Disentangling synergistic climate drivers on the evolution of two species of planktonic foraminifera on regional and global scales

Evolution is driven by a combination of biotic and abiotic factors. When quantifying the effects of abiotic drivers, evolutionary change is generally described as a response to a single environmental parameter assumed to represent global climate. However, climate is a complex system of many interacting factors and characterized by high regional variability. Therefore, to understand the role of climate in evolutionary change, we need to consider multiple environmental parameters, across local, regional and global scales, as well as their interactions.

The deep-sea microfossil record is sufficiently complete that sufficiently continuous multivariate climatic and multivariate trait data can be obtained from the same samples. Here we present morphological records of the planktonic foraminifera species Globoconella puncticulata and Truncorotalia crassaformis over a ~500,000-year interval directly preceding the extinction of G. puncticulata (2.41 Ma). Material was collected from five North Atlantic sites (ODP Sites 659 [18° N], 925 [3° N] and 981 [55° N], IODP Site U1313 [41° N] and DSDP Site 606 [37° N]). Test size and shape of over 35,000 individuals were measured and compared to site-specific records of sea surface temperature, primary productivity and marine aeolian dust deposition, as well as to global records of ice volume, ocean circulation and atmospheric CO₂, and all two-way interactions.

Morphological parameters respond weakly to individual climate parameters. Once interactions among all studied climate parameters were incorporated, abiotic change explained around 35% of the evolutionary variance. Observed covariances between environmental parameters vary strongly with glacial-interglacial cyclicity, implying that the relationships among climate variables and their relative influences on evolutionary change varied through time. This time dependence cautions against unfettered use of dimension reduction techniques, such as principal components analysis, to extract a single, supposedly dominant, proxy. Furthermore species’ responses differed between geographic locations, impressing the need to test how interactions among multiple climate variables at different regional settings shape the biotic microevolutionary response to local and global abiotic change.