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Updated: Apr 4, 2026

Field Experiments of Pollination Ecology: The Case of Lycoris sanguinea var. sanguinea
Published on: November 25, 2016
Interactive effects of elevation, species richness and extreme climatic events on plant-pollinator networks
Bernhard Hoiss1, Jochen Krauss1, Ingolf Steffan-Dewenter1
1Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Am Hubland, D-97074, Würzburg, Germany.
Abstract:
Plant-pollinator interactions are essential for the functioning of terrestrial ecosystems, but are increasingly affected by global change. The risks to such mutualistic interactions from increasing temperature and more frequent extreme climatic events such as drought or advanced snow melt are assumed to depend on network specialization, species richness, local climate and associated parameters such as the amplitude of extreme events. Even though elevational gradients provide valuable model systems for climate change and are accompanied by changes in species richness, responses of plant-pollinator networks to climatic extreme events under different environmental and biotic conditions are currently unknown. Here, we show that elevational climatic gradients, species richness and experimentally simulated extreme events interactively change the structure of mutualistic networks in alpine grasslands. We found that the degree of specialization in plant-pollinator networks (H2') decreased with elevation. Nonetheless, network specialization increased after advanced snow melt at high elevations, whereas changes in network specialization after drought were most pronounced at sites with low species richness. Thus, changes in network specialization after extreme climatic events depended on climatic context and were buffered by high species richness. In our experiment, only generalized plant-pollinator networks changed in their degree of specialization after climatic extreme events. This indicates that contrary to our assumptions, network generalization may not always foster stability of mutualistic interaction networks.
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