Kaire Toming

Assessing impacts of invasive phytoplankton: the Baltic Sea case.

There is an increasing understanding and requirement to take into account the effects of invasive alien species (IAS) in environmental quality assessments. While IAS are listed amongst the most important factors threatening marine biodiversity, information on their impacts remains unquantified, especially for phytoplankton species. This study attempts to assess the impacts of invasive alien phytoplankton in the Baltic Sea during 1980-2008. A bioinvasion impact assessment method (BPL - biopollution level index) was applied to phytoplankton monitoring data collected from eleven sub-regions of the Baltic Sea. BPL takes into account abundance and distribution range of an alien species and the magnitude of the impact on native communities, habitats and ecosystem functioning. Of the 12 alien/cryptogenic phytoplankton species recorded in the Baltic Sea only one (the dinoflagellate Prorocentrum minimum) was categorized as an IAS, causing a recognizable environmental effect.

First Experiences in Mapping Lake Water Quality Parameters with Sentinel-2 MSI Imagery

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.

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

Many lakes in boreal and arctic regions have high concentrations of CDOM (coloured dissolved organic matter). Remote sensing of such lakes is complicated due to very low water leaving signals. Ther ...

Potential phytoplankton indicator species for monitoring Baltic coastal waters in the summer period

There are very few time series documenting clear trends of change in the biomass of total phytoplankton or single taxa that coincide with trends of increasing nutrient concentrations. Weekly or biweekly monitoring since 1997 on a cross section of the central Gulf of Finland (NE Baltic Sea) with similar climatic and hydrographic conditions, but different nutrient levels, provided a uniform dataset. In order to evaluate seasonal (June–September) patterns of phytoplankton succession, more than 1,200 samples were statistically analyzed by selecting 12 dominant taxa using wet weight biomass values. In addition, the continuously measured hydrographic parameters on board the ships of opportunity, and simultaneous nutrient analyses gave high frequency information on the water masses. The objective of this study was to identify the taxa that may prove indicative in the assessment of eutrophication in the appropriate monitoring time periods. None of the most common bloom-forming species (Aphanizomenon sp., Nodularia spumigena, and Heterocapsa triquetra) showed reliable correlations with enhanced nutrient concentrations. The species we suggest as reliable eutrophication indicators—oscillatorialean cyanobacteria and the diatoms Cyclotella choctawhatcheeana and Cylindrotheca closterium—showed the best relationships with total phosphorus concentrations. Their maxima appear toward the end of July or in August–September when phytoplankton community structure is more stable, and less frequent observations may give adequate results. Another diatom, Skeletonema costatum, exhibited stronger correlations with dissolved inorganic and total nitrogen in June, during the period of the summer phytoplankton minimum.

Dissolved organic carbon and its potential predictors in eutrophic lakes

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.

Role of a productive lake in carbon sequestration within a calcareous catchment

For a long time, lakes were considered unimportant in the global carbon (C) cycle because of their small total area compared to the ocean. Over the last two decades, a number of studies have highlighted the important role of lakes in both sequestering atmospheric C and modifying the C flux from the catchment by degassing CO2 and methane and burying calcite and organic matter in the sediment. Based on a full C mass balance, high frequency measurements of lake metabolism and stable isotope analysis of a large shallow eutrophic lake in Estonia, we assess the role alkaline lakes play in augmenting the strength of terrestrial carbonate weathering as a temporary CO2 sink. We show that a large part of organic C buried in the sediments in this type of lakes originates from the catchment although a direct uptake from the atmosphere during periods of intensive phytoplankton growth in eutrophic conditions contributes to the carbon sink.

Mapping inland water carbon content with Landsat 8 data

ABSTRACT Landsat 8 is the first Earth observation satellite with sufficient radiometric and spatial resolution to allow global mapping of lake CDOM and DOC (coloured dissolved organic matter and dissolved organic carbon, respectively) content. Landsat 8 is a multispectral sensor however, the number of potentially usable band ratios, or more sophisticated indices, is limited. In order to test the suitability of the ratio most commonly used in lake carbon content mapping, the green–red band ratio, we carried out fieldwork in Estonian and Brazilian lakes. Several atmospheric correction methods were also tested in order to use image data where the image-to-image variability due to illumination conditions would be minimal. None of the four atmospheric correction methods tested, produced reflectance spectra that matched well with in situ measured reflectance. Nevertheless, the green–red band ratio calculated from the reflectance data was in correlation with measured CDOM values. In situ data show that there is a strong correlation between CDOM and DOC concentrations in Estonian and Brazilian lakes. Thus, mapping the global CDOM and DOC content from Landsat 8 is plausible but more data from different parts of the world are needed before decisions can be made about the accuracy of such global estimation.

Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea

The launch of Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A in 2016 is the beginning of a new era in long time, continuous, high frequency water quality monitoring of coastal waters. ...

Predicting the cover and richness of intertidal macroalgae in remote areas: a case study in the Antarctic Peninsula

Abstract Antarctica is an iconic region for scientific explorations as it is remote and a critical component of the global climate system. Recent climate change causes a dramatic retreat of ice in Antarctica with associated impacts to its coastal ecosystem. These anthropogenic impacts have a potential to increase habitat availability for Antarctic intertidal assemblages. Assessing the extent and ecological consequences of these changes requires us to develop accurate biotic baselines and quantitative predictive tools. In this study, we demonstrated that satellite‐based remote sensing, when used jointly with in situ ground‐truthing and machine learning algorithms, provides a powerful tool to predict the cover and richness of intertidal macroalgae. The salient finding was that the Sentinel‐based remote sensing described a significant proportion of variability in the cover and richness of Antarctic macroalgae. The highest performing models were for macroalgal richness and the cover of green algae as opposed to the model of brown and red algal cover. When expanding the geographical range of the ground‐truthing, even involving only a few sample points, it becomes possible to potentially map other Antarctic intertidal macroalgal habitats and monitor their dynamics. This is a significant milestone as logistical constraints are an integral part of the Antarctic expeditions. The method has also a potential in other remote coastal areas where extensive in situ mapping is not feasible.