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Emiliania huxleyi (Lohmann) evolved from the genus Gephyrocapsa Kamptner (Prymneosiophyceae) of the coccolithophore family Naёlaerhadaceae. Over the past 100 thousand years E. huxleyi has acquired the status of the most ecologically predominant coccolithophore due to its remarkable adaptability to a variety of environmental conditions and interspecific competitiveness. E. huxleyi plays an important role in both the marine carbon system and carbon cycling between the atmosphere and ocean due to its ability to produce organic and inorganic carbon as well as to form massive blooms throughout the world ocean. This study examines both older information and recent findings to shed light on the current tendencies in the two-way interactions between E. huxleyi blooms and the immediate and global environment under conditions of climate change. The assembled knowledge has emerged from laboratory and mesocosm instrumental investigations, retrievals of satellite remote sensing data, machine learning/statistical analyses, and numerical simulations. Special attention is given to both the quantitative data reported over the last two decades on such interactions, and the only very recently appearing mid-term projections of E. huxleyi bloom dynamics across the world ocean. These blooms strongly affect the atmosphere and ocean carbon cycles. They reduce CO2 fluxes from by ~50% to ~150% as is documented for the North Atlantic, and on the global scale release particulate inorganic carbon as calcium calcite in the amounts assessed at 0.4 to 4.8 PgC/yr. At the same time, they are also sensitive to the atmospheric and oceanic state. This results in E. huxleyi blooms having an increased impact on the environment in response to ongoing global warming.

Background: The high prevalence of skin hyperpigmentation makes it necessary to search for remedies that could hinder this process. Among such substances, tyrosinase inhibitors can be distinguished, which may be pyrimidine derivatives. Objectives: This study aimed to investigate new compounds with anti-tyrosinase activity in 2-substituted tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4(3H)-one by an in vitro analysis and investigating their molecular docking. Methods: A molecular docking was performed using AutoDock 4.0 with the 3-dimensional structure of tyrosinase of the fungus Agaricus bisporus from the Protein Data Bank (PDB; rcsb.org) with identification number 2Y9X. A synthesis of 2-substituted tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4(3H)-one was carried out during the heterocyclization reaction of azomethine derivatives of 2-amino-4,5,6,7-tetrahydro-1-benzothiophene-3-carboxamide in glacial acetic acid with the addition of dimethyl sulfoxide. Tyrosinase activity was determined in vitro by the spectrophotometric method. Results: Molecular docking data suggest the feasibility of synthesizing 2-substituted tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4(3H)-one as possible tyrosinase inhibitors. Of particular interest are compounds with hydroxy groups in the radical. Next, pharmacological screening showed that the leading compound is 4g. It is likely that metal–ligand interactions are the main interactions in the active site of tyrosinase because kojic acid, hydroquinone, and lactic acid (reference compounds), as well as compounds with only hydroxy groups in phenyl substituents (4b, 4c, and 4g), have the greatest anti-tyrosinase activity. Conclusions: As a result of molecular docking studies, the feasibility of synthesizing 2-substituted tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4(3H)-one as potential tyrosinase inhibitors was justified. 2-Substituted tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4(3H)-one was obtained using new synthesis conditions. The leading compound is 4g containing a fragment of 2,4-dihydroxybenzene.

Short summary We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for sustainable development in the Artic-boreal region. Air quality in China and long-range transport of the atmospheric pollutants was also indicated as one of the most crucial topics of the research agenda. This paper summarizes results obtained during the last five years in the Northern Eurasian region. It also introduces recent observations on the air quality in the urban environments in China. The main regions of interest are the Russian Arctic, Northern Eurasian boreal forests (Siberia) and peatlands and on the mega cities in China. We frame our analysis against research themes introduced in 2015. We summarize recent progress in the understanding of the land – atmosphere – ocean systems feedbacks. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, such as enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate the climate change and the socio-economic development to tackle air quality issues.

A 19-year (1998–2016) continuous dataset is presented of coccolithophore Emiliania huxleyi distributions and activity, i.e. the release of CaCO3 in water and the decrease of uptake of dissolved CO2 by Emiliania huxleyi cells (e.g. Kondrik et al., 2018a), in Arctic and sub-Arctic seas. The dataset is based on optical remote-sensing data (mostly OC CCI data) with assimilation of different relevant in situ observations, preprocessed with authorial algorithms. Alongside bloom locations, we provide both detailed information on E. huxleyi impacts on carbon balance and the sub-datasets of quantified coccolith concentrations, particulate inorganic carbon content and CO2 partial pressure in water driven by coccolithophores. All data are presented on a regular 4×4 km grid at a temporal resolution of 8 days. The paper describes the theoretical and methodological basis for all processing and modelling steps. The data are available on Zenodo: https://doi.org/10.5281/zenodo.1402033.

Subsumed under the category of ocean colour (OC) data fusion tools, a new approach is developed to efficiently use the merits of two OC satellite sensors differing in their spatial and spectral resolution characteristics. The tool permits to combine high spectral but lower spatial resolution optical data from one satellite sensor with higher spatial resolution but lower spectral resolution data from the other one into an image possessing simultaneously both high spectral and high spatial resolution qualities.The developed algorithm employs the artificial intelligence tool: emulated/artificial neuron networks (AANs).The developed ANN algorithm performance and efficiency are demonstrated for Lake Michigan. The fusion was effected making use of multiband data from Sentinel-2 Multispectral Instrument (MSI) and MODIS-Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. In this version MODIS-Aqua sensor is chosen as an analog of the Sentinel 3 OLCI, whose spectrometric and atmospheric corrected data are yet unavailable.The multi-sensor (MS) optical-optical fusion results have persuasively demonstrated the efficiency of the approach and its applicability to studies of natural water bodies of different optical complexity. It can be utilized in combination with any biogeochemical retrieval algorithms.In the case of retrieving water quality parameters (WQP) in optically shallow aquatic environments, the employment of the fusion tool developed is particularly promising as the bottom reflectance properties are frequently highly heterogeneous. Indeed, in such cases, remote sensing optical data acquired at simultaneously high spatial and spectral resolution are certainly more advantageous as compared to that acquired separately by two different sensors operating either at high spatial (but low spectral) or high spectral (but low spatial) resolution.For the retrieval of WQP in optically shallow waters (OSW) a special algorithm called Biooptical Retrieval Algorithm (BOREALI) - OSW was applied to study the eastern coastal zone of Lake Michigan. The application of both the OC fusion tool and our BOREALI-OSW algorithm permitted to document both interannual dynamics in WQPs as well as bottom substrate spatial heterogeneity in the target OSW area of Lake Michigan.

Based on the method developed for the delineation of E. huxleyi blooms, a new technique is achieved for (1) the automated detection of E. huxleyi blooms among coexisting massive blooms of microalgae species of other phytoplankton groups and (2) quantifying the boom surface of this type of coccolithophores. As a result, according to the data of the Climate Change Initiative Ocean Colour (OC CCI) for 1998–2013, we have obtained multiyear time series of variability in both the incidence of E. huxleyi bloom and its area in the North, Norwegian, Greenland, Barents, and Bering seas. It is found that E. huxleyi blooms propagate within the intra-annual cycle from the studied middle-latitude marine areas towards the northern areas of the Northern Atlantic Ocean (NAO) and the Arctic Ocean (AO) following the pathways of the main Gulfstream and its branches. It is also found that E. huxleyi blooms are formed annually, initially in the vicinity of the British Islands; then they successively emerge in the northward direction following the western coast of the Great Britain, turn over its northern extremity to reach, firstly, the North Sea (in May), the Norwegian Sea, and finally the Greenland Sea (in June). Then they burst out in the Barents Sea, where the typical period of blooming lasts until late August and, in some years, even to mid-September. We determine the patterns of maximal rates and duration of blooms for each of the seas studied in the Atlantic and Arctic Oceans. As for the Bering Sea, the temporal and spatial variability in the growth of E. huxleyi has an irregular pattern: after a period of remarkably high expression of this phenomenon in 1998–2001, there was an abrupt decrease in both the number and, especially, extent of bloom areas.

Making use of the OC CCI (Ocean Colour Climate Change Initiative) satellite data, and based on the developed both Emiliania huxleyi bloom contouring methodologies and binary masks, areas of coccoli...

Озеро Мичиган относится к олиготрофному типу водоемов. Сильнее всего это проявляется в прибрежной зоне, где гидрологический режим вод формируется под действием различных природных и антропогенных факторов, протекающих на водосборной территории. Влияние дна достаточно сильно искажает регистрируемый спутником сигнал, препятствуя выполнению дистанционного зондирования параметров качества воды в этой части озера. Для извлечения из спутниковых снимков параметров качества воды в оптически мелких районах озера Мичиган был разработан новый биооптический алгоритм. Он основан на модели переноса излучения, гидрооптической модели озера Мичиган и многомерной оптимизации и позволяет получать оценку концентрации всех основных оптически активных веществ (ОАВ) в областях с различным типом дна: песок, ил, макрофиты (Chara или Cladophora) и известняковая галька. Тестирование алгоритма показало, что при очень низких концентрациях ОАВ (менее 0,01 в соответствующих единицах измерения) оптическое влияние дна становится незначительным при глубине около 20 метров. В воде с более высокими концентрациями взвешенного вещества (ВВ) и хлорофилла влияние дна становится неразличимым при глубине ~10 м. Тестирование чувствительности алгоритма к шуму показало, что чем меньше толщина исследуемого водного столба и чем выше альбедо дна, тем выше погрешность восстановления концентраций ОАВ. Например, в случае песчаного дна и глубины 5 м погрешность в 10 % при оценке альбедо дна приводит к ошибкам в 18, 28 и 10 % при восстановлении хлорофилла, ВВ и окрашенного растворенного органического вещества соответственно.

Producing very extensive blooms in the world’s oceans in both hemispheres, a coccolithophore E. huxleyi affects both marine ecology and carbon fluxes at the atmosphere-ocean interface. In turn, it is subject to impacts of multiple co-acting environmental forcings responsible for spatio-temporal dynamics in E. huxleyi blooms. To reveal the individual importance of each forcing factor (FF) that is known to significantly control the extent and intensity of E. huxleyi blooms, the 1998-2016 spaceborne time series of sea surface temperature and salinity, incident photosynthetically active radiation, and the Ekman depth relevant to the North, Norwegian, Greenland, Labrador, Barents and Bering seas were employed. The descriptive statistical approach showed that E. huxleyi phytoplankton blooms were capable of arising and developing within wide but expressly sea-specific FFs ranges. Sea-specific FFs ranges, within which the blooms are particularly extensive were identified. The Random Forest Classifier (RFC) allowed to reliably rank the FFs in terms of their role in E. huxleyi bloom spatiotemporal dynamics in each target sea. High prediction ability of RFC modelling (>70%) confirms the adequacy of the developed FFs prioritization models. Although the parameters of the carbon chemistry system per se were beyond consideration, however, over the twenty years of observations, the prioritized FFs have not failed to explain the registered patterns of the spatial extent of and particulate inorganic carbon content in E. huxleyi blooms. Also, several verifications (pastcasts) showed a high degree of their consistency with the observations. Collectively, these results tell in favor of sufficiency of the FFs employed.

Producing very extensive blooms in the world's oceans in both hemispheres, a coccolithophore E. huxleyi is capable of affecting both the marine ecology and carbon fluxes at the atmosphere-ocean interface. At the same time, it is subject to the impact of multiple co-acting environmental forcings, which determine the spatio-temporal dynamics of E. huxleyi blooming phenomenon. To reveal the individual importance of each forcing factor (FF) that is known to significantly control the extent and intensity of E. huxleyi blooms and can be retrieved from remote sensing data, we used long-term spatial time series (1998–2016) of sea surface temperature and salinity, incident photosynthetically active radiation, and Ekman layer depth relevant to the marine environments located in the North Atlantic, Arctic and North Pacific oceans, namely the North, Norwegian, Greenland, Labrador, Barents and Bering seas. The FFs retrieved were subjected to statistical analyses. The descriptive statistical approach has shown that E. huxleyi phytoplankton were highly adaptive to the environmental conditions and capable of arising and developing within wide FFs ranges, which proved to be expressly sea-specific. It was also found that there were FFs optimal ranges (also sea-specific), within which the blooms were particularly extensive. The application of the Random Forest Classifier (RFC) approach to each target sea allowed to reliably rank the FFs considered in terms of their role in the spatio-temporal dynamics of E. huxleyi blooms. With the only exception of the Bering Sea, allegedly due to temporally established untypical hydrological conditions, the prediction ability of RFC modeling characterized in terms of precision, recall, and f1-score generally was in excess of 70 %, thus indicating the adequacy of the developed models for FFs prioritization with regard to E. huxleyi blooms.

The algorithm of effective geometric hashing of the facial feature hyperspace for the accelerated search of the most similar face descriptors by their cosine similarity is described in the present study. The algorithm includes 6 required stages of processing descriptors extracted by a neural network from face images. The first stage is filtration of the descriptor database by selecting the most representative descriptor for each person from the set of descriptors corresponding to his/her different face images. The second stage is evaluation of a number of statistical values for all the components of the selected descriptors. The third stage is intermediate hashing through quantization of every descriptor component value so that almost the same quantity of descriptors corresponds to any quantum number. The fourth stage is statistical processing of the descriptor database to determine the most discriminative descriptor key components and their hierarchy. The fifth stage is calculation of the descriptor hash code for every most representative descriptor from the considered database. The sixth final stage is a special cataloging of data in the form of a multi-tiered directory ordered by the hash codes. The search acceleration is achieved through sparse processing of the whole directory when the hash code obtained for the requested person descriptor acts as a very selective search filter. The developed algorithm always provides the same absolute accuracy as the brute-force search. Through the example of the LFW dataset consideration, the average search acceleration by about 100 times is achieved under conditions that the descriptors have been extracted by a neural network trained on the WiderFace dataset with application of the additive angular margin loss function.

A 19-year (1998–2016) continuous dataset of coccolithophore E. huxleyi distributions and activity in Arctic and Subarctic seas is presented. The dataset is based on optical remote sensing data (mostly OC CCI data) with assimilation of different relevant in-situ observations, preprocessed with authorial algorithms. Alongside with bloom locations, we also provide both detailed information on E. huxleyi impacts within the bloom area on marine environments and the subdatasets of quantified coccolith concentrations, particulate inorganic carbon content and CO2 partial pressure in water driven by coccolithophores. All data are presented on a regular 4×4 km grid at a temporal resolution of 8 days. The paper describes the theoretical and methodological basis for all processing and modeling steps. The data are available on Zenodo: https://doi.org/10.5281/zenodo.1402033.

A coccolithophore E. huxleyi is one of the most significant sources of inorganic carbon in the world oceans. Forming vast bloom areas this species can affect the carbon balance in the atmosphere-ocean system, and thus interfere with climate and marine ecology. We obtained from 6 seas located at high latitudes a 19-year time series (1998-2016) of spaceborne data on this phenomenon as well as data on the phenomenon-affecting oceanographic and atmospheric variables. To efficiently concatenate and eventually analyze versatile data of huge size on the aforementioned blooms, a special GIS infrastructure (GISI) is developed. It is built on the principles of a service-based architecture with microservices. The GISI includes both a server application that controls information flows and automated data processing. Microservices with the RESTful architecture for data access and three types of interfaces for researchers are at the base of GISI. Researchers working with the GIS use both a dedicated web client for searching and downloading the required data, a desktop client developed as an extension for an open source desktop GIS QGIS and a Python library developed for the implementation of methods of interaction with the server. Another part of GISI is a virtual-machine based environment for user-side data processing. The use of such a system allows to improve the bloom identification, to map the variations in bloom location, extent, and its inherent properties as well as to perform time series analyses.

The Arctic marine climate system is changing rapidly, seen as warming of the ocean and atmosphere, decline of sea ice cover, increase in river discharge, acidification of the ocean, and changes in marine ecosystems. Socio-economic activities in the coastal and marine Arctic are simultaneously changing. This calls for establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX). There is a need for more in-situ observations on the marine atmosphere, sea ice, and ocean, but increasing the amount of such observations is a pronounced technological and logistical challenge. The SMEAR (Station Measuring Ecosystem-Atmosphere Relations) concept can be applied in coastal and archipelago stations, but in the Arctic Ocean it will probably be more cost-effective to further develop a strongly distributed marine observation network based on autonomous buoys, moorings, Autonomous Underwater Vehicles (AUV), and Unmanned Aerial Vehicles (UAV). These have to be supported by research vessel and aircraft campaigns, as well as various coastal observations, including community-based ones. Major manned drifting stations may occasionally serve comparable to terrestrial SMEAR Flagship stations. To best utilize the observations, atmosphere-ocean reanalyses need to be further developed. To well integrate MA-PEEX with the existing terrestrial/atmospheric PEEX, focus is needed on the river discharge and associated fluxes, coastal processes, as well as atmospheric transports in and out of the marine Arctic. More observations and research are also needed on the specific socio-economic challenges and opportunities in the marine and coastal Arctic, and on their interaction with changes in the climate and environmental system. MA-PEEX will promote international collaboration, sustainable marine meteorological, sea ice, and oceanographic observations, advanced data management, and multidisciplinary research on the marine Arctic and its interaction with the Eurasian continent.

A pilot satellite-based investigation of modulations exerted upon mixed-layer phytoplankton fields by cyclones was performed for the first time across a selected part of the Arctic Ocean, the Barents Sea BS. Resorting to a synergistic approach, cyclones were first identified from NCEP/NCАR data for the summer period during 2003–2013, and their propagation throughout the BS was further surveyed. The above-water wind force was retrieved from QuikSCAT data. These data were further accompanied by ocean colour data from SeaWiFS and MODIS to examine the spatial and temporal distributions of surficial phytoplankton chlorophyll concentration chl dynamics along the trajectory of the cyclone’s footprint across the sea. Sea surface temperature was retrieved from MODIS data. The specific trajectory of cyclone passage across the BS area, depression depth, and wind speed proved to be conjointly the main factors determining the sign, amplitude, and duration of modulations of phytoplankton chl. The spaceborne data obtained over more than a decade indicate that, on balance, the cyclone passage led to increase in chl within the cyclone footprint area. On average, this increase did not exceed 1–2 μg l–1, which is nevertheless appreciable given that the mean chl within the cyclone footprint rarely exceeded 1 μg l–1. However, chl enhancement within the footprint area lasted only within the range of a few days to a fortnight, with the footprint area generally accounting for about 14% of the BS area. During the vegetation season April–August, rarely till mid-September, the number of cyclones prone to optical and infrared remote sensing was about 2–3. In light of the above, arguably the cyclones studied are hardly capable of boosting annual primary productivity in the BS. Moreover, it can be conjectured that the same conclusion can be drawn with respect to the pelagic Arctic tracts that are generally less productive and more extensively cloud-covered than the BS. However, this supposition requires further studies in order to advance our understanding of the actual role of cyclones in modulation of Arctic Ocean productivity and ecosystem functioning.

This article offers a reconstruction of the vegetation and climate of the south-western Siberian Baraba forest-steppe area during the last ca. 8000 years. The analysis of palynological data from the sediment core of Lake Bolshie Toroki using quantitative methods has made it possible to reconstruct changes of the dominant types of vegetation and mean July air temperatures. Coniferous forests grew in the vicinity of the lake, and mean July air temperatures were similar to present-day ones between 7.9 and 7.0 kyr BP. The warmest and driest climate occurred at 7.0-5.0 kyr BP. At that time, the region had open steppe landscapes; birch groves began to spread. A cooling trend is seen after 5.5 kyr BP, when forest-steppe began to emerge. Steppe communities started to dominate again after 1.5 kyr BP. Mean July air temperatures lower than now are reconstructed for the period of 1.9-1 kyr BP, and then the temperatures became similar to present-day ones. Comparing the archaeological data on the types of economy of the population which inhabited the Baraba forest-steppe with the data on changes in the natural environment revealed a connection between the gradual transition from hunting and fishing to livestock breeding and the development of forest-steppe landscapes with a decrease in the area covered by forests. The development of the forest-steppe as an ecotonic landscape starting around 5 kyr BP might have contributed to the coexistence of several archaeological cultures with different types of economy on the same territory. (C) 2017 Elsevier Ltd. All rights reserved.

Solidly underpinned by abounding observations, it is presently a commonly shared opinion that, as a result of climate change, there is a greater degree of warming at high latitudes than at lower altitudes, which is predicted to become worse over the twenty-first century.

Numerical model simulation of marine processes, originating from complex physical, chemical, and biological phenomena, enables studying the conditions of the marine ecosystem behavior, the biotransformation of organogenic substances, and the formation of the water component chemical structure and water quality in both unperturbed natural conditions and under anthropogenic forcing. Such studies make it possible to estimate the role of natural factors and the consequences of economic activity in watershed areas, as well as the effects of industrial and domestic discharges upon the state of the marine ecosystem. One of the possible directions of research is the study of transformation of biogenic substances and ecosystem bioproductivity in the target water body by making use of a developed model describing the transformation of organogenic substances, namely, the organic and mineral forms of N, P, Si, doc, and O2.

The Bay of Biscay is a gulf of the northeast Atlantic Ocean lying along the western coast of France from Brest southwards to the Spanish border, and the northern coast of Spain in the Spanish Basque Country. Its limits are defined as a line joining Cap Ortegal (43° 46′N, 7° 52′W) to Penmarch Point (47° 48′N, 4° 22′W).

Along with the blooms of the diatom-dominated phytoplankton community, outbursts of the harmful green alga Lepidodinium chlorophorum occur in the essentially coastal zone of the Bay.

Comprehensive investigations of biogeochemical processes in marine ecosystems by means of remote sensing become significantly more efficient provided many satellite images from various sources are synergistically employed.

Emiliania huxleyi algae are known to enhance CO2 partial pressure in their ambient water, (pCO2)w. Thus, over such bloom areas, the atmospheric column-averaged dry air mole fraction of carbon dioxide (XCO2) is likely to increase, which has not been yet quantified on basin scales. Here we report on an Orbiting Carbon Observatory (OCO-2) satellite study of the influence of E. huxleyi blooms on XCO2 over the Black Sea. We established that concurrently with a (pCO2)w significant rise, there is an increase in the overlying XCO2 within the range ~1 to nearly 2 ppmv, which is on the order of the planetary annual increase of XCO2. As we found, (∆pCO2)w in the Back Sea and Subpolar and Polar seas are closely comparable. This strongly indicates that E. huxleyi blooms do weaken carbon sinks in the ocean on a large scale, which can be consequential for global climatology and marine biogeochemistry.

Based on MODIS data, a significant decline in the intensity and spatial extension of blooms of coccolithophore E. huxleyi in Arctic waters in 2002–2010 is revealed and quantified. This 9-year tendency has been unfolding against a background of negative trends in the dynamics of SST and levels of incident PAR and summer-time NAO, which collectively, but with a predominance of the NAO influence, are believed to be the main drivers of the decline of E. huxleyi blooms and the associated decline in inorganic carbon production in the Arctic Basin.

Spaceborne one month averaged data, predominantly from the Sea-viewing Wide Field-of-view Sensor SeaWiFS and partly from the Moderate Resolution Imaging Spectroradiometer MODIS, were used to investigate changes in primary production PP by phytoplankton in the Arctic Ocean from 1998 to 2010. Several PP retrieval algorithms were tested against the collected in situ data, and it was shown that the algorithm by Behrenfeld and Falkowski gave the best results with the coefficient of correlation, r , equal to 0.8 and 0.75, respectively, for the pelagic and shelf zones. Based on the performed test, the Behrenfeld and Falkowski algorithm was further applied for determining both the annual PP in the Arctic and the PP trend over the above-mentioned time period. Results of our analysis indicate that PP in the Arctic has increased by ˜15.9% over 13 years 1998–2010. This finding, as well as the absolute annual values of PP remotely quantified in the present study, is at odds with analogous numerical assessments by other workers. These disagreements are thought to be due to differences in the applied methodologies of satellite data processing such as cloud masking and determination of phytoplankton concentration within 1 overcast areas and 2 areas of massive growth of coccolithophores as well as 3 in the shelf zone prone to a significant influence of land and river run-off.

An algorithm that utilizes individual lake hydro-optical (HO) models has been developed for the Great Lakes that uses SeaWiFS, MODIS, or MERIS satellite data to estimate concentrations of chlorophyll, dissolved organic carbon, and suspended minerals. The Color Producing Agent Algorithm (CPA-A) uses a specific HO model for each lake. The HO models provide absorption functions for the Color Producing Agents (CPAs) (chlorophyll (chl), colored dissolved organic matter (as dissolved organic carbon, doc), and suspended minerals (sm)) as well as backscatter for the chlorophyll, and suspended mineral parameters. These models were generated using simultaneous optical data collected with in situ measurements of CPAs collected during research cruises in the Great Lakes using regression analysis as well as using specific absorption and backscatter coefficients at specific chl, doc, and sm concentrations. A single average HO model for the Great Lakes was found to generate insufficiently accurate concentrations for Lakes Michigan, Erie, Superior and Huron. These new individual lake retrievals were evaluated with respect to EPA in situ field observations, as well as compared to the widely used OC3 MODIS retrieval. The new algorithm retrievals provided slightly more accurate chl values for Lakes Michigan, Superior, Huron, and Ontario than those obtained using the OC3 approach as well as providing additional concentration information on doc and sm. The CPA-A chl retrieval for Lake Erie is quite robust, producing reliable chl values in the reported EPA concentration ranges. Atmospheric correction approaches were also evaluated in this study.

Multi-decadal extensive ship borne biochemical investigations conducted by the Limnological Institute in St. Petersburg (Russian Academy of Sciences) have shown that since the mid-1980s the ecosystem of Lake Ladoga (at that time a mesotrophic water body) has undergone significant and multifaceted alterations primarily as a result of a dramatic cutting of external phosphorus input enforced by the administrative measures taken at the Russian federal and regional levels. Using the SeaWiFS data for the time period 1998–2004, the seasonal dynamics of spatial distributions of phytoplankton chlorophyll and dissolved organic matter in Lake Ladoga have been documented and analyzed. It is shown that the hydro-optical characteristics of the lake's water have undergone appreciable modifications as compared to the mid-1980s. Contrary to expectations that these changes would bring about some amelioration of the lake's ecological state, ship-based and spaceborne observations indicate that the attained decrease in phosphorous input has not resulted in “healing” of the lake's ecology. It is proposed that during the lake's mesotrophic period, a specific mechanism of phosphorus release from dissolved organic matter has gradually developed. As a result, the lake's phosphorous concentrations have continued to be higher than expected. In addition changes in local atmospheric forcing are manifested not only in remotely sensed color data but also in the inter-annual behavior of the spring thermal bar derived from the AVHRR multi-year observations.