Biodiversity is a central notion in ecology, conservation and global change biology. Because it is represented by one word, we often treat it like it is one concept that can be measured by one number. We also treat it like anthropogenic impacts on biodiversity can be assessed by one number giving the difference in biodiversity before and after an impact. In reality biodiversity is a high dimensional concept. Biodiversity changes nonlinearly with scale. This means that any assessment of biodiversity or biodiversity change must be done in a scale-explicit way. Biodiversity is also a variety of concepts that depend on how we calibrate the importance of common vs. rare species. And leaving aside the wide varieties of anthropogenic factors that can influence biodiversity, there are at least three core ecological processes that determine the amount of biodiversity or biodiversity change. Ecologists need tools that can handle this complexity.
Results/Conclusions
I present a simple and a more complex version of a methodology that can simultaneously address all three aspects of scale-dependence, variation in meaning of biodiversity, and multiple ecological drivers of biodiversity and biodiversity change. The complex methodology relies on three different types of rarefaction curves. The simple methodology relies on a multivariate set of well-known biodiversity metrics that describe the corners of the rarefaction curves. I present a meta-analysis of data that shows that biodiversity is scale dependent (and more strongly that 33% of all rarefaction curves actually cross) and that the aforementioned well-known biodiversity metrics are surprisingly uncorrelated (r2<20%). Thus the nature of biodiversity has many degrees of freedom. I present several case studies of anthropogenic impacts that have very distinct fingerprints of which of the three ecological processes driving biodiversity that they impact.