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Creators/Authors contains: "Roth‐Nebelsick, Anita"

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  1. null (Ed.)
  2. The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO2) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO2beyond direct measurements requires the use of paleoproxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. In this study, we critically evaluated, categorized, and integrated available proxies to create a high-fidelity and transparently constructed atmospheric CO2record spanning the past 66 million years. This newly constructed record provides clearer evidence for higher Earth system sensitivity in the past and for the role of CO2thresholds in biological and cryosphere evolution. 
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  3. A variety of proxies have been developed to reconstruct paleo‐CO2from fossil leaves. These proxies rely on some combination of stomatal morphology, leafδ13C, and leaf gas exchange. A common conceptual framework for evaluating these proxies is lacking, which has hampered efforts for inter‐comparison. Here we develop such a framework, based on the underlying physics and biochemistry. From this conceptual framework, we find that the more extensively parameterised proxies, such as the optimisation model, are likely to be the most robust. The simpler proxies, such as the stomatal ratio model, tend to under‐predict CO2, especially in warm (>15°C) and moist (>50%humidity) environments. This identification of a structural under‐prediction may help to explain the common observation that the simpler proxies often produce estimates of paleo‐CO2that are lower than those from the more complex proxies and other, non‐leaf‐based CO2proxies. The use of extensively parameterised models is not always possible, depending on the preservation state of the fossils and the state of knowledge about the fossil's nearest living relative. With this caveat in mind, our analysis highlights the value of using the most complex leaf‐based model as possible. 
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