4.3 Article

Experimental environmental change and mutualistic vs. antagonistic plant flower-visitor interactions

出版社

ELSEVIER GMBH, URBAN & FISCHER VERLAG
DOI: 10.1016/j.ppees.2010.12.001

关键词

Global change; Pollination; Herbivory; Bees; Flies; Functional complementarity

资金

  1. German Ministry of Research and Education (BMBF)
  2. German Science Foundation (DFG)
  3. German Federal Environmental Foundation (DBU)

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Habitat modification and human-induced climate change are having a severe impact on ecosystems. Plant-insect interactions in particular might become disrupted due to species-specific responses of plants and insects towards these changes. We investigated how environmental change affects flower visitation and pollination with a field study simulating pollinator habitat loss (distance to semi-natural habitat), phenological shift (anticipated flowering) and environmentally induced growth (enhanced flower height). We established 16 habitat islands of potted plants of Sinapis arvensis L., recorded all flower visitors (mainly bees, flies and pollen beetles) and quantified the seed set. Experimentally elevated flowers were less often visited by flies, while visitation by bees was not affected. Further, plants distant from calcareous grassland were less often visited by bees but visitation by flies did not decrease. Anticipated flowering reduced the number of both pollinators and herbivorous pollen beetles and increased the reproductive success (seeds per plant) of S. arvensis, showing that the loss of mutualists was compensated by an escape from antagonists. During the natural flowering period more seeds were produced close to grasslands, especially by plants of natural height, presumably due to the higher bee visitation rate. However, seed production appeared to be relatively tolerant to multiple environmental changes due to complementary patterns among the different flower visitor guilds. Our results suggest complex interactions of environmental change with responses of mutualists and antagonists, making general predictions difficult. (C) 2011 Elsevier GmbH. All rights reserved.

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