scholarly journals Exploring biogeochemical and ecological redundancy in phytoplankton communities in the global ocean

2021 ◽  
Author(s):  
Stephanie Dutkiewicz ◽  
Philip W. Boyd ◽  
Ulf Riebesell
Author(s):  
Kevin D. Friedland ◽  
John R. Moisan ◽  
Aurore A. Maureaud ◽  
Damian C. Brady ◽  
Andrew J. Davies ◽  
...  

Large marine ecosystems (LMEs) are highly productive regions of the world ocean under anthropogenic pressures; we analyzed trends in sea surface temperature (SST), cloud fraction (CF), and chlorophyll concentration (CHL) over the period 1998–2019. Trends in these parameters within LMEs diverged from the world ocean. SST and CF inside LMEs increased at greater rates inside LMEs, whereas CHL decreased at a greater rates. CHL declined in 86% of all LMEs and of those trends, 70% were statistically significant. Complementary analyses suggest phytoplankton functional types within LMEs have also diverged from those characteristic of the world ocean, most notably, the contribution of diatoms and dinoflagellates, which have declined within LMEs. LMEs appear to be warming rapidly and receiving less solar radiation than the world ocean, which may be contributing to changes at the base of the food chain. Despite increased fishing effort, fishery yields in LMEs have not increased, pointing to limitations related to productivity. These changes raise concerns over the stability of these ecosystems and their continued ability to support services to human populations.


2016 ◽  
Vol 9 (11) ◽  
pp. 4071-4085 ◽  
Author(s):  
Esteban Acevedo-Trejos ◽  
Gunnar Brandt ◽  
S. Lan Smith ◽  
Agostino Merico

Abstract. Biodiversity is one of the key mechanisms that facilitate the adaptive response of planktonic communities to a fluctuating environment. How to allow for such a flexible response in marine ecosystem models is, however, not entirely clear. One particular way is to resolve the natural complexity of phytoplankton communities by explicitly incorporating a large number of species or plankton functional types. Alternatively, models of aggregate community properties focus on macroecological quantities such as total biomass, mean trait, and trait variance (or functional trait diversity), thus reducing the observed natural complexity to a few mathematical expressions. We developed the PhytoSFDM modelling tool, which can resolve species discretely and can capture aggregate community properties. The tool also provides a set of methods for treating diversity under realistic oceanographic settings. This model is coded in Python and is distributed as open-source software. PhytoSFDM is implemented in a zero-dimensional physical scheme and can be applied to any location of the global ocean. We show that aggregate community models reduce computational complexity while preserving relevant macroecological features of phytoplankton communities. Compared to species-explicit models, aggregate models are more manageable in terms of number of equations and have faster computational times. Further developments of this tool should address the caveats associated with the assumptions of aggregate community models and about implementations into spatially resolved physical settings (one-dimensional and three-dimensional). With PhytoSFDM we embrace the idea of promoting open-source software and encourage scientists to build on this modelling tool to further improve our understanding of the role that biodiversity plays in shaping marine ecosystems.


2020 ◽  
Vol 12 (5) ◽  
pp. 840 ◽  
Author(s):  
Dabin Lee ◽  
SeungHyun Son ◽  
HuiTae Joo ◽  
Kwanwoo Kim ◽  
Myung Joon Kim ◽  
...  

In recent years, the change of marine environment due to climate change and declining primary productivity have been big concerns in the East/Japan Sea, Korea. However, the main causes for the recent changes are still not revealed clearly. The particulate organic carbon (POC) to chlorophyll-a (chl-a) ratio (POC:chl-a) could be a useful indicator for ecological and physiological conditions of phytoplankton communities and thus help us to understand the recent reduction of primary productivity in the East/Japan Sea. To derive the POC in the East/Japan Sea from a satellite dataset, the new regional POC algorithm was empirically derived with in-situ measured POC concentrations. A strong positive linear relationship (R2 = 0.6579) was observed between the estimated and in-situ measured POC concentrations. Our new POC algorithm proved a better performance in the East/Japan Sea compared to the previous one for the global ocean. Based on the new algorithm, long-term POC:chl-a ratios were obtained in the entire East/Japan Sea from 2003 to 2018. The POC:chl-a showed a strong seasonal variability in the East/Japan Sea. The spring and fall blooms of phytoplankton mainly driven by the growth of large diatoms seem to be a major factor for the seasonal variability in the POC:chl-a. Our new regional POC algorithm modified for the East/Japan Sea could potentially contribute to long-term monitoring for the climate-associated ecosystem changes in the East/Japan Sea. Although the new regional POC algorithm shows a good correspondence with in-situ observed POC concentrations, the algorithm should be further improved with continuous field surveys.


2020 ◽  
Author(s):  
Roy El Hourany ◽  
Chris Bowler ◽  
Carlos Mejia ◽  
Michel Crépon ◽  
Sylvie Thiria

<p>The regionalization of the Mediterranean Sea has been the subject of many studies. It is a miniature ocean where most of the processes of the global ocean are encountered (Lejeusne et al., 2010). Several features of the Mediterranean (near-tropical ocean in summer with a well-formed thermocline, near-polar ocean in winter with deep convection, multiple basins with different characteristics) make it a hotspot of marine biodiversity (Coll and al., 2010) and consequently vulnerable to climate change. It is therefore important to characterize the present state of the Mediterranean Sea with robust estimators in order to study the long-term evolution of this mesocosm.</p><p>We present a partitioning of the Mediterranean Sea in regions having well defined characteristics with respect to Sea Surface Temperature and surface chlorophyll observed by satellite, and Argo mixed layer depth. This regionalization was performed by using an innovative classification based on neural networks, the so-called 2S-SOM. Its major advantage is to consider the specificity of the variables by adding automatically, through machine learning, specific weights to each of them, which facilitates the classification and consequently highlights the regional correlations. The 2S-SOM provided a well differentiated regionalization of the Mediterranean Sea waters into seven bioregions governed by specific physical and biogeochemical processes such as Intermediate-water formation in the Aegean Sea, large surface currents in the Adriatic and the Alboran, deep winter convection phenomena in the Balearic and stratification phenomena during summer in the eastern part of the Mediterranean Sea.</p><p>Besides, in order to highlight the phytoplankton diversity in these regions, we processed the satellite ocean color observations with a specific neural network approach (SOM-PFT, El Hourany et al., 2019). As a result, specific phytoplankton communities characterized by their seasonal variability are associated with the obtained Mediterranean bioregions; the dominance of the Nanophytoplankton groups is largely observed in the western basin during the period ranging from autumn to spring. While the dominance of different types of cyanobacteria Synechococcus and Prochlorococcus is highlighted in summer and more precisely in the waters of the eastern basin. Diatoms dominate throughout the year in the coastal and shallow regions, which can be explained by the presence of terrigenous input necessary for the development of this type of phytoplankton. Diatoms also largely benefit from the strong deep convection in the Balearic Sea marked by a large bloom at the end of winter convection in March.</p><p>This work will be further extended to study the phytoplankton diversity at global scale using various data set from the Tara Oceans.</p>


2020 ◽  
Vol 644 ◽  
pp. 1-13 ◽  
Author(s):  
MY Gorbunov ◽  
E Shirsin ◽  
E Nikonova ◽  
VV Fadeev ◽  
PG Falkowski

Phytoplankton are extraordinarily diverse, comprising 13 phylogenetic groups, with diatoms, dinoflagellates, and haptophytes among the most prominent eukaryotes in the ocean. Development of sensor technologies for rapid taxonomic and physiological analysis of phytoplankton communities is crucial for ecological monitoring programs in the global ocean. We describe a novel, ultra-sensitive, multi-spectral fluorescence induction and relaxation instrument (a mini-FIRe) and examine its analytical capability of rapidly determining phytoplankton taxonomic groups, as well as physiological characteristics and photosynthetic rates. We collected and analyzed the database of spectral and photosynthetic properties of major taxonomic groups of phytoplankton. We revealed that the spectral shape of the functional absorption cross-section of Photosystem II (PSII), sPSII(lex), is remarkably constrained within each major phylogenetic group of eukaryotic phytoplankton, including diatoms, haptophytes, dinoflagellates, and chlorophytes. Variability in sPSII(lex) within each group was significantly smaller than the difference between groups. We also examined the classical excitation spectra of chl a fluorescence yields, Fm(lex). Our comparative analysis revealed that sPSII(lex) is a better and more specific proxy for taxonomic analysis. For instance, our developed sPSII-based algorithm correctly identified 90% of experimental data, compared to 77% identified by the Fm-based algorithm. Our results suggest that the multi-color variable fluorescence analysis offers a tool for combined physiological and taxonomic analysis, including identification of major phyla within the ‘red’ lineage of eukaryotic phytoplankton.


2021 ◽  
Vol 119 (1) ◽  
pp. e2114602118
Author(s):  
Boris Sauterey ◽  
Ben A. Ward

The stoichiometric coupling of carbon to limiting nutrients in marine phytoplankton regulates the magnitude of biological carbon sequestration in the ocean. While clear links between plankton C:N ratios and environmental drivers have been identified, the nature and direction of these links, as well as their underlying physiological and ecological controls, remain uncertain. We show, with a well-constrained mechanistic model of plankton ecophysiology, that while nitrogen availability and temperature emerge as the main drivers of phytoplankton C:N stoichiometry in the North Atlantic, the biological mechanisms involved vary depending on the spatiotemporal scale and region considered. We find that phytoplankton C:N stoichiometry is overall controlled by nitrogen availability below 40° N, predominantly driven by ecoevolutionary shifts in the functional composition of the phytoplankton communities, while phytoplankton stoichiometric plasticity in response to dropping temperatures and increased grazing pressure dominates at higher latitudes. Our findings highlight the potential of “organisms-to-ecosystems” modeling approaches based on mechanistic models of plankton biology accounting for physiology, ecology, and trait evolution to explore and explain complex observational data and ultimately improve the predictions of global ocean models.


2016 ◽  
Vol 542 ◽  
pp. 51-62 ◽  
Author(s):  
JR Graff ◽  
TK Westberry ◽  
AJ Milligan ◽  
MB Brown ◽  
G Dall’Olmo ◽  
...  

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