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Randomization tests for quantifying species importance to ecosystem function
Article first published online: 23 MAY 2011
© 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society
Methods in Ecology and Evolution
Volume 2, Issue 6, pages 634–642, December 2011
How to Cite
Gotelli, N. J., Ulrich, W. and Maestre, F. T. (2011), Randomization tests for quantifying species importance to ecosystem function. Methods in Ecology and Evolution, 2: 634–642. doi: 10.1111/j.2041-210X.2011.00121.x
- Issue published online: 5 DEC 2011
- Article first published online: 23 MAY 2011
- Received 21 February 2011; accepted 13 April 2011 Handling Editor: Dan Faith
- biological soil crust;
- natural experiment;
- null model;
- presence–absence matrix;
- randomization test
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 × 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 β-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.