Trait matching of flower visitors and crops predicts fruit set better than trait diversity

Lucas A. Garibaldi; Ignasi Bartomeus; Riccardo Bommarco; Alexandra M. Klein; Saul A. Cunningham; Marcelo A. Aizen; Virginie Boreux; Michael P. D. Garratt; Luisa G. Carvalheiro; Claire Kremen; Carolina L. Morales; Christof Schueepp; Natacha P. Chacoff; Breno M. Freitas; Vesna Gagic; Andrea Holzschuh; Björn 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-Dewenter; Hisatomo Taki; Teja Tscharntke; Carlos H. Vergara; Blandina F. Viana; Michal Woyciechowski

doi:10.1111/1365-2664.12530

Trait matching of flower visitors and crops predicts fruit set better than trait diversity

Lucas A. Garibaldi, Ignasi Bartomeus, Riccardo Bommarco, Alexandra M. Klein, Saul A. Cunningham, Marcelo A. Aizen, Virginie Boreux, Michael P. D. Garratt, Luisa G. Carvalheiro, Claire Kremen, Carolina L. Morales, Christof Schueepp, Natacha P. Chacoff, Breno M. Freitas, Vesna Gagic, Andrea Holzschuh, Björn Klatt, Kristin M. Krewenka, Smitha Krishnan, Margaret M. MayfieldIris Motzke, Mark Otieno, Jessica Petersen, Simon G. Potts, Taylor H. Ricketts, Maj Rundlöf, Amber Sciligo, Palatty Allesh Sinu, Ingolf Steffan-Dewenter, Hisatomo Taki, Teja Tscharntke, Carlos H. Vergara, Blandina F. Viana, Michal Woyciechowski

University of Göttingen

Research output: Contribution to journal › Review article › peer-review

Abstract

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. 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. Editor's Choice

Original language	English
Pages (from-to)	1436-1444
Journal	Journal of Applied Ecology
Volume	52
Issue number	6
DOIs	https://doi.org/10.1111/1365-2664.12530
Publication status	Published - 2015

Subject classification (UKÄ)

Ecology

Free keywords

agroecosystems
body size
ecosystem functioning
ecosystem services
mouthpart length
nectar accessibility
pollination
trait evenness
trait richness

Access to Document

10.1111/1365-2664.12530

LIBERATION: LInking farmland Biodiversity to Ecosystem seRvices for effective
Kleijn, D. (Project coordinator), Smith, H. (PI), Sahlin, U. (Researcher), Brady, M. V. (Researcher), van der Putten, W. H. (PI), Potts, S. G. (PI), Bommarco, R. (PI), Steffan-Dewenter, I. (PI), Koellner, T. (PI), Báldi, A. (PI), Marini, L. (PI), Tryjanowski, P. (Researcher), Gemmill-Herren, B. (PI), de Groot, G. A. (PI), Hedlund, K. (PI), Ekroos, J. (Researcher) & Baey, C. (Researcher)
European Commission - FP7
2013/01/01 → 2017/01/31
Project: Research

Cite this

Garibaldi, L. A., Bartomeus, I., Bommarco, R., Klein, A. M., Cunningham, S. A., Aizen, M. A., Boreux, V., Garratt, M. P. D., Carvalheiro, L. G., Kremen, C., Morales, C. L., Schueepp, C., Chacoff, N. P., Freitas, B. M., Gagic, V., Holzschuh, A., Klatt, B., Krewenka, K. M., Krishnan, S., ... Woyciechowski, M. (2015). Trait matching of flower visitors and crops predicts fruit set better than trait diversity. Journal of Applied Ecology, 52(6), 1436-1444. https://doi.org/10.1111/1365-2664.12530

@article{b78f2094d653419ba6d5aa911eefc359,

title = "Trait matching of flower visitors and crops predicts fruit set better than trait diversity",

abstract = "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. 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. Editor's Choice",

keywords = "agroecosystems, body size, ecosystem functioning, ecosystem services, mouthpart length, nectar accessibility, pollination, trait evenness, trait richness",

author = "Garibaldi, {Lucas A.} and Ignasi Bartomeus and Riccardo Bommarco and Klein, {Alexandra M.} and Cunningham, {Saul A.} and Aizen, {Marcelo A.} and Virginie Boreux and Garratt, {Michael P. D.} and Carvalheiro, {Luisa G.} and Claire Kremen and Morales, {Carolina L.} and Christof Schueepp and Chacoff, {Natacha P.} and Freitas, {Breno M.} and Vesna Gagic and Andrea Holzschuh and Bj{\"o}rn Klatt and Krewenka, {Kristin M.} and Smitha Krishnan and Mayfield, {Margaret M.} and Iris Motzke and Mark Otieno and Jessica Petersen and Potts, {Simon G.} and Ricketts, {Taylor H.} and Maj Rundl{\"o}f and Amber Sciligo and Sinu, {Palatty Allesh} and Ingolf Steffan-Dewenter and Hisatomo Taki and Teja Tscharntke and Vergara, {Carlos H.} and Viana, {Blandina F.} and Michal Woyciechowski",

year = "2015",

doi = "10.1111/1365-2664.12530",

language = "English",

volume = "52",

pages = "1436--1444",

journal = "Journal of Applied Ecology",

issn = "1365-2664",

publisher = "John Wiley & Sons Inc.",

number = "6",

}

Garibaldi, LA, Bartomeus, I, Bommarco, R, Klein, AM, Cunningham, SA, Aizen, MA, Boreux, V, Garratt, MPD, Carvalheiro, LG, Kremen, C, Morales, CL, Schueepp, C, Chacoff, NP, Freitas, BM, Gagic, V, Holzschuh, A, Klatt, B, Krewenka, KM, Krishnan, S, Mayfield, MM, Motzke, I, Otieno, M, Petersen, J, Potts, SG, Ricketts, TH, Rundlöf, M, Sciligo, A, Sinu, PA, Steffan-Dewenter, I, Taki, H, Tscharntke, T, Vergara, CH, Viana, BF & Woyciechowski, M 2015, 'Trait matching of flower visitors and crops predicts fruit set better than trait diversity', Journal of Applied Ecology, vol. 52, no. 6, pp. 1436-1444. https://doi.org/10.1111/1365-2664.12530

TY - JOUR

T1 - Trait matching of flower visitors and crops predicts fruit set better than trait diversity

AU - Garibaldi, Lucas A.

AU - Bartomeus, Ignasi

AU - Bommarco, Riccardo

AU - Klein, Alexandra M.

AU - Cunningham, Saul A.

AU - Aizen, Marcelo A.

AU - Boreux, Virginie

AU - Garratt, Michael P. D.

AU - Carvalheiro, Luisa G.

AU - Kremen, Claire

AU - Morales, Carolina L.

AU - Schueepp, Christof

AU - Chacoff, Natacha P.

AU - Freitas, Breno M.

AU - Gagic, Vesna

AU - Holzschuh, Andrea

AU - Klatt, Björn

AU - Krewenka, Kristin M.

AU - Krishnan, Smitha

AU - Mayfield, Margaret M.

AU - Motzke, Iris

AU - Otieno, Mark

AU - Petersen, Jessica

AU - Potts, Simon G.

AU - Ricketts, Taylor H.

AU - Rundlöf, Maj

AU - Sciligo, Amber

AU - Sinu, Palatty Allesh

AU - Steffan-Dewenter, Ingolf

AU - Taki, Hisatomo

AU - Tscharntke, Teja

AU - Vergara, Carlos H.

AU - Viana, Blandina F.

AU - Woyciechowski, Michal

PY - 2015

Y1 - 2015

N2 - 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. 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. Editor's Choice

AB - 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. 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. Editor's Choice

KW - agroecosystems

KW - body size

KW - ecosystem functioning

KW - ecosystem services

KW - mouthpart length

KW - nectar accessibility

KW - pollination

KW - trait evenness

KW - trait richness

U2 - 10.1111/1365-2664.12530

DO - 10.1111/1365-2664.12530

M3 - Review article

SN - 1365-2664

VL - 52

SP - 1436

EP - 1444

JO - Journal of Applied Ecology

JF - Journal of Applied Ecology

IS - 6

ER -

Trait matching of flower visitors and crops predicts fruit set better than trait diversity

Abstract

Subject classification (UKÄ)

Free keywords

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Projects

LIBERATION: LInking farmland Biodiversity to Ecosystem seRvices for effective

Cite this