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

This manuscript aims to reconstruct past summer temperatures in Siberia over the last 32,000 years. Four approaches are developed based on modern datasets (observations and fossil records) and applied to a sediment archive (a core from Lake Billyakh). Each method entails specific benefits and drawbacks, which makes the approaches highly complementary and strengthens the robustness and quality of the study. In particular, the approaches combining “raw” GBIF data or species distribution models derived from these data (a method mostly used in ecology) with taxon-specific probability density functions to link taxa to climatic conditions are very original in palaeoenvironmental contexts.

It is also noteworthy that using plant sedaDNA communities in combination with several statistical approaches significantly improved predictive accuracy (see median bias and root-mean-squared error of prediction), compared to other proxies (e.g. pollen, chironomids). Another strength of the study is the availability of a large modern surface-sample dataset (203 sites), which was used for training (WA-PLS, MAT) and for independent validation of the methods (GBIF-SPD or SDM-SPD).

My main concern relates to the impact on reconstructions that incorporate the SPDs approach of the relative contributions of different taxa estimated by sedaDNA, which most likely do not reflect their actual contributions in the landscape. Since this information is used to weight the SPDs, I think the potential impact should be discussed. This could be addressed in section 4.3. At present, the only mention is in the outlook section: “Furthermore, integrating absolute quantification methods (e.g. DNA-based biomass estimates) could reduce PCR-related biases, enhancing proxy accuracy (Ushio et al., 2018).”

In addition, in my view, the manuscript would benefit from a section addressing other climate proxies beyond vegetation assemblage reconstructions (e.g. BrGDGTs, chironomids, δ18O from diatoms or ostracods).

Specific comments

• L27:I would add “in appropriate contexts, i.e. where vegetation composition is primarily driven by climatic conditions.”
• L50:Perhaps mention topography as well?
• L285–286:The sentence is awkward: “However, some taxa occur with high abundance that occur today under warm conditions including Crepinidae_01 and Asteraceae_03.” → Suggested: “However, some highly abundant taxa also occur today under warm conditions (e.g. Crepinidae_01 and Asteraceae_03).”
• L294:For “outlier taxa”, please provide a definition: e.g. taxa with warm ecological preferences found during glacial periods, or the opposite.
• L339:The word “quantitatively” seems unnecessary — temperature is inherently quantitative.
• L349–350:Specify that you are referring to chironomid head capsules, not chironomid DNA.
• L359–361:Runoff refers only to the flow of water over the land surface (rain, snowmelt). Strictly speaking, this does not necessarily include erosion, which is the key process in Giguet-Covex et al. (2019). Suggested formulation:
  
  “SedaDNA mainly originates from the lake’s immediate catchment, since erosion of the surrounding slopes is the dominant transport process.”
• L375:With Courtin et al., 2021, you may also cite Giguet-Covex et al., 2019.
• L380: I would precise "...of direct and indirect climate drivers..."
• L391:Figure 6 is not placed correctly in the sentence.
• L396–401:The explanation could be clarified. Current text:“The plant metabarcoding assemblages from Lake Billyakh used for reconstruction are substantially more diverse than the pollen data (73 vs. 41 taxa), likely contributing to a more stable reconstruction. In contrast, the pollen-based reconstruction displays greater variability (Fig. 4), possibly due to a lower signal-to-noise ratio stemming from fewer taxa contributing to the reconstruction. This interpretation aligns with findings by Heiri and Lotter (2010), who demonstrated that lower taxonomic resolution in chironomid-based temperature reconstructions decreases sensitivity in detecting subtle climate variations.”
  
  ➡ Suggestion: Make the link between diversity and stability explicit. For example:
  
  “A higher number of taxa increases the likelihood of detecting species with narrow ecological niches, which may strengthen the climate signal and improve the signal-to-noise ratio. This mechanism, rather than diversity per se, may explain the stability of the sedaDNA-based reconstruction.” Also, clarify the distinction between diversity and taxonomic resolution to avoid confusion (you first speak about diversity and at the end about taxonomic resolution).
• L407:I assume you mean Figure 4.
• L423:Please provide the RMSEP value for the plantDNA_PDF/SDM approach.
• L425–427:Clarify whether you are referring to all approaches or only the PDF-based ones. The results for WA-PLS and MAT in Fig. 2 seem less clear.

Figure improvements

• Fig. 1: Add a blue border to the text boxes associated with sedaDNA (field sampling, laboratory analyses, bioinformatics). In the bioinformatics part, remove animals (since only plant data were used here).
• Fig. 2: The ΔT for Billyakh is not shown — could you add its color code? Also, include the number of modern lake sediment sites used.
• Fig. 4: Highlight (e.g. in bold) taxa detected in both periods.