Title

Assessment of mean annual precipitation and pCO2 effect on C3 land plant carbon isotope fractionation

Presentation Type

Event

Start Date

27-4-2019 9:30 AM

End Date

10-5-2019 10:44 AM

Abstract

Recent growth chamber experiments suggest under controlled moisture condition, the carbon isotope fractionation of C3 land plants is positively correlated with environmental CO2 concentrations. Therefore, sedimentary organic carbon isotopes have been used as proxies for atmospheric CO2 levels in the geologic past. Modern large dataset on organic carbon isotopes of C3 land plants also reveal a positive correlation between fractionation and mean annual precipitation (MAP). However, the effect of precipitation and CO2 sometimes cancel each other, making it difficult to interpret the carbon isotope signals. This led to the suggestion that if CO2 is known at any given time in the geologic past, then MAP can be estimated or vice versa. Here, we test this hypothesis by conducting a geospatial correlation analysis on modern carbon isotopes of C3 land plants and mean annual precipitation dataset to find region-specific statistically significant correlation and apply this region-specific regression to infer past climate. We obtain climate data, including MAP, CO2 and fossil organic carbon isotopes in the Quaternary to perform the least square regression. This study expects potential for the usage of this regression equation to correct for changes in MAP in geological samples to offer more reliable pCO2 estimates based on empirical relationship between MAP, CO2, and carbon isotope fractionation. It will help better understand how climate will change due to anthropogenic CO2 emissions by understanding the drivers of past climate change.

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Apr 27th, 9:30 AM May 10th, 10:44 AM

Assessment of mean annual precipitation and pCO2 effect on C3 land plant carbon isotope fractionation

Recent growth chamber experiments suggest under controlled moisture condition, the carbon isotope fractionation of C3 land plants is positively correlated with environmental CO2 concentrations. Therefore, sedimentary organic carbon isotopes have been used as proxies for atmospheric CO2 levels in the geologic past. Modern large dataset on organic carbon isotopes of C3 land plants also reveal a positive correlation between fractionation and mean annual precipitation (MAP). However, the effect of precipitation and CO2 sometimes cancel each other, making it difficult to interpret the carbon isotope signals. This led to the suggestion that if CO2 is known at any given time in the geologic past, then MAP can be estimated or vice versa. Here, we test this hypothesis by conducting a geospatial correlation analysis on modern carbon isotopes of C3 land plants and mean annual precipitation dataset to find region-specific statistically significant correlation and apply this region-specific regression to infer past climate. We obtain climate data, including MAP, CO2 and fossil organic carbon isotopes in the Quaternary to perform the least square regression. This study expects potential for the usage of this regression equation to correct for changes in MAP in geological samples to offer more reliable pCO2 estimates based on empirical relationship between MAP, CO2, and carbon isotope fractionation. It will help better understand how climate will change due to anthropogenic CO2 emissions by understanding the drivers of past climate change.