Toward Determining the Spatio-Temporal Variability of Upper-Ocean Ecosystem Stoichiometry From Satellite Remote Sensing

Tanioka, Tatsuro; Fichot, Cédric G.; Matsumoto, Katsumi

doi:10.3389/fmars.2020.604893

Cited by 11 publications

(12 citation statements)

References 115 publications

(155 reference statements)

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“…While data on long-term changes in the phytoplankton community exists, we do not have comparable time series of phytoplankton elemental stoichiometry. Using a trait-based phytoplankton model coupled with satellite inputs 38 , we estimated long-term patterns in the phytoplankton C:P ratio in the Sargasso Sea (Fig. 7 ).…”

Section: Resultsmentioning

confidence: 99%

Adaptive carbon export response to warming in the Sargasso Sea

et al. 2022

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Ocean ecosystem models predict that warming and increased surface ocean stratification will trigger a series of ecosystem events, reducing the biological export of particulate carbon to the ocean interior. We present a nearly three-decade time series from the open ocean that documents a biological response to ocean warming and nutrient reductions wherein particulate carbon export is maintained, counter to expectations. Carbon export is maintained through a combination of phytoplankton community change to favor cyanobacteria with high cellular carbon-to-phosphorus ratios and enhanced shallow phosphorus recycling leading to increased nutrient use efficiency. These results suggest that surface ocean ecosystems may be more responsive and adapt more rapidly to changes in the hydrographic system than is currently envisioned in earth ecosystem models, with positive consequences for ocean carbon uptake.

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Section: Resultsmentioning

confidence: 99%

Adaptive carbon export response to warming in the Sargasso Sea

et al. 2022

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“…5 ). Changes such as these in phytoplankton stoichiometry could ultimately increase the efficiency of the biological pump [20] , [57] , [58] , [59] . Following Broecker’s mathematical representation [13] , carbon export is proportional to the uptake rate of the limiting nutrient by phytoplankton multiplied by the ratio of C:Limting Nutrient (e.g., N or P).…”

Section: Resultsmentioning

confidence: 99%

“…Recently, Inomura et al developed a coarse-grained model of phytoplankton (Cell Flux Model of Phytoplankton: CFM-Phyto) [19] and has used the model to estimate the C:P ratio of phytoplankton in the ocean [20] . Conceptually, the model combines physiological acclimation of phytoplankton on elemental stoichiometry [21] , [22] , coarse-grained macromolecular allocations (e.g., proteins, DNAs, RNAs, carbohydrate, chlorophyll) [23] , [24] , [25] , [26] , and broad-brush proteomics informed from recent proteome studies [27] , [28] , [29] .…”

Section: Introductionmentioning

confidence: 99%

Modeled temperature dependencies of macromolecular allocation and elemental stoichiometry in phytoplankton

Armin

Inomura

2021

Computational and Structural Biotechnology Journal

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“…The ratio can vary over time in response to changes in the ecological balance between exponential growth and equilibrium phases, and with the availability N and P nutrients (Klausmeier et al 2004). It is shown that the nutrient availability in the sunlit ocean governs the phytoplankton distribution and latitudinal patterns of elemental proportions of particulate organic matter (POM) in the global ocean (Martiny et al 2013a, b;Tanioka et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Role of eddies and N2 fixation in regulating C:N:P proportions in the Bay of Bengal

et al. 2021

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Recent observations and numerical simulations have profoundly established that the C:N:P ratios in the ocean deviate from the canonical Redfield Ratio (106:16:1). Physical and biogeochemical processes have been hypothesized to be responsible for this deviation. However, a paucity of concurrent observations on biogeochemical and physical parameters have barred us to understand their exact role on the C:N:P ratios. For this purpose, we have sampled the Bay of Bengal for its C, N, and P contents in the organic and inorganic pools from 5 to 2000 m depth at eight stations (five coastal and three open ocean) during boreal spring 2019. Mesoscale anticyclonic eddies were identified at two of the sampling stations, where nutrient concentrations were lower in the top layer (5 m to the depth of chlorophyll maximum) compared to those at the non-eddy stations. Mean (NO 3 -?NO 2 -):PO 4 3ratio was lower at the anticyclonic eddy stations compared to that at the non-eddy stations in the top layer. Yet C:N:P ratios in the particulate and dissolved organic matter in the top layer were the same at anticyclonic eddy and non-eddy stations. Overall the mean C:N:P ratios were 249:39:1 in particulate organic matter and 2338:146:1 in dissolved organic matter in the top layer. Biological N 2 fixation was not a driver in controlling the N:P ratio of the export flux and the subsurface water nutrient ratios during spring. Although the Bay of Bengal receives large riverine influx, its influence in changing the C:N:P ratios was small during this study.

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Toward Determining the Spatio-Temporal Variability of Upper-Ocean Ecosystem Stoichiometry From Satellite Remote Sensing

Cited by 11 publications

References 115 publications

Adaptive carbon export response to warming in the Sargasso Sea

Adaptive carbon export response to warming in the Sargasso Sea

Modeled temperature dependencies of macromolecular allocation and elemental stoichiometry in phytoplankton

Role of eddies and N2 fixation in regulating C:N:P proportions in the Bay of Bengal

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