful reproduction of more than 87% of flowering plant species: they are thus vital to ecosystem health and agricultural services world-wide. To investigate honey bee exposure to pesticides, 168 pollen samples and 142 wax comb samples were collected from colonies within six stationary apiaries in six U.S. states. These samples were analyzed for evidence of pesticides. Samples were taken bi-weekly when each colony was active. Each apiary included thirty colonies, of which five randomly chosen colonies in each apiary were sampled for pollen. The pollen samples were separately pooled by apiary. There were a total of 714 detections in the collected pollen and 1008 detections in collected wax. A total of 91 different compounds were detected: of these, 79 different pesticides and metabolites were observed in the pollen and 56 were observed in the wax. In all years, insecticides were detected more frequently than were fungicides or herbicides: one third of the detected pesticides were found only in pollen. The mean (standard deviation (SD)) number of detections per pooled pollen sample varied by location from 1.1 (1.1) to 8.7 (2.1). Ten different modes of action were found across all four years and nine additional modes of action occurred in only one year. If synergy in toxicological response is a function of simultaneous occurrence of multiple distinct modes of action, then a high frequency of potential synergies was found in pollen and wax-comb samples. Because only pooled pollen samples were obtained from each apiary, and these from only five colonies per apiary per year, more data are needed to adequately evaluate the differences in pesticide exposure risk to honey bees among colonies in the same apiary and by year and location.

Drosophila suzukii (Matsumura), or spotted wing drosophila, has become a major pest concern for berry growers in the United States. In this study, we evaluated the economic impacts of D. suzukii on the Maine wild blueberry industry from two perspectives. The first analysis estimated the state-level economic impacts of D. suzukii on the wild blueberry industry in Maine in the absence of control. We found that D. suzukii could result in drastic revenue losses to the industry, which could be over $6.8 million under the worst-case scenario (assuming a 30% yield reduction). In the second analysis, we used Monte Carlo simulation to compare the expected revenues under different management strategies for a typical wild blueberry farm in Maine. The analysis focused on a decision-making week during the harvesting season, which the grower can choose in between three control strategies: no-control, early harvest, or insecticide application. The results suggested that insecticide applications are not economically optimal in most low infestation risk scenarios. Furthermore, although the early harvest strategy is one of the strategies to avoid D. suzukii infestations for wild blueberry production in Maine, the tradeoff is the revenue loss from the unripe crop. Using the simulation results, we summarized optimal harvest timing regarding the fruit maturity level under different D. suzukii infestation risk scenarios, which can minimize the revenue loss from adopting the early harvest management strategy.

A long-term investigation of D. suzukii dynamics in wild blueberry fields from 2012–2018 demonstrates relative abundance is either still increasing or exhibiting periodicity seven years after the initial invasion. Relative abundance is determined by physiological date of first detection and air temperatures the previous winter. Date of first detection of flies does not determine date of fruit infestation. The level of fruit infestation is determined by year, fly pressure, and insecticide application frequency. Frequency of insecticide application is determined by production system. Non-crop wild fruit and predation influences fly pressure; increased wild fruit abundance results in increased fly pressure. Increased predation rate reduces fly pressure, but only at high abundance of flies, or when high levels of wild fruit are present along field edges. Male sex ratio might be declining over the seven years. Action thresholds were developed from samples of 92 fields from 2012–2017 that related cumulative adult male trap capture to the following week likelihood of fruit infestation. A two-parameter gamma density function describing this probability was used to develop a risk-based gradient action threshold system. The action thresholds were validated from 2016–2018 in 35 fields and were shown to work well in two of three years (2016 and 2017).

Pollinator-dependent agriculture heavily relies upon a single pollinator—the honey bee. To diversify pollination strategies, growers are turning to alternatives. Densely planted reservoirs of pollen- and nectar-rich flowers (pollination reservoirs, hereafter “PRs”) may improve pollination services provided by wild bees. Our focal agroecosystem, lowbush blueberry (Vaccinium angustifolium Aiton), exists in a simple landscape uniquely positioned to benefit from PRs. First, we contrast bee visitation rates and use of three types of PR. We consider the effects of PRs on wild bee diversity and the composition of bumble bee pollen loads. We contrast field-level crop pollination services between PRs and controls four years postestablishment. Last, we calculate the time to pay for PR investment. Social bees preferentially used clover plantings; solitary bees preferentially used wildflower plantings. On average, bumble bee pollen loads in treatment fields contained 37% PR pollen. PRs significantly increased visitation rates to the crop in year 4, and exerted a marginally significant positive influence on fruit set. The annualized costs of PRs were covered by the fourth year using the measured increase in pollination services. Our findings provide evidence of the positive impact of PRs on crop pollination services.

Recent pollinator declines highlight the importance of evaluating economic risk of agricultural systems heavily dependent on rented honey bees or native pollinators. Our study analyzed variability of native bees and honey bees, and the risks these pose to profitability of Maine’s wild blueberry industry. We used cross-sectional data from organic, low-, medium-, and high-input wild blueberry producers in 1993, 1997–1998, 2005–2007, and from 2011 to 2015 (n = 162 fields). Data included native and honey bee densities (count/m²/min) and honey bee stocking densities (hives/ha). Blueberry fruit set, yield, and honey bee hive stocking density models were estimated. Fruit set is impacted about 1.6 times more by native bees than honey bees on a per bee basis. Fruit set significantly explained blueberry yield. Honey bee stocking density in fields predicted honey bee foraging densities. These three models were used in enterprise budgets for all four systems from on-farm surveys of 23 conventional and 12 organic producers (2012–2013). These budgets formed the basis of Monte Carlo simulations of production and profit. Stochastic dominance of net farm income (NFI) cumulative distribution functions revealed that if organic yields are high enough (2,345 kg/ha), organic systems are economically preferable to conventional systems. However, if organic yields are lower (724 kg/ha), it is riskier with higher variability of crop yield and NFI. Although medium-input systems are stochastically dominant with lower NFI variability compared with other conventional systems, the high-input system breaks even with the low-input system if honey bee hive rental prices triple in the future.

Declines in wild and managed bee species richness and abundances have been observed throughout Europe and North America in recent decades. These declines have led to questions regarding pollination of wild and cultivated plants. In response to these concerns, efforts towards the conservation of pollinators have been initiated. Part of this conservation effort should be to provide the basic nutritional needs for bees. Nutrition plays one of the most important roles in bee growth, development, and reproduction. There is a large body of information regarding honey bee nutrition, whereas we lack nutritional information on native wild bees. Our knowledge of bumble bee nutritional needs has increased since the introduction of commercial rearing and sale of certain bumble bee species; however, there is still a lack of basic nutritional guidelines such as minimum dietary needs of proteins, amino acids, lipids, and sterols. The large difference in physiology and life history between honey bees and North American wild bees suggests that their nutritional requirements could be quite different.