Toward a global calibration for quantifying past oxygenation in oxygen minimum zones using benthic Foraminifera

Abstract

Abstract. Oxygen minimum zones (OMZs) are oceanic areas largely depleted in dissolved oxygen, nowadays considered in expansion in the face of global warming. To investigate the relationship between OMZ expansion and global climate changes during the late Quaternary, quantitative oxygen reconstructions are needed but are still in their early development. Here, past bottom water oxygenation (BWO) was quantitatively assessed through a new, fast, semi-automated, and taxon-independent morphometric analysis of benthic foraminiferal tests, developed and calibrated using WNP (western North Pacific, including its marginal seas), ENP (eastern North Pacific), and ESP (eastern South Pacific) OMZ samples. This new approach is based on an average size and shape index for each sample. This method, as well as two already published micropalaeontological techniques based on benthic foraminiferal assemblages' variability and porosity investigation of a single species, was calibrated here based on availability of new data from 45 core tops recovered along an oxygen gradient (from 0.03 to 2.88 mL L−1) from the WNP, ENP, EEP (eastern Equatorial Pacific), ESP, SWACM (southwest African continental margin), and AS (Arabian Sea) OMZs. Global calibrated transfer functions are herein proposed for these methods. These micropalaeontological reconstruction approaches were then applied to a palaeorecord from the ENP OMZ to examine the consistency and limits of these methods, as well as the relative influence of bottom and pore waters on these micropalaeontological tools. Both the assemblage and morphometric approaches (which are also ultimately based on the ecological response of the complete assemblage and faunal succession according to BWO) gave similar and consistent past BWO reconstructions, while the porosity approach (based on a single species and its unique response to a mixed signal of bottom and pore waters) showed ambiguous estimations.