the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Aug 2026
Phytoplankton community responses to 20th century eutrophication of Swiss Plateau lakes: a proxy comparison from short sediment cores
Abstract. During the last century, temperate lakes have been strongly impacted by human eutrophication and climate change, causing shifts in phytoplankton communities and higher abundance of cyanobacteria. Paleolimnological reconstructions can extend the timeframe of observations beyond the extent of monitoring data and reveal long-term changes in aquatic communities. Existing paleolimnological studies often rely on proxies that are solely indicative of individual algal groups. As a result, reconstructing the overall algal community composition remains challenging. Here, we analyzed and cross-validated multiple proxies for phytoplankton community composition in sediment cores from three lakes on the Swiss Plateau that underwent extreme eutrophication in the 20th century. We measured the relative abundance of phytosterols and phytol (phytol:sterol index, PSI) and hydrogen isotope offsets between C16:0 fatty acid and phytol (δ2HC16:0 Acid/Phytol) and used these to detect past changes in the relative proportions of eukaryotic algae and cyanobacteria. We compared these new organic geochemical proxies with observational data and with gene amplicon sequence variants (ASVs) from plastid-derived 23S rRNA. PSI and δ2HC16:0 Acid/Phytol values were generally in good agreement with cyanobacterial 23S rRNA ASVs, and all proxies indicated increasing proportions of cyanobacteria in response to eutrophication. However, our study also revealed potential biases associated with each individual algal proxy. Specifically, δ2HC16:0 Acid/Phytol values were impacted by non-algal lipid sources, while the abundance of small coccoid cyanobacterial taxa was overestimated by 23S rRNA ASVs relative to their biovolume. Still, the combination of PSI and δ2HC16:0 Acid/Phytol values with other algal proxies is a promising tool for tracing the long-term relative abundance of cyanobacteria and could provide a comprehensive picture of changes in phytoplankton communities over millennial timescales.
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Status: open (until 21 Nov 2026)
- RC1: 'Comment on egusphere-2026-4300', Anonymous Referee #1, 11 Sep 2026 reply
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RC2: 'Comment on egusphere-2026-4300', Anonymous Referee #2, 23 Oct 2026
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Comments on egusphere-2026-4300
“Phytoplankton community responses to 20th century eutrophication of Swiss Plateau lakes: a proxy comparison from short sediment cores”, by Klatt et al
General thoughts
The use of paleolimnological methods to ”hindcast” species changes and the ecological factors leading to lake eutrophication has been used in other lake systems worldwide for decades. What is new about this study is the authors’ use if a more extensive array of proxies, including some rarely used in paleo work (e.g., phytol-sterol index, lipid isotope fractionation, bacterial and plastid ASVs) to capture a more complete assessment. They examined phytoplankton change using sediment cores collected from three well-studied lakes, to assess effects specifically during the 20th century. As a result, this is a very “method-heavy” paper. Importantly, the study also evaluated the efficacy and biases associated with different chemical and molecular proxies, something paleolimnologists rarely do. The text is quite long and extensive but generally well written, with few grammatical or wording issues.
Reviewer comment: Due to the very wide array of methods used, this reviewer could not comment fully on methods outside my area of expertise.
Introduction. A good general review of past and recent paleo methodologies that have been used to assess climate and eutrophication changes in lakes. The authors summarize and explain more recently developed measures such as the phytol:sterol index (PSI) and δ2H lipid values, and algal molecular markers, which should be a beneficial addition to the limnological literature.
Methods. The authors provide a highly detailed explanation of the ecological conditions of the three study lakes. The many methods that were employed are described in great detail. A few need further explanation and clarification (see specific comments by line number), or proper citations. An explanation is needed regarding the uncertainty / reliability the PSI ratio (see specific comments below). The strategy used to identify informative ASVs for eukaryotic algae from 23S rRNA amplicons need better explanation and justification.
Results. The authors provide an extensive and impressive amount of data, often plotting multiple sets of data in one large figure. The general impression from this reader is there are multiple lines of evidence that clearly support the idea that change is occurring over time, and that some factors (e.g. TP) are likjely involved. But with this amount of information, many details are difficult for to recognize (or see) and in places, are confusing. Separated figures would be much more helpful.
Good agreements between PSI and some algal 23S rRNA ASVs data, and indications about cyanobacteria over longer time periods is a strong point of this very large study. However, the high incidence of “Bangiophyceae” in the ASV signals suggest a real concern about their ASV data. This issue requires much more thought than what is suggested, besides “inaccurate taxonomic assignments.” I offer detailed comments on this problem, below. I suggest the use of the term “phytoplankton assemblage,” rather the “community” throughout the paper. The latter term implies connections and associations that are not necessarily present or demonstrated here. To their credit, the authors correctly admit there were weaknesses in some of the methods that were used (e.g. line 674-676). I suggest that the authors consider more deeply the causes for biases or errors associated with some of the chemical and molecular proxies that were used. This would be helpful for future researchers aiming to apply some of these new approaches.
I did not cross-check references cited in the text vs. the References list.
Specific comments by line numbers
98-99: the “eutrophic” and “hypertrophic” classifications of Lampert & Sommer (1993) are somewhat at variance with other classifications. For example, in Dillon & Molot (2024), eutrophic range is 16-386 (mean 84); hypertrophic range is 750-1200. It is worth considering that these trophic categories are based on different empirical studies and not actual (direct) measurements. [Molot & Dillon 2024. The Phosphorus Cycle. In Wetzel's Limnology (pp. 359-425). Academic Press.]
127-128: Can the dates of wastewater treatment and restrictions on the use of P-containing detergents in this region be dated more precisely than “1980s”? This would be of importance with regard to identifying changes in lake-water TP in the figures.
138: Nutrient releases from sewage or what sources?
142-143: see comment for lines 127-128.
156: change “dry weight” to “dry mass”
159-160: Explain this more fully.
166: (a) Explain in more detail what is meant by “air control samples as described by Armbrecht et al. (2022).” (b) I presume this refers to the negative controls for DNA extractions? Were any water or autoclaved sediment samples use as negative controls? (c) What checks were made to account for mixing between sections of the cores? (d) what positive controls were used?
172: Details vague: “10 min on a vibratory mixer (highest speed)”. Generally, the use of bead beaters specifies the material (glass, ceramic, etc.), size, and mass of beads, and operating specifics of the equipment (e.g., 962 g, 45 s, 3 cycles). Size and material affect recovery.
198-202: Clarify: What do the “samples” refer to from which DNA reads were obtained? Does a “sample” (17 samples, ”14 samples”, etc.) refer to a section (i.e., date) from a specific section of a core? Unclear.
211-213: What basis was used to discern “non-algal ASVs”?
215: How were ASV data normalized?
250-260: Question: were other lipids such as EPA or other PUFAs also considered? Explain.
265-267: Provide a little more explanation for this estimation of TOC.
278-279: From what laboratory at Indiana University?
300-315: A large amount of uncertainty (variation) is included (but unknown) within the computation of the PSI ratio. This number is based on so many individual measures, each of which has some variation of its own. Ratios can be tricky! Variation can be hidden when multiple variables are combined. Do you have any measures to meaningfully quantify or estimate PSI variation and confidence intervales?
324-325: Source of algal biovolume calculations?? The authors cite “(Narwani et al., 2019)”, but that article does not explain formulas or their method. In turn, the Narwani et al. (2019) article cites another source: “Carvalho et al. 2007. Phytoplankton classification tool (phase 2). Edinburgh, UK: PCSSP.” This is a technical report of the U.K. Environment Agency. Looking further, one finds tables and data “… based on measurements made during counting…” of samples collected in the U.K. and Ireland. Calculations were given for 112 common species seen in their samples from U/.K. lakes and rivers. Later, in Appendix 1A, one finds generalized formulas for those cells of colonies not on their common species list. In sum, it is unclear how the authors of the present manuscript actually obtained their biovolume values.
345: This subsection label, “3 Results” is confusing. I suggest renaming as “3 Community Analysis”. These are not results, but another (multivariate) method.
364: Wording? “…again co-occurring with significant changes…” Statistically significant, or “major” changes?
381: Confusing wording: “derived mainly from Bangiophyceae” or “correlated with from Bangiophyceae”? See also comments on lines 510-555.
385: Wording, change: “were found” to “were detected”
395: Wording, change: “was stable” to “was unchanged”
401: Insert “Numbers of ASVs of Cyanobacteriota…”
409: Fig, 4A: I am dubious about including ASV and biovolume data on the same figure for the cyanobacteria. Plotted together, the scales imply a difference that may not exist. I suggest that the biovolume data be placed in a separate (sub-) figure as an inset (in its own box).
510-514, 550-555: The high incidence of “Bangiophyceae” in the ASV signals? Indeed there must be inaccurate taxonomic assignments, but this will depend a great deal on which gene regions were used. I suspect that if some plastid sequences were not chosen carefully enough (this reviewer did not dig into this in detail), “red” plastid information could have come from several unrelated algal lineages. For example, diatoms possess through their evolution, a red algal plastid by secondary endosymbiosis. And although the authors founds apparent “matches,” the NCBI database is not without its own errors. The authors should look into this issue more fully.
580-582: I question the conclusion in the statement that “cell counts documented the persistent abundance of Cryptophyceae which were mostly (?) not reflected by sedimentary algal ASVs. The poor preservation of Cryptophyceae DNA in sediment records may be associated with preferential DNA degradation…”.
- This could also be due to a similar issue with the gene regions used to obtain ASVs “representative” of members of the Cryptophyceae. They too are the results of multiple secondary endosymbioses.Citation: https://doi.org/10.5194/egusphere-2026-4300-RC2
Data sets
Phytoplankton community responses to 20th century eutrophication of Swiss Plateau lakes: A proxy comparison from short sediment cores Antonia Klatt, Jan Waelchli, Daniel B. Nelson, Theresa Wietelmann, Nathalie Dubois, S. Nemiah Ladd https://doi.org/10.5061/dryad.ht76hdrz6
Model code and software
Klatt_etal_2026_SwissPlateau_Lakes Antonia Klatt, Jan Waelchli https://github.com/antoniaKlatt/Klatt_etal_2026_SwissPlateau_Lakes
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General comments:
The manuscript by Klatt et al. has applied three different proxies (i.e., phytol:sterol index, PSI) and hydrogen isotope offsets between C16:0 fatty acid and phytol (δ2HC16:0 Acid/Phytol) and 23S metabarcoding to detect past changes in the relative proportions of eukaryotic algae and cyanobacteria from three different sediment core records. The new geochemical proxies seem very interesting and have great potential, but I think the authors could make their comparisons more quantitative.
Specific comments:
I believe the team has executed the lab work proficiently and interpreted the data cautiously, but I would have liked to see some statistical comparison of the data. I did not see any formal quantitative comparison of the different proxies as correlations or mixed model analyses where all the data could be pooled and data nested from the same core could be expressed as a random factor.
As a result, some statements in the text lack robust support. For example, line 505 “Regarding changing proportions of cyanobacteria and eukaryotic algae, PSI and δ2HC16:0 Acid/Phytol values recorded generally the same trends as cyanobacterial and eukaryotic algal plastid 23S rRNA ASVs.”
There are also places in the text where the authors report that the conditions are quite stable and yet their loess trend line is increasing. For example, on line 357 “In Greifensee, the PSI was relatively stable from the mid-1800s until ~ 1940” OR line 398 “δ2HC16:0 Acid/Phytol values fluctuated between ~ 140 ‰ and 200 ‰ from the late 1800s until ~ 1937 CE”