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Data available via the Dryad Digital Repository https://doi.org/10.5061/dryad.63xsj3v39 (Roquer-Beni et al., 2021)., Functional traits mediate the response of communities to disturbances (response traits) and their contribution to ecosystem functions (effect traits). To predict how anthropogenic disturbances influence ecosystem services requires a dual approach including both trait concepts. Here, we used a response–effect trait conceptual framework to understand how local and landscape features affect pollinator functional diversity and pollination services in apple orchards. We worked in 110 apple orchards across four European regions. Orchards differed in management practices. Low-intensity (LI) orchards were certified organic or followed close-to-organic practices. High-intensity (HI) orchards followed integrated pest management practices. Within each management type, orchards encompassed a range of local (flower diversity, agri-environmental structures) and landscape features (orchard and pollinator-friendly habitat cover). We measured pollinator visitation rates and calculated trait composition metrics based on 10 pollinator traits. We used initial fruit set as a measure of pollination service. Some pollinator traits (body size and hairiness) were negatively related to orchard cover and positively affected by pollinator-friendly habitat cover. Bee functional diversity was lower in HI orchards and decreased with increased landscape orchard cover. Pollination service was not associated with any particular trait but increased with pollinator trait diversity in LI orchards. As a result, LI orchards with high pollinator trait diversity reached levels of pollination service similar to those of HI orchards. Synthesis and applications. Pollinator functional diversity enables pollinator communities to respond to agricultural intensification and to increase pollination function. Our results show that efforts to promote biodiversity provide greater returns in low-intensity than in high-intensity orchards. The fact that low-intensity orchards with high pollinator functional diversity reach levels of pollination services similar to those of high-intensity orchards provides a compelling argument for the conversion of high-intensity into low-intensity farms., This research (EcoFruit project) was funded through the 2013–2014 BiodivERsA/FACCE-JPI joint call (2014-74), Spanish MinECo (PCIN-2014-145-C02), German BMBF (PT-DLR/BMBF, 01LC1403) and Swedish Research Council Formas (2014-1784) by Formas (2013-934 to M.T.), Stiftelsen Lantbruksforskning (H1256150 to M.P.), INIA (RTA2013-00039-C03-00 to G.A. and M.M.), MinECo/FEDER (CGL2015-68963-C2-2-R to D.G.), FI-AGAUR (to L.R.-B.) and MinECo (RYC-2015-18448 to X.A.).

2017-2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, and with the funding organisations AEI, NWO, ECCyT and NSF Funding information, Allen-Perkins A, Magrach A, Dainese M, Garibaldi LA, Kleijn D, Rader R, Reilly JR, Winfree R, Lundin O, McGrady CM, Brittain C, Biddinger DJ, Artz DR, Elle E, Hoffman G, Ellis JD, Daniels J, Gibbs J, Campbell JW, Brokaw J, Wilson JK, Mason K, Ward KL, Gundersen KB, Bobiwash K, Gut L, Rowe LM, Boyle NK, Williams NM, Joshi NK, Rothwell N, Gillespie RL, Isaacs R, Fleischer SJ, Peterson SS, Rao S, Pitts-Singer TL, Fijen T, Boreux V, Rundlöf M, Viana BF, Klein AM, Smith HG, Bommarco R, Carvalheiro LG, Ricketts TH, Ghazoul J, Krishnan S, Benjamin FE, Loureiro J, Castro S, Raine NE, de Groot GA, Horgan FG, Hipólito J, Smagghe G, Meeus I, Eeraerts M, Potts SG, Kremen C, García D, Miñarro M, Crowder DW, Pisanty G, Mandelik Y, Vereecken NJ, Leclercq N, Weekers T, Lindstrom SAM, Stanley DA, Zaragoza-Trello C, Nicholson CC, Scheper J, Rad C, Marks EAN, Mota L, Danforth B, Park M, Bezerra ADM, Freitas BM, Mallinger RE, Oliveira da Silva F, Willcox B, Ramos DL, D da Silva E Silva F, Lázaro A, Alomar D, González-Estévez MA, Taki H, Cariveau DP, Garratt MPD, Nabaes Jodar DN, Stewart RIA, Ariza D, Pisman M, Lichtenberg EM, Schüepp C, Herzog F, Entling MH, Dupont YL, Michener CD, Daily GC, Ehrlich PR, Burns KLW, Vilà M, Robson A, Howlett B, Blechschmidt L, Jauker F, Schwarzbach F, Nesper M, Diekötter T, Wolters V, Castro H, Gaspar H, Nault BA, Badenhausser I, Petersen JD, Tscharntke T, Bretagnolle V, Willis Chan DS, Chacoff N, Andersson GKS, Jha S, Colville JF, Veldtman R, Coutinho J, Bianchi FJJA, Sutter L, Albrecht M, Jeanneret P, Zou Y, Averill AL, Saez A, Sciligo AR, Vergara CH, Bloom EH, Oeller E, Badano EI, Loeb GM, Grab H, Ekroos J, Gagic V, Cunningham SA, Åström J, Cavigliasso P, Trillo A, Classen A, Mauchline AL, Montero-Castaño A, Wilby A, Woodcock BA, Sidhu CS, Steffan-Dewenter I, Vogiatzakis IN, Herrera JM, Otieno M, Gikungu MW, Cusser SJ, Nauss T, Nilsson L, Knapp J, Ortega-Marcos JJ, González JA, Osborne JL, Blanche R, Shaw RF, Hevia V, Stout J, Arthur AD, Blochtein B, Szentgyorgyi H, Li J, Mayfield MM, Woyciechowski M, Nunes-Silva P, Halinski de Oliveira R, Henry S, Simmons BI, Dalsgaard B, Hansen K, Sritongchuay T, O'Reilly AD, Chamorro García FJ, Nates Parra G, Magalhães Pigozo C, Bartomeus I

Hairiness is a salient trait of insect pollinators that has been linked to thermoregulation, pollen uptake and transportation, and pollination success. Despite its potential importance in pollination ecology, hairiness is rarely included in pollinator trait analyses. This is likely due to the lack of standardized and efficient methods to measure hairiness. We describe a novel methodology that uses a stereomicroscope equipped with a live measurement module software to quantitatively measure two components of hairiness: hair density and hair length. We took measures of the two hairiness components in 109 insect pollinator species (including 52 bee species). We analyzed the relationship between hair density and length and between these two components and body size. We combined hair density and length measures to calculate a hairiness index and tested whether hairiness differed between major pollinator groups and bee genera. Body size was strongly and positively correlated to hair length and weakly and negatively correlated to hair density. The correlation between the two hairiness components was weak and negative. According to our hairiness index, butterflies and moths were the hairiest pollinator group, followed by bees, hoverflies, beetles, and other flies. Among bees, bumblebees (Bombus) and mason bees (Osmia) were the hairiest taxa, followed by digger bees (Anthophorinae), sand bees (Andrena), and sweat bees (Halictini). Our methodology provides an effective and standardized measure of the two components of hairiness (hair density and length), thus allowing for a meaningful interpretation of hairiness. We provide a detailed protocol of our methodology, which we hope will contribute to improve our understanding of pollination effectiveness, thermal biology, and responses to climate change in insects., Hairiness is a fundamental functional trait in pollinator ecology related to thermoregulation and pollination effectiveness. Surprisingly, there is a lack of standard methods to measure this trait. We provide an effective method to quantitatively measure hairiness to contribute to filling an important gap in pollinator data bases and to improve our understanding of the ecology and evolution of a threatened group of organisms that provide an essential ecosystem service.

1. Pollination by insects is a key input into many crops, with managed honeybees often being hired to support pollination services. Despite substantial research into pollination management, no European studies have yet explored how and why farmers managed pollination services and few have explored why beekeepers use certain crops. 2. Using paired surveys of beekeepers and farmers in 10 European countries, this study examines beekeeper and farmer perceptions and motivations surrounding crop pollination. 3. Almost half of the farmers surveyed believed they had pollination service deficits in one or more of their crops. 4. Less than a third of farmers hired managed pollinators; however, most undertook at least one form of agri‐environment management known to benefit pollinators, although few did so to promote pollinators. 5. Beekeepers were ambivalent towards many mass‐flowering crops, with some beekeepers using crops for their honey that other beekeepers avoid because of perceived pesticide risks. 6. The findings highlight a number of largely overlooked knowledge gaps that will affect knowledge exchange and co‐operation between the two groups. Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Number: 841.11.001; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, Grant/Award Number: 43001; Natural Environment Research Council, Grant/Award Number: NE/K015419/1 and NE/N014472/1; Javna Agencija za Raziskovalno Dejavnost RS, Grant/Award Number: V4‐1622 and P1‐0255; Rural and Environment Science and Analytical Services Division; Bayer Crop Science; European Cooperation in Science and Technology, Grant/Award Number: oc‐2013‐1‐15320; BBSRC, Grant/ Award Number: BB/R00580X/1; The Scottish Government Rural Affairs and the Environment Strategic Research Programme info:eu-repo/semantics/publishedVersion

Wild and managed bees provide pollination services to both crops and wild plants, and a variety of other services from which humans benefit. We summarize the most important and recent findings on bees as providers of provisioning, regulating and cultural ecosystem services. With comprehensive literature searches, we first identified ten important bee species for global pollination of crops, which include wild and managed honey bees, bumble bees, orchard-, cucumber- and longhorn bees. We second summarized bee-dependent ecosystem services to show how bees substantially contribute to food security, medical resources, soil formation or spiritual practices, highlighting their wide range of benefits for human well-being and to identify future research needs.

Ecologists have long suspected that species are more likely to interact if their traits match in a particular way. For example, a pollination interaction may be more likely if the proportions of a bee's tongue fit a plant's flower shape. Empirical estimates of the importance of trait-matching for determining species interactions, however, vary significantly among different types of ecological networks. Here, we show that ambiguity among empirical trait-matching studies may have arisen at least in parts from using overly simple statistical models. Using simulated and real data, we contrast conventional generalized linear models (GLM) with more flexible Machine Learning (ML) models (Random Forest, Boosted Regression Trees, Deep Neural Networks, Convolutional Neural Networks, Support Vector Machines, naive Bayes, and k-Nearest-Neighbor), testing their ability to predict species interactions based on traits, and infer trait combinations causally responsible for species interactions. We find that the best ML models can successfully predict species interactions in plant-pollinator networks, outperforming GLMs by a substantial margin. Our results also demonstrate that ML models can better identify the causally responsible trait-matching combinations than GLMs. In two case studies, the best ML models successfully predicted species interactions in a global plant-pollinator database and inferred ecologically plausible trait-matching rules for a plant-hummingbird network, without any prior assumptions. We conclude that flexible ML models offer many advantages over traditional regression models for understanding interaction networks. We anticipate that these results extrapolate to other ecological network types. More generally, our results highlight the potential of machine learning and artificial intelligence for inference in ecology, beyond standard tasks such as image or pattern recognition., 48 pages, 5 figures

The research was part of the EcoFruit project funded through the 2013-2014 BiodivERsA/FACCEJPI joint call(agreement BiodivERsA-FACCE2014-74),with the national funders German Federal Ministry of Education and Research(PT-DLR/BMBF) (grant 01LC1403), the Spanish Ministerio de Economía y Competitividad (MinECo) (project PCIN-2014-145-C02)and Swedish Research Council Formas(grant2014-1784).There search was also funded by Formas(grant2013-934 to MT),Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (project RTA2013-00039-C03-00 to GA and MM;FPI-INIA fellow ship to RMS),MinECo/FEDER (project CGL2015-68963-C2-2-R to DG) and FI fellowship(Generalitat de Catalunya) to LRB, Happe, A.-K., Alins, G., Blüthgen, N., Boreux, V., Bosch, J., García, D., Hambäck, P.A., Klein, A.-M., Martínez-Sastre, R., Miñarro, M., Müller, A.-K., Porcel, M., Rodrigo, A., Roquer-Beni, L., Samnegård, U., Tasin, M., Mody, K.

Pollination is an ecosystem service that directly contributes to agricultural production, and can therefore provide a strong incentive to conserve natural habitats that support pollinator populations. However, we have yet to provide consistent and convincing pollination service valuations to effectively slow the conversion of natural habitats. We use coffee in Kodagu, India, to illustrate the uncertainties involved in estimating costs and benefits of pollination services. First, we fully account for the benefits obtained by coffee agroforests that are attributable to pollination from wild bees nesting in forest habitats. Second, we compare these benefits to the opportunity cost of conserving forest habitats and forgoing conversion to coffee production. Throughout, we systematically quantify the uncertainties in our accounting exercise and identify the parameters that contribute most to uncertainty in pollination service valuation. We find the value of pollination services provided by one hectare of forest to be 25% lower than the profits obtained from converting that same surface to coffee production using average values for all parameters. However, our results show this value is not robust to moderate uncertainty in parameter values, particularly that driven by variability in pollinator density. Synthesis and applications. Our findings emphasize the need to develop robust estimates of both value and opportunity costs of pollination services that take into account landscape and management variables. Our analysis contributes to strengthening pollination service arguments used to help stakeholders make informed decisions on land use and conservation practices. © 2019 The Authors. Journal of Applied Ecology © 2019 British Ecological Society

Forest fragments in agricultural landscapes are recognised to provide a variety of ecosystem services, several of which benefit neighbouring agricultural land uses. Pollination of crops is one such service that has attracted much research and public attention, yet the dependency of crops on pollinators, and the role of forest fragments in providing this service, remains contentious. Indeed, the trend towards increasing crop production through intensification is at odds with the expected concurrent decline in pollination. We investigated the combined effect of distance from forest and forest size on pollinator abundance at coffee agro-forests in Kodagu District, India, under two contrasting flowering scenarios: irrigation triggered flowering in a single agro-forest, and rain triggered flowering at all the remaining agro-forests that received rain but were not previously irrigated. Three social bee species, Apis dorsata, Apis cerana and Tetragonula iridipennis were the main flower visitors. In rain-fed agro-forests, the total visitor abundance at coffee flowers decreased with increasing distance to the nearest forest. When the three main pollinators were analysed separately, the abundances of A. dorsata and T. iridipennis decreased with increasing distance from a neighbouring forest patch but this distance effect was reduced with an increase in size of the nearby forest. An increase in pollinator abundance at coffee flowers increased coffee fruit set in rain-fed agro-forests. Irrigated agro-forests had far higher pollinator abundance and fruit set than rain-fed agro-forests. We attribute this to the small-scale staggered flowering of irrigated agro-forests resulting in the concentration of pollinators at these sites regardless of its proximity to forests or the size of nearby forest. Agro-forest shade tree species richness also negatively affected pollinator abundance in rain-fed agro-forests. Although our results show that distance to forest and size of neighbouring forest fragments do affect the abundance of pollinators at coffee, at least in rain-fed agro-forests, justifying the conservation of large forest remnants is problematic on this account as there was no direct effect of forest on coffee fruit set. This is likely to be because there remains a high density of forest remnants within Kodagu, and a threshold of forest cover at which crop fruit set begins to be affected by pollinator scarcity has yet to be reached. By controlling the timing of flowering through irrigation or managing domesticated bee hives, farmers effectively reduce the dependency on nearby forest cover for pollinator services irrespective of the distance between forests and agro-forests, but these management practices incur costs that not every farmer can cover.

International audience; AbstractAgroforestry systems usually include a high density and diversity of shade trees. Such systems often have a large diversity of fauna and flora and provide local and regional ecosystem services. Shade trees are, however, being removed to increase crop production in many tropical regions. There is little knowledge on the effect of shade trees on crop production in the context of trade-offs with other management practices. We therefore compared the benefits of exotic versus native shade trees on coffee production. We evaluated the importance of shade tree management for crop production in the context of management practices. Management practices included fertilization, liming, coffee pruning, weeding, and irrigation in 113 coffee agroforests in Kodagu, India, over a wide range of shade tree density, tree species diversity, and shade cover. We studied, in particular, Grevillea and non-Grevillea shade trees, the latter including mostly native tree species. Results show that a rise of 100 non-Grevillea shade tree per hectare increased production of berries by 5.6 % and larger beans by 6.25 %. Irrigation and liming increased berry production respectively by 16 and 20 %. These management interventions are likely to offset the relatively small negative effect of reducing shade density of non-Grevillea trees on coffee production. Recommendations based on an understanding of shade tree management alone can be misleading with regard to crop production.

Climate change is altering the phenology of trophically linked organisms, leading to increased asynchrony between species with unknown consequences for ecosystem services. Although phenological mismatches are reported from several ecosystems, experimental evidence for altering multiple ecosystem services is hardly available. We examined how the phenological shift of apple trees affected the abundance and diversity of pollinators, generalist and specialist herbivores and predatory arthropods. We stored potted apple trees in the greenhouse or cold store in early spring before transferring them into orchards to cause mismatches and sampled arthropods on the trees repeatedly. Assemblages of pollinators on the manipulated and control trees differed markedly, but their overall abundance was similar indicating a potential insurance effect of wild bee diversity to ensure fruit set in flower-pollinator mismatch conditions. Specialized herbivores were almost absent from manipulated trees, while less-specialized ones showed diverse responses, confirming the expectation that more specialized interactions are more vulnerable to phenological mismatch. Natural enemies also responded to shifted apple tree phenology and the abundance of their prey. While arthropod abundances either declined or increased, species diversity tended to be lower on apple trees with shifted phenology. Our study indicates novel results on the role of biodiversity and specialization in plant-insect mismatch situations.

Under the current scenario of continuing human population growth, achieving high agricultural yield while conserving forest biodiversity is challenging scientists and policy makers alike. There is ongoing debate as to whether biodiversity should be integrated on the same land (land sharing) or separated from agriculture (land sparing). Here, we present examples of land-sharing practices (agroforestry systems and multipurpose forests) and demonstrate that forest biodiversity conservation does not necessarily compromise crop yield. There is no simple trade-off between biodiversity and yield, and the complexity of crop yield–biodiversity relationships has not yet been fully investigated, at either the habitat or the landscape scale. We argue that land-sparing management has to be considered at different spatial scales. Agriculturein large-scale land sparing (intensive agriculture separated from forest remnants) generally does not benefit much from ecosystem services mediated by forest biodiversity, but small forest remnants can enhance biodiversityin large agricultural and forestry plantations. Small-scale land sparing (intensive agriculture connected to forest remnants) promotes beneficial organisms and their associated ecosystem services. In such landscapes, wild beneficial organisms, e.g. a diversity of pollinators, can enhance and stabilize crop pollination in intensively managed fields due to spillover from forests into crop fields. Functional connectivity of forest remnants (single trees, treelines, hedgerows and forest patches) in high-input agricultural landscapescan enhance biodiversity and ecosystem services, but future research needs to consider connectivity at various land-sparing scales to evaluate their conservation effectiveness. Furthermore, landscape developmentsminimizing possible adverse consequences of forest conservation on crop production are currently often overlooked but need to be considered in future research and landscape planning. We argue that both land sharing and land sparing can promote biodiversity without compromising high yields, and that a combination of management strategies at different spatial scales, including the maintenance of forest connectivity, may most effectively safeguard both biodiversity and livelihood security.

Conserving tropical ecosystems is one of the foremost challenges of the 21st century. Lately, conservation efforts have focused on advancing conservation through dialogue and interaction with and among diverse stakeholders. Knowledge sharing, and specifically the transfer of scientific knowledge, can raise ecological awareness among stakeholders and is necessary to facilitate dialogue, yet the communication of tropical scientific research to local stakeholders is rarely effectively implemented. Such a communication gap potentially undermines the conservation and management of natural resources. The papers in this special section highlight the difficulties and benefits of sharing ecological knowledge, as well as the underlying reasons for why a research-implementation gap has arisen.

Knowledge sharing between scientists and nonscientist stakeholders is necessary to implement research findings in an appropriate and effective manner within the context of the environment and conservation sectors. Yet scientific ecological knowledge is rarely shared and transferred effectively. This special section has addressed a number of opportunities and barriers to the improvement of scientific communication and knowledge transfer with respect to environmental management in tropical settings. A main challenge is seen in creating a research `impact-metric' system, which is fundamental to foster knowledge sharing with institutional research incentives. Partnering with local institutions and research centers as well as participatory research methods will promote effective knowledge exchange. Research relevance and impact will be improved by matching interdisciplinary research with local capacity building and support through research activities. We conclude that training the next generation of tropical biologists through more effective knowledge sharing will be crucial to the long term success of scientifically based environmental management in tropical regions.

Crop productivity is improved by ecosystem services, including pollination, but this should be set in the context of trade-offs among multiple management practices. We investigated the impact of pollination services on coffee production, considering variation in fertilization, irrigation, shade cover, and environmental variables such as rainfall (which stimulates coffee flowering across all plantations), soil pH, and nitrogen availability. After accounting for management interventions, bee abundance improved coffee production (number of berries harvested). Some management interventions, such as irrigation, used once to trigger asynchronous flowering, dramatically increased bee abundance at coffee trees. Others, such as the extent and type of tree cover, revealed interacting effects on pollination and, ultimately, crop production. The effects of management interventions, notably irrigation and addition of lime, had, however, far more substantial positive effects on coffee production than tree cover. These results suggest that pollination services matter, but managing the asynchrony of flowering was a more effective tool for securing good pollination than maintaining high shade tree densities as pollinator habitat. Complex interactions across farm and landscape scales, including both management practices and environmental conditions, shape pollination outcomes. Effective production systems therefore require the integrated consideration of management practices in the context of the surrounding habitat structure. This paper points toward a more strategic use of ecosystem services in agricultural systems, where ecosystem services are shaped by the coupling of management interventions and environmental variables.

Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro (Sede Andina) y Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); Argentina. Fil: Steffan Dewenter, Ingolf. University of Würzburg. Biocentre. Department of Animal Ecology and Tropical Biology; Germany. Fil: Winfree, Rachael. Rutgers University. Evolution and Natural Resources. Department of Ecology; USA. Fil: Aizen, Marcelo A. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche (CRUB). Instituto de Investigaciones en Biodiversidad y Medioambiente (INIBIOMA). Laboratorio Ecotono; Argentina. Fil: Bommarco, Riccardo. Swedish University of Agricultural Sciences. Department of Ecology; Sweden. Fil: Cunningham, Saul A. CSIRO Ecosystem Sciences; Australia. Fil: Kremen, Claire. University of California. Environmental Sciences Policy and Management; USA. Fil: Carvalheiro, Luísa G. University of Leeds. School of Biology; UK. Naturalis Biodiversity Center; Netherlands. Fil: Harder, Lawrence D. University of Calgary. Department of Biological Sciences; Canada. Fil: Afik, Ohad. Hebrew University of Jerusalem. Robert H. Smith Faculty of Agriculture, Food and Environment. Department of Entomology; Israel. Fil: Bartomeus, Ignasi. Rutgers University. Department of Entomology, Evolution and Natural Resources; USA. Fil: Benjamin, Faye. Rutgers University. Evolution and Natural Resources. Department of Ecology; USA. Fil: Boreux, Virginie. Leuphana University. Institute of Ecology; Germany. Department of Environmental Systems Science; Switzerland. Fil: Cariveau, Daniel. Rutgers University. Evolution and Natural Resources. Department of Ecology; USA. Fil: Chacoff, Natacha P. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e IML. Instituto de Ecología Regional; Argentina. Fil: Dudenhöffer, Jan H. Agroscope Reckenholz-Tänikon Research Station ART. Ecological Farming Systems; Switzerland. Fil: Freitas, Breno M. Universidade Federal do Ceará. Departamento de Zootecnia–CCA; Brazil. Fil: Greenleaf, Sarah S. University of California. Environmental Sciences Policy and Management; USA. Fil: Hipólito, Juliana. Universidade Federal da Bahia. Departamento de Zoologia. Instituto de Biologia; Brazil. Fil: Holzschuh, Andrea. University of Würzburg. Biocentre. Department of Animal Ecology and Tropical Biology; Germany. Fil: Howlett, Brad. New Zealand Institute for Plant and Food Research; New Zealand. Fil: Isaacs, Rufus. Michigan State University. Department of Entomology; USA. Fil: Javorek, Steven K. Atlantic Food and Horticulture Research Centre. Agriculture and Agri-Food Canada; Canada. Fil: Kennedy, Christina M. Nature Conservancy. Development by Design Program; USA. Fil: Krewenka, Kristin M. Georg-August-University. Department of Crop Sciences. Agroecology; Germany. Fil: Krishnan, Smitha. ETH Zürich. Department of Environmental Systems Science; Switzerland. Fil: Mandelik, Yael. Hebrew University of Jerusalem. Robert H. Smith Faculty of Agriculture, Food and Environment. Department of Entomology; Israel. Fil: Mayfield, Margaret M. University of Queensland. School of Biological Sciences and Ecology Centre; Australia. Fil: Motzke, Iris. Leuphana University. Ecosystem Functions. Institute of Ecology; Germany. Georg-August-University. Department of Crop Sciences. Agroecology; Germany. Fil: Munyuli, Theodore. National Center for Research in Natural Sciences. Department of Biology; Democratic Republic of Congo. Fil: Nault, Brian A. Cornell University. Department of Entomology. New York State Agricultural Experiment Station; USA. Fil: Otieno, Mark. University of Reading. School of Agriculture, Policy and Development; UK. Fil: Petersen, Jessica. Cornell University. Department of Entomology. New York State Agricultural Experiment Station; USA. Fil: Pisanty, Gideon. Hebrew University of Jerusalem. Robert H. Smith Faculty of Agriculture, Food and Environment. Department of Entomology; Israel. Fil: Potts, Simon G. University of Reading. School of Agriculture, Policy and Development; UK. Fil: Rader, Romina. Stockholm University. Department of Physical Geography and Quaternary Geology; Sweden. Fil: Ricketts, Taylor H. University of Vermont. Gund Institute for Ecological Economics; USA. Fil: Rundlöf, Maj. Swedish University of Agricultural Sciences. Department of Ecology; Sweden. Lund University. Department of Biol-ogy; Sweden. Fil: Seymour, Colleen L. South African National Institute of Biodiversity. Applied Biodiversity Research Division; South Africa. Fil: Schüepp, Christof. University of Bern. Institute of Ecology and Evolution, Community Ecology; Switzerland. University of Koblenz-Landau. Ecosystem Analysis; Germany. Fil: Szentgyörgyi, Hajnalka. Jagiellonian University. Institute of Environmental Sciences; Poland. Fil: Taki, Hisatomo. Forestry and Forest Products Research Institute. Department of Forest Entomology; Japan. Fil: Tscharntke, Teja. Georg-August-University. Department of Crop Sciences. Agroecology; Germany. Fil: Vergara, Carlos H. Universidad de las Américas Puebla. Departamento de Ciencias Químico-Biológicas; Mexico. Fil: Viana, Blandina F. Universidade Federal da Bahia. Instituto de Biologia. Departamento de Zoologia; Brazil. Fil: Wanger, Thomas C. Georg-August-University. Department of Crop Sciences. Agroecology; Germany. Fil: Westphal, Catrin. Georg-August-University. Department of Crop Sciences. Agroecology; Germany. Fil: Williams, Neal. University of California. Department of Entomology; USA. Fil: Klein, Alexandra M. Leuphana University. Ecosystem Functions. Institute of Ecology; Germany. The diversity and abundance of wild insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. We found universally positive associations of fruit set with flower visitation by wild insects in 41 crop systems worldwide. In contrast, fruit set increased significantly with flower visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively; an increase in wild insect visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Visitation by wild insects and honey bees promoted fruit set independently, so pollination by managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild insect assemblages will enhance global crop yields.