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EDITOR'S CHOICE: REVIEW: Trait matching of flower visitors and crops predicts fruit set better than trait diversity
Author(s) -
Garibaldi Lucas A.,
Bartomeus Ignasi,
Bommarco Riccardo,
Klein Alexandra M.,
Cunningham Saul A.,
Aizen Marcelo A.,
Boreux Virginie,
Garratt Michael P. D.,
Carvalheiro Luísa G.,
Kremen Claire,
Morales Carolina L.,
Schüepp Christof,
Chacoff Natacha P.,
Freitas Breno M.,
Gagic Vesna,
Holzschuh Andrea,
Klatt Björn K.,
Krewenka Kristin M.,
Krishnan Smitha,
Mayfield Margaret M.,
Motzke Iris,
Otieno Mark,
Petersen Jessica,
Potts Simon G.,
Ricketts Taylor H.,
Rundlöf Maj,
Sciligo Amber,
Sinu Palatty Allesh,
SteffanDewenter Ingolf,
Taki Hisatomo,
Tscharntke Teja,
Vergara Carlos H.,
Viana Blandina F.,
Woyciechowski Michal
Publication year - 2015
Publication title -
journal of applied ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.503
H-Index - 181
eISSN - 1365-2664
pISSN - 0021-8901
DOI - 10.1111/1365-2664.12530
Subject(s) - pollinator , species evenness , biology , pollination , trait , species richness , abundance (ecology) , ecology , pollen , computer science , programming language
Summary 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.