Review of coral reef bleaching monitoring technology based on SST

doi:10.6046/gtzyyg.2018.02.03

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Abstract

Influenced by the global warming,coral reef bleaching phenomenon is more and more serious and approximately 1/3 of the world’s coral is facing possible extinction. Sea water temperature anomaly is one of the most important causes of coral reef bleaching and mortality. NOAA has developed thermal stress satellite products for coral reef bleaching monitoring based on sea surface temperature(SST),including 50 km and 5 km spatial resolution. This paper presents the research status of coral reef bleaching,and introduces the methods and algorithms that NOAA has developed for monitoring coral reef bleaching. There is also a case study of coral reef bleaching monitoring in South China Sea based on NOAA’s coral reef bleaching monitoring products. It is shown that it is very probable that coral reef bleaching already occurred in the study area in June 2015. This paper expounds the necessity and urgency of exploring the related research on coral bleaching warning methods in China through research review and case study,and provides relevant research and technical reference.

Keywords coral reef bleaching bleaching hotspot degree heat week bleaching warning

TP79

Corresponding Authors: Yulin CAI E-mail: 1763571319@qq.com;yulin_cai@163.com

Issue Date: 30 May 2018

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	Xuan SUN
	Yulin CAI
	Linlin SUO
	Shangfeng JIA

Cite this article:

Xuan SUN,Yulin CAI,Linlin SUO, et al. Review of coral reef bleaching monitoring technology based on SST[J]. Remote Sensing for Land & Resources, 2018, 30(2): 21-28.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.02.03 OR https://www.gtzyyg.com/EN/Y2018/V30/I2/21

Fig.1 SST anomalies on Nov.4,2016

Fig.2 Coral reef bleaching hotspot on Nov.4,2016

Fig.3 Coral reef bleaching DHW on Nov.4,2016

Fig.4 Coral reef bleaching alert area on Nov.4,2016

Tab.1 Stress levels of coral reef bleaching alert areas

Fig.5 Monthly average of SST at point A in 2015

Fig.6 Daily value of SST at point A in June,2015

Fig.7 Bleaching hotspots of 6 days in June,2015

Fig.8 Degree heating weeks of 6 days in June,2015

Fig.9 Maximum of bleaching alert area of four weeks in June,2015

Fig.10 Map of the maximum of bleaching alert areas in June,2015

[1]	秦昭, 王汶松 . 珊瑚礁卑微生命筑造的地质奇观[J].中国国家地理, 2009(1):54-70. url: http://www.cqvip.com/Main/Detail.aspx?id=29800546
[1]	Qin Z, Wang W S . Coral reefs,geological wonders made of humble life[J].Chinese National Geography, 2009(1):54-70.
[2]	Liu G, Heron S F, Eakin C M , et al. Reef-scale thermal stress monitoring of coral ecosystems:New 5-km global products from NOAA coral reef watch[J]. Remote Sensing, 2014,6(11):11579-11606. doi: 10.3390/rs61111579 url: http://www.mdpi.com/2072-4292/6/11/11579
[3]	李淑, 余克服 . 珊瑚礁白化研究进展[J]. 生态学报, 2007,27(5):2059-2069. doi: 10.3321/j.issn:1000-0933.2007.05.047 url: http://www.cqvip.com/Main/Detail.aspx?id=24555630
[3]	Li S, Yu K F . Recent development in coral reef bleaching research[J]. Acta Ecologica Sinica, 2007,27(5):2059-2069.
[4]	潘艳丽, 唐丹玲 . 卫星遥感珊瑚礁白化概述[J]. 生态学报, 2009,29(9):5076-5080. doi: 10.3321/j.issn:1000-0933.2009.09.057 url: http://d.wanfangdata.com.cn/Periodical/stxb200909057
[4]	Pan Y L, Tang D L . General introduction to satellite remote sensing of coral reef bleaching[J]. Acta Ecologica Sinica, 2009,29(9):5076-5080.
[5]	Wilkinson C R.Status of Coral Reefs of the World: 2002[M]. Townsville:Australian Institute of Marine Science, 2002: 1-377.
[6]	Liu G, Strong A E, Skirving W.Remote sensing of sea surface temperatures during 2002 Barrier Reef coral bleaching[J]. EOS, 2003,84(15):137-144. doi: 10.1029/2003EO150001 url: http://doi.wiley.com/10.1029/2003EO150001
[7]	余克服 . 南海珊瑚礁及其对全新世环境变化的记录与响应[J]. 中国科学(地球科学), 2012,42(8):1160-1172.
[7]	Yu K F . Coral reefs in the South China Sea:Their response to and records on past environmental changes[J]. Science China (Earth Sciences), 2012,55(8):1217-1229.
[8]	Eakin C M, Morgan J A, Heron S F, et al.Caribbean corals in crisis:Record thermal stress, bleaching, and mortality in 2005[J]. PLoS One, 2010,5(11):e13969. doi: 10.1371/journal.pone.0013969 pmid: 21125021 url: http://dx.plos.org/10.1371/journal.pone.0013969
[9]	Wellington G M, Glynn P W, Strong A E , et al. Crisis on coral reefs linked to climate change[J]. EOS, 2001,82(1):1-5. doi: 10.1029/01EO00001 url: http://onlinelibrary.wiley.com/doi/10.1029/01EO00001/abstract
[10]	Goreau T, McClanahan T, Hayes R , et al.Conservation of coral reefs after the 1998 global bleaching event[J]. Conservation Biology, 2000,14(1):5-15. doi: 10.1046/j.1523-1739.2000.00011.x url: http://doi.wiley.com/10.1046/j.1523-1739.2000.00011.x
[11]	Wilkinson C R.Status of Coral Reefs of the World:2008[M]. Townsville: Australian Institute of Marine Science, 2008: 296-296.
[12]	Yonge C M, Nicholls A G.Studies on the Physiology of Corals:IV.the Structure,Distribution and Physiology of the Zooxanthellae[R].Scientific Reports/Great Barrier Reef Expedition 1928—1929, 1931,1:135-176.
[13]	朱葆华, 王广策, 黄勃 , 等. 温度、缺氧、氨氮和硝氮对3种珊瑚白化的影响[J]. 科学通报, 2004,49(17):1743-1748. doi: 10.3321/j.issn:0023-074X.2004.17.010 url: http://d.wanfangdata.com.cn/Periodical/kxtb200417010
[13]	Zhu B H, Wang G C, Huang B , et al. Effects of temperature,hypoxia,ammonia and nitrate on the bleaching among three coral species[J]. Chinese Science Bulletin, 2004,49(18):1923-1928.
[14]	Perez S F, Cook C B, Brooks W R . The role of symbiotic dinoflagellates in the temperature-induced bleaching response of the subtropical sea anemone Aiptasia pallida[J]. Journal of Experimental Marine Biology and Ecology, 2001,256(1):1-14. doi: 10.1016/S0022-0981(00)00282-3 pmid: 11137501 url: http://linkinghub.elsevier.com/retrieve/pii/S0022098100002823
[15]	Iglesias-Prieto R, Matta J L, Robins W A , et al. Photosynthetic response to elevated temperature in the symbiotic dinoflagellate Symbiodinium microadriaticum in culture[J]. Proceedings of the National Academy of Sciences of the United States of America, 1992,89(21):10302-10305. doi: 10.1073/pnas.89.21.10302 pmid: 11607337 url: http://www.pnas.org/cgi/doi/10.1073/pnas.89.21.10302
[16]	Bhagooli R, Hidaka M . Comparison of stress susceptibility of in hospite and isolated Zooxanthellae among five coral species[J]. Journal of Experimental Marine Biology and Ecology, 2003,291(2):181-197. doi: 10.1016/S0022-0981(03)00121-7 url: http://linkinghub.elsevier.com/retrieve/pii/S0022098103001217
[17]	Warner M E, Fitt W K, Schmidt G W . Damage to photosystem Ⅱ in symbiotic dinoflagellates:A determinant of coral bleaching[J]. Proceedings of the National Academy of Sciences of the United States of America, 1999,96(14):8007-8012. doi: 10.1073/pnas.96.14.8007 pmid: 10393938 url: http://www.pnas.org/cgi/doi/10.1073/pnas.96.14.8007
[18]	Lesser M P, Shick J M . Effects of irradiance and ultraviolet radiation on photoadaptation in the zooxanthellae of Aiptasia pallida:Primary production,photoinhibition,and enzymic defenses against oxygen toxicity[J]. Marine Biology, 1989,102(2):243-255. doi: 10.1007/BF00428286 url: http://link.springer.com/10.1007/BF00428286
[19]	Glynn P W, D’Croz L. Experimental evidence for high temperature stress as the cause of El Niño-coincident coral mortality[J]. Coral Reefs, 1990,8(4):181-191. doi: 10.1007/BF00265009 url: http://link.springer.com/10.1007/BF00265009
[20]	Berkelmans R, Willis B L . Seasonal and local spatial patterns in the upper thermal limits of corals on the inshore Central Great Barrier Reef[J]. Coral Reefs, 1999,18(3):219-228. doi: 10.1007/s003380050186 url: http://link.springer.com/10.1007/s003380050186
[21]	Strong A E, Liu G, Meyer J , et al.Coral reef watch 2002[J]. Bulletin of Marine Science, 2004,75(2):259-268.
[22]	Goreau T J, Hayes R L . Coral bleaching and ocean “Hot Spots”[J]. AMBIO - A Journal of the Human Environment, 1994,23(3):176-180.
[23]	Montgomery R S, Strong A E . Coral bleaching threatens ocean,life and coral bleaching[J]. EOS, 1994,75(13):145-147. url: http://www.mendeley.com/research/coral-bleaching-threatens-ocean-life-coral-bleaching/
[24]	Liu G, Rauenzahn J L, Heron S F , et al. NOAA Coral Reef Watch 50 km Satellite Sea Surface Temperature-Based Decision Support System for Coral Bleaching Management[R].NOAA Technical Report NESDIS 143,Washington, DC:NOAA, 2013: 33.
[25]	Strong A E, Barrientos C S, Duda C, et al. Improved satellite techniques for monitoring coral reef bleaching [C]//Proceedings of the 8th International Coral Reef Symposium.Panama:[s.n.], 1997.

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