Research about the occurrence and extent of the cyanobacterial blooms in the Baltic Sea is critical due to their increased magnitude and frequency. Monitoring of the blooms is complicated due to their spatially and temporally heterogeneous nature. For adequate assessment of the water quality, phytoplankton dynamics needs to be tracked in large areas with high monitoring frequency. The main objectives of this study were (1) to describe phytoplankton community composition by pigment-based chemotaxonomy and validate the results with microscopy; (2) to improve the retrieval of information about phytoplankton community by combining remote sensing with laboratory based approaches (3) to develop a region-specific algorithm to calculate cyanobacteria biomass from reflectance spectra; (4) to detect and quantify potentially toxic bloom-forming cyanobacteria with molecular methods. In our study the reflectance-based chlorophyll a (Chl a) values overestimated the High- performance Liquid Chromatography (HPLC) values although the correlations with HPLC Chl a measurements were very strong (r ∼ 0.8, p < 0.001). We found that 709 nm/620 nm reflectance ratio correlated strongly (r = 0.75, p < 0.01) to cyanobacteria wet biomass in CDOM-rich Väinameri even at low cyanobacterial biomass levels. Correlations between pigment-based chemotaxonomy and microscopy were significant in case of cyanobacteria (r = 0.73, p < 0.01), cryptophytes (r = 0.71, p < 0.05) and dinoflagellates (r = 0.64, p < 0.05).
We used HPLC to identify and quantify pigments in a Holocene sediment record from large, shallow Lake Peipsi, Estonia. The aim of our study was to track the influence of long-term climate change (i.e. temperature fluctuations) on past dynamics of aquatic primary producers. Sedimentary pigments were separated and quantified in 182 samples that span the last ca. 10,000 years. There was an increasing trend in sedimentary pigment concentrations from basal to upper sediment layers, suggesting a gradual increase in lake trophic status through time. Using additive models, our results suggested that primary producer dynamics in Lake Peipsi were closely related to temperature fluctuations. We, however, identified two periods (early Holocene and after ca. 2.5 cal ka BP) when the relationship between primary producer composition and temperature was weak, suggesting the influence of additional drivers on the primary producer community. We postulate that: (a) the increase of primary producer biomass in the early Holocene could have been caused by input of allochthonous organic matter and nutrients from the flooded areas when water level in Lake Peipsi was increasing, and (b) changes in the abundance and structure of primary producer assemblages since ca. 2.5 cal ka BP was related to widespread agricultural activities in the Lake Peipsi catchment. These results suggest that human activities can disrupt the relationship between the primary producer community and temperature in large, shallow lakes.
The coexistence of potentially toxic bloom-forming cyanobacteria (CY) and generally smaller-sized grazer communities has raised the question of zooplankton (ZP) ability to control harmful cyanobacterial blooms and highlighted the need for species-specific research on ZP-CY trophic interactions in naturally occurring communities. A combination of HPLC, molecular and stable isotope analyses was used to assess in situ the importance of CY as a food source for dominant crustacean ZP species and to quantify the grazing on potentially toxic strains of Microcystis during bloom formation in large eutrophic Lake Peipsi (Estonia). Aphanizomenon, Dolichospermum, Gloeotrichia and Microcystis dominated bloom-forming CY, while Microcystis was the major genus producing cyanotoxins all over the lake. Grazing studies showed that CY, and especially colonial CY, formed a significant, and also preferred component of algae ingested by the cladocerans Bosmina spp. and Daphnia spp. while this was not the case for the more selective calanoid copepod Eudiaptomus gracilis. Molecular analyses confirmed the presence of CY, including Microcystis, in ZP guts. Further analyses using qPCR targeting cyanobacterial genus-specific mcyE synthase genes indicated that potentially toxic strains of Microcystis can be ingested directly or indirectly by all the dominant crustacean grazers. However, stable isotope analyses indicated that little, if any, assimilation from ingested bloom-forming CY occurred. The study suggests that CY, and particularly Microcystis with both potentially toxic and non-toxic strains, can be widely ingested by cladoceran grazers during a bloom event with implications for control of CY abundance and for transfer of CY toxins through the food web.
Relationships between biomass and ecological factors including trophic interactions were examined to understand the dynamics of six fish species in Lake Võrtsjärv, a large shallow eutrophic lake located in Estonia (north-eastern Europe). The database contained initially 31 predictive variables that were monitored in situ for nearly forty years. The strongest predictive variables were selected by three parallel approaches: single correlation (Pearson), a multivariate method (Co-inertia analyses), and a machine learning algorithm (Random Forests), followed by a Generalized Least Squares model to determine meaningful relationships with fish biomass. Models with both additive and interactive effects were constructed. The results revealed that the indicators of degraded ecological conditions (high cyanobacteria biomass and their proportion in total phytoplankton, high summer temperature, high nutrient concentration) were negatively correlated to fish biomass. Benthic macroinvertebrates and other biotic predictors (biomass of specific fish prey and predators) were also important contributors to fish biomass dynamics. Together, abiotic and biotic factors explained 40–60% of the variance of fish biomass, depending of the species. Our findings suggest that both abiotic and biotic factors control fish biomass changes in this eutrophic lake.
We calculated the allochthonous organic carbon (OC) mass balance for thirteen natural lakes using lake water budget, catchment features and water column chemistry variables as input of a process-based model. Parameter distribution and uncertainty of model outputs were assessed within a Bayesian framework.
Theoretical pelagic primary production of phytoplankton and benthic primary production of periphyton were modelled for two small lakes in Estonia (Northeast Europe). Although located only 500 m apart, the water colour and light attenuation of these two lakes differed markedly. The Secchi depth (SD) in the clear‐water lake was 4.5 m and only 0.47 m in the dark‐water lake. The total phosphorus (TP) concentrations were, respectively, 15 μg/L and 28 μg/L. An empirical model whose inputs were morphometric, light conditions and dissolved organic carbon parameters obtained from in situ measurements was employed for the present study. The model calculated primary production with a time‐step of 10 min, and a spatial resolution of 10 cm, from sunrise to sunset and from lake surface to lake bottom. The primary production of periphyton and phytoplankton was almost equal in the clear lake, whereas only phytoplankton contributed to whole‐lake primary production in the dark lake because of the stronger light attenuation in the water column. The results of the present study indicated the depth‐distribution profiles differed dramatically between the two lakes. The clear lake had a deep, U‐shaped curve, with the productive layer reaching considerable depth soon after sunrise and maintaining a similar profile throughout the light hours. In contrast, the dark lake production declined rapidly with increasing depth, whereas the profile changed over the day reaching the greatest depth at noon.
The objective of this study was to forecast the combined influence of three stressors (climate change, land use, water abstraction) on the phytoplankton (cyanobacteria) and zooplankton (rotifer) biomass of Lake Võrtsjärv, a large lake situated in Estonia (north-eastern Europe), for the mid-21st century (2030-2060)
1] High-frequency physical observations from 40 temperate lakes were used to examine the relative contributions of wind shear (u *) and convection (w *) to turbulence in the surface mixed layer. Seasonal patterns of u * and w * were dissimilar; u * was often highest in the spring, while w * increased throughout the summer to a maximum in early fall. Convection was a larger mixed-layer turbulence source than wind shear (u * /w * < 0.75) for 18 of the 40 lakes, including all 11 lakes <10 ha. As a consequence, the relative contribution of convection to the gas transfer velocity (k, estimated by the surface renewal model) was greater for small lakes. The average k was 0.54 m day À1 for lakes <10 ha. Because u * and w * differ in temporal pattern and magnitude across lakes, both convection and wind shear should be considered in future formulations of lake-air gas exchange, especially for small lakes. Citation: Read, J. S., et al. (2012), Lake-size dependency of wind shear and convection as controls on gas exchange, Geophys. Res. Lett.
Aiming at building the carbon budget for further climate change impact research in the large and shallow northern temperate Lake Võrtsjärv, the present paper focuses on reconstructing the full phytoplankton primary production (PP) data series for the lake for the period of 1982–2009 covered by disconnected measurements, and testing the uncertainties involved both in the PP measurements and bio-optical modelling. During this 28-year period, in situ PP was measured in Võrtsjärv in 18 years with 14C-assimilation technique. We reconstructed the full time series using a semi-empirical PP simulation model based on continuously measured PAR irradiance and interpolated values of monthly measured chlorophyll a (C chl). The modelling results, which proved highly reliable during the calibration phase, correlated rather weakly with the annual PP estimates for the 18 years, which were based on 2-h incubations at midday, 1–2 times per month. Being based on continuous irradiance data, the modelled PP can be considered more reliable than the sparse measurements, especially for short to medium term studies. We demonstrate that in the long-term, the bio-optical method can be biased if changes in water colour or water level alter the light climate causing adaptive responses in the cellular chlorophyll content of light-limited phytoplankton.
Different sources of particulate organic matter (POM) as well as its composition affect the biological food web and hence the self-purification potential and water quality of rivers. We studied the effect of a large shallow lake on the POM pool of the water passing through it. Over four years, we analysed monthly the amount and composition of POM and a set of environmental variables in the inflows and in the outflow of Lake Võrtsjärv (Estonia). In the inflows, the live pool of POM consisted of phytoplankton – small crypto-, dino-, and chlorophytes. The concentration of chlorophyll a (Chl a), as a proxy of phytoplankton biomass, was positively correlated with temperature and total phosphorus and negatively with dissolved silica, total nitrogen, and discharge. In the outflow, the share of the live component of POM was much larger than in the inflows but was also dominated by phytoplankton represented by grazing resistant filamentous cyanobacteria. Chl a was positively correlated with total phosphorus, temperature, pH, and precipitation, and negatively with dissolved silica, total nitrogen, and discharge in the outflow. The different amounts, composition, and seasonal dynamics of POM in the inflows and in the outflow have potentially substantial impacts on the food web with a predominating classical pathway in the inflows versus a detrital pathway in the outflow.
We aimed at quantifying the importance of limnological variables in the decadal rise of cyanobacteria biomass in shallow hemiboreal lakes. We constructed estimates of cyanobacteria (blue-green algae) biomass in a large, eutrophic lake (Estonia, Northeastern Europe) from a database comprising 28 limnological variables and spanning more than 50 years of monitoring. Using a dual-model approach consisting in a boosted regression trees (BRT) followed by a generalized least squares (GLS) model, our results revealed that six variables were most influential for assessing the variance of cyanobacteria biomass. Cyanobacteria response to nitrate concentration and rotifer abundance was negative, whereas it was positive to pH, temperature, cladoceran and copepod biomass. Response to total phosphorus (TP) and total phosphorus to total nitrogen ratio was very weak, which suggests that actual in-lake TP concentration is still above limiting values. The most efficient GLS model, which explained nearly two thirds (r2 = 0.65) of the variance of cyanobacteria biomass included nitrate concentration, water temperature and pH. The very high number of observations (maximum n = 525) supports the robustness of the models. Our results suggest that the decadal rise of blue-green algae in shallow lakes lies in the interaction between cultural eutrophication and global warming which bring in-lake physical and chemical conditions closer to cyanobacteria optima.
Understanding of the true role of lakes in the global carbon cycle requires reliable estimates of dissolved organic carbon (DOC) and there is a strong need to develop remote sensing methods for mapping lake carbon content at larger regional and global scales. Part of DOC is optically inactive. Therefore, lake DOC content cannot be mapped directly. The objectives of the current study were to estimate the relationships of DOC and other water and environmental variables in order to find the best proxy for remote sensing mapping of lake DOC. The Boosted Regression Trees approach was used to clarify in which relative proportions different water and environmental variables determine DOC. In a studied large and shallow eutrophic lake the concentrations of DOC and coloured dissolved organic matter (CDOM) were rather high while the seasonal and interannual variability of DOC concentrations was small. The relationships between DOC and other water and environmental variables varied seasonally and interannually and it was challenging to find proxies for describing seasonal cycle of DOC. Chlorophyll a (Chl a), total suspended matter and Secchi depth were correlated with DOC and therefore are possible proxies for remote sensing of seasonal changes of DOC in ice free period, while for long term interannual changes transparency-related variables are relevant as DOC proxies. CDOM did not appear to be a good predictor of the seasonality of DOC concentration in Lake Võrtsjärv since the CDOM–DOC coupling varied seasonally. However, combining the data from Võrtsjärv with the published data from six other eutrophic lakes in the world showed that CDOM was the most powerful predictor of DOC and can be used in remote sensing of DOC concentrations in eutrophic lakes.
We assembled data from a global network of automated lake observatories to test hypotheses regarding the drivers of ecosystem metabolism. We estimated daily rates of respiration and gross primary production (GPP) for up to a full year in each lake, via maximum likelihood fits of a free-water metabolism model to continuous high-frequency measurements of dissolved oxygen concentrations. Uncertainties were determined by a bootstrap analysis, allowing lake-days with poorly constrained rate estimates to be down-weighted in subsequent analyses. GPP and respiration varied considerably among lakes and at seasonal and daily timescales. Mean annual GPP and respiration ranged from 0.1 to 5.0 mg O2 L−1 d−1 and were positively related to total phosphorus but not dissolved organic carbon concentration. Within lakes, significant day-to-day differences in respiration were common despite large uncertainties in estimated rates on some lake-days. Daily variation in GPP explained 5% to 85% of the daily variation in respiration after temperature correction. Respiration was tightly coupled to GPP at a daily scale in oligotrophic and dystrophic lakes, and more weakly coupled in mesotrophic and eutrophic lakes. Background respiration ranged from 0.017 to 2.1 mg O2 L−1 d−1 and was positively related to indicators of recalcitrant allochthonous and autochthonous organic matter loads, but was not clearly related to an indicator of the quality of allochthonous organic matter inputs.
Autotrophic picoplankton (0.2-2μm) can be a significant contributor to primary production and hence play an important role in carbon flow. The phytoplankton community structure in the Baltic Sea is very region specific and the understanding of the composition and dynamics of pico-size phytoplankton is generally poor. The main objective of this study was to determine the contribution of picoeukaryotic algae and their taxonomic composition in late summer phytoplankton community of the West-Estonian Archipelago Sea. We found that about 20% of total chlorophyll a (Chl a) in this area belongs to autotrophic picoplankton. With increasing total Chl a, the Chl a of autotrophic picoplankton increased while its contribution in total Chl a decreased. Picoeukaryotes play an important role in the coastal area of the Baltic Sea where they constituted around 50% of the total autotrophic picoplankton biomass. The most abundant groups of picoeukaryotic algae were cryptophytes (16%), chlorophytes (13%) and diatoms (9%). Picocyanobacteria were clearly dominated by phycoerythrin containing Synechococcus. The parallel use of different assessment methods (CHEMTAX and flow cytometry) revealed the share of eukaryotic and prokaryotic part of autotrophic picoplankton.
We developed an index (MESH –Macroinvertebrates in Estonia: Score of Hydromorphology) to assess hydromorphological quality of Estonian surface waters based on macroinvertebrate taxonomic composition. The MESH is an average score based on the affinities of selected indicator taxa to flow velocity and bottom type. As both parameters were highly correlated (r=0.65) indicator response to both parameters were combined. The list of MESH indicators includes 394 freshwater macroinvertebrate taxa derived from 3282 samples collected from rivers and lakes during 1985–2009. The indicators were selected out of 690 taxa, by applying the information-theoretical Kullback–Leibler divergence. The individual scores of macroinvertebrates range from 0 to 3, the higher scores indicating faster flow and/or solid bottom substrate. For standing waters, flow velocity was always considered zero. Among the reference waterbodies, mean MESH was the highest for small streams followed by middle streams, large streams, and lakes. In lakes with medium water hardness (the prevailing type in Estonia), the MESH decreased gradually from stony to muddy bottom. The highest MESH values for standing waters were observed in the stony surf zone of very large lakes (area>100km2). The lowest values occurred for small lakes with exceptional hydrochemical characteristics (soft- and darkwater, and calcareous types). Similarly, MESH indicated stream degradation by damming. Mean MESH in reservoirs with a muddy bottom was significantly lower than in reservoirs with a hard bottom, or in unregulated stream sections.
Due to requirements of EU Water Framework Directive, the popularity of littoral macroinvertebrate communities as indicators in quality assessment of lakes has continuously increased. However, it is not always clear what the indices actually reflect. The littoral is an area linking the lake and the adjacent terrestrial environment, and is integrating the influences from both habitats on the aquatic biota. In addition, natural and anthropogenic environmental factors cannot always be disentangled easily. Our study was based on littoral macroinvertebrate data from 296 hand net samples collected from 196 natural Estonian lowland lakes during 2000-2010. The aim was to identify relationships between relevant macroinvertebrate metrics and several natural and anthropogenic factors. Five metrics (total taxon richness, Shannon diversity H', number of EPT taxa, Average Score Per Taxon (ASPT), and Swedish Acidity Index) were used. In addition, a new hydromorphological index, MESH (Macroinvertebrates in Estonia: Score of Hydromorphology) was tested against the environmental factors. First, we analysed the relationships between the metrics and factors according to Estonian lake typology. In order to estimate the effects of factors on biological quality, the effect of the lake type was thereafter eliminated. The highest number of significant relationships was found in relation to natural factors, such as diversity of vegetation types, general relative vegetation coverage, lake area and latitude. In general, the human-related factors had unexpectedly low relationships with most of the metrics. Average Score Per Taxon predictably increased with the percentage of natural land use area in the lake's catchment. However, the lake water concentration of total phosphorus - a typical indicator of eutrophication in freshwaters - did not reveal a significant relationship with any of the tested metrics. We suggest that the expected ecological relationships were obscured by a general low human stress on Estonian lakes, in combination with a high residual natural variability in the littoral.
The causes of horizontal differences in metabolic activities between lake zones are still poorly understood. We carried out a two-year study of lake metabolism in two contrasting parts of a large shallow lake using the open-water technique based on high-frequency measurements of dissolved oxygen concentrations. We expected that the more sheltered and macrophyte-rich southern part of the lake receiving a high hydraulic load from the main inflow will exhibit equal or higher rate of metabolic processes compared to the open pelagic zone, and higher temporal variability, including anomalous metabolic estimates such as negative gross primary production (GPP) or community respiration (CR) due to rapid water exchange. Our results showed that anomalous metabolic estimates occurred at both stations with a similar frequency and were related rather to certain wind directions, which likely contributed to stronger water exchange between the littoral and pelagic zones. Periods of auto- and heterotrophy (daily mean NEP> or <0) had a 50:50 distribution at the Central Station while the proportions were 30:70 at the Southern Station. High areal GPP estimated in our study exceeding nearly twice the long-term average 14C primary production, showed the advantages of the free-water technique in integrating the metabolism of all communities, a large part of which has remained undetected by the traditional bottle or chamber incubation techniques.
Over the past 15 years, an increasing number of studies in limnology have been using data from high-frequency measurements (HFM).This new technology offers scientists a chance to investigate lakes at time scales that were not possible earlier and in places where regular sampling would be complicated or even dangerous. This has allowed capturing the effects of episodic or extreme events, such as typhoons on lakes. In the present paper we review the various fields of limnology such as monitoring, studying highly dynamic processes, lake metabolism studies, and budget calculations where HFM has been applied, and which have benefitted most from the application. Our meta-analysis showed that more than half of the high-frequency studies from lakes were made in North-America and Europe. The main field of application has been lake ecology (monitoring, lake metabolism) followed by physical limnology. Water temperature and dissolved oxygen have been the most universal and commonly measured parameters and we review the various study purposes for which these measurements have been used. Although a considerable challenge forthe future, our review highlights that broadening the spatial scale of HFM would substantially broaden the applicability of these data across a spectrum of different fields.
To quantify the effects of recent and potential future decreases in surface wind speeds on lake thermal stratification, we apply the one-dimensional process-based model MyLake to a large, shallow, polymictic lake, Võrtsjärv. The model is validated for a 3-year period and run separately for 28 years using long-term daily atmospheric forcing data from a nearby meteorological station. Model simulations show exceptionally good agreement with observed surface and bottom water temperatures during the 3-year period. Similarly, simulated surface water temperatures for 28 years show remarkably good agreement with long-term in situ water temperatures. Sensitivity analysis demonstrates that decreasing wind speeds has resulted in substantial changes in stratification dynamics since 1982, while increasing air temperatures during the same period had a negligible effect. Atmospheric stilling is a phenomenon observed globally, and in addition to recent increases in surface air temperature, needs to be considered when evaluating the influence of climate change on lake ecosystems.
We employed a Bayesian model to assess the metabolic state of 8 Estonian lakes representing the 8 lake types according to the European Union Water Framework Directive. We hypothesized that long-term averages of light-related variables would be better predictors of lake metabolism than nutrient-related variables. Model input parameters were in situ high-frequency measurements of dissolved oxygen, temperature, and irradiance. Model simulations were conducted for several (5–12) diel cycles for each lake during the summer season. Accounting for uncertainty, the results from the Bayesian model revealed that 2 lakes were autotrophic for the duration of the experiment, 1 was heterotrophic, and 5 were balanced or had an ambiguous metabolic state. Cross-comparison with a traditional bookkeeping model showed that the majority of lakes were in metabolic balance. A strong coupling between primary production and respiration was observed, with the share of autochthonous primary production respired by consumers increasing with light extinction and nutrient-related variables. Unlike gross primary production, community respiration was strongly related to light extinction, dissolved organic carbon (DOC) and total phosphorus. These findings suggest that a drastic decrease in light-limited primary production along the DOC gradient counter-balanced nutrient supply in the darker lakes and thus blurred the relationship between primary production and nutrients. Thus, contrary to our hypothesis, both light and nutrient-related variables seemed to be good predictors of lake respiration and its coupling to lake primary production.
We constructed a model chain into which regional climate-related variables (air temperature, precipitation) and a lake’s main tributary hydrological indicators (river flow, dissolved inorganic carbon) were employed for predicting the evolution of planktonic blue-green algae (cyanobacteria) and zooplankton (rotifer) biomass in that lake for the mid-21st century. Simulations were based on the future climate predicted under both the Representative Concentration Pathways 4.5 and 8.5 scenarios which, combined with three realistic policy-making and basin land-use evolution lead to six scenarios for future water quality. Model outputs revealed that mean annual river flow is expected to decline between 3 to 20%, depending of the scenario. Concentration of river dissolved inorganic carbon is predicted to follow the opposite trend and might soar up to twice the 2005-2014 average concentration. Lake planktonic primary producers will display quantitative changes in the future decades whereas zooplankters will not. A 2 to 10% increase in mean cyanobacteria biomass is accompanied by a stagnation (-3 to +2%) of rotifer biomass. Changes in cyanobacteria and rotifer phenology are expected: a surge of cyanobacteria biomass in winter and a shortening of the rotifer biomass spring peak. The expected quantitative changes on the biota were magnified in those scenarios where forested area conversion to cropland and water abstraction were the greatest.
The influence of functional group specific production and respiration patterns on a lake's metabolic balance remains poorly investigated to date compared to whole-system estimates of metabolism. We employed a summed component ecosystem approach for assessing lake-wide and functional group-specific metabolism (gross primary production (GPP) and respiration (R)) in shallow and eutrophic Lake Võrtsjärv in central Estonia during three years. Eleven functional groups were considered: piscivorous and benthivorous fish; phyto-, bacterio-, proto- and metazooplankton; benthic macroinvertebrates, bacteria and ciliates; macrophytes and their associated epiphytes. Metabolism of these groups was assessed by allometric equations coupled with daily records of temperature and hydrology of the lake and measurements of food web functional groups biomass. Results revealed that heterotrophy dominated most of the year, with a short autotrophic period observed in late spring. Most of the metabolism of the lake could be attributed to planktonic functional groups, with phytoplankton contributing the highest share (90% of GPP and 43% of R). A surge of protozooplankton and bacterioplankton populations forming the microbial loop caused the shift from auto- to heterotrophy in midsummer. Conversely, the benthic functional groups had overall a very small contribution to lake metabolism. We validated our ecosystem approach by comparing the GPP and R with those calculated from O2 measurements in the lake. Our findings are also in line with earlier productivity studies made with 14C or chlorophyll a (chl-a) based equations. Ideally, the ecosystem approach should be combined with diel O2 approach for investigating critical periods of metabolism shifts caused by dynamics in food-web processes.
Autotrophic structure refers to the partitioning of whole-ecosystem primary production between benthic and planktonic primary producers. Autotrophic structure remains poorly understood especially because of the paucity of estimates regarding benthic primary production. We used a conceptual model for numerically exploring the autotrophic structure of 13 hemiboreal lakes situated in the Baltic Sea catchment. We also used diel variations in primary production profiles to graphically evaluate levels of light and/or nutrient limitation in lakes. The input morphometric data, light extinction coefficients and dissolved carbon parameters were mostly obtained from in situ measurements. Results revealed that cross- and within-lake autotrophic structure varied greatly: one lake was clearly dominated by benthic production, and three lakes by phytoplankton production. In the rest, phytoplankton production was generally dominant but switch to benthic dominance was possible. The modelled primary production profiles varied according to lake water clarity and bathymetry. Our results clearly indicate that the relative contribution of benthic primary production to whole-lake primary production should be taken into account in studies about hemiboreal and boreal lakes.
The distribution of whole-lake primary production between planktonic and benthic habitat, also called autotrophic structure, carries critical information about lake food web layout and organic matter fluxes. Although planktonic primary production has been intensively studied since the onset of limnology, the paucity of estimates for benthic production is still blatant, meaning that autotrophic structure of lakes remains poorly known to date. In this study we have modelled both planktonic and benthic production and autotrophic structure of Estonian lakes, representing the overwhelming majority of this country inland water volume. We employed an empirical model based on a limited set of variables easily available from basic limnological databases, with a high precision in time (10 min) and depth (every 10 cm). Our results showed that although the studied Estonian lakes ranged from periphyton- to phytoplankton-dominated, phytoplankton represented on average 90% of their primary production. Shallow and/or clear lakes with low chlorophyll a (chla) were generally more favourable to benthic production than deep and/or turbid lakes. An increase of chla and turbidity in hemi-boreal lakes caused by climate warming is expected to skew the pelagic to benthic production ratio even more towards dominance of phytoplankton, with dramatic consequences on lake carbon fluxes.
The importance of lakes and reservoirs leads to the high need for monitoring lake water quality both at local and global scales. The aim of the study was to test suitability of Sentinel-2 Multispectral Imager’s (MSI) data for mapping different lake water quality parameters. In situ data of chlorophyll a (Chl a), water color, colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) from nine small and two large lakes were compared with band ratio algorithms derived from Sentinel-2 Level-1C and atmospherically corrected (Sen2cor) Level-2A images. The height of the 705 nm peak was used for estimating Chl a. The suitability of the commonly used green to red band ratio was tested for estimating the CDOM, DOC and water color. Concurrent reflectance measurements were not available. Therefore, we were not able to validate the performance of Sen2cor atmospheric correction available in the Sentinel-2 Toolbox. The shape and magnitude of water reflectance were consistent with our field measurements from previous years. However, the atmospheric correction reduced the correlation between the band ratio algorithms and water quality parameters indicating the need in better atmospheric correction. We were able to show that there is good correlation between band ratio algorithms calculated from Sentinel-2 MSI data and lake water parameters like Chl a (R2 = 0.83), CDOM (R2 = 0.72) and DOC (R2 = 0.92) concentrations as well as water color (R2 = 0.52). The in situ dataset was limited in number, but covered a reasonably wide range of optical water properties. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for lake monitoring and research, especially taking into account that the data will be available routinely for many years, the imagery will be frequent, and free of charge.
Although massive fish kills are wide-spread and can be economically devastating, there is little information on exact causal mechanisms of fish kills in nature. In large shallow Lake Vortsjarv, sporadic fish kills have been registered mainly in cold winters, yet in 2013, an unexpected fish kill occurred beginning mid-June. At the time of the fish kill, an investigation was conducted to determine species composition, number, and sizes of dead fish along the lake shore. To determine possible causes of the fish kill, we analysed the dynamics of key physical and chemical parameters of lake water, including diurnal fluctuations of water temperature (WT), pH, dissolved oxygen (DO), ammonium ion concentrations (NH4-N), and the development of water stratification, during the growing season of 2013 using high-frequency water quality monitoring buoy and monthly manual monitoring data. Environmental data between 2010 and 2012 were used as a reference because no fish kill occurred. The results suggest that the fish kill was induced by a combination of successive and co-occurring extreme water parameters such as high WT (up to 24.5 °C), pH (up to 9.2), and NH4-N (up to 0.13 mg L⁻¹), short-term stratification, and low DO concentration in the bottom water (0.49 mg L-1, saturation 5.4%) induced by quick warming of this shallow lake after a long ice-covered period and leading to a likely ammonia poisoning and hypoxia. The main target species was the bottom-dwelling ruffe (Gymnocephalus cernuus), indicating that the summer kill started at the bottom of the lake. The event highlights the significance of short-term disturbances on fish populations, which can be detected only using high-frequency monitoring data.
Nowadays automated monitoring buoys are widely applied. Day-to-day variation and distribution of dissolved oxygen (DO) in different lake types is already well known. However, data on dissolved CO2 are still rare, because the relatively low reliability and accuracy and high price of CO2 sensors. Recently, the usage of CO2 sensors has increased although mostly in the upper mixed layers of lakes. Continuous profile measurements of CO2 are still very scarce. In year 2014 we measured DO and CO2 every 10 to 30 minutes during one week at up to four different depths in all 8 Estonia lake types, according to European Water Framework Directive. In case of fully mixed lakes only two depths were measured. In case of stratified lakes two sensors were placed in the epilimnion, one in the metalimnion and one in the hypolimnion. CO2 differed largely between lakes. The highest CO2 value in the surface layer (11.9 mg/L) was measured in highly calcareous polymictic Lake Äntu Sinijärv, but the record highest value (45 mg/L) was measured near the bottom of hypertrophic stratified Lake Erastvere. Lowest near bottom CO2 concentrations were measured in Lake Peipsi, which is the 5th largest lake in Europe.