Statistics

Many ecologists are R users, but we vary in our understanding of the math and statistical theory behind models we use. There is no clear consensus on what should be the basic mathematical training of ecologists. To learn what the community thinks, we invite you to fill out a short and anonymous questionnaire on this topic here. The questionnaire was designed by Frédéric Barraquand, a graduate student at Université Pierre et Marie Curie, in collaboration with the International Network of Next-Generation Ecologists (INNGE)....

So, I’ve blogged about this topic before, way back on 5 Jan this year. Matt Helmus, a postdoc in the Wootton lab at the University of Chicago, published a paper with Anthony Ives in Ecological Monographs this year (abstract here). The paper addressed a new statistical approach to phylogenetic community structure. As I said in the original post, part of the power of the PGLMM (phylogenetic generalized linear mixed models) approach is that you don’t have to conduct quite so many separate statistical tests as with the previous null model/randomization approach....

A new paper out in Ecology by Xiao and colleagues (in press, here) compares the use of log-transformation to non-linear regression for analyzing power-laws. They suggest that the error distribution should determine which method performs better. When your errors are additive, homoscedastic, and normally distributed, they propose using non-linear regression. When errors are multiplicative, heteroscedastic, and lognormally distributed, they suggest using linear regression on log-transformed data. The assumptions about these two methods are different, so cannot be correct for a single dataset....