Browsing by Author "Klein, Alexandra M."

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    A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems
    (Blackwell Publishing Ltd, 2013) Kennedy, Christina M.; Lonsdorf, Erick; Neel, Maile C.; Williams, Neal M.; Ricketts, Taylor H.; Winfree, Rachael; Bommarco, Riccardo; Brittain, Claire; Burley, Alana L.; Cariveau, Daniel; Carvalheiro; Chacoff, Natacha P.; Cunningham, Saul A.; Danforth, Bryan N.; Dudenhoffer, Jan-Hendrick; Elle, Elizabeth; Gaines, Hanna R.; Garibaldi, Lucas A.; Gratton, Claudio; Holzschuh, Andrea; Isaacs, Rufus; Javorek, Steven K.; Jha, Shalene; Klein, Alexandra M.; Krewenka, Kristin; Mandelik, Yael; Mayfield, Margaret M.; Morandin, Lora; Neame, Lisa A.; Otieno, Mark; Park, Mia; Potts, Simon G.; Rundlof, Maj; Saez, Agustin; Steffan-Dewenter, Ingolf; Taki, Hisatomo; Viana, Blandina F.; Westphal, Catrin; Wilson, Julianna K.; Greenleaf, Sara S.; Kremen, Claire; Carvalheiro, Luisa G.
    Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture.
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    Trait matching of flower visitors and crops predicts fruit set better than trait diversity
    (Wiley Online Library, 2015) Garibaldi, Lucas A.; Otieno, Mark; Bartomeus, Ignasi; Bommarco, Riccardo; Klein, Alexandra M.; Cunningham, Saul A.; Aizen, Marcelo A.; Boreux, Virginie; Garratt, Michael P. D.; Carvalheiro, Luısa G.; Kremen, Claire; Morales, Carolina L.; Schuepp, Christof
    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.