EDITOR'S CHOICE: REVIEW: Trait matching of flower visitors and crops predicts fruit set better than trait diversity

• DOI: 10.1111/1365-2664.12530
• Publication Date: 2015-08-24T17:38:20Z
• Authors: Lucas A. Garibaldi; Ignasi Bartomeus; Riccardo Bommarco; Alexandra M. Klein; Saul A. Cunningham; Marcelo A. Aizen; Virginie Boreux; Michael P. D. Gar...; Luísa G. Carvalheiro; Claire Kremen; Carolina L. Morales; Christof Schüepp; Natacha P. Chacoff; Breno M. Freitas; Vesna Gagic; Andrea Holzschuh; Björn K. Klatt; Kristin M. Krewenka; Smitha Krishnan; Margaret M. Mayfield; Iris Motzke; Mark Otieno; Jessica Petersen; Simon G. Potts; Taylor H. Ricketts; Maj Rundlöf; Amber Sciligo; Palatty Allesh Sinu; Ingolf Steffan‐De...; Hisatomo Taki; Teja Tscharntke; Carlos H. Vergara; Blandina F. Viana; Michal Woyciechowski
• Keywords: Trait

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