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Negative carbon isotope excursions: an interpretive framework

Research output: Contribution to journalArticle

Original languageEnglish
JournalEnvironmental Research Letters
Volume14
Issue number8
DateAccepted/In press - 17 Jul 2019
DatePublished (current) - 14 Aug 2019

Abstract

Numerous negative carbon isotope excursions (nCIEs) in the geologic record occurring over 104–105 years are interpreted as episodes of massive carbon release. nCIEs help to illuminate the connection between past carbon cycling and climate variability. Theoretically, the size of a nCIE can be used to determine the mass of carbon released, provided that the carbon source is known or other environmental changes such as temperature or ocean pH can be constrained. A simple isotopic mass balance equation often serves as a first order estimate for the mass of carbon input, but this approach ignores the effects of negative carbon cycle-climate feedbacks. Here we show, using 432 earth system model simulations, that the mass of carbon release and associated environmental impacts for a nCIE of a given size and carbon source depend on the onset duration of that nCIE: the longer the nCIE onset duration, the greater the required carbon input in order to counterbalance the input of 13C-enriched carbon through carbonate compensation and weathering feedbacks. On timescales >103 years, these feedbacks remove carbon from the atmosphere so that the relative rise in atmospheric CO2 decreases with the nCIE onset duration. Consequently, the impacts on global temperature, surface ocean pH and saturation state are reduced if the nCIE has a long onset duration. The framework provided here demonstrates how constraints on the total nCIE duration and relative shape—together determining the onset duration—affect the interpretation of sedimentary nCIEs. Finally, we evaluate selected well-studied nCIEs, including the Eocene Thermal Maximum 2 (~54 Ma), the Paleocene–Eocene Thermal Maximum (~56 Ma), and the Aptian Oceanic Anoxic Event (~120 Ma), in the context of our model-based framework and show how modeled environmental changes can be used to narrow down the most likely carbon emissions scenarios.

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