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Quantitative climate reconstruction from sedimentary ancient DNA: framework; validation and application
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DOI：10.5194/cp-22-1159-2026.png)
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Abstract
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Abstract. Quantitative reconstructions of terrestrial climate conditions typically rely on biological proxies such as pollen. Despite their widespread use; these proxies exhibit inherent limitations such as low taxonomic resolution and complex taphonomies. Sedimentary ancient DNA (sedaDNA); particularly plant metabarcoding using chloroplast markers (trnL-gh); has emerged as a promising alternative offering enhanced taxonomic precision and local origin. Here; we present the framework for quantitative reconstruction of summer temperatures from sedaDNA assemblages applying methods that rely on surface samples for calibration (weighted-averaging partial least squares (WA-PLS); modern analogue technique (MAT)) and introducing a framework that combines modern plant occurrences and species distribution modeling (SDM) to derive taxon-specific probability density functions (PDFs) for calibration. Applying these approaches to sedaDNA data from 203 lake sediment-surface samples across Siberia; we obtained highly accurate reconstructions with median biases as low as 0.5 °C and a strong correlation with observed temperatures. Our method shows a low reconstruction bias when compared to those from other proxy calibration studies. Applied to a Lake Billyakh sediment core in eastern Siberia; our sedaDNA-based reconstructions using various approaches show similar trends and successfully reproduce regional climate changes over the past 32 000 years; aligning closely with independent pollen-based records. We also reveal that higher taxonomic resolution results in a more precise reconstruction due to narrower tolerance ranges with higher taxonomic resolution. The demonstrated reliability; low bias; and superior taxonomic resolution underscore the significant potential of sedaDNA as a robust and sensitive new terrestrial proxy for quantitative paleoclimatic research.
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