Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies

The composition of planktonic foraminiferal (PF) calcite is routinely used to reconstruct climate change and variability. However, PF ecology leaves a large imprint on the proxy signal. The seasonal and vertical habitat of planktonic foraminifera (PF) species varies spatially, causing variable offsets from annual mean surface conditions recorded by sedimentary assemblages. PF seasonality changes with temperature in a way that minimises the environmental change that individual species experience. While such habitat tracking could lead to an underestimation of spatial or temporal trends and variability in proxy records, most paleoceanographic studies are based on the assumption of a constant habitat. Although the controls on depth habitat variability are less well constrained, it is not unlikely that habitat tracking also affects PF depth habitat. Despite the implications, the effect of this behaviour on foraminifera proxy records has not yet been formally quantified on a global scale. Here we attempt to characterise the effect of habitat tracking on the amplitude of environmental change recorded in sedimentary PF using core top δ18O data from six species, which we compare to predicted δ18O. We find that the offset from mean annual near-surface δ18O values varies with temperature, with PF δ18O indicating warmer than mean conditions in colder waters (on average by −0.1 ‰ (or 0.4°C) per °C), thus providing a first-order quantification of the degree of underestimation due to habitat tracking. We then use an empirical model to estimate the contribution of seasonality to the observed difference between PF and annual mean δ18O and use the residual Δδ18O to assess trends in calcification depth. Our analysis indicates that in all species calcification depth increases with temperature. Consistent with hydrographic conditions, vertical habitat adjustment is dominant in tropical species, whereas cold-water species mainly changes their seasonality when tracking their "optimum" habitat. Assumptions of constant PF depth or seasonal habitat made when interpreting proxy records are thus invalid. The approach outlined here can be used to account for these effects, enabling more accurate reconstructions and improved data-model comparison.