scholarly journals Should we account for mesozooplankton reproduction and ontogenetic growth in biogeochemical modeling?

2021 ◽  
Author(s):  
Corentin Clerc ◽  
Olivier Aumont ◽  
Laurent Bopp
Keyword(s):  
Temporal Dynamics ◽  
Fecal Pellet ◽  
Ingestion Rate ◽  
Temporal Variations ◽  
Trophic Levels ◽  
Nutrient Concentrations ◽  
Biogeochemical Model ◽  
3 Dimensional ◽  
Mesozooplankton Biomass ◽  
Biogeochemical Models

AbstractMesozooplankton play a key role in marine ecosystems as they modulate the transfer of energy from phytoplankton to large marine organisms. In addition, they directly influence the oceanic cycles of carbon and nutrients through vertical migrations, fecal pellet production, respiration, and excretion. Mesozooplankton are mainly made up of metazoans, which undergo important size changes during their life cycle, resulting in significant variations in metabolic rates. However, most marine biogeochemical models represent mesozooplankton as protists-like organisms. Here, we study the potential caveats of this simplistic representation by using a chemostat-like zero-dimensional model with four different Nutrient-Phytoplankton-Zooplankton configurations in which the description of mesozooplankton ranges from protist-type organisms to using a size-based formulation including explicit reproduction and ontogenetic growth. We show that the size-based formulation strongly impacts mesozooplankton. First, it generates a delay of a few months in the response to an increase in food availability. Second, the increase in mesozooplankton biomass displays much larger temporal variations, in the form of successive cohorts, because of the dependency of the ingestion rate to body size. However, the size-based formulation does not affect smaller plankton or nutrient concentrations. A proper assessment of these top-down effects would require implementing our size-resolved approach in a 3-dimensional biogeochemical model. Furthermore, the bottom-up effects on higher trophic levels resulting from the significant changes in the temporal dynamics of mesozooplankton could be estimated in an end-to-end model coupling low and high trophic levels.

Impacts of riverine terrestrial organic matter on the lower trophic levels of an Arctic shelf ecosystem

2021 ◽  
Author(s):  
Michael Bedington ◽  
Ricardo Torres ◽  
Luca Polimene ◽  
Phillip Wallhead ◽  
Bennett Juhls ◽  
...  
Keyword(s):  
Organic Matter ◽  
Future Climate ◽  
Trophic Levels ◽  
The Arctic ◽  
Nutrient Concentrations ◽  
Climate Scenarios ◽  
Arctic Ecosystems ◽  
Terrestrial Organic Matter ◽  
Biogeochemical Models ◽  
Near Shore

<p>The Arctic ocean receives 11% of the entire global river discharge via several great Arctic rivers that drain vast catchments underlain with carbon-rich permafrost. Arctic marginal shelf seas are therefore heavily influenced by terrestrial dissolved organic matter (tDOM) supply, influencing coastal biogeochemical processes and food-webs, as well as physio-chemical properties (e.g. stratification or nutrient concentrations).</p><p>Whilst carbon and associated macronutrients supplied by tDOM may enhance the nutrient and carbon substrates for lower trophic levels (phytoplankton/zooplankton), promoting increased local and regional productivity, it can also have opposing effects through a series of indirect processes (e.g. increased light absorption limiting light penetration through the water column). Understanding the relative importance and timing of these processes, and how they vary spatially, is necessary to identify how land-ocean interfaces currently operate.</p><p>Future climate scenarios indicate increased quantities of riverine tDOM delivered to the near-shore, with increased freshwater runoff and greater terrestrial permafrost thaw and erosion. This is likely to be exacerbated by the disappearance of seasonal sea ice cover and increased coastal erosion rates. We can therefore expect changes in planktonic phenology and productivity, with concomitant changes in bacterial and higher trophic level success. Understanding how these factors interact and may change under future climate scenarios is therefore critical to predict the future impact on shelf sea Arctic ecosystems and the ecosystem services they provide.</p><p>In the Changing Arctic Carbon cycle in the cOastal Ocean Near-shore (CACOON) project (UK-Germany collaboration) we are using coupled hydrodynamic-biogeochemical models in the extensive shallow shelf of the Laptev sea to explore the relationship between these factors. The ecosystem model ERSEM has been adapted to explicitly include a tDOM component. This coupled model system allows us to investigate both the role of present day tDOM in an Arctic coastal ecosystem and to project the potential impacts of increased tDOM input in future.</p>

scholarly journals Seasonal Patterns in Phytoplankton Biomass across the Northern and Deep Gulf of Mexico: A Numerical Model Study

2017 ◽  
Author(s):  
Fabian A. Gomez ◽  
Sang-Ki Lee ◽  
Yanyun Liu ◽  
Frank J. Hernandez Jr. ◽  
Frank E. Muller-Karger ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Phytoplankton Biomass ◽  
Three Dimensional ◽  
Trophic Levels ◽  
Biogeochemical Model ◽  
Seasonal Patterns ◽  
Biogeochemical Models ◽  
Model Study ◽  
Numerical Model Study

Abstract. Biogeochemical models that simulate realistic lower trophic levels dynamics, including the representation of main phytoplankton and zooplankton functional groups, are valuable tools for our understanding of natural and anthropogenic disturbances in marine ecosystems. However, 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 phytoplankton biomass, we configured a 14-component biogeochemical model that explicitly represents nanophytoplankton, diatoms, micro-, and mesozooplankton. Our model outputs compare well with satellite and in situ observations, reproducing dominant seasonal patterns in chlorophyll and primary production. The model results show that diatom growth is strongly silica limited (> 95 %) in the deep GoM, and both nitrogen and silica limited (30–70 %) in the northern shelf. Nanophytoplankton growth is weakly nutrient limited in the Mississippi delta year-round (

scholarly journals Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model

2020 ◽  
Vol 17 (13) ◽  
pp. 3385-3407 ◽  
Author(s):  
Taylor A. Shropshire ◽  
Steven L. Morey ◽  
Eric P. Chassignet ◽  
Alexandra Bozec ◽  
Victoria J. Coles ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Secondary Production ◽  
Food Source ◽  
Net Primary Production ◽  
Zooplankton Biomass ◽  
Spatiotemporal Variability ◽  
Biogeochemical Model ◽  
Feeding Mode ◽  
Mesozooplankton Biomass ◽  
Biogeochemical Models

Abstract. Zooplankton play an important role in global biogeochemistry, and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton standing stocks cannot be estimated using remote sensing techniques. Hence, coupled physical–biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton biomass estimates from PBMs has been a major challenge due to sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993 to 2012 and validate the model against an extensive combination of biomass and rate measurements. Spatial variability in a multidecadal database of mesozooplankton biomass for the northern GoM is well resolved by the model with a statistically significant (p < 0.01) correlation of 0.90. Mesozooplankton secondary production for the region averaged 66±8×109 kg C yr−1, equivalent to ∼10 % of net primary production (NPP), and ranged from 51 to 82×109 kg C yr−1, with higher secondary production inside cyclonic eddies and substantially reduced secondary production in anticyclonic eddies. Model results from the shelf regions suggest that herbivory is the dominant feeding mode for small mesozooplankton (< 1 mm), whereas larger mesozooplankton are primarily carnivorous. In open-ocean oligotrophic waters, however, both mesozooplankton groups show proportionally greater reliance on heterotrophic protists as a food source. This highlights an important role of microbial and protistan food webs in sustaining mesozooplankton biomass in the GoM, which serves as the primary food source for early life stages of many commercially important fish species, including tuna.

scholarly journals Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical-biogeochemical model

2019 ◽  
Author(s):  
Taylor A. Shropshire ◽  
Steven L. Morey ◽  
Eric P. Chassignet ◽  
Alexandra Bozec ◽  
Victoria J. Coles ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Net Primary Production ◽  
Spatiotemporal Variability ◽  
Biogeochemical Model ◽  
Zooplankton Abundance ◽  
Mesozooplankton Biomass ◽  
Biogeochemical Models ◽  
Zooplankton Dynamics ◽  
Remote Sensing Techniques ◽  
Specific Growth Rates

Abstract. Zooplankton play an important role in global biogeochemistry and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton abundances cannot be estimated using remote sensing techniques. Hence, coupled physical-biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton abundance estimates from PBMs has been a major challenge as a result of sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993–2012 and validate the model against an extensive combination of in situ biomass and rate measurements including total mesozooplankton biomass, size-fractionated mesozooplankton biomass and grazing rates, microzooplankton specific grazing rates, surface chlorophyll, deep chlorophyll maximum depth, phytoplankton specific growth rates, and net primary production. Spatial variability in mesozooplankton biomass climatology observed in a multi-decadal database for the northern GoM is well resolved by the model with a statistically significant (p 

scholarly journals Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kuang-Yu Chang ◽  
William J. Riley ◽  
Sara H. Knox ◽  
Robert B. Jackson ◽  
Gavin McNicol ◽  
...  
Keyword(s):  
Temperature Sensitivity ◽  
Spatial Scales ◽  
Biogeochemical Model ◽  
Spatial And Temporal Variability ◽  
Biogeochemical Models ◽  
Model Parameterization ◽  
Machine Learning Model ◽  
Meta Analyses ◽  
The Relationship ◽  
Global Carbon

AbstractWetland methane (CH4) emissions ($${F}_{{{CH}}_{4}}$$ F C H 4 ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$ F C H 4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$ F C H 4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$ F C H 4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$ F C H 4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.

scholarly journals Generalized receptor law governs phototaxis in the phytoplanktonEuglena gracilis

2015 ◽  
Vol 112 (22) ◽  
pp. 7045-7050 ◽  
Author(s):  
Andrea Giometto ◽  
Florian Altermatt ◽  
Amos Maritan ◽  
Roman Stocker ◽  
Andrea Rinaldo
Keyword(s):  
Algal Blooms ◽  
Nonlinear Response ◽  
Temporal Dynamics ◽  
Freshwater Ecosystems ◽  
Trophic Levels ◽  
Light Fields ◽  
Light Sources ◽  
Mathematical Framework ◽  
Heterogeneous Environments ◽  
Light Conditions

Phototaxis, the process through which motile organisms direct their swimming toward or away from light, is implicated in key ecological phenomena (including algal blooms and diel vertical migration) that shape the distribution, diversity, and productivity of phytoplankton and thus energy transfer to higher trophic levels in aquatic ecosystems. Phototaxis also finds important applications in biofuel reactors and microbiopropellers and is argued to serve as a benchmark for the study of biological invasions in heterogeneous environments owing to the ease of generating stochastic light fields. Despite its ecological and technological relevance, an experimentally tested, general theoretical model of phototaxis seems unavailable to date. Here, we present accurate measurements of the behavior of the algaEuglena graciliswhen exposed to controlled light fields. Analysis ofE. gracilis’ phototactic accumulation dynamics over a broad range of light intensities proves that the classic Keller–Segel mathematical framework for taxis provides an accurate description of both positive and negative phototaxis only when phototactic sensitivity is modeled by a generalized “receptor law,” a specific nonlinear response function to light intensity that drives algae toward beneficial light conditions and away from harmful ones. The proposed phototactic model captures the temporal dynamics of both cells’ accumulation toward light sources and their dispersion upon light cessation. The model could thus be of use in integrating models of vertical phytoplankton migrations in marine and freshwater ecosystems, and in the design of bioreactors.

scholarly journals Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

2012 ◽  
Vol 9 (7) ◽  
pp. 2793-2819 ◽  
Author(s):  
L. Meng ◽  
P. G. M. Hess ◽  
N. M. Mahowald ◽  
J. B. Yavitt ◽  
W. J. Riley ◽  
...  
Keyword(s):  
Soil Ph ◽  
High Latitude ◽  
Large Range ◽  
Rice Paddy ◽  
Temporal Variations ◽  
Methane Emissions ◽  
Biogeochemical Model ◽  
Atmospheric Methane ◽  
Rice Paddies ◽  
Community Land Model

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources are still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model, because there are large differences between simulated fractional inundation and satellite observations, and thus we do not use CLM4-simulated hydrology to predict inundated areas. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid-cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1 (including the soil sink) and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78% of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. However, sensitivity studies show a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions (excluding emissions from rice paddies). The large range is sensitive to (1) the amount of methane transported through aerenchyma, (2) soil pH (±100 Tg CH4 yr−1), and (3) redox inhibition (±45 Tg CH4 yr−1). Results are sensitive to biases in the CLMCN and to errors in the satellite inundation fraction. In particular, the high latitude methane emission estimate may be biased low due to both underestimates in the high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4.

scholarly journals Interactive impacts of meteorological and hydrological conditions on the physical and biogeochemical structure of a coastal system

2020 ◽  
Vol 17 (20) ◽  
pp. 5097-5127 ◽  
Author(s):  
Onur Kerimoglu ◽  
Yoana G. Voynova ◽  
Fatemeh Chegini ◽  
Holger Brix ◽  
Ulrich Callies ◽  
...  
Keyword(s):  
Central Region ◽  
German Bight ◽  
Outer Region ◽  
Coupled Model ◽  
Oxygen Depletion ◽  
Flood Event ◽  
Nutrient Concentrations ◽  
Biogeochemical Model ◽  
Low Oxygen ◽  
Coastal System

Abstract. The German Bight was exposed to record high riverine discharges in June 2013, as a result of flooding of the Elbe and Weser rivers. Several anomalous observations suggested that the hydrodynamical and biogeochemical states of the system were impacted by this event. In this study, we developed a biogeochemical model and coupled it with a previously introduced high-resolution hydrodynamical model of the southern North Sea in order to better characterize these impacts and gain insight into the underlying processes. Performance of the model was assessed using an extensive set of in situ measurements for the period 2011–2014. We first improved the realism of the hydrodynamic model with regard to the representation of cross-shore gradients, mainly through inclusion of flow-dependent horizontal mixing. Among other characteristic features of the system, the coupled model system can reproduce the low salinities, high nutrient concentrations and low oxygen concentrations in the bottom layers observed within the German Bight following the flood event. Through a scenario analysis, we examined the sensitivity of the patterns observed during July 2013 to the hydrological and meteorological forcing in isolation. Within the region of freshwater influence (ROFI) of the Elbe–Weser rivers, the flood event clearly dominated the changes in salinity and nutrient concentrations, as expected. However, our findings point to the relevance of the peculiarities in the meteorological conditions in 2013 as well: a combination of low wind speeds, warm air temperatures and cold bottom-water temperatures resulted in a strong thermal stratification in the outer regions and limited vertical nutrient transport to the surface layers. Within the central region, the thermal and haline dynamics interactively resulted in an intense density stratification. This intense stratification, in turn, led to enhanced primary production within the central region enriched by nutrients due to the flood but led to reduction within the nutrient-limited outer region, and it caused a widespread oxygen depletion in bottom waters. Our results further point to the enhancement of the current velocities at the surface as a result of haline stratification and to intensification of the thermohaline estuarine-like circulation in the Wadden Sea, both driven by the flood event.

scholarly journals Spatial and Temporal Variations of Nitrogen and Phosphorus in Surface Water and Groundwater of Mudong River Watershed in Huixian Karst Wetland, Southwest China

2021 ◽  
Vol 13 (19) ◽  
pp. 10740
Author(s):  
Linyan Pan ◽  
Junfeng Dai ◽  
Zhiqiang Wu ◽  
Liangliang Huang ◽  
Zupeng Wan ◽  
...  
Keyword(s):  
Surface Water ◽  
Temporal Dynamics ◽  
Flow Direction ◽  
Influencing Factor ◽  
Shallow Groundwater ◽  
Temporal Variations ◽  
Field Investigation ◽  
Spatial And Temporal Variation ◽  
Nitrogen And Phosphorus ◽  
River Watershed

When considering the factors affecting the spatial and temporal variation of nitrogen and phosphorus in karst watersheds, the unique karst hydrogeology as an internal influencing factor cannot be ignored, as well as natural factors such as meteorological hydrology and external factors such as human activities. A watershed-scale field investigation was completed to statistically analyze spatial and temporal dynamics of nitrogen and phosphorus through the regular monitoring and collection of surface water and shallow groundwater in the agricultural-dominated Mudong River watershed in the Huixian Karst Wetland over one year (May 2020 to April 2021). Our research found that non-point source pollution of nitrogen (84.5% of 239 samples TN > 1.0 mg/L) was more serious than phosphorus (7.5% of 239 samples TP > 0.2 mg/L) in the study area, and shallow groundwater nitrogen pollution (98.3% of 118 samples TN > 1.0 mg/L) was more serious than surface water (68.6% of 121 samples TN > 1.0 mg/L). In the three regions with different hydrodynamic features, the TN concentration was higher and dominated by NO3−-N in the river in the northern recharge area, while the concentrations of TN and TP were the highest in shallow groundwater wells in the central wetland core area and increased along the surface water flow direction in the western discharge area. This research will help improve the knowledge about the influence of karst hydrodynamic features on the spatial patterns of nitrogen and phosphorus in water, paying attention to the quality protection and security of water in karst areas with a fragile water ecological environment.

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

&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt; flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO&lt;sub&gt;2&lt;/sub&gt; emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO&lt;sub&gt;2 &lt;/sub&gt;can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes, and on the amount of CO&lt;sub&gt;2&lt;/sub&gt; emissions that remain in the atmosphere.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

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