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1.
Nat Commun ; 15(1): 5532, 2024 Jul 08.
Artigo em Inglês | MEDLINE | ID: mdl-38977666

RESUMO

The ocean's Meridional Overturning Circulation (MOC) brings carbon- and nutrient-rich deep waters to the surface around Antarctica. Limited by light and dissolved iron, photosynthetic microbes incompletely consume these nutrients, the extent of which governs the escape of inorganic carbon into the atmosphere. Changes in MOC upwelling may have regulated Southern Ocean outgassing, resulting in glacial-interglacial atmospheric CO2 oscillations. However, numerical models that explore this positive relationship do not typically include a feedback between biological activity and abundance of organic chelating ligands that control dissolved iron availability. Here, I show that incorporating a dynamic ligand parameterization inverts the modelled MOC-atmospheric CO2 relationship: reduced MOC nutrient upwelling decreases biological activity, resulting in scant ligand production, enhanced iron limitation, incomplete nutrient usage, and ocean carbon outgassing, and vice versa. This first-order response suggests iron cycle feedbacks may be a critical driver of the ocean's response to climate changes, independent of external iron supply.

2.
Geophys Res Lett ; 48(7): e2020GL091746, 2021 Apr 16.
Artigo em Inglês | MEDLINE | ID: mdl-34219838

RESUMO

The ocean's "biological pump" significantly modulates atmospheric carbon dioxide levels. However, the complexity and variability of processes involved introduces uncertainty in interpretation of transient observations and future climate projections. Much research has focused on "parametric uncertainty," particularly determining the exponent(s) of a power-law relationship of sinking particle flux with depth. Varying this relationship's functional form introduces additional "structural uncertainty." We use an ocean biogeochemistry model substituting six alternative remineralization profiles fit to a reference power-law curve, to systematically characterize structural uncertainty, which, in atmospheric pCO2 terms, is roughly 50% of parametric uncertainty associated with varying the power-law exponent within its plausible global range, and similar to uncertainty associated with regional variation in power-law exponents. The substantial contribution of structural uncertainty to total uncertainty highlights the need to improve characterization of biological pump processes, and compare the performance of different profiles within Earth System Models to obtain better constrained climate projections.

3.
Proc Natl Acad Sci U S A ; 117(9): 4842-4849, 2020 03 03.
Artigo em Inglês | MEDLINE | ID: mdl-32071221

RESUMO

Iron is the limiting factor for biological production over a large fraction of the surface ocean because free iron is rapidly scavenged or precipitated under aerobic conditions. Standing stocks of dissolved iron are maintained by association with organic molecules (ligands) produced by biological processes. We hypothesize a positive feedback between iron cycling, microbial activity, and ligand abundance: External iron input fuels microbial production, creating organic ligands that support more iron in seawater, leading to further macronutrient consumption until other microbial requirements such as macronutrients or light become limiting, and additional iron no longer increases productivity. This feedback emerges in numerical simulations of the coupled marine cycles of macronutrients and iron that resolve the dynamic microbial production and loss of iron-chelating ligands. The model solutions resemble modern nutrient distributions only over a finite range of prescribed ligand source/sink ratios where the model ocean is driven to global-scale colimitation by micronutrients and macronutrients and global production is maximized. We hypothesize that a global-scale selection for microbial ligand cycling may have occurred to maintain "just enough" iron in the ocean.


Assuntos
Retroalimentação , Ferro/metabolismo , Oceanos e Mares , Água do Mar/química , Água do Mar/microbiologia , Bactérias/metabolismo , Simulação por Computador , Cianobactérias/metabolismo , Compostos Férricos/metabolismo , Ferro/análise , Quelantes de Ferro , Ligantes , Micronutrientes , Modelos Biológicos , Nutrientes , Fotoquímica , Sideróforos/metabolismo , Microbiologia da Água
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