[1] Huang J-H (黄建辉), Han X-G (韩兴国). A review on the bcogeochemical cycling in forest ecosystems: Theories and methods. Chinese Bulletin of Botany (植物学报), 1995, 12(suppl.2): 195-223 (in Chinese) [2] Song C-L (宋春林), Sun X-Y (孙向阳), Wang G-X (王根绪). A review on carbon and water interactions of forest ecosystem and its impact factors. Chinese Journal of Applied Ecology (应用生态学报), 2015, 26(9): 2891-2902 (in Chinese) [3] Saba VS, Friedrichs MAM, Carr ME, et al. Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT. Global Biogeochemical Cycles, 2010, 24: 811-829 [4] Lalli CM, Parsons TR. Biological Oceanography: An Introduction. 2nd Ed. Oxford: Butterworth-Heinemann, 1997 [5] Saba VS, Friedrichs MAM, Antoine D, et al. An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe. Biogeosciences Discussions, 2011, 7: 489-503 [6] Wu P-Z (吴培中). Satellite measuring for ocean primary productivity. Remote Sensing Forland and Resources (国土资源遥感), 2004, 12(3): 7-15 (in Chinese) [7] Tang S-L (唐世林), Chen C-Q (陈楚群), Zhan H-G (詹海刚). Retrieval progress of ocean primary production by remote sensing. Journal of Oceanography in Taiwan Strait (台湾海峡), 2006, 25(4): 591-598 (in Chinese) [8] Fei Z-L (费尊乐), Zhu M-Y (朱明远). Determination of marine primary productivity. Advances in Marine Science (海洋科学进展), 1984, 2(1): 86-90 (in Chinese) [9] Behrenfeld MJ, Boss E, Siegel DA, et al. Carbon-based ocean productivity and phytoplankton physiology from space. Global Biogeochemical Cycles, 2005, 19: 177-202 [10] Kiefer DA, Mitchell BG. A simple, steady state description of phytoplankton growth based on absorption cross section and quantum efficiency. Limnology and Oceano-graphy, 1983, 28: 770-776 [11] Liu L-M (刘良明). An Introduction to Satellite Oceanic Remote Sensing. Wuchang: Wuhan University Press, 2005 (in Chinese) [12] Campbell JW, Antoine D, Armstrong R, et al. Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance. Global Biogeochemical Cycles, 2002, 16: doi: 10.1029/2001GB001444 [13] Behrenfeld MJ, Randerson J, Mcclain C, et al. Temporal variations in the photosynthetic biosphere. Science, 2001, 291: 2594-2597 [14] Ondrusek ME, Bidigare RR, Waters K, et al. A predictive model for estimating rates of primary production in the subtropical North Pacific Ocean. Deep Sea Research Part II Topical Studies in Oceanography, 2001, 48: 1837-1863 [15] Wang MH, Shi W. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. Optics Express, 2007, 15: 15722-15733 [16] Westberry T, Behrenfeld MJ, Siegel DA, et al. Carbon-based primary productivity modeling with vertically resolved photoacclimation. Global Biogeochemical Cycles, 2008, 22: GB2024, doi: 10.1029/2007GB003078 [17] Smith RC, Eppley RW, Baker KS. Correlation of primary production as measured aboard ship in Southern California coastal waters and as estimated from satellite chlorophyll images. Marine Biology, 1982, 66: 281-288 [18] Eppley RW, Steward E, Abbott MR, et al. Estimating ocean primary production from satellite chlorophyll: Introduction to regional differences and statistics for the Southern California Bight. Journal of Plankton Research, 1985, 7: 57-70 [19] Longhurst A, Sathyendranath S, Platt T, et al. An estimate of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research, 1995, 17: 1245-1271 [20] Antoine D, Morel A. Oceanic primary production. 1. Adaptation of a spectral light-photosynthesis model in view of application to satellite chlorophyll observations. Global Biogeochemical Cycles, 1996, 10: 43-55 [21] Parsons TR, Takahashi M, Hargrava B. Biological Oceanographic Process. 3rd Ed. New York: Pergamum Press, 1984: 380-381 [22] Li S-H (李四海), Wang H (王 宏), Xu W-D (许卫东). Research and progress in satellite ocean color remote sensing. Advances in Earth Sciences (地球科学进展), 2000, 15(2): 190-196 (in Chinese) [23] Zhou W-F (周为峰). The introduction of international plans in monitoring ocean color on the gestational satellites. World Science Technology Research and Development (世界科技研究与发展), 2008, 30(2): 180-184 (in Chinese) [24] Liu L-M (刘良明), Zhu J-D (祝家东). Preliminary study on trend of ocean color sensor development. Remote Sensing Information (遥感信息), 2011(2): 111-119 (in Chinese) [25] Lin M-S (林明森), Zhang Y-G (张有广), Yuan X-Z (袁欣哲). The development course and trend of ocean remote sensing satellite. Acta Oceanologica Sinica (海洋学报), 2015, 37(1): 1-10 (in Chinese) [26] International Ocean Colour Coordinating Group. Ocean-Colour Sensors [EB/OL]. (2014-03-04) [2015-06-29]. http://www.ioccg.org/sensors_ioccg.html. [27] Ryther JH. Photosynthesis in the ocean as a function of light intensity. Limnology and Oceanography, 1956, 1: 61-70 [28] Talling J. The phytoplankton population as a compound photosynthetic system. New Phytologist, 1957, 56: 133-149 [29] Bannister TT. Production equations in terms of chlorophyll concentration quantum yield, and upper limit to production. Limnology and Oceanography, 1974, 19: 1-12 [30] Lee Z, Marra J, Perry MJ et al. Estimating oceanic primary productivity from ocean color remote sensing: A strategic assessment. Journal of Marine Systems, 2015, 149: 50-59 [31] Behrenfeld MJ, Falkowski PG. A consumer’s guide to phytoplankton primary productivity models. Limnology and Oceanography, 1997, 42: 1479-1491 [32] Lee YJ, Matrai PA, Friedrichs MAM, et al. An assessment of phytoplankton primary productivity in the arctic ocean from satellite ocean color/in situ chlorophylla-based models. Journal of Geophysical Research: Oceans, 2015, 120: 6508-6541 [33] Guan W-G (官文江), He X-Q (何贤强), Pan D-L (潘德炉), et al. Estimation of ocean primary production by remote sensing in Bohai Sea, Yellow Sea and East China Sea. Journal of Fisheries of China (水产学报), 2005, 29(3): 367-372 (in Chinese) [34] Wang X-Q (王晓琦), Xing X-G (邢小罡), Wang J-P (王金平), et al. A satellite-based analysis on the seasonal variations and inter-relationships between chlorophyll and particle in the South China Sea. Acta Oceanologica Sinica (海洋学报), 2015, 37(10): 26-38 (in Chinese) [35] Bricaud A, Babin M, Morel A, et al. Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization. Journal of Geophysical Research: Oceans, 1995, 100: 13321-13332 [36] Loisel H, Bosc E, Stramski D, et al. Seasonal variability of the backscattering coefficient in the Mediterranean Sea based on satellite SeaWIFS imagery. Geophysical Research Letters, 2001, 28: 4203-4206 [37] Stramski D, Reynolds RA, Kahru M, et al. Estimation of particulate organic carbon in the ocean from satellite remote sensing. Science, 1999, 285: 239-242 [38] Durand MD, Olson RJ. Contributions of phytoplankton light scattering and cell concentration changes to diel variations in beam attenuation in the equatorial pacific from flow cytometric measurements of pico-, ultra- and nano plankton. Deep Sea Research Part Ⅱ: Topical Stu-dies in Oceanography, 1996, 43: 891-906 [39] Green RE, Sosik HM, Olson RJ. Contributions of phytoplankton and other particles to inherent optical properties in New England continental shelf waters. Limnology and Oceanography, 2003, 48: 2377-2391 [40] Green RE, Sosik HM. Analysis of apparent optical pro-perties and ocean color models using measurements of seawater constituents in New England continental shelf surface waters. Journal of Geophysical Research: Oceans, 2004, 109: 325-347 [41] Behrenfeld MJ, Boss E. The beam attenuation to chlorophyll ratio: An optical index of phytoplankton physiology in the surface ocean. Deep Sea Research Part Ⅰ: Oceanographic Research, 2003, 50: 1537-1549 [42] Behrenfeld MJ, Boss E. Beam attenuation and chlorophyll concentration as alternative optical indices of phytoplankton biomass. Journal of Marine Research, 2006, 64: 431-451 [43] Garver SA, Siegel DA. Inherent optical property inversion of ocean color spectra and its biogeochemical interpretation: 1. Time series from the Sargasso Sea. Journal of Geophysical Research: Oceans, 1997, 102:18607-18625 [44] Maritorena S, Siegel DA, Ar P. Optimization of a semianalytical ocean color model for global-scale applications. Applied Optics, 2002, 41: 2705-2714 [45] Siegel DA, Maritorena S, Nelson NB, et al. Global distribution and dynamics of colored dissolved and detrital organic materials. Journal of Geophysical Research: Oceans, 2002, 107: 1-14 [46] Sheng MA, Yang XF, Tao Z, et al. Assessment of uncertainties of ocean color parameters for the ocean carbon-based productivity model. IOP Conference Series: Earth and Environmental Science, 2014, 17: 682-691 [47] Lee ZP, Lance VP, Shang SL, et al. An assessment of optical properties and primary production derived from remote sensing in the Southern Ocean (SO GasEx). Journal of Geophysical Research: Oceans, 2011, 116: 111-121 [48] Carder KL, Hawes SK, Baker KA, et al. Reflectance model for quantifying chlorophyll-a in the presence of productivity degradation products. Journal of Geophysical Research Atmospheres, 1991, 96: 20599-20611 [49] Carder KL, Chen FR, Lee ZP, et al. Semianalytic mo-derate-resolution imaging spectrometer algorithms for chlorophyll-a and absorption with bio-optical domains based on nitrate-depletion temperatures. Journal of Geophysical Research Atmospheres, 1999, 104: 5403-5421 [50] IOCCG. Remote sensing of inherent optical properties: Fundamentals, tests of algorithms, and applications//Lee ZP, ed. Reports of the International Ocean-Colour Coordinating Group, No. 5. IOCCG, Dartmouth, Canada: IOCCG, 2006: 1-126 [51] Lee Z, Carder KL, Arnone RA. Deriving inherent optical properties from water color: A multiband quasi-analytical algorithm for optically deep waters. Applied Optics, 2002, 41: 5755-5772 [52] Marra J, Trees CC, O'Reilly JE. Phytoplankton pigment absorption: A strong predictor of primary productivity in the surface ocean. Deep Sea Research Part Ⅰ: Oceanographic Research, 2007, 54: 155-163 [53] Hirawake T, Takao S, Horimoto N, et al. A phytoplankton absorption-based primary productivity model for remote sensing in the Southern Ocean. Polar Biology, 2011, 34: 291-302 [54] Lee ZP, Carder KL, Steward RG, et al. Estimating primary production at depth from remote sensing. Applied Optics, 1996, 35: 463-474 [55] Huot Y, Babin M, Bruyant F. Photosynthetic parameters in the beaufort sea in relation to the phytoplankton community structure. Biogeosciences, 2013, 10: 3445-3454 [56] Platt T, Sathyendranath S. Estimators of primary production for interpretation of remotely sensed data on ocean color. Journal of Geophysical Research: Oceans, 1993, 98: 14561-14576 [57] Cong P-F (丛丕福), Wang C-L (王臣立), Qu L-M (曲丽梅), et al. Remotely sensed estimation models of ocean primary production. Ecology and Environment (生态环境学报), 2009, 18(3): 1016-1019 (in Chinese) [58] Antoine D, André J, Morel A. Oceanic primary production. 2. Estimation at global scale from satellite (coastal zone color scanner) chlorophyll. Global Biogeochemical Cycles, 1996, 10: 57-69 [59] Behrenfeld MJ, Falkowski PG. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography, 1997, 42:1-20 [60] Carr ME, Friedrichs MAM, Schmeltz M, et al. A comparison of global estimates of marine primary production from ocean color. Deep Sea Research Part Ⅱ: Topical Studies in Oceanography, 2006, 53: 741-770 [61] Li G-S (李国胜), Wang F (王 芳), Liang Q (梁 强), et al. Estimation of ocean primary productivity by remote sensing and information to spatio-temporal variation mechanism for the East China Sea. Acta Geographica Sinica (地理学报), 2003, 58(4): 483-493 (in Chinese) [62] Tan S-C (檀赛春), Shi G-Y (石广玉). Remote sensing for ocean primary productivity and its spatio-temporal variability in the China Sea. Acta Geographica Sinica (地理学报), 2006, 61(11): 1189-1199 (in Chinese) [63] Yin Y (殷 燕), Zhang Y-L (张运林), Shi Z-Q (时志强), et al. Estimation of spatial and seasonal changes in phytoplankton production in Meiliang Bay, Lake Taihu, based on the vertically generalized production model and MODIS data. Acta Ecologica Sinica (生态学报), 2012, 32(11): 3528-3537 (in Chinese) [64] Balch W, Evans R, Brown J, et al. The remote sensing of ocean primary productivity: Use of a new data compi-lation to test satellite algorithms. Journal of Geophysical Research: Oceans, 1992, 97: 2279-2293 [65] He L-H (何丽鸿), Wang H-Y (王海燕), Lei X-D (雷相东). Parameter Sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model. Chinese Journal of Applied Ecology(应用生态学报), 2016, 27(2): 412-420 (in Chinese) [66] Hu C, Carder KL, Muller-Karger FE. How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors. Remote Sensing of Environment, 2001, 76: 239-249 [67] Hu C, Feng L, Lee ZP, et al. Dynamic range and sensitivity requirements of satellite ocean color sensors: Learning from the past. Virtual Journal for Biomedical Optics, 2012, 51: 6045-6062 [68] Chavez FP, Messié M, Pennington JT. Marine primary production in relation to climate variability and change. Annual Review of Marine Science, 2011, 3: 227-260 [69] Pei S-F (裴绍峰), Laws EA, Ye S-Y (叶思源), et al. Study on the discrepancy in applying 14C tracer technique to measure marine primary productivity. Marine Sciences (海洋科学), 2014, 38(12): 149-156 (in Chinese) [70] Xing X-G (邢小罡), Zhao D-Z (赵冬至), Hervé C, et al. A new autonomous observation platform of marine biogeochemistry: Bio-Argo floats.Marine Environmental Science (海洋环境科学), 2012, 31(5): 733-739 (in Chinese) |