| 21 May 2025
Leveraging 20 Years of Remote Sensing to Characterize Surface Phytoplankton Seasonality and Long-Term Trends in Lake Tanganyika
Abstract. Lake Tanganyika, the world's second-largest freshwater lake by volume, is a vital resource for millions in East Africa, providing water, food, and economic opportunities while supporting exceptional biodiversity.
Chlorophyll-a concentration (Chl-a) is a key indicator of phytoplankton biomass and primary productivity, and thus a proxy for the health of aquatic ecosystems. In Lake Tanganyika, Chl-a is known to display strong spatiotemporal horizontal variability with an exceptionally low annual mean and wide ranges of concentrations compared to other tropical or temperate great lakes. This variability is influenced by the lake's hydrodynamic cycle driven by air temperature and wind seasonality. Phytoplankton biomass is suspected to be decreasing due to a strengthening of water column stratification induced by climate change. However, the particular spatiotemporal variability and trends in phytoplankton biomass have never been examined using a lake-wide, temporally continuous long-term record. This study bridges this gap by analyzing satellite remote sensing-derived Chl-a data from the ESA Climate Change Initiative Lakes dataset across the entire surface of Lake Tanganyika over a 20-year period. It offers insight into the Chl-a dynamics with an unprecedented timespan and spatial coverage.
The analysis reveals distinct seasonal patterns in Chl-a concentrations, with shallow regions (depth <170 m) maintaining high levels year-round, while deeper areas exhibit pronounced seasonality tightly linked to known wind patterns. To further explore these spatial differences in seasonal dynamics, the study identifies seven clusters of co-varying Chl-a concentrations, each displaying distinct seasonal behaviours that reflect the lake's hydrodynamic cycle. Long-term trends indicate a decline in Chl-a concentrations of -9 % per decade in deep regions, suggesting decreasing primary productivity. However, this overall decline is nuanced by monthly patterns. In deep regions, the low Chl-a concentrations, mainly observed between November and April, tend to decrease over time at rates between -5 to -15 % per decade when averaged over entire clusters. In contrast high Chl-a values recorded during the most productive months, from August to October, show increasing trends up to 25 %. Nearly all shallow areas, meanwhile, display year-round increases up to 35 % across the Chl-a distribution, with particularly sharp rises in extreme values.
The findings underscore the complexity of Lake Tanganyika's Chl-a dynamics. The observed trends may have significant consequences for the lake's trophic structure and the communities dependent on its resources. Further research is needed to elucidate the underlying drivers of these changes and to assess their broader ecological and socio-economic impacts.
Competing interests: Some authors (Marnik Vanclooster) are members of the editorial board of journal Hydrology and Earth System Sciences.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
The manuscript is well written, easy to read, and makes an interesting point about the high spatial heterogeneity found in deep, very large lakes. Reading the abstract, introduction and methodology, it seems that the study is well structured. The methodology used appears appropriate for the study's objectives. However, the second part of the manuscript, including the results, discussion and conclusion, is less convincing.
The first remark concerns the use of the terms 'shallow coastal area', given that Lake Tanganyika is deep, even in the coastal zones. According to Moss et al. (2003), shallow lakes have a depth of less than 3 m. Secondly, the use of 'high values of Chl-a' is misleading. According to the OECD (1992), eutrophic lakes have a mean Chl-a concentration between 8 and 25 mg/m³. Therefore, the terminology must first be revised. In Lake Tanganyika, we can only speak of littoral/coastal versus pelagic areas, or of 'shallower areas' for comparison purposes, and of lower and higher concentrations of Chl-a, because Lake Tanganyika is an oligotrophic lake. See also later in the minor/specific comments.
Another point is the error associated with the concentration values. Maps showing the standard deviation, for example, are not displayed. There is a risk of speculating on data with a high degree of error because low Chl-a concentrations cast doubt on the reliability of the detection. This applies to both algorithms and spectrophotometric methods. This point is also valid for trend calculations.
From the abstract, it seemed that meteorological and climatic data (e.g. air temperature and wind) were used in the analysis to establish a relationship with Chl-a variability. However, this data was not used in the study, which seems to have been based solely on an assessment of Chl-a evolution.
Lake Surface Water Temperature (LSWT, another Lakes_cci variable) was also mentioned in the Materials and Methods section, but was not presented in the Results section to complement the spatial analysis of Lake Tanganyika. Another point that is missing is the fact that transparency, or Secchi disk depth, was not considered in the work, even though it is fundamental to phytoplankton blooms (see also minor comments later). Remote sensing data relate to surface waters and the euphotic zone, neither of which were discussed in the study. Light penetration is essential not only for phytoplankton, but also for Chl-a measurements using remote sensing techniques.
Another variable which is also available from Lakes_cci dataset is lake water level, that can be related with LSWT and Chl-a evolution in the long-time series. The importance of the levels are mentioned in the discussion but the data are also available and should have been integrated.
As a consequence of this lack in the analysis, the conclusions drawn are not fully appropriate or supported by the findings of this work. See later in the specific comment section.
A significant part of the discussion relates to deep and shallow lakes, but this is not appropriate given the initial remark raised. We could speak of the coastal and pelagic zones for comparison. Furthermore, some statements relate to wind direction and intensity, as well as air temperature, but no data are reported (probably from the literature). While I agree that ground-based wind data are not available, reanalysis data such as wind components (as well as air temperature) are available from the ERA5-Land dataset. Given the size of Lake Tanganyika, the spatial resolution of this data is almost acceptable.
Finally, in the discussion it is useful to mention also the limits of the dataset which can influence the results (e.g. data gap from 2012 to 2016, less availability of data in the rainfall season due to cloud cover).
Other comments:
I suggest adding some more recent citations to the first paragraphs of the introduction, for example lines 34–46.
Line 104: “Lake Tanganyika’s water is remarkably clear and nutrient levels at the surface are generally low.” Some reference data for secchi disk depth would be appreciated.Line 110 and later: “mg C m-2” without point (mg C.m-2).
Line 115-135: Move to Intro or to support discussion?
Line 144: “Most lakes, including Tanganyika, show data gaps during the 2012 to 2016 period due to validation issues.” Incorrect, in the current available version (2.1), MODIS data for Tanganyika were not released. Delete this sentence or update accordingly.
Line 155: “95% missing values”. Is almost always and with a patchy distribution of the pixel? It seems a large “threshold”.
Line 220: “These coastal zones usually extend a few kilometres offshore and are relatively shallow, with depths generally not exceeding 250 m (Figure 1). They exhibit consistently high to very high median concentrations throughout the year, above 3 mg.m-3 in some areas.” I suggest to change the terminology for shallow areas and “high” median values, as shallow lakes are lakes with a depth < 3 m and eutrophic lakes have a mean Chl-a concentration in the range 8-25 mg m-3. For this reason it would be better say something like this: “These coastal zones usually extend a few kilometres offshore and are shallower (<250 m) compared to the pelagic areas, and they exhibit higher Chl-a concentration above 3 mg m-3 in some areas.”
Line 407: “Ground-based wind data are limited, and the reliability of historical wind speed records in the region remains a subject of debate (Eschenbach, 2004; O’Reilly et al., 2003).” Reanalysis data are available and suitable for this case study. I suggest including them in the work.
Lines:417-419: “This duality suggests that Lake Tanganyika exhibits characteristics of both a shallow lake becoming more eutrophic and a deep lake becoming more oligotrophic, adding to the complexity of its ecological functioning.” And Lines 428-430: “The contrasting trajectories suggest that Lake Tanganyika is simultaneously exhibiting characteristics of a deep, nutrient-limited system undergoing further oligotrophication and a shallow system experiencing intensified phytoplankton growth.
As in the previous comment, I don't think these statements are entirely accurate, because Tanganyika doesn't exhibit more "eutrophic" waters (at least not a higher concentration of 3 mg/m³ compared to open waters).
Lines 423-425: “The analysis confirms that shallow areas exhibit persistently high Chl-a concentrations year-round, whereas pelagic regions show strong seasonal variability, with peak productivity following wind-driven mixing events.” This is not really an outcome of this study, as wind was not included in the analysis. It is more a speculative sentence most likely based on literature research.