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Ecological effects of extreme drought on Californian herbaceous plant communities

  • Author(s): Copeland, SM
  • Harrison, SP
  • Latimer, AM
  • Damschen, EI
  • Eskelinen, AM
  • Fernandez-Going, B
  • Spasojevic, MJ
  • Anacker, BL
  • Thorne, JH
  • et al.

Published Web Location

https://doi.org/10.1002/ecm.1218
Abstract

© 2016 by the Ecological Society of America. Understanding the consequences of extreme climatic events is a growing challenge in ecology. Climatic extremes may differentially affect varying elements of biodiversity, and may not always produce ecological effects exceeding those of "normal" climatic variation in space and time. We asked how the extreme drought years of 2013- 2014 affected the cover, species richness, functional trait means, functional diversity, and phylogenetic diversity of herbaceous plant communities across the California Floristic Province. We compared the directions and magnitudes of these drought effects with expectations from four "pre-drought" studies of variation in water availability: (1) a watering experiment, (2) a long- Term (15-yr) monitoring of interannual variability, (3) a resampling of historic (57-yr- old) plots within a warming and drying region, and (4) natural variation in communities over a broad geographic gradient in precipitation. We found that the drought was associated with consistent reductions in species richness and cover, especially for annual forbs and exotic annual grasses, but not with changes in functional or phylogenetic diversity. Except for total cover and cover of exotic annual grasses, most drought effects did not exceed quantitative expectations based on the four pre-drought studies. Qualitatively, plant community responses to the drought were most concordant with responses to pre-drought interannual rainfall variability in the 15-yr monitoring study, and least concordant with responses to the geographic gradient in precipitation. Our results suggest that, at least in the short term, extreme drought may cause only a subset of community metrics to respond in ways that exceed normal background variability.

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