EXTINCTION THROUGH TIME AND SPACE: A MULTIVARIATE FRAMEWORK FOR EXTINCTION RISK

How predictable is extinction? Geographic range-size contractions, decreasing abundance and changes in species morphology have all separately been proposed as early warning signals for population decline. However, how these ecological facets interact is less clear. Abundance and body size together have been shown to be a better predictor of marine megafauna decline than either parameter alone, and high abundance can in some cases buffer the higher extinction risk of smaller geographic ranges. These results suggest that a reliance on single ecological facets biases estimates of extinction risk. To improve predictability of extinction, multiple early warning signals need to be combined into a multivariate framework.

The fossil record is the only direct source of ‘natural’ extinction dynamics, yet its notorious incompleteness inhibits our ability to accurately determine population extinction risk through time and space. Marine microfossils are the exception to this rule: their large population size, global distribution and excellent preservation potential allow for multivariate trait analyses. Sample collection and specimen identification is a time-consuming process that limits the size of a dataset that can be generated by individual researchers, but museum collections provide unique opportunities to generate large, global datasets required for extinction dynamics through time and across space. Here, we digitise the CLIMAP and PRISM foraminifera assemblage slides collections to compare morphology, range size, abundance and phylogenetic relatedness between suvivors, and species that became extinct since the mid-Pliocene warm period. Our results will provide the first clade-wide multivariate framework of extinction and shed new light on the complex interplay of factors driving extinction.