Louis Sutter

Synergistic interactions of ecosystem services: florivorous pest control boosts crop yield increase through insect pollination

Insect pollination and pest control are pivotal functions sustaining global food production. However, they have mostly been studied in isolation and how they interactively shape crop yield remains largely unexplored. Using controlled field experiments, we found strong synergistic effects of insect pollination and simulated pest control on yield quantity and quality. Their joint effect increased yield by 23%, with synergistic effects contributing 10%, while their single contributions were 7% and 6%, respectively. The potential economic benefit for a farmer from the synergistic effects (12%) was 1.8 times greater than their individual contributions (7% each). We show that the principal underlying mechanism was a pronounced pest-induced reduction in flower lifetime, resulting in a strong reduction in the number of pollinator visits a flower receives during its lifetime. Our findings highlight the importance of non-additive interactions among ecosystem services (ES) when valuating, mapping or predicting them and reveal fundamental implications for ecosystem management and policy aimed at maximizing ES for sustainable agriculture.

Enhancing plant diversity in agricultural landscapes promotes both rare bees and dominant crop‐pollinating bees through complementary increase in key floral resources

Summary Enhancing key floral resources is essential to effectively mitigate the loss of pollinator diversity and associated provisioning of pollination functions in agro-ecosystems. However, effective floral provisioning measures may diverge among different pollinator conservation targets, such as the conservation of rare species or the promotion of economically important crop pollinators. We examined to what extent such diverging conservation goals could be reconciled. We analysed plant–bee visitation networks of 64 herbaceous semi-natural habitats representing a gradient of plant species richness to identify key resource plants of the three distinct conservation target groups: rare bees (of conservation concern), dominant wild crop-pollinating bees and managed crop-pollinating bees (i.e. honeybees). Considering overall flower visitation, rare bees tended to visit nested subsets of plant species that were also visited by crop pollinators (46% and 77% nestedness in the dissimilarity between rare bees and wild crop pollinators or managed honeybees respectively). However, the set of preferred plant species, henceforth ‘key plant species’ (i.e. those species disproportionately more visited than expected according to their floral abundance) was considerably more distinct and less nested among bee target groups. Flower visits of all bee target groups increased with plant species richness at a similar rate. Importantly, our analyses revealed that an exponential increase in the flower abundance of the identified key plant species and complementarity in the bee visitation pattern across plant species ─ rather than total flower abundance ─ were the major drivers of these relationships. Synthesis and applications. We conclude that the multiple goals of preserving high bee diversity, conserving rare species and sustaining crop pollinators can be reconciled if key plant species of different target groups are simultaneously available. This availability is facilitated by a high floral resource complementarity in the plant community. The list of identified key resource plant species we provide here can help practitioners such as land managers and conservationists to better design and evaluate pollinator conservation and restoration measures according to their goals. Our findings highlight the importance of identifying and promoting such plant species for pollinator conservation in agricultural landscapes.

Pollinator size and its consequences: Predictive allometry for pollinating insects

Body size is an integral functional trait that underlies pollination-related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non-bee taxa. Predictive allometric models that consider biogeography, phylogenetic relatedness and intraspecific variation are urgently required to ensure greater accuracy. Here, we measured body size, as dry weight, and intertegular distance (ITD) of 391 bee species (4035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America and South America. We updated existing models within a Bayesian mixed-model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism and biogeographic region. In addition, we used ordinary least squares (OLS) regression to assess intraspecific dry weight – ITD relationships for 10 bee and five hoverfly species. Including co-variates led to more robust interspecific body size predictions for both bees (Bayesian R2: 0.946; ΔR2 0.047) and hoverflies (Bayesian R2: 0.821; ΔR2 0.058) relative to models with ITD alone. In contrast, at the intraspecific level, our results demonstrate that ITD is an inconsistent predictor of body size for bees (R2: 0.02 – 0.66) and hoverflies (R2: −0.11 – 0.44). Therefore, predictive allometry is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, ‘pollimetry’, which provides a comprehensive resource for allometric research concerning insect pollinators worldwide.