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Periods of large igneous province (LIP) magmatism have shaped Earth’s biological and climatic history, causing major climatic shifts and biological reorganizations. The vegetation response to LIP-induced perturbations may affect the efficiency of the carbon-climate regulation system and the post-LIP climate evolution. Using an eco-evolutionary vegetation model, we demonstrate here that the vegetation’s climate adaptation capacity, through biological evolution and geographic dispersal, is a major determinant of the severity and longevity of LIP-induced hyperthermals and can promote the emergence of a new climatic steady state. Proxy-based temperature reconstructions of the Permian-Triassic, Triassic-Jurassic, and Paleocene-Eocene hyperthermals match the modeled trajectories of bioclimatic disturbance and recovery. We conclude that biological vegetation dynamics shape the multimillion-year Earth system response to sudden carbon degassing and global warming episodes. [ABSTRACT FROM AUTHOR]

The stable oxygen (δ18Oshell) and carbon (δ13Cshell) isotope ratios retrieved from the carbonate shell of terrestrial gastropods can be used as an environmental proxy and are thought to reflect dietary composition and ambient climatic conditions (e.g. precipitation amount, humidity, temperature). Here, we generate high‐resolution isotopic profiles of nine modern land snails of the genus Placostylus, collected from two locations in New Caledonia and one location in New Zealand. We found that snails from New Zealand had, on average, higher δ18Oshell values than their counterparts in New Caledonia, which surprisingly runs counter to the expected relationship based on the isotopic composition of rainwater between these two regions. Specimens from New Caledonia exhibit ephemeral decreases in their δ18Oshell values, which could be linked to extreme precipitation events in this region, while snails from New Zealand have less variation in their δ18Oshell values. Snails from New Zealand had, on average, slightly higher δ13Cshell than their counterparts in New Caledonia, but a large difference in carbon isotopes was sometimes observed between snails collected at the same location. Most snails exhibit a temporal trend in their δ13Cshell values, indicating potential shifts in diet through to maturity. [ABSTRACT FROM AUTHOR]

Paleoclimate data assimilation (DA) is a tool for reconstructing past climates that directly integrates proxy records with climate model output. Despite the potential for DA to expand the scope of quantitative paleoclimatology, these methods remain difficult to implement in practice due to the multi-faceted requirements and data handling necessary for DA reconstructions, the diversity of DA methods, and the need for computationally efficient algorithms. Here, we present DASH, a MATLAB toolbox designed to facilitate paleoclimate DA analyses. DASH provides command line and scripting tools that implement common tasks in DA workflows. The toolbox is highly modular and is not built around any specific analysis, and thus DASH supports paleoclimate DA for a wide variety of time periods, spatial regions, proxy networks, and algorithms. DASH includes tools for integrating and cataloguing data stored in disparate formats, building state vector ensembles, and running proxy (system) forward models. The toolbox also provides optimized algorithms for implementing ensemble Kalman filters, particle filters, and optimal sensor analyses with variable and modular parameters. This paper reviews the key components of the DASH toolbox and presents examples illustrating DASH's use for paleoclimate DA applications. [ABSTRACT FROM AUTHOR]

Paleoclimate data assimilation (DA) is a novel tool for reconstructing past climates that directly integrates proxy records with climate model output. Despite the potential for DA to expand the scope of quantitative paleoclimatology, these methods remain difficult to implement in practice due to the multi-faceted requirements and data handling necessary for DA reconstructions, the diversity of DA methods, and the need for computationally efficient algorithms. Here, we present DASH, a MATLAB toolbox designed to facilitate paleoclimate DA analyses. DASH provides command line and scripting tools that implement common tasks in DA workflows. The toolbox is highly modular and is not built around any specific analysis, and thus DASH supports paleoclimate DA for a wide variety of time periods, spatial regions, proxy networks, and algorithms. DASH includes tools for integrating and cataloguing data stored in disparate formats, building state vector ensembles, and running proxy (system) forward models. The toolbox also provides optimized algorithms for implementing ensemble Kalman filters, particle filters, and optimal sensor analyses with variable and modular parameters. This paper reviews the key components of the DASH toolbox and presents examples illustrating DASH's use for paleoclimate DA applications. [ABSTRACT FROM AUTHOR]