| 18 Aug 2025
Marine eukaryote community responses to the climate and oceanographic changes in Storfjordrenna (southern Svalbard) over the past ⁓14.0 kyr BP: Insights from sedimentary ancient DNA analysis
Abstract. Sedimentary ancient DNA (sedaDNA) metabarcoding is an emerging method to reconstructing the response of marine organisms to past climate and oceanographic changes, including rare and non-fossilized taxa. Marine sedaDNA records from the Arctic are scarce, especially those focusing on the impact of environmental shifts on the biodiversity and functional composition of marine eukaryote communities. Here, we present a sedaDNA eukaryotic record from the sediment core retrieved in Storfjordrenna, southern Svalbard, spanning the termination of the Bølling-Allerød, the Younger Dryas, and the Holocene (13.3–1.3 kyr BP). We successfully recovered the eukaryotic communities and identified them by their ecological roles. Our study showed that the eukaryotic biodiversity in Storfjordrenna remained relatively stable, except during transitions between major climatic intervals. These shifts were marked by changes in richness and relative abundance, driven by factors such as perennial ice cover, surface water cooling, and subsurface Atlantic water influx. Cercozoans and MAST emerged as dominant heterotrophs, characterized by high ecological flexibility and broad tolerance. The primary productivity was primarily driven by ArW-associated phytoplankton, including diatoms (Thalassiosira and Chaetoceros), green algae (Micromonas), and autotrophic dinoflagellates (Polarella glacialis,) as well as mixoplanktonic silicoflagellate Pseudopedinella elastica. The ASV-based indicator analysis revealed that uncultured Cercozoan lineages and MAST taxa were primarily associated with AW proxies, whereas parasitic dinoflagellates (Dino-group I) and choanoflagellates were more closely aligned with ArW proxies. The analysis of indicator responses shows the complex interactions within eukaryotic communities and reveals a strong association among functional ecological groups, which impacts ecosystem productivity and regulation. This complexity highlights the limitations of traditional single proxy approaches to accurately reconstructing paleoenvironmental conditions. Our study demonstrates the potential of high-resolution marine sedaDNA metabarcoding in elucidating responses to past climate changes and in improving our understanding of the intricate interactions within eukaryotic communities in marine ecosystems.
The manuscript provides a reconstruction based on eDNA of the ‘eukaryotic’ community of Storfjordrenna over approximately 14K years before present. The samples were retrieved from a previously analysed sediment core (gravity core JM09-020-GC) and aims to use ancient sedimentary DNA to identify a more complete community of eukaryotes over time, adding to the microfossil work that has been previously reported by Lacka and colleagues. The goal of the study was to fill an information gap.
The introduction provides a brief synopsis of the region and core site, which can be influenced by either Arctic or Atlantic currents.
A concern is whether the site, with a constantly moving fronts of Atlantic and Arctic is useful as a proxy for detecting warmer periods. How integrative is the data within the strata sampled?
A second concern is whether the information from the bioinformatically classified amplicons is sufficient for the detailed interpretation of ecology for different epochs. The amplicons were assigned at order, family and sometimes genus level, and then used to infer functional roles and provenance of the community members. While this approach could be sufficient for some groups, for others accurate species identification is critical. Although statistically possible, the assignment to providence is questionable, and the interpolation of trophic status doubtful given the lack of confirmatory experimental data.
A major question is why the V1V2 region was targeted given most microbial eukaryotic studies primarily target V4, with V9 the second most used. It seems V1V2 sequences would greatly limit the taxonomic resolution of the study. A second question on the use V1V2 is that, since they are at an end of the gene, it seems that the region would be more prone to degradation over time.
The ‘missing 3.5 kyr is also problematic, does this fit with other mid Holocene anomalies with warmer river inputs (more terrestrial?). Would the region be affected by Siberian rivers (e.g. see Dong et al. Nature communication 2022. Doi: 10.1038/s41467-022-33106-1)? How does this fit with the low mass accumulation rates given in Lacka et al. 2015? Despite the low accumulation those authors still reported forams in those sediments. So was the lack of signal due to higher DNA degradation rates?
Most of the discussion seems to rely on supplementary figures and data, and the key points should be put in an integrating figure at the end.
Overall, I am not sure how the analysis and conclusions have improved our understanding of the future trajectory of the Arctic biota, given that this region has always been on the front between Atlantic and Arctic waters
Specific comments.
Abstract:
Line 25: define acronyms such as ArW on first mention. Please check elsewhere as well.
Introduction:
Line 48: It is more usual to list references in chronological order.
Line 54: change ‘it’ to “biodiversity”. I was not sure; the sentence was quite long.
Line 64: what is meant by “significant’ was there a statistical test?
Line 74: was the core taken from the trough south of Stofjorden? Please clarify.
Line 80-82: The study is correlative, and the detected changes could be a response to any number of environmental conditions. The results suggest trajectories.
Methods
Line 123: please justify the use of the V1V2 region, the vast majority of other amplicon 18S rRNA gene surveys target V4. See above comments
Line 138; Why 50 cycles? 30 is more usual and more cycles can lead to artifacts, e.g. “point mutations” and primer dimers. Fewer cycles lead to higher taxa richness estimates (e.g. Wu et al. BMC Microbiology https://doi.org/10.1186/1471-2180-10-255).
Lien 152 : Ibarbalz et al. is not in the reference list.
Line 205: Is there an explanation for the low number of reads between 4.0 and 7.5 kyr BP? See comment above.
Line 236. Figure 2, no time patterns are evident. What is the utility of this analysis?
Line 243, what is meant by “stable” in the context of the missing 3.5 kyr?
Line 277: The term microzooplankton is ambiguous, it can also mean very small metazoans, distinguished from e.g. large calnanus species. Referring back to the previous paragraph; how realistic is it to separate mixotrophic dinoflagellates and heterotrophic dinoflagellates at the taxonomic level compiled in figure 3.
Figure 3b is confusing as it seems ecological groups and taxonomic gropes are given with the list of other heterotrophs. Perhaps this should be 2 separate sub figures
Discussion
Line 360: ‘patterns” would be a better word than ‘dynamics”
Line 427: Micromonas polaris is pan arctic and occurs throughout the euphotic water column all year round. The Grant et al. paper is only about sediment and ignores the huge amount of data records for this species. M. polaris is not adapted to increased warming.
Line 474; how is extreme defined here and throughout.
Line 487: I believe it would be nutrient “resupply” rather than “resuspension” Nutrients are incorporated into biomass, which needs to be broken down by bacteria etc. They then re-enter the euphotic zone as inorganic nutrient, by physical oceanographic processes; such as upwelling, deep mixing or lateral advection.
Line 544: Heterocapsa arctica in the Arctic should not be confused with Heterocapsa bohalensis the HAB species. This is an example of the danger of generalizing (see above comment on the need for species identification.)
Lin 602: all of the results are correlative and a more cautious interpretation is needed.