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The Scientific World Journal
Volume 2012, Article ID 365409, 9 pages
http://dx.doi.org/10.1100/2012/365409
Research Article

A Refined Methodology for Defining Plant Communities Using Postagricultural Data from the Neotropics

Biology Department, Oklahoma State University, Oklahoma City, OK 73107, USA

Received 30 October 2011; Accepted 8 December 2011

Academic Editor: Qinfeng Guo

Copyright © 2012 Randall W. Myster. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

How best to define and quantify plant communities was investigated using long-term plot data sampled from a recovering pasture in Puerto Rico and abandoned sugarcane and banana plantations in Ecuador. Significant positive associations between pairs of old field species were first computed and then clustered together into larger and larger species groups. I found that (1) no pasture or plantation had more than 5% of the possible significant positive associations, (2) clustering metrics showed groups of species participating in similar clusters among the five pasture/plantations over a gradient of decreasing association strength, and (3) there was evidence for repeatable communities—especially after banana cultivation—suggesting that past crops not only persist after abandonment but also form significant associations with invading plants. I then showed how the clustering hierarchy could be used to decide if any two pasture/plantation plots were in the same community, that is, to define old field communities. Finally, I suggested a similar procedure could be used for any plant community where the mechanisms and tolerances of species form the “cohesion” that produces clustering, making plant communities different than random assemblages of species.