scholarly journals Observing and modelling phytoplankton community structure in the North Sea

2017 ◽  
Vol 14 (6) ◽  
pp. 1419-1444 ◽  
Author(s):  
David A. Ford ◽  
Johan van der Molen ◽  
Kieran Hyder ◽  
John Bacon ◽  
Rosa Barciela ◽  
...  

Abstract. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical–biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs.

2016 ◽  
Author(s):  
David A. Ford ◽  
Johan van der Molen ◽  
Kieran Hyder ◽  
John Bacon ◽  
Rosa Barciela ◽  
...  

Abstract. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models have therefore yet to be properly validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical-biogeochemical ocean models, the biogeochemical components of which are different variants of the widely-used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. A comparison of the formulations and parameterisations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed biodiversity. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs.


2015 ◽  
Vol 12 (13) ◽  
pp. 4051-4066 ◽  
Author(s):  
M. Thyssen ◽  
S. Alvain ◽  
A. Lefèbvre ◽  
D. Dessailly ◽  
M. Rijkeboer ◽  
...  

Abstract. Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of its biomass and dynamics will help to understand ocean ecosystems and refine global climate models. Relevant data sets of phytoplankton defined at a functional level and on a sub-meso- and daily scale are thus required. In order to achieve this, an automated, high-frequency, dedicated scanning flow cytometer (SFC, Cytobuoy b.v., the Netherlands) has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a PocketFerryBox during a cruise in the North Sea, 08–12 May 2011 (DYMAPHY project, INTERREG IV A "2 Seas"), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high spatial resolution basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analysing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. For the first time, the community structure observed from the automated flow cytometry data set was compared with PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high-frequency in situ sampling and remote sensing was found to be more than 2 times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the 2 days for which matchups were available suggest that it is possible to label PHYSAT anomalies using automated flow cytometry to resolve not only dominant groups but also community structure.


2014 ◽  
Vol 11 (11) ◽  
pp. 15621-15662
Author(s):  
M. Thyssen ◽  
S. Alvain ◽  
A. Lefèbvre ◽  
D. Dessailly ◽  
M. Rijkeboer ◽  
...  

Abstract. Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of their biomass and dynamics will help to understand ocean ecosystems and refine global climate models. This requires relevant datasets of phytoplankton at a functional level and on a daily and sub meso scale. In order to achieve this, an automated, high frequency, dedicated scanning flow cytometer (SFC, Cytobuoy, NL), has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a~pocket Ferry Box during a cruise in the North Sea, 8–12 May 2011 (DYMAPHY project, INTERREG IV A "2 Seas"), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high resolution spacial basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analyzing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. The community structure observed from the automated flow cytometry was compared with the PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high frequency in situ sampling and the remote sensing was found to be two to three times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the two days for which matchups were available, suggest that it is possible to label PHYSAT anomalies not only with dominant groups, but at the level of the community structure.


2016 ◽  
Vol 29 (7) ◽  
pp. 2529-2541 ◽  
Author(s):  
Jacob L. Høyer ◽  
Ioanna Karagali

Abstract A 30-yr climate data record (CDR) of sea surface temperature (SST) has been produced with daily gap-free analysis fields for the North Sea and the Baltic Sea region from 1982 to 2012 by combining the Pathfinder AVHRR satellite data record with the Along-Track Scanning Radiometer (ATSR) Reprocessing for Climate (ARC) dataset and with in situ observations. A dynamical bias correction scheme adjusts the Pathfinder observations toward the ARC and in situ observations. Largest Pathfinder–ARC differences are found in the summer months, when the Pathfinder observations are up to 0.4°C colder than the ARC observations on average. Validation against independent in situ observations shows a very stable performance of the data record, with a mean difference of −0.06°C compared to moored buoys and a 0.46°C standard deviation of the differences. The mean annual biases of the SST CDR are small for all years, with a negligible temporal trend when compared against drifting and moored buoys. Analysis of the SST CDR reveals that the monthly anomalies for the North Sea, the Danish straits, and the central Baltic Sea regions show a high degree of correlation for interannual and decadal time scales, whereas the monthly variability differs from one region to another. The linear trends of the 1982–2012 SST anomaly time series range from 0.037°C yr−1 for the North Sea to 0.041°C yr−1 for the Baltic Sea.


2020 ◽  
Author(s):  
Oceana ◽  
Helena Álvarez ◽  
Allison L. Perry ◽  
Jorge Blanco ◽  
Silvia Garcia ◽  
...  

To help fill gaps in knowledge about marine biodiversity in the North Sea, Oceana carried out two eight week research expeditions, in 2016 and 2017. Oceana’s surveys documented a wide range of habitats and species that are considered priorities for conservation, under national, EU, and international frameworks that recognise them as threatened and/or establish legal requirements for their protection.Oceana’s research has underscored the fact that much remains to be discovered about marine life on the seabed of the North Sea. Continued research is critical for informing efforts to recover biodiversity, an urgent priority in the face of the multiple, intense pressures facing the North Sea’s marine habitats and species.


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