| 19 Feb 2026
Long-term changes in phytoplankton phenology, biomass, and community structure in the northern Baltic Sea
Abstract. Phytoplankton seasonality integrates signals of climate forcing, anthropogenic pressure, and natural physical variability, making it a sensitive indicator of ecosystem change in coastal seas. We analysed a 52-year phytoplankton monitoring time series (1966–2018) from twenty-six stations in the Helsinki Archipelago, Gulf of Finland, to examine long-term changes in phytoplankton phenology, biomass, and community composition.
Generalized additive mixed models revealed a pronounced seasonal cycle dominated by a short spring bloom, whose timing advanced steadily at an average rate of approximately 2.7 days per decade. In contrast, total phytoplankton biomass exhibited stepwise changes rather than gradual trends, with a marked decline in both spring and summer biomass in the late 1980s and early 1990s. This shift coincided temporally with a period of major restructuring of municipal wastewater treatment in the Helsinki metropolitan area.
Community composition responded differently from biomass. Distance-based ordination showed that long-term temporal trends and seasonal variation acted largely independently on community structure, with compositional change more strongly associated with decadal-scale trends than with seasonality. Time-series decomposition identified changepoints in community seasonality around 1972 and 2000. Following the latter, summer biomass increased while spring bloom intensity remained comparatively unchanged, consistent with a reorganisation of seasonal community structure rather than a reversal of long-term recovery.
Together, these results demonstrate that phytoplankton phenology, biomass, and community composition capture complementary aspects of ecosystem change. Long-term observations allow disentangling gradual climate-driven shifts, targeted management effects, and episodic physical disturbances, highlighting the value of phytoplankton seasonality as an integrative indicator in the northern Baltic Sea.
The manuscript entitled "Long-term changes in phytoplankton phenology, biomass, and community structure in the northern Baltic Sea” is highly interesting due to its analysis of data spanning more than 50 years. Such a long-term dataset is rare and extremely valuable in marine ecology.
The study is of considerable scientific importance in the context of environmental changes driven by global climate change, which should be strongly emphasized. The long-term data analyzed clearly illustrate phytoplankton phenology in the studied region and indicate that the spring bloom has advanced by approximately 2.7 days per decade.
The research methodology is sophisticated, which is worth noting as an unquestionable strength of this work. The author effectively applies mathematical techniques to estimate a range of parameters, Generalized Additive Mixed Models (GAMM) and BEAST—for detecting points of change—as well as dbRDA, a modern and appropriate tool for analyzing long time series.
Nevertheless, despite the generally positive assessment of the work, the author has not been without a number of shortcomings, which I, as the reviewer of this work, am obliged to point out.
The primary weakness is the lack of a clear characterization of the input dataset on which all analyses are based. Given the large size of the dataset, with high temporal and spatial resolution, it is essential to specify what the 52-year dataset includes: whether it concerns phytoplankton classes or organisms, whether abundance or biomass is analyzed, how biomass was determined, with what accuracy, and using which methodology. Histograms showing the distribution of input data would be highly informative.
Moreover, such an extensive long-term dataset is the result of work of many people. It remains unclear whether sampling and analyses were conducted as a part of the monitoring program. Many questions arise during reading that remain unanswered.
Detailed comments:
In my opinion, the study area (Gulf of Finland) should be specified in the title. Additionally, the title is not fully consistent with the manuscript content. The phrase “community structure” is not adequately reflected in the study. Nowhere in the manuscript is it clearly explained what structural changes occurred—whether shifts in proportions between algal groups or changes in dominant species within groups. I suggest revising the title or providing analyses that substantiate this claim.
This section requires expansion, clarification, and appropriate references. It appears overly concise. Some statements need greater specificity. For example, the first paragraph mentions “chronic eutrophication” without specifying the time period. Furthermore, nutrient inputs to the Baltic Sea have been regulated for years; referring to HELCOM reports would strengthen this section.
Statements such as:
It is also unclear whether the described trends apply to the entire Baltic Sea or specifically to the study area. This should be clarified. Additionally, basic information on bloom-forming groups should be included.
3. Methodology
As noted, a section describing the input data is essential. For such a long-term dataset, it is important to define the temporal resolution of sampling and whether it was consistent across years. This directly affects the precision of phenological analyses, particularly bloom onset estimation.
Furthermore, phytoplankton biomass must be clearly defined, including how it was measured, which organisms are included, and in what units it is expressed.
4. Data analysis
The subsection title should not be an acronym. Unexplained terms such as “mgcv package in R” should be clarified for less advanced readers. Units of all parameters should also be provided.
Specific remarks:
5. Results
Figures lack units for the presented parameters and should be corrected.
The author should aim for greater precision in wording. For example:
It is unclear whether data in Fig. 4 are spatially averaged across the study area. Similarly:
Paragraph 215: The statement regarding bloom duration (1–2 months) would be more convincing if the input data and their temporal resolution were clearly presented.
The subsection “Community composition” does not actually present such results. There is no information on phytoplankton composition, even at the level of major groups, let alone taxa. Thus, Section 3.1 does not fulfill its stated purpose.
The dataset should be analyzed in terms of biodiversity and properly described.
6. Discussion
Including additional environmental parameters would strengthen the interpretation, for example hydrological context. Changes in surface water temperature may also play a role alongside nutrient inputs.
The discussion focuses mainly on physico-chemical aspects (inflows and nutrients), while biological factors such as zooplankton and trophic interactions are omitted. These could be suggested as directions for future research.
The results should also be discussed in the broader context of the entire Baltic Sea, as the study area (Helsinki Archipelago) limits generalization. Are similar biomass trends observed elsewhere?
Paragraph 325: Regarding Major Baltic Inflows (1993), these events introduce high-salinity, dense water that spreads along the bottom, while stratification limits mixing with surface waters. Therefore, their direct influence on surface layers is questionable and, if present, likely indirect. This should be clarified. The manuscript suggests a causal relationship without providing strong evidence.