A New Approach to Measuring Biodiversity

Biodiversity indices are valuable for ecological science, and also as EBVs for communicating biodiversity trends with stakeholders and policy makers. Although there many are indices to measure biodiversity, the problem is that there are many indices to measure biodiversity. This is because biodiversity has many facets, and each one can be viewed in several ways. The indices that are commonly used (e.g. Hill numbers for alpha diversity) have been developed for specific facets, rather than as part of a whole.

 

Here we present an approach to biodiversity indices that integrates the different levels of species-level biodiversity into one framework. It is based on theory from both statistical and ecological modelling, where we connect the indices to means and variances of species occurrence and abundance. From this we derive new biodiversity indices which either cover the same aspect of biodiversity as old indices, or give us new angles to look at biodiversity. These indices all sum up to the total biodiversity. Because the indices have an underlying model, we can easily incorporate additional drivers, e.g. environmental predictors (to see how they drive community dis-similarity), traits, space and phylogeny. This also opens up the possibility to more directly link the indices to ecological theory and models.

 

We will present the framework, and show how our indices align with traditional measures of alpha and beta diversity, for both species richness and community composition. One of the major benefits of the framework is that it is straightforward to incorporate the sampling design of data (or sampling lack-of-design) into the analysis, extracting estimates of uncertainty, or explicitly incorporate space or time. Overall, our framework better facilitates the development of theoretically sound EBVs, to not only allow us to summarise biodiversity in a consistent way at different levels, but to look at how different impacts, e.g. climate or land use change, will affect spatial patterns of biodiversity.