Quantitative climate reconstruction from sedimentary ancient DNA: framework, validation and application

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 analog 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.