scholarly journals Zooplankton trophic dynamics drive carbon export efficiency

2021 ◽  
Author(s):  
Camila Serra-Pompei ◽  
Ben A. Ward ◽  
Jérôme Pinti ◽  
André W. Visser ◽  
Thomas Kiørboe ◽  
...  
Keyword(s):  
3D Model ◽  
Deep Ocean ◽  
Growth Efficiency ◽  
Size Spectrum ◽  
Particulate Carbon ◽  
Carbon Export ◽  
Detrital Particles ◽  
Planktonic Community ◽  
Clear Relation ◽  
Spectrum Model

AbstractThe flux of detrital particles produced by plankton is an important component of the biological carbon pump. We investigate how food web structure and organisms’ size regulate particulate carbon export efficiency (the fraction of primary production that is exported via detrital particles at a given depth). We use the Nutrient-Unicellular-Multicellular (NUM) mechanistic size-spectrum model of the planktonic community (unicellular pro-tists and copepods), embedded within a 3D model representation of the global ocean circulation. The ecosystem model generates emergent food webs and size distributions of all organisms and detrital particles. Model outputs are compared to field data. We find that strong predation by copepods increases export efficiency, while protist predation reduces it. We find no clear relation between primary production and export efficiency. Temperature indirectly drives carbon export efficiency by affecting the biomass of copepods. High temperatures, combined with nutrient limitation, result in low growth efficiency, smaller trophic transfer to higher trophic levels, and decreased carbon export efficiency. Even though copepods consume a large fraction of the detritus produced, they do not markedly attenuate the particle flux. Our simulations illustrate the complex relation between the planktonic food web and export efficiency, and highlights the central role of zooplankton and their size structure.Plain Language SummaryPlankton are small organisms that live in the ocean. Plankton remove CO2 from the atmosphere by doing photosynthesis and sinking to the deep ocean, where the CO2 is sequestered. Photosynthesis can be measured by satellites, and therefore, knowing the fraction of photosynthesis that sinks to the deep ocean could allow making more accurate predictions of the concentration of CO2 in the atmosphere. This fraction of photosynthesis that is exported is termed “carbon export efficiency”. However, the drivers that define this carbon export efficiency are not well understood. To explore these drivers, we used computer simulations that include many planktonic organisms in a 3D model of the oceans. The model generates a detailed representation of the body sizes of plankton and of particle sizes, which is one of the main features defining sinking rates of particles in nature. We find that export efficiency is high when large zooplankton consume large amounts of prey. Temperature decreases export efficiency by reducing how efficient large plankton grow. Finally, we do not find a clear relation between photosynthesis and export efficiency, which has been much discussed in the literature. This provides mechanistic explanations to previous field observations and generates new hypotheses to be tested.Key Points:We used a 3D size-spectrum model of the planktonic community to understand the drivers of particulate carbon export efficiencyWe find that high temperature decreases growth efficiency, trophic transfer efficiency and associated carbon export efficiency.Systems that are top-down controlled by zooplankton can have high export efficiencies depending on the size of the dominant zooplankton.

Shifts in plankton size spectra modulate growth and coexistence of anchovy and sardine in upwelling systems

2016 ◽  
Vol 73 (4) ◽  
pp. 611-621 ◽  
Author(s):  
T. Mariella Canales ◽  
Richard Law ◽  
Julia L. Blanchard
Keyword(s):  
Size Structure ◽  
Prey Availability ◽  
Empirical Work ◽  
Size Composition ◽  
Size Spectrum ◽  
Small Particles ◽  
Size Spectra ◽  
Factors Influencing ◽  
Spectrum Model ◽  
Model Scenarios

Fluctuations in the abundance of anchovy (Engraulis spp.) and sardine (Sardinops sagax) are widespread in marine ecosystems, but the causes still remain uncertain. Differences between the planktonic prey availability, selectivity, and predation between anchovy and sardine have been suggested as factors influencing their dynamics. Using a dynamical multispecies size-spectrum model, we explore the consequences of changes in plankton size composition, together with intraguild predation and cannibalism, on the coexistence of these species. The shift towards smaller plankton has led to a reduction in the growth rate of both species. The effect was more deleterious on anchovy growth because it is unable to filter small particles. In model scenarios that included the effects of cannibalism and predation, anchovy typically collapsed under conditions favouring smaller sized plankton. The two species coexisted under conditions of larger sized plankton, although strong predation in conjunction with weak cannibalism led to the loss of sardine. The model provides new testable predictions for the consequences of plankton size structure on anchovy and sardine fluctuations. Further empirical work is needed to test these predictions in the context of climate change.

scholarly journals Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float

2010 ◽  
Vol 7 (6) ◽  
pp. 8477-8520 ◽  
Author(s):  
W. Bagniewski ◽  
K. Fennel ◽  
M. J. Perry ◽  
E. A. D'Asaro
Keyword(s):  
North Atlantic ◽  
Spring Bloom ◽  
Deep Ocean ◽  
Complex Model ◽  
Optical Observations ◽  
Model Parameters ◽  
Carbon Export ◽  
The North ◽  
Chemical Measurements ◽  
The North Atlantic

Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15%. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is much larger for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has slightly better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

A Continuous Size Spectrum for Particulate Matter in the Sea

1967 ◽  
Vol 24 (5) ◽  
pp. 909-915 ◽  
Author(s):  
R. W. Sheldon ◽  
T. R. Parsons
Keyword(s):  
Particle Diameter ◽  
Particulate Material ◽  
Size Spectrum ◽  
Particulate Carbon ◽  
Particle Volume ◽  
Carbon And Nitrogen ◽  
Total Particle ◽  
Volume Measurements ◽  
Good Agreement

The size spectrum of particulate material in seawater can easily be expressed as total particle volume versus the logarithm of particle diameter. This appears to be the most informative way to present the data and it is also aptly suited to the classical divisions of nanno-, micro-, and macroplankton.A realistic measure of the volume of irregularly shaped particles such as phytoplankton chains could be made with a Coulter Counter. Particle volume measurements were in good agreement with estimates based on microscopic determination of particle diameter. There were also highly significant correlations between total particle volume, as indicated by the counter, and particulate carbon and nitrogen.

scholarly journals Sinking particles promote vertical connectivity in the ocean microbiome

2018 ◽  
Vol 115 (29) ◽  
pp. E6799-E6807 ◽  
Author(s):  
Mireia Mestre ◽  
Clara Ruiz-González ◽  
Ramiro Logares ◽  
Carlos M. Duarte ◽  
Josep M. Gasol ◽  
...  
Keyword(s):  
Surface Waters ◽  
Deep Ocean ◽  
Rrna Gene ◽  
Carbon Export ◽  
Size Fractions ◽  
Sinking Particles ◽  
Prokaryotic Diversity ◽  
Compositional Variability ◽  
Organic Particles ◽  
Community Connectivity

The sinking of organic particles formed in the photic layer is a main vector of carbon export into the deep ocean. Although sinking particles are heavily colonized by microbes, so far it has not been explored whether this process plays a role in transferring prokaryotic diversity from surface to deep oceanic layers. Using Illumina sequencing of the 16S rRNA gene, we explore here the vertical connectivity of the ocean microbiome by characterizing marine prokaryotic communities associated with five different size fractions and examining their compositional variability from surface down to 4,000 m across eight stations sampled in the Atlantic, Pacific, and Indian Oceans during the Malaspina 2010 Expedition. Our results show that the most abundant prokaryotes in the deep ocean are also present in surface waters. This vertical community connectivity seems to occur predominantly through the largest particles because communities in the largest size fractions showed the highest taxonomic similarity throughout the water column, whereas free-living communities were more isolated vertically. Our results further suggest that particle colonization processes occurring in surface waters determine to some extent the composition and biogeography of bathypelagic communities. Overall, we postulate that sinking particles function as vectors that inoculate viable particle-attached surface microbes into the deep-sea realm, determining to a considerable extent the structure, functioning, and biogeography of deep ocean communities.

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 Balanced harvesting is the bioeconomic equilibrium of a size-structured Beverton-Holt model

2016 ◽  
Vol 74 (1) ◽  
pp. 112-120 ◽  
Author(s):  
Michael J. Plank
Keyword(s):  
Single Species ◽  
Size Spectrum ◽  
Ecosystem Structure ◽  
Fishing Mortality ◽  
Biomass Transfer ◽  
Body Sizes ◽  
Relative Production ◽  
Ecosystem Structure And Functioning ◽  
Classical Size ◽  
Spectrum Model

Balanced harvesting (BH) was introduced as an alternative strategy to size-at-entry fishing with the aim of maintaining ecosystem structure and functioning. BH has been criticized on a number of grounds, including that it would require an infeasible level of micromanagement and enforcement. Recent results from a size-spectrum model show that the distribution of fishing mortality across body sizes that emerges from the behaviour of a large number of fishing agents corresponds to BH in a single species. Size-spectrum models differ from classical size-structured models used in fisheries as they are based on a bookkeeping of biomass transfer from prey to predator rather than a von Bertalanffy growth model. Here we investigate a classical Beverton-Holt model coupled with the Gordon-Schaefer harvesting model extended to allow for differential fishing pressure at different body sizes. This models an open-access fishery in which individual fishing agents act to maximize their own economic return. We show that the equilibrium of the harvesting model produces an aggregate fishing mortality that is closely matched to the production at different body sizes, in other words BH of a single species. These results have significant implications because they show that the robustness of BH does not depend on arguments about the relative production levels of small versus large fish.

A functional size-spectrum model of the global marine ecosystem that resolves zooplankton composition

2020 ◽  
Vol 435 ◽  
pp. 109265
Author(s):  
Ryan F. Heneghan ◽  
Jason D. Everett ◽  
Patrick Sykes ◽  
Sonia D. Batten ◽  
Martin Edwards ◽  
...  
Keyword(s):  
Marine Ecosystem ◽  
Size Spectrum ◽  
Spectrum Model ◽  
Functional Size

scholarly journals Modeling the Dynamics of Multispecies Fisheries: A Case Study in the Coastal Water of North Yellow Sea, China

2020 ◽  
Vol 7 ◽  
Author(s):  
Jia Wo ◽  
Chongliang Zhang ◽  
Xindong Pan ◽  
Binduo Xu ◽  
Ying Xue ◽  
...  
Keyword(s):  
Model Validation ◽  
Fisheries Management ◽  
Yellow Sea ◽  
Sensitivity Analyses ◽  
Size Spectrum ◽  
Quality Of Data ◽  
Estimation Model ◽  
North Yellow Sea ◽  
Multispecies Fisheries ◽  
Spectrum Model

Ecosystem models have been developed for detecting community responses to fishing pressure and have been widely applied to predict the ecological effects of fisheries management. Key challenges of ecosystem modeling lie in the insufficient quantity and quality of data, which is unfortunately common in the marine ecosystems of many developing countries. In this study, we aim to model the dynamics of multispecies fisheries under data-limited circumstances, using a multispecies size-spectrum model (MSSM) implemented in the coastal ecosystem of North Yellow Sea, China. To make most of available data, we incorporated a range of data-limited methods for estimating the life-history parameters and conducted model validation according to empirical data. Additionally, sensitivity analyses were conducted to evaluate the impacts of input parameters on model predictions regarding the uncertainty of data and estimating methods. Our results showed that MSSM could provide reasonable predictions of community size spectra and appropriately reflect the community composition in the studied area, whereas the predictions of fisheries yields were biased for certain species. Errors in recruitment parameters were most influential on the prediction of species abundance, and errors in fishing efforts substantially affected community-level indicators. This study built a framework to integrate parameter estimation, model validation, and sensitivity analyses altogether, which could guide model development in similar mixed and data-limited fisheries and promote the use of size-spectrum model for ecosystem-based fisheries management.

scholarly journals Parameter uncertainty of a dynamic multispecies size spectrum model

2016 ◽  
Vol 73 (4) ◽  
pp. 589-597 ◽  
Author(s):  
Michael A. Spence ◽  
Paul G. Blackwell ◽  
Julia L. Blanchard
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Size Structure ◽  
Management Strategies ◽  
Optimization Methods ◽  
Series Data ◽  
Size Spectrum ◽  
Aquatic Communities ◽  
The North ◽  
Spectrum Model

Dynamic size spectrum models have been recognized as an effective way of describing how size-based interactions can give rise to the size structure of aquatic communities. They are intermediate-complexity ecological models that are solutions to partial differential equations driven by the size-dependent processes of predation, growth, mortality, and reproduction in a community of interacting species and sizes. To be useful for quantitative fisheries management these models need to be developed further in a formal statistical framework. Previous work has used time-averaged data to “calibrate” the model using optimization methods with the disadvantage of losing detailed time-series information. Using a published multispecies size spectrum model parameterized for the North Sea comprising 12 interacting fish species and a background resource, we fit the model to time-series data using a Bayesian framework for the first time. We capture the 1967–2010 period using annual estimates of fishing mortality rates as input to the model and time series of fisheries landings data to fit the model to output. We estimate 38 key parameters representing the carrying capacity of each species and background resource, as well as initial inputs of the dynamical system and errors on the model output. We then forecast the model forward to evaluate how uncertainty propagates through to population- and community-level indicators under alternative management strategies.

scholarly journals Assessing uncertainty of a multispecies size-spectrum model resulting from process and observation errors

2015 ◽  
Vol 72 (8) ◽  
pp. 2223-2233 ◽  
Author(s):  
Chongliang Zhang ◽  
Yong Chen ◽  
Yiping Ren
Keyword(s):  
Life History ◽  
Community Structure ◽  
Fisheries Management ◽  
Dynamic Models ◽  
Environmental Variability ◽  
Size Spectrum ◽  
Sampling Errors ◽  
Fishing Activity ◽  
Scale Parameters ◽  
Spectrum Model

AbstractEcosystem models, specifically multispecies dynamic models, have been increasingly used to project impacts of fishing activity on the trophodynamics of ecosystems to support ecosystem-based fisheries management. Uncertainty is unavoidable in modelling processes and needs to be recognized and properly quantified before models are utilized. Uncertainty was assessed in this study for a multispecies size-spectrum model that quantifies community structure and ecological characteristics. The uncertainty was assumed to result from errors in fish life-history and metabolic scale parameters, environmental variability, fishing variability, and sampling errors. Given the same level of imprecision, metabolic scale parameters had the dominant influence on the uncertainty of the size spectrum modelling results, followed by life-history parameters. Both types of errors led to “scenario uncertainty”, suggesting the possible existence of alternative states of community structure. Environmental variability, fishing variability, and observation errors resulted in “statistical uncertainty”, implying that such uncertainty can be described adequately in statistical terms. The results derived from such a simulation study can provide guidance for identifying research priorities to help narrow the gap in scientific knowledge and reduce the uncertainty in fisheries management.

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