Despite the importance of insect pollination to produce marketable fruits, insect pollination management is limited by insufficient knowledge about key crop pollinator species. This lack of knowledge is due in part to (1) the extensive labour involved in collecting direct observations of pollen transport, (2) the variability of insect assemblages over space and time and (3) the possibility that pollinators may need access to wild plants as well as crop floral resources. We address these problems using strawberry in the United Kingdom as a case study. First, we compare two proxies for estimating pollinator importance: flower visits and pollen transport. Pollen‐transport data might provide a closer approximation of pollination service, but visitation data are less time‐consuming to collect. Second, we identify insect Overall, pollinator importances estimated based on easier‐to‐collect visitation data were strongly correlated with importances estimated based on pollen loads. Both frameworks suggest that bees ( Moving beyond species identities, abundant, relatively specialised insects with long active periods are likely to provide more pollination services. Most insects visiting strawberry plants also carried pollen from wild plants, suggesting that pollinators need diverse floral resources. Identifying essential pollinators or pollinator parameters based on visitation data will reach the same general conclusions as those using pollen transport data, at least in monoculture crop systems. Managers may be able to enhance pollination service by preserving habitats surrounding crop fields to complement pollinators' diets and provide habitats for diverse life stages of wild pollinators.
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Abstract parameters that are associated with high importance as pollinators, estimated using each of the proxies above. Third, we estimated insects' use of wild plants as well as the strawberry crop.Apis andBombus ) and hoverflies (Eristalis ) are likely to be key pollinators of strawberries, although visitation data underestimate the importance of bees. -
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Abstract The arrangement of plant species within a landscape influences pollination via changes in pollinator movement trajectories and plant–pollinator encounter rates. Yet the combined effects of landscape composition and pollinator traits (especially specialisation) on pollination success remain hard to quantify empirically.
We used an individual‐based model to explore how landscape and pollinator specialisation (degree) interact to influence pollination. We modelled variation in the landscape by generating gradients of plant species intermixing—from no mixing to complete intermixing. Furthermore, we varied the level of pollinator specialisation by simulating plant–pollinator (six to eight species) networks of different connectance. We then compared the impacts of these drivers on three proxies for pollination: visitation rate, number of consecutive visits to the focal plant species and expected number of plants pollinated.
We found that the spatial arrangements of plants and pollinator degree interact to determine pollination success, and that the influence of these drivers on pollination depends on how pollination is estimated. For most pollinators, visitation rate increases in more plant mixed landscapes. Compared to the two more functional measures of pollination, visitation rate overestimates pollination service. This is particularly severe in landscapes with high plant intermixing and for generalist pollinators. Interestingly, visitation rate is less influenced by pollinator traits (pollinator degree and body size) than are the two functional metrics, likely because ‘visitation rate’ ignores the order in which pollinators visit plants. However, the visitation sequence order is crucial for the expected number of plants pollinated, since only prior visits to conspecific individuals can contribute to pollination. We show here that this order strongly depends on the spatial arrangements of plants, on pollinator traits and on the interaction between them.
Taken together, our findings suggest that visitation rate, the most commonly used proxy for pollination in network studies, should be complemented with more functional metrics which reflect the frequency with which individual pollinators revisit the same plant species. Our findings also suggest that measures of landscape structure such as plant intermixing and density—in combination with pollinators' level of specialism—can improve estimates of the probability of pollination.
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Abstract Smallholder farmers are some of the poorest and most food insecure people on Earth. Their high nutritional and economic reliance on home‐grown produce makes them particularly vulnerable to environmental stressors such as pollinator loss or climate change which threaten agricultural productivity. Improving smallholder agriculture in a way that is environmentally sustainable and resilient to climate change is a key challenge of the 21st century.
Ecological intensification, whereby ecosystem services are managed to increase agricultural productivity, is a promising solution for smallholders. However, smallholder farms are complex socio‐ecological systems with a range of social, ecological and environmental factors interacting to influence ecosystem service provisioning. To truly understand the functioning of a smallholder farm and identify the most effective management options to support household food and nutrition security, a holistic, systems‐based understanding is required.
In this paper, we propose a network approach to understand, visualise and model the complex interactions occurring among wild species, crops and people on smallholder farms. Specifically, we demonstrate how networks may be used to (a) identify wild species with a key role in supporting, delivering or increasing the resilience of an ecosystem service; (b) quantify the value of an ecosystem service in a way that is relevant to the food and nutrition security of smallholders; and (c) understand the social interactions that influence the management of shared ecosystem services.
Using a case study based on data from rural Nepal, we demonstrate how this framework can be used to connect wild plants, pollinators and crops to key nutrients consumed by humans. This allows us to quantify the nutritional value of an ecosystem service and identify the wild plants and pollinators involved in its provision, as well as providing a framework to predict the effects of environmental change on human nutrition.
Our framework identifies mechanistic links between ecosystem services and the nutrients consumed by smallholder farmers and highlights social factors that may influence the management of these services. Applying this framework to smallholder farms in a range of socio‐ecological contexts may provide new, sustainable and equitable solutions to smallholder food and nutrition security.
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Abstract Aim How do factors such as space, time, climate and other ecological drivers influence food web structure and dynamics? Collections of well‐studied food webs and replicate food webs from the same system that span biogeographical and ecological gradients now enable detailed, quantitative investigation of such questions and help integrate food web ecology and macroecology. Here, we integrate macroecology and food web ecology by focusing on how ecogeographical rules [the latitudinal diversity gradient (LDG), Bergmann's rule, the island rule and Rapoport's rule] are associated with the architecture of food webs.
Location Global.
Time period Current.
Major taxa studied All taxa.
Methods We discuss the implications of each ecogeographical rule for food webs, present predictions for how food web structure will vary with each rule, assess empirical support where available, and discuss how food webs may influence ecogeographical rules. Finally, we recommend systems and approaches for further advancing this research agenda.
Results We derived testable predictions for some ecogeographical rules (e.g. LDG, Rapoport's rule), while for others (e.g., Bergmann's and island rules) it is less clear how we would expect food webs to change over macroecological scales. Based on the LDG, we found weak support for both positive and negative relationships between food chain length and latitude and for increased generality and linkage density at higher latitudes. Based on Rapoport's rule, we found support for the prediction that species turnover in food webs is inversely related to latitude.
Main conclusions The macroecology of food webs goes beyond traditional approaches to biodiversity at macroecological scales by focusing on trophic interactions among species. The collection of food web data for different types of ecosystems across biogeographical gradients is key to advance this research agenda. Further, considering food web interactions as a selection pressure that drives or disrupts ecogeographical rules has the potential to address both mechanisms of and deviations from these macroecological relationships. For these reasons, further integration of macroecology and food webs will help ecologists better understand the assembly, maintenance and change of ecosystems across space and time.
