Impacts of honeybee density on crop yield: A meta‐analysis

Abstract

1. There is increasing recognition that pollination deficits are limiting crop yields world-wide. However, management strategies for optimal insect pollination are still unclear for most crops. Current management focuses on providing high densities of honeybees, but recommended densities are highly variable, even within single crops and cultivars.2. We performed an extensive literature search to record honeybee densities (colony density and/or flower visitation rates) and crop productivity (fruit set, seed set, fruit weight and/or yield). Effect sizes were represented as the difference in crop productivity between the two most extreme levels of honeybee densities.3. Out of 795 reviewed studies, only 22 analysed the effect of at least two levels of honeybee densities on crop productivity (reporting 60 resulting effect sizes in total). Moreover, few recommendations for crop pollination management are based on results from controlled experimental designs, and with comparable methodology.4. We found that both colony density and visitation rates increased all the productivity variables. However, effects were nonlinear for visitation rates, suggesting that there is an optimum (mean of 8-10 visits per flower) beyond which more honeybees are not beneficial (and can even be detrimental) for crop productivity. 5. Effect sizes for visitation rates were greater than that for colony densities, suggesting that visitation rates are a more direct measure of the pollination process.Data on the relation between colony density and visitation rates are lacking.Interestingly, effect sizes for visitation rates were greater for crops with separate sexes than those with hermaphroditic flowers; therefore, the benefits of honeybee pollination vary according to the crop biology.6. Synthesis and applications. Current practices for crop pollination assume that more honeybees are always better for crop yield, even if the effect of this management on crop production still unclear. In contrast, our analyses suggest that there is an optimum for honeybee densities. Despite the importance of honeybees and pollinator-dependent crops world-wide, there is a lack of studies designed for finding such an optimal level of crop pollination. Our analyses further suggest that visitation rates could be used as a proxy to guide management recommendations such as colony density and spatial arrangement.

No such thing as a free lunch: interaction costs and the structure and stability of mutualistic networks

“…We therefore based our modelling approach on net benefit curves for which empirical evidence exists. In particular, we used a type II functional response to model interaction cost that combined with the type II functional response of the mutualistic benefit produce net‐benefit curves that matched those empirically observed in plant–pollinator communities (Morris et al , Rollin and Garibaldi ). When interaction cost is assumed to be absent, then the saturating benefit curve equals the net‐benefit curve; when the cost is different from zero, the combination of the benefit and cost type II functional response curves may generate a unimodal curve (Supplementary material Appendix 1 Fig.…”

“…However, it remains unknown whether costs inflicted by consumers to resources, e.g. those observed in plant–pollinator interactions where too many visits of pollinators diminish plant reproductive success (Sáez et al , Rollin and Garibaldi ), would impact the network structure–stability relationship. Even though the final outcome might be still beneficial for both partners, the incorporation of the cost into models of mutualistic dynamics could have a strong influence on the dynamics of the populations that interact within a community (Holland and DeAngelis ), ultimately affecting community stability and structural attributes.…”

Crop pollination management needs flower‐visitor monitoring and target values

“…Free, ). However, these guidelines do not accurately predict the actual pollination services crop plants receive (Rollin & Garibaldi, ). A fixed number of hives can translate into contrasting visitation rates to crop flowers because hives can have different population sizes or be located at varying distances (and configurations) to crop flowers.…”

“…A fixed number of hives can translate into contrasting visitation rates to crop flowers because hives can have different population sizes or be located at varying distances (and configurations) to crop flowers. Furthermore, visitation to crop flowers also depends on the intrinsic features of the crop itself and the external context such as the attractiveness of neighbouring vegetation and interactions with wild pollinators (Rollin & Garibaldi, ). We argue that pollination management for pollinator‐dependent crops should be based on direct measures of pollinator activity and that this can be accomplished by monitoring flower visitation rates.…”

“…It is generally assumed that more pollinators on flowers are always better, because more pollen grains are deposited on the stigmas (Vázquez, Morris, & Jordano, ). However, there is a nonlinear relation of visitation rates with crop yield (Figure ), where, under high visitation rates, the benefit of having more pollinators is lower, or even reversed, becoming detrimental (Aizen et al, ; Rollin & Garibaldi, ; Sáez et al, ). Therefore, a key issue is estimating the optimal number of pollinators required to maximize ovule fertilization and yield for each crop (Figure ).…”