Chlorophyll variability in the oligotrophic gyres: mechanisms, seasonality and trends
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A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the five subtropical ocean gyres using satellite data: chlorophyll-a (Chl-a) retrievals from ocean color, sea surface temperature (SST), and sea-level anomaly (SLA). Trend analysis was also performed on mixed-layer data derived from ocean model gridded temperature and salinity profiles (1998-2010). The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm with improved accuracy in low Chl-a waters. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all five gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline. On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.
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Decreasing Chl-a concentrations have been recently reported in all five subtropical gyres.
“Decreasing Chl-a concentrations have been recently reported in all five subtropical gyres (Martinez et al., 2020;Signorini et al., 2015;Vantrepotte & Mélin, 2009).”
From Recent Trends in SST, Chl‐<i>a</i>, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre (2021) · cites this paper as Signorini et al., 2015
The Abstract reports significant downward Chl-a trends in four subtropical gyres, but a weak, statistically insignificant upward trend in the South Pacific gyre. The Summary and Conclusions likewise identifies the South Pacific as the exception, so the paper does not report decreasing Chl-a in all five. (LLM, conf=0.92)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe global upper ocean has warmed during recent decades, and this warming is accompanied by a decrease in chlorophyll-a and productivity.
“The global upper ocean has been warming during the last decades accompanied with a chlorophyll-a (Chl-a) and productivity decrease.”
From Recent Trends in SST, Chl‐<i>a</i>, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre (2021) · cites this paper as Signorini et al., 2015
The Abstract and Summary and Conclusions report warming and declining net primary production across five subtropical gyres over 1998–2013. Chlorophyll-a declined in four gyres, but the South Pacific gyre had a weak, statistically insignificant increase. The paper studies these gyres, not the global upper ocean as a whole. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe SST results for the open ocean are in good agreement with the literature.
“Although both higher and lower trends were detected by different authors for different time periods for the open ocean, our results are in good agreement with the literature (Table 2).(Good et al., 2006;Hansen et al., 2006;Signorini et al., 2015).”
From Recent Trends in SST, Chl‐<i>a</i>, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre (2021) · cites this paper as Signorini et al., 2015
Signorini et al. (2015) detected significant negative trends in NPP and Chl-a for the North Atlantic subtropical gyre.
“Signorini et al. (2015) detected significant negative trends in NPP and Chl-a for the North Atlantic subtropical gyre.”
From Recent Trends in SST, Chl‐<i>a</i>, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre (2021) · cites this paper as Signorini et al. (2015)
Climatological changes in physical forcing such as surface warming/cooling may significantly alter these processes.
“Climatological changes in the physical forcing such as surface warming/cooling may significantly alter these processes (Signorini et al., 2015).”
From Recent Trends in SST, Chl‐<i>a</i>, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre (2021) · cites this paper as Signorini et al., 2015
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Research works printed but not linked: 27
- Brix, H., Gruber, N., Karl, D. M., and Bates, N. R. (2006). On the rela- tionships between primary, net community, and export production in sub- tropical gyres. Deep-sea Res. II, Top. Stud. Oceanogr. 53, 698-717. doi: 10.1016/j.dsr2.2006.01.024 · DOI
- Carton, J. A., Chepurin, G., Cao, X. H., and Giese, B. (2000). A sim- ple ocean data assimilation analysis of the global upper ocean 1950-95. part i: methodology. J. Phys. Oceanogr. 30, 294-309. doi: 10.1175/1520- 0485(2000)030%3C0294:ASODAA%3E2.0.CO;2 · DOI
- Franz, B. A., Bailey, S. W., Meister, G., and Werdell, P. J. (2012). Quality and con- sistency of the NASA ocean color data record. Proc. Ocean Optics. XXI, Glasgow. Scotland 8-12. doi: 10.13140/2.1.2960.4169 · DOI
- Franz, B. A., Behrenfeld, M. J., Siegel, D. A., and Werdell, P. J. (2014). Global ocean phytoplankton ["in state of the climate in 2013"]. Bull. Am. Meteor. Soc. 95, S78-S80. doi: 10.1175/2014BAMSStateoftheClimate. · DOI
- Gregg, W. W., and Rousseaux, C. S. (2014). Decadal trends in global pelagic ocean chlorophyll: a new assessment integrating multiple satellites, in situ data, and models. J. Geophys. Res. Oceans 119, 5921-5933, doi: 10.1002/2014JC010158 · DOI
- Hu, C., Lee, Z., and Franz, B. (2012). Chlorophyll algorithms for oligotrophic oceans: a novel approach based on three-band reflectance difference. J. Geophys. Res. Oceans 117:25. doi: 10.1029/2011JC007395 · DOI
- Laws, E. A., Ditullio, G. R., and Redalje, D. G. (1987). High phytoplankton growth and production-rates in the North Pacific Subtropical Gyre. Limnol. Oceanogr. 32, 905-918. doi: 10.4319/lo.1987.32.4.0905 · DOI
- Letelier, R. M., Bidigare, R. R., Hebel, D. V., Ondrusek, M., Winn, C., and Karl, D. M. (1993). Temporal variability of phytoplankton community struc- ture based on pigment analysis. Limnol. Oceanogr. 38, 1420-1437. doi: 10.4319/lo.1993.38.7.1420 · DOI
- Marañón, E., Behrenfeld, M. J., Gonzalez, N., Mourino, B., and Zubkov, M. V. (2003). High variability of primary production in oligotrophic waters of the Atlantic Ocean: uncoupling from phytoplankton biomass and size structure. Marine Ecol. Progress Series 257, 1-11. doi: 10.3354/meps257001 · DOI
- Marañón, E., Holligan, P. M., Barciela, R., González, N., Mouriño, B., Pazó, M. J., et al. (2001). Patterns of phytoplankton size structure and productivity in contrasting open-ocean environments. Mar. Ecol. Prog. Ser. 216, 43-56. doi: 10.3354/meps216043 · DOI
- Marañón, E., Holligan, P. M., Varela, M., Mourino, B., and Bale, A. J. (2000). Basin-scale variability of phytoplankton biomass, production and growth in the Atlantic Ocean. Deep-sea Res. I, Oceanogr. Res. Papers 47, 825-857. doi: 10.1016/S0967-0637(99)00087-4 · DOI
- Marra, J., and Heinemann, K. R. (1987). Primary production in the North Pacific Central Gyre -some new measurements based on C-14. Deep-sea Res. A, Oceanogr. Res. Papers 34, 1821-1829. doi: 10.1016/0198-0149(87)90056-2 · DOI
- McClain, C. R., and Firestone, J. (1993). An Investigation of Ekman Upwelling in the North-Atlantic. J. Geophys. Res. Oceans 98, 12327-12339. doi: 10.1029/93JC00868 · DOI
- McClain, C. R., Signorini, S. R., and Christian, J. R. (2004). Subtropical gyre vari- ability observed by ocean-color satellites. Deep-sea Res. II, Top. Stud. Oceanogr. 51, 281-301. doi: 10.1016/j.dsr2.2003.08.002 · DOI
- Meister, G., and Franz, B. A. (2014). Corrections to the MODIS Aqua calibration derived from MODIS Aqua ocean color products. IEEE Trans. Geo. Rem. Sens. 52, 6534-6541. doi: 10.1109/TGRS.2013.2297233 · DOI
- Mignot, A., Claustre, H., Uitz, J., Poteau, A., D'ortenzio, F., and Xing, X. (2014). Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: a bio-argo float investi- gation. Global Biogeochem. Cycles 28, 856-876. doi: 10.1002/2013GB004781 · DOI
- Morel, A. H., Claustre, and Gentili, B. (2010). The most oligotrophic subtropical zones of the global ocean: similarities and differences in terms of chlorophyll and yellow substance, Biogeosciences 7, 3139-3151. doi: 10.5194/bg-7-3139- 2010 · DOI
- O'Reilly, J. E., Maritorena, S., Mitchell, B. G., Siegel, D. A., Carder, K. L., Garver, S. A., et al. (1998). Ocean color chlorophyll algorithms for SeaWiFS. J. Geophys. Res. Oceans 103, 24937-24953. doi: 10.1029/98JC02160 · DOI
- Pedlosky, J. (1990). The dynamics of the Oceanic Subtropical Gyres. Science 248, 316-322. doi: 10.1126/science.248.4953.316 · DOI
- Polovina, J. J., Howell, E. A., and Abecassis, M. (2008). Ocean's least productive waters are expanding. Geophys. Res. Lett. 35:L03618. doi: 10.1029/2007GL031745 · DOI · Paper page
- Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and Schlax, M. G. (2007). Daily high-resolution-blended analyses for sea surface temperature. J. Clim. 20, 5473-5496. doi: 10.1175/2007JCLI1824. · DOI
- Signorini, S. R., and McClain, C. R. (2009). Effect of uncertainties in climato- logic wind, ocean pCO 2 , and gas transfer algorithms on the estimate of global sea-air CO 2 flux. Global Biogeochem. Cycles 23:GB2025, doi: 10.1029/2008GB 003246 · DOI
- Signorini, S. R., and McClain, C. R. (2012). Subtropical gyre variability as seen from satellites. Remote Sensing Lett. 3, 471-479. doi: 10.1080/01431161.2011.625053 · DOI
- Turk, D., Mcphaden, M. J., Busalacchi, A. J., and Lewis, M. R. (2001). Remotely sensed biological production in the equatorial Pacific. Science 293, 471-474. doi: 10.1126/science.1056449 · DOI
- Werdell, P. J., and Bailey, S. W. (2005). An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation. Remote Sens. Environ. 98, 122-140. doi: 10.1016/j.rse.2005.07.001 · DOI
- Westberry, T., Behrenfeld, M. J., Siegel, D. A., and Boss, E. (2008). "Carbon- based primary productivity modeling with vertically resolved photoacclimation. Global Biogeochemical Cycles 22, GB2024.1998). Chemoreception," in The Physiology of Fishes, ed D. H. Evans (Boca Raton, FL: CRC Press), 375-405.
- Winn, C. L., Campbell, J., Christian, R., Letelier, D., Hebel, J., Dore, L., et al. (1995), Seasonal variability in the phytoplankton community of the north pacific sub- tropical gyre. Global Biogeochem. Cycles 9, 605-620. doi: 10.1029/95GB02149 · DOI
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Siemer, J. P., Machín, F., González‐Vega, A., Arrieta, J. M., Gutiérrez‐Guerra, M. A., Pérez‐Hernández, M. D., Vélez‐Belchí, P., Hernández‐Guerra, A., & Fraile‐Nuez, E. (2021) · Journal of Geophysical Research: Oceans · doi:10.1029/2021jc017268 · Cited by 50 · see citing works
- Authors
- Signorini, S. R., Franz, B. A., & McClain, C. R.
- Affiliations
- Goddard Space Flight Center (US)
- ORCID
- Franz, Bryan A.
- Venue
- Frontiers in Marine Science
- Publisher
- Frontiers Media SA
- Published
- 2015-02-02
- Volume
- 2
- ISSN
- 2296-7745 (ISSN-L)
- OpenAlex
- W2093589900
- Cited by
- 160
- References
- 0
- Citations by year
- 2026: 16 · 2025: 14 · 2024: 24 · 2023: 26 · 2022: 12 · 2021: 18 · 2020: 11 · 2019: 18 · 2018: 8 · 2017: 8 · 2016: 4 · 2015: 1
- FWCI
- 5.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Marine Science (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Aeronautics and Space Administration
- Centre National d’Etudes Spatiales
- National Oceanic and Atmospheric Administration
- Graduate School, University of Maryland
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Marine and coastal ecosystems
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- oligotrophic gyres, net primary productivity, mixed layer depth, nutricline, vertical mixing, seasonal variation, sea surface temperature trends, sea level anomalies, atmospheric CO2 uptake, carbon cycle, North Pacific gyre, North Atlantic gyre, South Atlantic gyre, South Pacific Gyre
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