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Cite this paper: |
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Dandan ZHAO, Le GAO, Yongsheng XU. Quantification of the impact of environmental factors on chlorophyll in the open ocean[J]. Journal of Oceanology and Limnology, 2021, 39(2): 447-457 |
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Quantification of the impact of environmental factors on chlorophyll in the open ocean |
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| Dandan ZHAO1,2,3,4, Le GAO1,2,4, Yongsheng XU1,2,4 |
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1 Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;
2 Laboratory for Ocean and Climate Dynamics, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China;
4 Center for Ocean Mega-Science, Chinese Academy of Sciences Qingdao 266071, China |
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| Abstract: |
| Many previous studies of the impact of oceanic environmental factors on chlorophyll (CHL) in a specific region focused on sea surface temperature (SST), mixed-layer depth (MLD), or wind stress (WS) alone. In this study, relationship between CHL and all those environmental factors (SST, MLD, and WS) in the open ocean was quantified for five regions within the subtropical gyres and the variation trend of 13-year (2003-2015) was analyzed using satellite observations and Argo measurements. The correlation analysis results show that MLD was correlated positively with CHL, SST was correlated negatively with CHL, and the correlation between CHL and WS was either positive or negative. Based on the significance of the correlations, models representing the relationships were established using the multiple linear regression and analyzed, showing that the environmental factors were the major determinants of CHL change. The regression coefficients show that both SST and MLD have remarkable effect on CHL. Our derived models could be used to diagnose the past changes, understand present variability, and predict the future state of CHL changes based on environmental factors, and help us understand the dynamics of CHL variation in the open ocean. |
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| Key words:
chlorophyll (CHL)|mixed layer depth (MLD)|multiple linear regression|sea surface temperature (SST)
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| Received: 2019-05-05 Revised: 2019-11-22 |
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References:
Behrenfeld M J, O'Malley R T, Siegel D A, McClain C R, Sarmiento J L, Feldman G C, Milligan A J, Falkowski P G, Letelier R M, Boss E S. 2006. Climate-driven trends in contemporary ocean productivity. Nature, 444(7120):752-755, https://doi.org/10.1038/nature05317.
Bentamy A, Grodsky S A, Carton J A, Croizé-Fillon D, Chapron B. 2012. Matching ASCAT and QuikSCAT winds. Journal of Geophysical Research:Oceans, 117(C2):C02011, https://doi.org/10.1029/2011JC007479.
Chelton D B, Gaube P, Schlax M G, Early J J, Samelson R M. 2011a. The influence of nonlinear mesoscale eddies on near-surface oceanic chlorophyll. Science, 334(6054):328-332, https://doi.org/10.1126/science.1208897.
D'Sa E J, Korobkin M. 2009. Wind influence on chlorophyll variability along the Louisiana-Texas coast from satellite wind and ocean color data. In:Proceedings of SPIE7473, Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2009. SPIE, Berlin, Germany. 747305p, https://doi.org/10.1117/12.830537.
Fay A R, McKinley G A. 2017. Correlations of surface ocean pCO2 to satellite chlorophyll on monthly to interannual timescales. Global Biogeochemical Cycles, 31(3):436-455, https://doi.org/10.1002/2016GB005563.
Feng J F, Durant J M, Stige L C, Hessen D O, Hjermann D Ø, Zhu L, Llope M, Stenseth N C. 2015. Contrasting correlation patterns between environmental factors and chlorophyll levels in the global ocean. Global Biogeochemical Cycles, 29(12):2 095-2 107, https://doi.org/10.1002/2015GB005216.
George D G, Edwards R W. 1976. The Effect of wind on the distribution of chlorophyll a and crustacean plankton in a shallow eutrophic reservoir. Journal of Applied Ecology, 13(3):667-690, https://doi.org/10.2307/2402246.
Gregg W W, Casey N W, McClain C R. 2005. Recent trends in global ocean chlorophyll. Geophysical Research Letters, 32(3):L03606, https://doi.org/10.1029/2004GL021808.
Huang R X, Russell S. 1994. Ventilation of the subtropical north pacific. Journal of Physical Oceanography, 24(12):2 589-2 605, https://doi.org/10.1175/1520-0485(1994)024<2589:votsnp>2.0.co;2.
Itoh S, Yasuda I, Saito H, Tsuda A, Komatsu K. 2015. Mixed layer depth and chlorophyll a:Profiling float observations in the Kuroshio-Oyashio extension region. Journal of Marine Systems, 151:1-14, https://doi.org/10.1016/j.jmarsys.2015.06.004.
Ji C X, Zhang Y Z, Cheng Q M, Tsou J Y, Jiang T C, Liang X S. 2018. Evaluating the impact of sea surface temperature(SST) on spatial distribution of chlorophyll-a concentration in the East China Sea. International Journal of Applied Earth Observation and Geoinformation, 68:252-261, https://doi.org/10.1016/j.jag.2018.01.020.
Kavak M T, Karadogan S. 2012. The relationship between sea surface temperature and chlorophyll concentration of phytoplanktons in the Black Sea using remote sensing techniques. Journal of Environmental Biology, 33(2 Suppl.):493-498.
Killworth P D, Cipollini P, Uz B M, Blundell J R. 2004. Physical and biological mechanisms for planetary waves observed in satellite-derived chlorophyll. Journal of Geophysical Research:Oceans, 109(C7):C07002, https://doi.org/10.1029/2003JC001768.
Liu F F, Chen C Q, Zhan H G. 2012. Decadal variability of chlorophyll a in the South China Sea:a possible mechanism. Chinese Journal of Oceanology and Limnology, 30(6):1 054-1 062, https://doi.org/10.1007/s00343-012-1282-9.
Longhurst A. 1993. Seasonal cooling and blooming in tropical oceans. Deep Sea Research Part I:Oceanographic Research Papers, 40(11-12):2 145-2 165, https://doi.org/10.1016/0967-0637(93)90095-K.
Lovenduski N S, Gruber N, Doney S C. 2008. Toward a mechanistic understanding of the decadal trends in the Southern Ocean carbon sink. Global Biogeochemical Cycles, 22(3):GB3016, https://doi.org/10.1029/2007GB003139.
McClain C R, Signorini S R, Christian J R. 2004. Subtropical gyre variability observed by ocean-color satellites. Deep Sea Research Part II:Topical Studies in Oceanography, 51(1-3):281-301, https://doi.org/10.1016/j.dsr2.2003.08.002.
McQuatters-Gollop A, Mee L D, Raitsos D E, Shapiro G I. 2008. Non-linearities, regime shifts and recovery:The recent influence of climate on Black Sea chlorophyll. Journal of Marine Systems, 74(1-2):649-658, https://doi.org/10.1016/j.jmarsys.2008.06.002.
Nezlin N P, Li B L. 2003. Time-series analysis of remotesensed chlorophyll and environmental factors in the Santa Monica-San Pedro Basin off Southern California. Journal of Marine Systems, 39(3-4):185-202, https://doi.org/10.1016/S0924-7963(03)00030-7.
Qiu F W, Fang W D, Fang G H. 2011. Seasonal-to-interannual variability of chlorophyll in central western South China Sea extracted from SeaWiFS. Chinese Journal of Oceanology and Limnology, 29(1):18-25, https://doi.org/10.1007/s00343-011-9931-y.
Raymont J E G. 1980. Plankton and Productivity in the Oceans. Phytoplankton, vol. 1. 2nd edn. Pergamon, Oxford. 489p.
Uz B M, Yoder J A. 2004. High frequency and mesoscale variability in SeaWiFS chlorophyll imagery and its relation to other remotely sensed oceanographic variables. Deep Sea Research Part II:Topical Studies in Oceanography, 51(10-11):1 001-1 017, https://doi.org/10.1016/j.dsr2.2004.03.003.
Wang D K, Wang H, Li M, Liu M M, Wu X Y. 2013. Role of Ekman transport versus Ekman pumping in driving summer upwelling in the South China Sea. Journal of Ocean University of China, 12(3):355-365, https://doi.org/10.1007/s11802-013-1904-7.
Webster I T, Hutchinson P A. 1994. Effect of wind on the distribution of phytoplankton cells in lakes revisited. Limnology and Oceanography, 39(2):365-373, https://doi.org/10.4319/lo.1994.39.2.0365.
Wentz F J. 1997. A well-calibrated ocean algorithm for special sensor microwave/imager. Journal of Geophysical Research:Oceans, 102(C4):8 703-8 718, https://doi.org/10.1029/96JC01751.
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