scholarly journals Dynamics of the Deep Chlorophyll Maximum in the Black Sea as depicted by BGC-Argo floats

2021 ◽  
Author(s):  
Arthur Capet ◽  
florian ricour ◽  
Fabrizio D'Ortenzio ◽  
Bruno Delille ◽  
Marilaure Grégoire
Keyword(s):  
Black Sea ◽  
Global Ocean ◽  
The Black Sea ◽  
Second Phase ◽  
Deep Chlorophyll Maximum ◽  
Phytoplankton Productivity ◽  
Spatial Homogeneity ◽  
Argo Floats ◽  
Chlorophyll Maximum ◽  
Basin Scale

<p>The deep chlorophyll maximum (DCM) is a well known feature of the global ocean. However, its description and the study of its formation are a  challenge, especially in the peculiar environment that is the Black Sea. The retrieval of chlorophyll a (Chla) from fluorescence (Fluo) profiles recorded by biogeochemical-Argo (BGC-Argo) floats is not trivial in the Black Sea, due to the very high content of colored dissolved organic matter (CDOM) which contributes to the fluorescence signal and produces an apparent increase of the Chla concentration with depth.</p><p>Here, we revised Fluo correction protocols for the Black Sea context using co-located in-situ high-performance liquid chromatography (HPLC) and BGC-Argo measurements. The processed set of Chla data (2014–2019) is then used to provide a systematic description of the seasonal DCM dynamics in the Black Sea and to explore different hypotheses concerning the mechanisms underlying its development.</p><p>Our results show that the corrections applied to the Chla profiles are consistent with HPLC data. In the Black Sea, the DCM begins to form in March, throughout the basin, at a density level set by the previous winter mixed layer. During a first phase (April-May), the DCM remains attached to this particular layer. The spatial homogeneity of this feature suggests a hysteresis mechanism, i.e., that the DCM structure locally influences environmental conditions rather than adapting instantaneously to external factors.</p><p>In a second phase (July-September), the DCM migrates upward, where there is higher irradiance, which suggests the interplay of biotic factors. Overall, the DCM concentrates around 45 to 65% of the total chlorophyll content within a 10 m layer centered around a depth of 30 to 40 m, which stresses the importance of considering DCM dynamics when evaluating phytoplankton productivity at basin scale.</p>

scholarly journals Dynamics of the deep chlorophyll maximum in the Black Sea as depicted by BGC-Argo floats

2021 ◽  
Vol 18 (2) ◽  
pp. 755-774
Author(s):  
Florian Ricour ◽  
Arthur Capet ◽  
Fabrizio D'Ortenzio ◽  
Bruno Delille ◽  
Marilaure Grégoire
Keyword(s):  
Black Sea ◽  
Global Ocean ◽  
The Black Sea ◽  
Second Phase ◽  
Deep Chlorophyll Maximum ◽  
Phytoplankton Productivity ◽  
Chl A ◽  
Argo Floats ◽  
Chlorophyll Maximum ◽  
Basin Scale

Abstract. The deep chlorophyll maximum (DCM) is a well-known feature of the global ocean. However, its description and the study of its formation are a challenge, especially in the peculiar environment that is the Black Sea. The retrieval of chlorophyll a (chl a) from fluorescence (Fluo) profiles recorded by Biogeochemical Argo (BGC-Argo) floats is not trivial in the Black Sea, due to the very high content of coloured dissolved organic matter (CDOM) which contributes to the fluorescence signal and produces an apparent increase in the chl a concentration with depth. Here, we revised Fluo correction protocols for the Black Sea context using co-located in situ high-performance liquid chromatography (HPLC) and BGC-Argo measurements. The processed set of chl a data (2014–2019) is then used to provide a systematic description of the seasonal DCM dynamics in the Black Sea and to explore different hypotheses concerning the mechanisms underlying its development. Our results show that the corrections applied to the chl a profiles are consistent with HPLC data. In the Black Sea, the DCM begins to form in March, throughout the basin, at a density level set by the previous winter mixed layer. During a first phase (April–May), the DCM remains attached to this particular layer. The spatial homogeneity of this feature suggests a hysteresis mechanism, i.e. that the DCM structure locally influences environmental conditions rather than adapting instantaneously to external factors. In a second phase (July–September), the DCM migrates upward, where there is higher irradiance, which suggests the interplay of biotic factors. Overall, the DCM concentrates around 45 % to 65 % of the total chlorophyll content within a 10 m layer centred around a depth of 30 to 40 m, which stresses the importance of considering DCM dynamics when evaluating phytoplankton productivity at basin scale.

scholarly journals Dynamics of the Deep Chlorophyll Maximum in the Black Sea as depicted by BGC-Argo floats

2020 ◽  
Author(s):  
Florian Ricour ◽  
Arthur Capet ◽  
Fabrizio D'Ortenzio ◽  
Bruno Delille ◽  
Marilaure Grégoire
Keyword(s):  
Black Sea ◽  
High Performance ◽  
Global Ocean ◽  
The Black Sea ◽  
Fluorescence Signal ◽  
Deep Chlorophyll Maximum ◽  
Lateral Loads ◽  
Spatial Homogeneity ◽  
Argo Floats ◽  
Chlorophyll Maximum

Abstract. The Deep Chlorophyll Maximum (DCM) is a well known feature of the global ocean. However, its description and the study of its formation are a challenge, especially in the peculiar Black Sea environment. The retrieval of Chlorophyll a (Chla) from fluorescence (Fluo) profiles recorded by Biogeochemical-Argo (BGC-Argo) floats is not trivial in the Black Sea, due to the very high content of Colored Dissolved Organic Matter (CDOM) which contributes to the fluorescence signal and produces an apparent increase of the Chla concentration with depth. Here we revised Fluo correction protocols for the Black Sea context using co-located in-situ High-Performance Liquid Chromatography (HPLC) and BGC-Argo measurements. The processed set of Argo Chla data (2014–2019) is then used to provide a systematic description of the seasonal DCM dynamics in the Black Sea, and to explore different hypotheses concerning the mechanisms underlying its development. Our results show that the corrections applied to Chla profiles are consistent with HPLC data. In the Black Sea, the DCM is initiated in March, throughout the basin, at a pycnal level set by the previous winter mixed layer. The DCM then remains attached to this particular layer until the end of September. The spatial homogeneity of this feature suggests a self-sustaining DCM structure, locally influencing environmental conditions rather than adapting instantaneously to external factors. In summer, the DCM concentrates around 50 to 65 % of the total chlorophyll content around a depth of 30 m, where light conditions ranged from 0.5 to 4.5 % of surface incoming irradiance. In October, as the DCM structure is gradually eroded, a longitudinal gradient appears in the DCM pycnal depth, indicating that autumnal mixing induces a relocation of the DCM which is this time driven by regional factors, such as nutrients lateral loads and turbidity.

scholarly journals Phytoplankton light absorption in the deep chlorophyll maximum layer of the Black Sea

2018 ◽  
Vol 52 (sup1) ◽  
pp. 123-136 ◽  
Author(s):  
T. Churilova ◽  
V. Suslin ◽  
H.M. Sosik ◽  
T. Efimova ◽  
N. Moiseeva ◽  
...  
Keyword(s):  
Black Sea ◽  
Light Absorption ◽  
The Black Sea ◽  
Deep Chlorophyll Maximum ◽  
Chlorophyll Maximum

Basin scale spatiotemporal analysis of shoreline change in the Black Sea

2021 ◽  
Vol 252 ◽  
pp. 107247
Author(s):  
Tahsin Görmüş ◽  
Berna Ayat ◽  
Burak Aydoğan ◽  
Florin Tătui
Keyword(s):  
Black Sea ◽  
Shoreline Change ◽  
Spatiotemporal Analysis ◽  
The Black Sea ◽  
Basin Scale

Evaluation of ecotourism sites: a GIS-based multi-criteria decision analysis

Kybernetes ◽  
2018 ◽  
Vol 47 (8) ◽  
pp. 1664-1686 ◽  
Author(s):  
Cihan Çetinkaya ◽  
Mehmet Kabak ◽  
Mehmet Erbaş ◽  
Eren Özceylan
Keyword(s):  
Black Sea ◽  
Real Data ◽  
The Black Sea ◽  
Second Phase ◽  
Content Type ◽  
Black Sea Region ◽  
Evaluation Approach ◽  
Third Phase ◽  
Proposed Model ◽  
Promethee Method

Purpose The aim of this study is to evaluate the potential geographic locations for ecotourism activities and to select the best one among alternatives. Design/methodology/approach The proposed model consists of four sequential phases. In the first phase, different geographic criteria are determined based on existing literature, and data are gathered using GIS. On equal criteria weighing, alternative locations are determined using GIS in the second phase. In the third phase, the identified criteria are weighted using analytical hierarchy process (AHP) by various stakeholders of potential ecotourism sites. In the fourth phase, the PROMETHEE method is applied to determine the best alternative based on the weighted criteria. Findings A framework including four sequential steps is proposed. Using real data from the Black Sea region in Turkey, the authors test the applicability of the evaluation approach and compare the best alternative obtained by the proposed method for nine cities in the region. Consequently, west of Sinop, east of Artvin and south of the Black Sea region are determined as very suitable locations for ecotourism. Research limitations/implications The first limitation of the study is considered the number of included criteria. Another limitation is the use of deterministic parameters that do not cope with uncertainty. Further research can be conducted for determining the optimum locations for different types of tourism, e.g. religion tourism, hunting tourism and golf tourism, for effective tourism planning. Practical implications The proposed approach can be applied to all area that cover the considered criteria. The approach has been tested in the Black Sea region (nine cities) in Turkey. Social implications Using the proposed approach, decision-makers can determine locations where environmentally responsible travel to natural areas to enjoy and appreciate nature that promotes conservation have a low visitor impact and provide for beneficially active socioeconomic involvement of local individuals. Originality/value To the best knowledge of the authors, this is the first study which applies a GIS-based multi-criteria decision-making approach for ecotourism site selection.

scholarly journals Lack of marine entry into Marmara and Black Sea-lakes indicate low relative sea level during MIS 3 in the northeastern Mediterranean

2019 ◽  
Author(s):  
Anastasia G. Yanchilina ◽  
Celine Grall ◽  
William B. F. Ryan ◽  
Jerry F. McManus ◽  
Candace O. Major
Keyword(s):  
Sea Level ◽  
Black Sea ◽  
Global Ocean ◽  
The Black Sea ◽  
Marmara Sea ◽  
Independent Data ◽  
Relative Sea Level ◽  
Mis 3 ◽  
History Of ◽  
Marine Isotope Stage 3

Abstract. The Marine Isotope Stage 3 (MIS 3) is considered a period of persistent and rapid climate and sea level variabilities during which eustatic sea level is observed to have varied by tens of meters. Constraints on local sea level during this time are critical for further estimates of these variabilities. We here present constraints on relative sea level in the Marmara and Black Sea regions in the northeastern Mediterranean, inferred from reconstructions of the history of the connections and disconnections (partial or total) of these seas together with the global ocean. We use a set of independent data from seismic imaging and core-analyses to infer that the Marmara and Black Seas remained connected persistent freshwater lakes that outflowed to the global ocean during the majority of MIS 3. Marine water intrusion during the early MIS-3 stage may have occurred into the Marmara Sea-Lake but not the Black Sea-Lake. This suggests that the relative sea level was near the paleo-elevation of the Bosporus sill and possibly slightly above the Dardanelles paleo-elevation, ~80 mbsl. The Eustatic sea level may have been even lower, considering the isostatic effects of the Eurasian ice sheet would have locally uplifted the topography of the northeastern Mediterrranean.

Coupled Hydrodynamic Ecosystem Model of the Black Sea at Basin Scale

1997 ◽  
pp. 487-499 ◽  
Author(s):  
M. Grégoire ◽  
J.-M. Beckers ◽  
J. C. J. Nihoul ◽  
E. Stanev
Keyword(s):  
Black Sea ◽  
Ecosystem Model ◽  
The Black Sea ◽  
Basin Scale

Biogeochemical controls on the Black Sea oxygen dynamics : relevant diagnostics, key processes and adequacy of the monitoring infrastructure.

2020 ◽  
Author(s):  
Arthur Capet ◽  
vandenbulcke Luc ◽  
Grégoire Marilaure
Keyword(s):  
Black Sea ◽  
3D Models ◽  
The Black Sea ◽  
Biogeochemical Model ◽  
Model Parameters ◽  
Biogeochemical Processes ◽  
Low Oxygen ◽  
Future Evolution ◽  
Basin Scale ◽  
Set Up

<p>An important deoxygenation trend has been described in the Black Sea over the five past decades from in-situ observations [1]. While the implications for basin-scale biogeochemistry and possible future trends of this dynamics are unclear, it is important to consolidate our means to resolve the dynamics of the Black Sea oxygen content in order to assess the likelihood of future evolution scenario, and the possible morphology of low-oxygen events. </p><p>Also, it is known that current global models simulate only about half the observed oceanic O2 loss and fail in reproducing its vertical distribution[2]. In parts, unexplained O2 losses could be attributed to illy parameterized biogeochemical processes within 3D models used to integrate those multi-elemental dynamics.</p><p>Biogeochemical processes involved in O2 dynamics are structured vertically and well separated in the stratified Black Sea. O2 sources proceed from air-sea fluxes and photosynthesis in the<br>photic zone. Organic matter (OM) is respired over a depth determined by its composition and<br>sinking, via succeeding redox reactions. Those intricate dynamics leave unknowns as regards the biogeochemical impacts of future deoxygenation on associated cycles, for instance on the oceanic carbon pump. Here we use the Black Sea scene to derive model-observation strategies to best address the global deoxygenation concern.</p><p>First, we decipher components of the O2 dynamics in the open basin, and discuss the way in which O2-based indicators informs on the relative importance of processes involved. Using 1D biogeochemical model set-up, we then conduct a sensitivity analysis to pin-point model parameters, ie. biogeochemical processes, that bears the largest part in the uncertainty of simulated results for those diagnostics. Finally, we identify among the most impacting parameters the ones that can most efficiently be constrained on the basis of modern observational infrastructure, and Bio-Argo in particular. </p><p>The whole procedure aims at orienting the development of observations networks and data assimilation approaches in order to consolidate our means to anticipate the marine deoxygenation challenge. </p><p>[1] Capet A et al., 2016, Biogeoscience, 13:1287-1297<br>[2] Oschlies A et al., 2018, Nature Geosci, 11(7):467–473</p>

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