scholarly journals Biogeochemical versus ecological consequences of modeled ocean physics

2016 ◽  
Author(s):  
Sophie Clayton ◽  
Stephanie Dutkiewicz ◽  
Oliver Jahn ◽  
Christopher Hill ◽  
Patrick Heimbach ◽  
...  
Keyword(s):  
Primary Production ◽  
Ocean Circulation ◽  
Mixed Layer ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Nutrient Supply ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Models

Abstract. Regional and idealized modeling studies have shown that increasing the physical resolution of biogeochemical models to include mesoscale and submesoscale dynamics can result in both increases and decreases in phytoplankton biomass and primary production, as well as changes in phytoplankton community structure. Here we present a systematic study of the differences generated by coupling the same ecological-biogeochemical model to a 1°, coarse-resolution, and 1/6°, eddy-permitting, global ocean circulation model. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional variations in integrated primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, deeper spring mixed layer depths in the eddy-permitting model result in increased light limitation during the spring bloom. Counter-intuitively, this does not drive a decrease in phytoplankton biomass, but is reflected in decreased primary production and zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity.

scholarly journals Biogeochemical versus ecological consequences of modeled ocean physics

2017 ◽  
Vol 14 (11) ◽  
pp. 2877-2889 ◽  
Author(s):  
Sophie Clayton ◽  
Stephanie Dutkiewicz ◽  
Oliver Jahn ◽  
Christopher Hill ◽  
Patrick Heimbach ◽  
...  
Keyword(s):  
Primary Production ◽  
Ocean Circulation ◽  
Mixed Layer ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Resource Competition ◽  
Nutrient Supply ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Competition Theory

Abstract. We present a systematic study of the differences generated by coupling the same ecological–biogeochemical model to a 1°, coarse-resolution, and 1∕6°, eddy-permitting, global ocean circulation model to (a) biogeochemistry (e.g., primary production) and (b) phytoplankton community structure. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional and seasonal variations in primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths (MLDs) are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, differences in winter mixed layer depths, the timing of the onset of the spring bloom and vertical nutrient supply result in lower primary production in the eddy-permitting model. Counterintuitively, this does not drive a decrease in phytoplankton biomass but results in lower zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity. The use of frameworks, such as resource competition theory, provides a tractable way to explore the differences and similarities that occur. As this model has many similarities to other widely used biogeochemical models that also resolve multiple phytoplankton phenotypes, this study provides important insights into how the results of running these models under different physical conditions might be more easily understood.

scholarly journals Seasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model study

2018 ◽  
Vol 15 (11) ◽  
pp. 3561-3576 ◽  
Author(s):  
Fabian A. Gomez ◽  
Sang-Ki Lee ◽  
Yanyun Liu ◽  
Frank J. Hernandez Jr. ◽  
Frank E. Muller-Karger ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Primary Production ◽  
Phytoplankton Biomass ◽  
Mississippi Delta ◽  
Three Dimensional ◽  
Rate Of Change ◽  
Integrated Analysis ◽  
Biogeochemical Model ◽  
Seasonal Patterns ◽  
Biogeochemical Models

Abstract. Biogeochemical models that simulate realistic lower-trophic-level dynamics, including the representation of main phytoplankton and zooplankton functional groups, are valuable tools for improving our understanding of natural and anthropogenic disturbances in marine ecosystems. Previous three-dimensional biogeochemical modeling studies in the northern and deep Gulf of Mexico (GoM) have used only one phytoplankton and one zooplankton type. To advance our modeling capability of the GoM ecosystem and to investigate the dominant spatial and seasonal patterns of phytoplankton biomass, we configured a 13-component biogeochemical model that explicitly represents nanophytoplankton, diatoms, micro-, and mesozooplankton. Our model outputs compare reasonably well with observed patterns in chlorophyll, primary production, and nutrients over the Louisiana–Texas shelf and deep GoM region. Our model suggests silica limitation of diatom growth in the deep GoM during winter and near the Mississippi delta during spring. Model nanophytoplankton growth is weakly nutrient limited in the Mississippi delta year-round and strongly nutrient limited in the deep GoM during summer. Our examination of primary production and net phytoplankton growth from the model indicates that the biomass losses, mainly due to zooplankton grazing, play an important role in modulating the simulated seasonal biomass patterns of nanophytoplankton and diatoms. Our analysis further shows that the dominant physical process influencing the local rate of change of model phytoplankton is horizontal advection in the northern shelf and vertical mixing in the deep GoM. This study highlights the need for an integrated analysis of biologically and physically driven biomass fluxes to better understand phytoplankton biomass phenologies in the GoM.

scholarly journals Evolution of primary production and its drivers on the Lebanese coast between 1986 and 2013

2020 ◽  
Vol 20 (4) ◽  
pp. 207-217
Author(s):  
Ali Fadel ◽  
Lama Salameh ◽  
Malak Kanj ◽  
Ahmad Kobaissi
Keyword(s):  
Primary Production ◽  
Phytoplankton Community ◽  
Controlling Factors ◽  
Sea Surface ◽  
Biogeochemical Model ◽  
Average Temperature ◽  
Biogeochemical Models ◽  
Increasing Trend ◽  
Production Dynamics ◽  
Lebanese Coast

AbstractPhysical-biogeochemical models help us to understand the dynamics and the controlling factors of primary production. In this study, the outputs of a validated hydrodynamic and biogeochemical model were used to elucidate the primary production dynamics between 1992 and 2012 for three studied sites on the Lebanese coast: Naqoura, Beirut, and Tripoli. The results showed that primary production presents a homogeneous spatial distribution along the Lebanese coastline. The phytoplankton community has a low optimal temperature. The thermocline develops in March, with maximum stratification in August and fades in October. Chlorophyll, dissolved oxygen and salinity were positively correlated throughout the water column. A significant increasing trend of sea surface temperature was found on the Lebanese coast over 27 years, between 1986 and 2013. Annual averages increased from 22°C in 1986 to 23.1°C in 2013 with the highest recorded average temperature of 23.7 °C in 2010.

scholarly journals Effects of nitrogen enrichment on zooplankton biomass and N:P recycling ratios across a DOC gradient in northern-latitude lakes

Hydrobiologia ◽  
2021 ◽  
Author(s):  
A.-K. Bergström ◽  
A. Deininger ◽  
A. Jonsson ◽  
J. Karlsson ◽  
T. Vrede
Keyword(s):  
Community Composition ◽  
Resource Use ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
N Fertilization ◽  
Zooplankton Biomass ◽  
Nitrogen Enrichment ◽  
C:N:P Stoichiometry ◽  
Food Quantity ◽  
N Enrichment

AbstractWe used data from whole-lake studies to assess how changes in food quantity (phytoplankton biomass) and quality (phytoplankton community composition, seston C:P and N:P) with N fertilization affect zooplankton biomass, community composition and C:N:P stoichiometry, and their N:P recycling ratio along a gradient in lake DOC concentrations. We found that despite major differences in phytoplankton biomass with DOC (unimodal distributions, especially with N fertilization), no major differences in zooplankton biomass were detectable. Instead, phytoplankton to zooplankton biomass ratios were high, especially at intermediate DOC and after N fertilization, implying low trophic transfer efficiencies. An explanation for the observed low phytoplankton resource use, and biomass responses in zooplankton, was dominance of colony forming chlorophytes of reduced edibility at intermediate lake DOC, combined with reduced phytoplankton mineral quality (enhanced seston N:P) with N fertilization. N fertilization, however, increased zooplankton N:P recycling ratios, with largest impact at low DOC where phytoplankton benefitted from light sufficiently to cause enhanced seston N:P. Our results suggest that although N enrichment and increased phytoplankton biomass do not necessarily increase zooplankton biomass, bottom-up effects may still impact zooplankton and their N:P recycling ratio through promotion of phytoplankton species of low edibility and altered mineral quality.

Using new observations and Machine Learning to improve organic sinking processes in the PlankTOM global ocean biogeochemical model 

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Lionel Guidi ◽  
Jean-Olivier Irisson
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Deep Ocean ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Carbon Export ◽  
Mixing Depth ◽  
Chl A ◽  
Biogeochemical Models

<p>A lot of effort has been put in the representation of surface ecosystem processes in global carbon cycle models, in particular through the grouping of organisms into Plankton Functional Types (PFTs) which have specific influences on the carbon cycle. In contrast, the transfer of ecosystem dynamics into carbon export to the deep ocean has received much less attention, so that changes in the representation of the PFTs do not necessarily translate into changes in sinking of particulate matter. Models constrain the air-sea CO<sub>2</sub> flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO<sub>2</sub> emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO<sub>2 </sub>can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO<sub>2</sub> fluxes, and on the amount of CO<sub>2</sub> emissions that remain in the atmosphere.</p><p>In this work we focus on the representation of organic matter sinking in global biogeochemical models, using the PlankTOM model in its latest version representing 12 PFTs. We develop and test a methodology that will enable the systematic use of new observations to constrain sinking processes in the model. The approach is based on a Neural Network (NN) and is applied to the PlankTOM model output to test its ability to reconstruction small and large particulate organic carbon with a limited number of observations. We test the information content of geographical variables (location, depth, time of year), physical conditions (temperature, mixing depth, nutrients), and ecosystem information (CHL a, PFTs). These predictors are used in the NN to test their influence on the model-generation of organic particles and the robustness of the results. We show preliminary results using the NN approach with real plankton and particle size distribution observations from the Underwater Vision Profiler (UVP) and plankton diversity data from Tara Oceans expeditions and discuss limitations.</p>

scholarly journals Large deep-sea zooplankton biomass mirrors primary production in the global ocean

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
S. Hernández-León ◽  
R. Koppelmann ◽  
E. Fraile-Nuez ◽  
A. Bode ◽  
C. Mompeán ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Primary Production ◽  
Deep Sea ◽  
Large Scale ◽  
Net Primary Production ◽  
Deep Ocean ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Global Coupling ◽  
Do So

AbstractThe biological pump transports organic carbon produced by photosynthesis to the meso- and bathypelagic zones, the latter removing carbon from exchanging with the atmosphere over centennial time scales. Organisms living in both zones are supported by a passive flux of particles, and carbon transported to the deep-sea through vertical zooplankton migrations. Here we report globally-coherent positive relationships between zooplankton biomass in the epi-, meso-, and bathypelagic layers and average net primary production (NPP). We do so based on a global assessment of available deep-sea zooplankton biomass data and large-scale estimates of average NPP. The relationships obtained imply that increased NPP leads to enhanced transference of organic carbon to the deep ocean. Estimated remineralization from respiration rates by deep-sea zooplankton requires a minimum supply of 0.44 Pg C y−1 transported into the bathypelagic ocean, comparable to the passive carbon sequestration. We suggest that the global coupling between NPP and bathypelagic zooplankton biomass must be also supported by an active transport mechanism associated to vertical zooplankton migration.

scholarly journals Skill assessment of the PELAGOS global ocean biogeochemistry model over the period 1980–2000

2009 ◽  
Vol 6 (11) ◽  
pp. 2333-2353 ◽  
Author(s):  
M. Vichi ◽  
S. Masina
Keyword(s):  
Organic Carbon ◽  
Mixed Layer ◽  
General Circulation ◽  
Net Primary Production ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Data Set ◽  
Surface Ocean ◽  
Ocean Biogeochemistry

Abstract. Global Ocean Biogeochemistry General Circulation Models are useful tools to study biogeochemical processes at global and large scales under current climate and future scenario conditions. The credibility of future estimates is however dependent on the model skill in capturing the observed multi-annual variability of firstly the mean bulk biogeochemical properties, and secondly the rates at which organic matter is processed within the food web. For this double purpose, the results of a multi-annual simulation of the global ocean biogeochemical model PELAGOS have been objectively compared with multi-variate observations from the last 20 years of the 20th century, both considering bulk variables and carbon production/consumption rates. Simulated net primary production (NPP) is comparable with satellite-derived estimates at the global scale and when compared with an independent data-set of in situ observations in the equatorial Pacific. The usage of objective skill indicators allowed us to demonstrate the importance of comparing like with like when considering carbon transformation processes. NPP scores improve substantially when in situ data are compared with modeled NPP which takes into account the excretion of freshly-produced dissolved organic carbon (DOC). It is thus recommended that DOC measurements be performed during in situ NPP measurements to quantify the actual production of organic carbon in the surface ocean. The chlorophyll bias in the Southern Ocean that affects this model as well as several others is linked to the inadequate representation of the mixed layer seasonal cycle in the region. A sensitivity experiment confirms that the artificial increase of mixed layer depths towards the observed values substantially reduces the bias. Our assessment results qualify the model for studies of carbon transformation in the surface ocean and metabolic balances. Within the limits of the model assumption and known biases, PELAGOS indicates a net heterotrophic balance especially in the more oligotrophic regions of the Atlantic during the boreal winter period. However, at the annual time scale and over the global ocean, the model suggests that the surface ocean is close to a weakly positive autotrophic balance in accordance with recent experimental findings and geochemical considerations.

scholarly journals Vertical distribution of chlorophyll <I>a</I> concentration and phytoplankton community composition from in situ fluorescence profiles: a first database for the global ocean

2015 ◽  
Vol 7 (2) ◽  
pp. 261-273 ◽  
Author(s):  
R. Sauzède ◽  
H. Lavigne ◽  
H. Claustre ◽  
J. Uitz ◽  
C. Schmechtig ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Community Composition ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Environmental Data ◽  
Global Ocean ◽  
Control Procedure ◽  
Chlorophyll A Concentration ◽  
Phytoplankton Community Composition

Abstract. In vivo chlorophyll a fluorescence is a proxy of chlorophyll a concentration, and is one of the most frequently measured biogeochemical properties in the ocean. Thousands of profiles are available from historical databases and the integration of fluorescence sensors to autonomous platforms has led to a significant increase of chlorophyll fluorescence profile acquisition. To our knowledge, this important source of environmental data has not yet been included in global analyses. A total of 268 127 chlorophyll fluorescence profiles from several databases as well as published and unpublished individual sources were compiled. Following a robust quality control procedure detailed in the present paper, about 49 000 chlorophyll fluorescence profiles were converted into phytoplankton biomass (i.e., chlorophyll a concentration) and size-based community composition (i.e., microphytoplankton, nanophytoplankton and picophytoplankton), using a method specifically developed to harmonize fluorescence profiles from diverse sources. The data span over 5 decades from 1958 to 2015, including observations from all major oceanic basins and all seasons, and depths ranging from the surface to a median maximum sampling depth of around 700 m. Global maps of chlorophyll a concentration and phytoplankton community composition are presented here for the first time. Monthly climatologies were computed for three of Longhurst's ecological provinces in order to exemplify the potential use of the data product. Original data sets (raw fluorescence profiles) as well as calibrated profiles of phytoplankton biomass and community composition are available on open access at PANGAEA, Data Publisher for Earth and Environmental Science. Raw fluorescence profiles: http://doi.pangaea.de/10.1594/PANGAEA.844212 and Phytoplankton biomass and community composition: http://doi.pangaea.de/10.1594/PANGAEA.844485

scholarly journals Simulation of anthropogenic CO<sub>2</sub> uptake in the CCSM3.1 ocean circulation-biogeochemical model: comparison with data-based estimates

2011 ◽  
Vol 8 (6) ◽  
pp. 10895-10933
Author(s):  
S. Wang ◽  
J. K. Moore ◽  
F. W. Primeau ◽  
S. Khatiwala
Keyword(s):  
Ocean Circulation ◽  
Model Comparison ◽  
Industrial Revolution ◽  
Large Fraction ◽  
Detailed Comparison ◽  
Global Ocean ◽  
Inversion Method ◽  
Biogeochemical Model ◽  
Climate System Model ◽  
Anthropogenic Carbon

Abstract. The global ocean has taken up a large fraction of the CO2 released by human activities since the industrial revolution. Quantifying the oceanic anthropogenic carbon (Cant) inventory and its variability is important for predicting the future global carbon cycle. The detailed comparison of data-based and model-based estimates is essential for the validation and continued improvement of our prediction capabilities. So far, three global estimates of oceanic Cant inventory that are "data-based" and independent of global ocean circulation models have been produced: one based on the ΔC* method, and two are based on reconstructions of the Green function for the surface-to-interior transport, the TTD method and the maximum entropy inversion method (KPH). The KPH method, in particular, is capable of reconstructing the history of Cant inventory through the industrial era. In the present study we use forward model simulations of the Community Climate System Model (CCSM3.1) to estimate the Cant inventory and compare the results with the data-based estimates. We also use the simulations to test several assumptions of the KPH method, including the assumption of constant climate and circulation, which is common to all the data-based estimates. Though the integrated estimates of global Cant inventories are consistent with each other, the regional estimates show discrepancies up to 50 %. The CCSM3 model underestimates the total Cant inventory, in part due to weak mixing and ventilation in the North Atlantic and Southern Ocean. Analyses of different simulation results suggest that key assumptions about ocean circulation and air-sea disequilibrium in the KPH method are generally valid on the global scale, but may introduce significant errors in Cant estimates on regional scales. The KPH method should also be used with caution when predicting future oceanic anthropogenic carbon uptake.

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