Associations between species and groups of sites: indices and statistical inference

TLDR

Ecologists study species–site group associations to understand ecological preferences and inform conservation, using indices such as the phi coefficient and the indicator value index (IndVal). The authors compare the phi coefficient and the indicator value index within a broader framework of related measures that includes several new indices. They employ permutation tests to assess the statistical significance of species–site group associations and bootstrap methods to obtain confidence intervals. The phi coefficient is more context‑dependent but highlights species preference, whereas the indicator value index’s components directly measure bioindicator value as positive predictive value and sensitivity, so ecologists should choose the index that matches their objective and compute confidence intervals to assess precision.

Abstract

Ecologists often face the task of studying the association between single species and one or several groups of sites representing habitat types, community types, or other categories. Besides characterizing the ecological preference of the species, the strength of the association usually presents a lot of interest for conservation biology, landscape mapping and management, and natural reserve design, among other applications. The indices most frequently employed to assess these relationships are the phi coefficient of association and the indicator value index (IndVal). We compare these two approaches by putting them into a broader framework of related measures, which includes several new indices. We present permutation tests to assess the statistical significance of species–site group associations and bootstrap methods for obtaining confidence intervals. Correlation measures, such as the phi coefficient, are more context‐dependent than indicator values but allow focusing on the preference of the species. In contrast, the two components of an indicator value index directly assess the value of the species as a bioindicator because they can be interpreted as its positive predictive value and sensitivity. Ecologists should select the most appropriate index of association strength according to their objective and then compute confidence intervals to determine the precision of the estimate.