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Fil: Garibaldi, Lucas A. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina. Fil: Garibaldi, Lucas A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina. Fil: Aizen, Marcelo A. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Río Negro, Argentina. Fil: Cunningham, Saul A. Australian National University. Australia. Fil: Harder, Lawrence. University of Calgary. Canada. Fil: Klein, Alexandra M. University of Freiburg. Alemania.

Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co-evolve.\ud World-wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed-effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance.\ud Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity.\ud The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar.\ud Synthesis and applications. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species.

Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Fil: Bartomeus, Ignasi. Estación Biológica de Doñana (EBD-CSIC). Dpto. Ecología Integrativa; España. Fil: Bommarco, Riccardo. Swedish University of Agricultural Sciences. Department of Ecology; Suecia. Fil: Klein, Alexandra M. University of Freiburg. Faculty of Environment and Natural Resources. Chair of Nature Conservation and Landscape Ecology; Alemania. Fil: Cunningham, Saul. CSIRO Land and Water; Australia. Fil: Aizen, Marcelo A. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Laboratorio Ecotono; Argentina. Fil: Aizen, Marcelo A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Biodiversidad y Medioambiente. Laboratorio Ecotono; Argentina. Fil: Boreux, Virginie. University of Freiburg. Faculty of Environment and Natural Resources. Chair of Nature Conservation and Landscape Ecology; Alemania. Fil: Garratt, Michael P. Reading University. School of Agriculture, Policy and Development. Centre for Agri-Environmental Research; Reino Unido. Fil: Carvalheiro, Luisa G. University of Leeds. School of Biology; Reino Unido. Fil: Carvalheiro, Luisa G. Naturalis Biodiversity Center; Países Bajos. Fil: Carvalheiro, Luisa G. Universidade de Brasilia. Departamento de Ecologia; Brasil. Fil: Kremen, Claire. University of California. Department of Environmental Science, Policy, and Management; Estados Unidos. Fil: Morales, Carolina L. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Laboratorio Ecotono; Argentina. Fil: Morales, Carolina L. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Biodiversidad y Medioambiente. Laboratorio Ecotono; Argentina. Fil: Schuepp, Christof. University of Bern. Institute of Ecology and Evolution; Suiza. Fil: Schuepp, Christof. University of Koblenz-Landau. Institute for Environmental Sciences; Alemania. Fil: Chacoff, Natacha P. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e IML. Instituto de Ecología Regional; Argentina. Fil: Freitas, Breno M. Universidade Federal do Ceara. Campus Universitario do Pici. Departamento de Zootecnia–CCA; Brasil. Fil: Gagic, Vesna. Swedish University of Agricultural Sciences. Department of Ecology; Suecia. Fil: Holzschuh, Andrea. University of Würzburg. Biocenter. Department of Animal Ecology and Tropical Biology; Alemania. Fil: Holzschuh, Andrea. Georg-August-University. Department of Crop Sciences. Agroecology; Alemania. Fil: Klatt, Bjorn K. Georg-August-University. Department of Crop Sciences. Agroecology; Alemania. Fil: Klatt, Bjorn K. Lund University. Centre for Environmental and Climate Research; Suecia. Fil: Krewenka, Kristin M. Georg-August-University. Department of Crop Sciences. Agroecology; Alemania. Fil: Krewenka, Kristin M. University of Hamburg. Biocentre Klein-Flottbek and Botanical Garden Biodiversity. Ecology and Evolution of Plants; Alemania. Fil: Krishnan, Smitha. ETH Zürich. Department of Environmental Systems Science; Suiza. Fil: Mayfield, Margaret M. The University of Queensland. School of Biological Sciences and the Ecology Centre; Australia. Fil: Motzke, Iris. University of Freiburg. Faculty of Environment and Natural Resources. Chair of Nature Conservation and Landscape Ecology; Alemania. Fil: Motzke, Iris. Georg-August-University. Department of Crop Sciences. Agroecology; Alemania. Fil: Otieno, Mark. Embu University College. Department of Agricultural Resource Management; Kenya. Fil: Petersen, Jessica. Cornell University. New York State Agricultural Experiment Station. Department of Entomology; Estados Unidos. Fil: Potts, Simon G. Reading University. School of Agriculture, Policy and Development. Centre for Agri-Environmental Research; Reino Unido. Fil: Ricketts, Taylor. University of Vermont. Gund Institute for Ecological Economics; Estados Unidos. Fil: Rundlof, Maj. Lund University. Department of Biology; Suecia. Fil: Sciligo, Amber. University of California. Department of Environmental Science, Policy, and Management; Estados Unidos. Fil: Allesh Sinu, Palatty. Central University of Kerala. Department of Animal Science; India. Fil: Steffan Dewenter, Ingolf. University of Würzburg. Biocenter. Department of Animal Ecology and Tropical Biology; Alemania. Fil: Taki, Hisatomo. Forestry and Forest Products Research Institute. Department of Forest Entomology; Japón. Fil: Tscharntke, Teja. Georg-August-University. Department of Crop Sciences. Agroecology; Alemania. Fil: Vergara, Carlos H. Universidad de las Américas Puebla. Departamento de Ciencias Químico-Biológicas; México. Fil: Viana, Blandina F. Universidade Federal da Bahia. Instituto de Biologia; Departamento de Zoologia; Brasil. Fil: Woyciechowski, Michal. Jagiellonian University. Institute of Environmental Sciences; Polonia. Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co‐evolve. World‐wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed‐effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance. Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity. The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar. Synthesis and applications. Despite contrasting floral traits for crops world‐wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species.

Recent evidence highlights the value of wild-insect species richness and abundance for crop pollination worldwide. Yet, deliberate physical importation of single species (eg European honey bees) into crop fields for pollination remains the mainstream management approach, and implementation of practices to enhance crop yield (production per area) through wild insects is only just beginning. With few exceptions, studies measuring the impacts of pollinator-supporting practices on wild-insect richness and pollination service success – particularly in relation to long-term crop yield and economic profit – are rare. Here, we provide a general framework and examples of approaches for enhancing pollinator richness and abundance, quantity and quality of pollen on stigmas, crop yield, and farmers' profit, including some benefits detected only through long-term monitoring. We argue for integrating the promotion of wild-insect species richness with single-species management to benefit farmers and society. Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Rio Negro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Carvalheiro, Luísa G.. University of Leeds. School of Biology; Reino Unido. Naturalis Biodiversity Center; Países Bajos Fil: Leonhardt, Sara D.. Universitat Wurzburg; Alemania Fil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentina Fil: Blaauw, Brett R.. Michigan State University; Estados Unidos Fil: Isaacs, Rufus. Michigan State University; Estados Unidos Fil: Kuhlmann, Michael. Natural History Museum; Reino Unido Fil: Kleijn, David. Alterra. Animal Ecology Team; Países Bajos. Wageningen University. Resource Ecology Group; Países Bajos Fil: Klein, Alexandra M.. University of Freiburg. Faculty of Environment and Natural Resources. Chair of Nature Conservation and Landscape Ecology; Alemania Fil: Kremen, Claire. University Of California Berkeley; Estados Unidos Fil: Morandin, Lora. University Of California Berkeley; Estados Unidos Fil: Scheper, Jeroen. Alterra. Animal Ecology Team; Países Bajos Fil: Winfree, Rachel. Rutgers University. Department of Ecology, Evolution and Natural Resources; Estados Unidos

Most ecosystem services, which are essential for human well-being, are globally declining, while the production of consumption goods, measured by GDP, is still growing. To adequately account for this opposite development in public cost-benefit analyses, it has been proposed - based on a two-goods extension of the Ramsey growth model - to apply good-specific discount rates for manufactured consumption goods and for ecosystem services. Using empirical data for ten ecosystem services across five countries and the world at large, we estimated the difference between the discount rates for ecosystem services and for manufactured consumption goods. In a conservative estimate, we found that ecosystem services in all countries should be discounted at rates that are significantly lower than the ones for manufactured consumption goods. On global average, ecosystem services should be discounted at a rate that is 0.9-0.3 %-points lower than the one for manufactured consumption goods. The difference is larger in less developed countries and smaller in more developed countries. This result supports and substantiates the suggestion that public cost-benefit-analyses should use country-specific dual discount rates - one for manufactured consumption goods and one for ecosystem services.

International audience

In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.

Biodiversity-ecosystem functioning (BEF) research grew rapidly following concerns that biodiversity loss would negatively affect ecosystem functions and the ecosystem services they underpin. However, despite evidence that biodiversity strongly affects ecosystem functioning, the influence of BEF research upon policy and the management of ‘real-world’ ecosystems, i.e., semi-natural habitats and agroecosystems, has been limited. Here, we address this issue by classifying BEF research into three clusters based on the degree of human control over species composition and the spatial scale, in terms of grain, of the study, and discussing how the research of each cluster is best suited to inform particular fields of ecosystem management. Research in the first cluster, small-grain highly controlled studies, is best able to provide general insights into mechanisms and to inform the management of species-poor and highly managed systems such as croplands, plantations, and the restoration of heavily degraded ecosystems. Research from the second cluster, small-grain observational studies, and species removal and addition studies, may allow for direct predictions of the impacts of species loss in specific semi-natural ecosystems. Research in the third cluster, large-grain uncontrolled studies, may best inform landscape-scale management and national-scale policy. We discuss barriers to transfer within each cluster and suggest how new research and knowledge exchange mechanisms may overcome these challenges. To meet the potential for BEF research to address global challenges, we recommend transdisciplinary research that goes beyond these current clusters and considers the social-ecological context of the ecosystems in which BEF knowledge is generated. This requires recognizing the social and economic value of biodiversity for ecosystem services at scales, and in units, that matter to land managers and policy makers.