Being an ecologist is all about the trade-off between effort, and time and money. Given infinite amounts of both, we would undoubtedly sample the heck out of nature. But it would be an exercise in diminishing returns: after a certain amount of sampling, we would fail to unturn any stone that has not already been unturned. Thus, ecology is a balancing act of effort: too little, and we have no real insight. Too much, and we’ve wasted a lot of time and money.
I’m always looking for ways to improve my balance, which is why I was interested to see a new paper in Ecology Letters called “Measures of precision for dissimilarity-based multivariate analysis of ecological communities” by Marti Anderson and Julia Santana-Garcon.
In a nutshell, the paper introduces a method for, “assessing sample-size adequacy in studies of ecological communities.” Put in a slightly different way, the authors have devised a technique for determining when additional sampling does not really improve one’s ability to describe whole communities — both the number of species, and their relative abundances. Perfect for evaluating when enough is enough, and adjusting the output of time and money!
In this post, I dig into this technique, show its applications using an example, and introduce a new R function to assess multivariate precision quickly and easily.