Abstract

Planktonic foraminifera are marine unicellular eukaryotes that have a world-wide distribution and are central to palaeoclimate reconstructions. Despite their importance, global bioregions based on their species composition have not been quantified, and non-linear relationships between species turnover and multiple environmental predictors have not been explored. Here, we use a recently-compiled global dataset of species composition in 3,796 marine surface sediments to (i) quantify planktonic foraminifera bioregions based on clustering methods, and (ii) model the linear and non-linear predictors of their spatial turnover using Bayesian Bootstrap Generalised Dissimilarity Models. We found four global planktonic foraminifera bioregions, confirming the bi-hemispheric distribution of cold-water species, but showing that these bioregions have different extents across the oceans. Sea-surface temperature (SST) is the main predictor of species turnover globally and within oceans. The SST-turnover relationship is mostly linear, but the rate of turnover decelerates in warm waters, suggesting that the SST signal in planktonic foraminifera composition becomes weaker in the tropics. Water depth emerges as an important, non-linear predictor of species composition in the Pacific and Indian ocean. Thus, in these oceans, biogeographical patterns in seafloor sediments are affected by fossil preservation. Other environmental variables such as net primary productivity and salinity affect species turnover non-linearly and differently among oceans. Together, our results show how the change in species composition can have different predictors and shapes across the world oceans.