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The influence of single elements on nested community structure
Article first published online: 25 MAR 2011
© 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society
Methods in Ecology and Evolution
Volume 2, Issue 5, pages 541–549, October 2011
How to Cite
Joppa, L. N. and Williams, R. (2011), The influence of single elements on nested community structure. Methods in Ecology and Evolution, 2: 541–549. doi: 10.1111/j.2041-210X.2011.00101.x
- Issue published online: 10 OCT 2011
- Article first published online: 25 MAR 2011
- Received 30 August 2010; accepted 5 February 2011 Handling Editor: Robert P Freckleton
- community ecology;
- ecological networks;
1. Asking whether or not an ecological community displays the structural property of nestedness is becoming increasingly common in ecological research. We note, however, a currently limited understanding of how individual matrix components (e.g. species as rows and sites as columns) and elements (e.g. a species’ occurrence at a site) contribute to overall community structure.
2. Here, we investigate the influence of single elements in a community matrix on overall community nestedness. We derive a unique extension to the popular nestedness algorithm NODF that is necessary for this analysis.
3. For 210 empirical communities, we show that elements, on average, determine a little less than 50% of a community’s nestedness value, with components determining the remainder. Looking at just matrix elements we find, on average, that 10% of elements determine 25% of a community’s nested structure. Further, we find statistical conclusions change for more than 20% of the empirical communities with the addition or removal of a single element.
4. Generally, the search for ecological pattern occurs by calculating a single metric designed to quantify the structure of an entire community. By showing the sensitivity of a metric to changes in a single element, our results cast doubt on the usefulness of this approach. That said, the extension to NODF that we present should allow researchers to better understand how individual elements in a community influence patterns of nestedness.