Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
The analysis of presence––absence matrices with ““null model”” randomization tests has been a major source of controversy in community ecology for over two decades. In this paper, I systematically compare the performance of nine null model algorithms and four co-occurrence indices with respect to Type I and Type II errors. The nine algorithms differ in whether rows and columns are treated as fixed sums, equiprobable, or proportional. The three models that maintain fixed row sums are invulnerable to Type I errors (false positives). One of these three is a modified version of the original algorithm of E. F. Connor and D. Simberloff. Of the four co-occurrence indices, the number of checkerboard combinations and the number of species combinations may be prone to Type II errors (false negatives), and may not reveal significant patterns in noisy data sets. L. Stone and A. Robert's checkerboard score has good power for detecting species pairs that do not co-occur together frequently, whereas D. Schluter's V ratio reveals nonrandom patterns in the row and column totals of the matrix. Degenerate matrices (matrices with empty rows or columns) do not greatly alter the outcome of null model analyses. The choice of an appropriate null model and index may depend on whether the data represent classic ““island lists”” of species in an archipelago or standardized ““sample lists”” of species collected with equal sampling effort. Systematic examination of a set of related null models can pinpoint how violation of the assumptions of the model contributes to nonrandom patterns.
Ecology – Ecological Society of America
Published: Sep 1, 2000
Keywords: assembly rules ; checkerboard distribution ; coexistence ; community structure ; competition ; co-occurrence ; Monte Carlo simulation ; null model ; presence––absence matrix ; randomization test ; species combinations
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.