MORALES Carolina Laura
Trait matching of flower visitors and crops predicts fruit set better than trait diversity
GARIBALDI LUCAS A.; BARTOMEUS IGNASI; RICCARDO BOMMARCO; KLEIN ALEXANDRA M. ; CUNNINGHAM SAUL A. ; AIZEN MARCELO ADRIAN; BOREUX VIRGINIE ; GARRATT MICHAEL P. D. ; CARVALHEIRO LUISA G.; KREMEN CLAIRE; MORALES CAROLINA LAURA
JOURNAL OF APPLIED ECOLOGY
WILEY-BLACKWELL PUBLISHING, INC
Lugar: Londres; Año: 2015 vol. 52 p. 1436 - 1444
1. Understanding the relationships between trait diversity, species diversity and ecosystemfunctioning is essential for sustainable management. For functions comprising two trophiclevels, trait matching between interacting partners should also drive functioning. However,the predictive ability of trait diversity and matching is unclear for most functions, particularlyfor crop pollination, where interacting partners did not necessarily co-evolve.2. World-wide, we collected data on traits of flower visitors and crops, visitation rates tocrop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchicalmixed-effects models, we tested whether flower visitor trait diversity and/or trait matchingbetween flower visitors and crops improve the prediction of crop fruit set (functioning)beyond flower visitor species diversity and abundance.3. Flower visitor trait diversity was positively related to fruit set, but surprisingly did notexplain more variation than flower visitor species diversity.4. The best prediction of fruit set was obtained by matching traits of flower visitors (bodysize and mouthpart length) and crops (nectar accessibility of flowers) in addition to flowervisitor abundance, species richness and species evenness. Fruit set increased with species richness,and more so in assemblages with high evenness, indicating that additional species offlower visitors contribute more to crop pollination when species abundances are similar.5. Synthesis and applications. Despite contrasting floral traits for crops world-wide, only theabundance of a few pollinator species is commonly managed for greater yield. Our resultssuggest that the identification and enhancement of pollinator species with traits matchingthose of the focal crop, as well as the enhancement of pollinator richness and evenness, willincrease crop yield beyond current practices. Furthermore, we show that field practitionerscan predict and manage agroecosystems for pollination services based on knowledge of just afew traits that are known for a wide range of flower visitor species.