4.6 Article

Randomization tests for quantifying species importance to ecosystem function

期刊

METHODS IN ECOLOGY AND EVOLUTION
卷 2, 期 6, 页码 634-642

出版社

WILEY
DOI: 10.1111/j.2041-210X.2011.00121.x

关键词

biological soil crust; lichen; natural experiment; null model; presence-absence matrix; randomization test

类别

资金

  1. Comunidad de Madrid [S-0505/AMB/0335]
  2. British Ecological Society [231/607]
  3. European Research Council under European Community [242658]
  4. US National Sciences Foundation [NSF DEB-0541936]
  5. US Department of Energy [022821]
  6. Polish Science Ministry [KBN 3 P04F 034 22, KBN2 P04F 039 29]

向作者/读者索取更多资源

1. Quantifying the contribution of different species to ecosystem function is an important challenge. We introduce simple randomization tests (and software) for quantifying the average effect of species on ecosystem variables measured in multiple plots with and without the presence of a particular species. These randomization tests formalize the analysis of uncontrolled natural experiments and quantify species effects in standardized deviation units. 2. We tested the method with data on ecosystem function in biological soil crust assemblages of lichens in semi-arid gypsum outcrops in central Spain. In sixty-three 50 cm x 50 cm sample plots, we measured the presence and percentage cover of 17 species of lichens and the levels of five important ecosystem variables (organic carbon, total nitrogen, urease activity, phosphatase activity and beta-glucosidase activity). The randomization tests revealed 13 positive and six negative associations between species presence and ecosystem function. 3. We used data from an independent microcosm experiment on ecosystem function and species composition to validate these results. Microcosms that had higher levels of organic carbon and total nitrogen also had higher average species effect scores (measured from the survey data) for the species that were present in each experimental treatment. 4. As in all natural experiments, strong species interactions, effects of unmeasured abiotic variables on species occurrence and reciprocal effects of ecosystem variables on species occurrence can potentially confound estimates of species importance. Nevertheless, the method we propose provides a simple index and statistical test of species importance that can form the basis for additional hypothesis tests and experimental studies of species occurrence and ecosystem function.

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