Foraminifera Species Distribution Models Inform Proxy Interpretation and Place Future Change in Geological Context

Tuesday, 15 December 2020
Peter Jacobs1, Kim de Mutsert1, Harry J Dowsett2 and Lukas Jonkers3, (1)George Mason University, Environmental Science and Policy, Fairfax, VA, United States, (2)U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA, United States, (3)MARUM - University of Bremen, Bremen, Germany
Planktic foraminifera, a type of zooplankton, are a frequently used proxy for ocean conditions in Earth's past. In addition to isotopic geochemical analyses of their shells, or tests, the spatial distribution and community composition of these foraminifera (i.e. faunal assemblages) are used to infer information about paleoenvironments. Standard faunal assemblage proxy reconstructions often reduce multidimensional environmental data into a single variable, typically temperature. However, when environmental covariates feature strong spatial autocorrelation, traditional methods may incorrectly interpret information from other variables as a temperature signal. Forward modeling using such transfer functions might also give an incomplete picture of how these plankton might be affected by climate change in the future. This study demonstrates how modern machine-learning based Species Distribution Modeling provides insights into both of these problems. Building models for several foraminifera taxa, it is demonstrated that temperature is an unquestionably important control on foraminifera distribution, but dissolved oxygen and nutrients also play a substantial role. By comparing future change in foraminifera habitats under several emissions scenarios to intervals from Earth's climatic past, changes in some taxa suitability- due to the magnitude of surface warming or decoupling between surface warming and dissolved oxygen trends- are found to result in habitat changes that are unprecedented for at least the last 20,000 years.