A stochastic, Lagrangian model of sinking biogenic aggregates in the ocean (SLAMS 1.0): model formulation, validation and sensitivity

Jokulsdottir, T.; Archer, David

doi:10.5194/gmd-9-1455-2016

Cited by 44 publications

(33 citation statements)

References 119 publications

(124 reference statements)

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“…In particular, this distribution may depend on the structure of the ecosystem in the euphotic zone. Biochemical analysis of the surface particulate organic matter has shown that its composition varies both in time and space as a result of differences in the phytoplankton and zooplankton species and interactions (Tegelaar et al, 1989;Kiriakoulakis et al, 2001;Lee et al, 2004;Mayzaud et al, 2014). Thus, the lability distribution of POM is unlikely to be constant both in time and space.…”

Section: Spatial Variations Of Remineralisation Efficiencymentioning

confidence: 99%

“…With the notable exception of Sempéré et al (2000), the inhomogeneous reactivity of POC has not been explicitly taken into account in marine biogeochemical modelling studies; the vast majority of the models use a single uniform decay rate for the whole particulate organic pool. Very recently, Jokulsdottir and Archer (2016) have designed a very detailed Lagrangian model of POC which explicitly assumes that aggregates are composed of various compounds with different labilities, in a manner similar to our approach. Unfortunately, they have not explored in their study the impacts this varying lability has on the POC distribution and on the POC fluxes.…”

Section: Introductionmentioning

confidence: 99%

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Variable reactivity of particulate organic matter in a global ocean biogeochemical model

et al. 2017

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Abstract. The marine biological carbon pump is dominated by the vertical transfer of particulate organic carbon (POC) from the surface ocean to its interior. The efficiency of this transfer plays an important role in controlling the amount of atmospheric carbon that is sequestered in the ocean. Furthermore, the abundance and composition of POC is critical for the removal of numerous trace elements by scavenging, a number of which, such as iron, are essential for the growth of marine organisms, including phytoplankton. Observations and laboratory experiments have shown that POC is composed of numerous organic compounds that can have very different reactivities. However, this variable reactivity of POC has never been extensively considered, especially in modelling studies. Here, we introduced in the global ocean biogeochemical model NEMO-PISCES a description of the variable composition of POC based on the theoretical reactivity continuum model proposed by Boudreau and Ruddick (1991). Our model experiments show that accounting for a variable lability of POC increases POC concentrations in the ocean's interior by 1 to 2 orders of magnitude. This increase is mainly the consequence of a better preservation of small particles that sink slowly from the surface. Comparison with observations is significantly improved both in abundance and in size distribution. Furthermore, the amount of carbon that reaches the sediments is increased by more than a factor of 2, which is in better agreement with global estimates of the sediment oxygen demand. The impact on the major macronutrients (nitrate and phosphate) remains modest. However, iron (Fe) distribution is strongly altered, especially in the upper mesopelagic zone as a result of more intense scavenging: vertical gradients in Fe are milder in the upper ocean, which appears to be closer to observations. Thus, our study shows that the variable lability of POC can play a critical role in the marine biogeochemical cycles which advocates for more dedicated in situ and laboratory experiments.

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Section: Spatial Variations Of Remineralisation Efficiencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

et al. 2017

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“…Several previous studies [8][9][10][11] have formulated prognostic models for the sinking particle flux. Kriest and Oschiles 12 examined what sinking characteristics contribute to a 'Martin curve' like flux profile and showed that a constant sinking velocity does not produce the characteristic attenuation in the profile.…”

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confidence: 99%

Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics

Omand

Govindarajan

et al. 2020

Sci Rep

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The sinking of organic particles produced in the upper sunlit layers of the ocean forms an important limb of the oceanic biological pump, which impacts the sequestration of carbon and resupply of nutrients in the mesopelagic ocean. Particles raining out from the upper ocean undergo remineralization by bacteria colonized on their surface and interior, leading to an attenuation in the sinking flux of organic matter with depth. Here, we formulate a mechanistic model for the depth-dependent, sinking, particulate mass flux constituted by a range of sinking, remineralizing particles. Like previous studies, we find that the model does not achieve the characteristic 'Martin curve' flux profile with a single type of particle, but instead requires a distribution of particle sizes and/or properties. We consider various functional forms of remineralization appropriate for solid/compact particles, and aggregates with an anoxic or oxic interior. We explore the sensitivity of the shape of the flux vs. depth profile to the choice of remineralization function, relative particle density, particle size distribution, and water column density stratification, and find that neither a power-law nor exponential function provides a definitively superior fit to the modeled profiles. The profiles are also sensitive to the time history of the particle source. Varying surface particle size distribution (via the slope of the particle number spectrum) over 3 days to represent a transient phytoplankton bloom results in transient subsurface maxima or pulses in the sinking mass flux. This work contributes to a growing body of mechanistic export flux models that offer scope to incorporate underlying dynamical and biological processes into global carbon cycle models. The oceans absorb about 2.5 × 10 12 kg of carbon from the atmosphere annually, amounting to a net uptake of about 40% of the anthropogenically produced CO 2 since industrialization 1. Understanding the controls on the oceanic uptake of atmospheric CO 2 is important for predicting how the uptake rate might change in the future. The oceanic biological pump 2 plays a significant role in this process: Phytoplankton produce organic matter by taking up dissolved inorganic carbon through photosynthesis in the sunlit ocean. While a major portion of this production is recycled, a small fraction (typically, less than 20%) rains out to depth, carrying with it organic carbon, nutrients and minerals. Such particles are formed through a variety of mechanisms: cells age, form cysts, are ingested and egested by zooplankton, aggregate, coagulate, and gradually sink as 'marine snow'. The sinking material varies in shape, size and character, ranging from individual cells to pellets and aggregates, most of which is rapidly colonized and consumed by heterotrophic bacteria, contributing to the attenuation of the sinking flux with depth (Fig. 1). The shape of the depth-diminishing flux profile has traditionally been characterized by empirical fits to data obtained from particle intercepting sediment traps 3 o...

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“…This has potentially useful implications for modelling the remineralisation of particulate organic matter fluxes. Models resolving the various processes that affect remineralisation rates and sinking velocities have recently been developed (Jokulsdottir and Archer, 2016;Cram et al, 2018) however, the requirements to model processes such as particle aggregation can be computationally expensive, limiting their application to 1-D models (Jokulsdottir and Archer, 2016;Cram et al, 2018) or to offline models (DeVries et al, 2014). A globally uniform change in b informed by these models could then used to calculate the impact on atmospheric CO 2 if the change in b is greater than 0.2.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of atmospheric CO2 to regional variability in particulate organic matter remineralization depths

Wilson¹,

Barker²,

Edwards³

et al. 2018

Preprint

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Abstract. The concentration of CO2 in the atmosphere is sensitive to changes in the depth at which sinking particulate organic matter is remineralised: often described as a change in the exponent "b" of the Martin curve. Sediment trap observations from deep and intermediate depths suggest there is a spatially heterogeneous pattern of b, particularly varying with latitude, but disagree over the exact spatial patterns. Here we use a biogeochemical model of the phosphorus cycle coupled with a steady-state representation of ocean circulation to explore the sensitivity of preformed phosphate and atmospheric CO2 to spatial variability in remineralisation depths. A Latin hypercube sampling method is used to simultaneously vary the Martin curve indepedently within 15 different regions, as a basis for a regression-based analysis used to derive a quantitative measure of sensitivity. Approximately 30&#8201;% of the sensitivity of atmospheric CO2 to changes in remineralisation depths is driven by changes in the Subantarctic region (36&#176;&#8201;S to 60&#176;&#8201;S), simliar in magnitude to the Pacific basin despite the much smaller area and lower productivity. Overall, the absolute magnitude of sensitivity is controlled by export production but the relative spatial patterns in sensitivity are predominantly constrained by ocean circulation pathways. The high sensitivity in the Subantarctic regions is driven by a combination of high export production and the high connectivity of these regions to regions important for the export of preformed nutrients such as the Southern Ocean and North Atlantic. Overall, regionally varying remineralisation depths contribute to variability in CO2 of between &#177;5&#8211;15 ppm relative to a global mean change in remineralisation depth. Future changes in the environmental and ecological drivers of remineralisation, such as temperature and ocean acidification, are expected to be most significant in the high latitudes where CO2 sensitivity to remineralisation is also highest. The importance of ocean circulation pathways to the high sensitivity in Subantarctic regions also has significance for past climates given the importance of circulation changes in the Southern Ocean.

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A stochastic, Lagrangian model of sinking biogenic aggregates in the ocean (SLAMS 1.0): model formulation, validation and sensitivity

Cited by 44 publications

References 119 publications

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics

Sensitivity of atmospheric CO<sub>2</sub> to regional variability in particulate organic matter remineralization depths

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A stochastic, Lagrangian model of sinking biogenic aggregates in the ocean (SLAMS 1.0): model formulation, validation and sensitivity

Cited by 44 publications

References 119 publications

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Sinking flux of particulate organic matter in the oceans: Sensitivity to particle characteristics

Sensitivity of atmospheric CO&lt;sub&gt;2&lt;/sub&gt; to regional variability in particulate organic matter remineralization depths

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Sensitivity of atmospheric CO<sub>2</sub> to regional variability in particulate organic matter remineralization depths