Dataset List

Vol.|Area

Data Details

Thermal Stress Prediction Dataset of Coral Reefs in South China Sea Islands (1982-2100)


CHEN Zhike1,2SU Fenzhen3ZUOXiuling*1
1Guangxi Laboratory on the Study of Coral Reefs in the South China Sea,School of Marine Sciences,Guangxi University,Nanning 530004,China2Heilongjiang Agricultural Reclamation Survey,Design and Research Institute,Harbin 150090,China3State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China

DOI:10.3974/geodb.2020.09.07.V1

Published:Dec. 2020

Visitors:1664       Data Files Downloaded:18      
Data Downloaded:216.96 MB      Citations:

Key Words:

chronic thermal stress,acute thermal stress,coral reef,South China Sea,Chinese Geographical Science,Acta Geographica Sinica,Scientia Geographica Sinica

Abstract:

Abnormal high sea surface temperature (SST) is the most widespread and threatening factor affecting coral reefs. Thermal stress prediction dataset of coral reefs in South China Sea Islands (1982-2100) was developed based on the SST data observed by NOAA AVHRR in 1982-2009 and the predicted SST data of the Second Generation Canadian Earth System Model (CanESM2) in CMIP5 in 2006-2100 in RCP4.5 and RCP8.5 scenarios in the South China Sea. The spatial patterns of chronic and acute thermal stress of coral reefs of the South China Sea Islands were extracted by using the linear regression method and the Degree Heating Weeks (DHW) index. The dataset includes: (1) chronic thermal stress data, which consists of the summer SST rise rate (℃/10a) observed by AVHRR in 1982-2009, and the summer SST rise rate (℃/10a) simulated by CanESM2 model in 2006-2100 under the scenarios of RCP4.5 and RCP8.5. (2) acute thermal stress, which consists of the accumulated time for which the ecosystem function is under reduced from acute stress events for all reef cells according to AVHRR observed time series in 1982-2009, monthly DHW and the years that reef locations start to experience bleaching conditions annually from March 2006 to December 2100 projected by CanESM2 model for RCP4.5 and RCP8.5 scenarios. The dataset is archived in .img data format, consists of 6862 data files with data size of 57.5 MB (Compressed to one single file with 12.0 MB). The analysis papers based on this dataset were published in Chinese Geographical Science, Vol. 75, No. 3, 2020, Acta Geographica Sinica, Vol. 75, No. 3, 2020, and Scientia Geographica Sinica, Vol. 40, No. 5, 2020.

Foundation Item:

National Natural Science Foundation of China (41801341); Guangxi Natural Science Foundation of China (2018JJB150030); Chinese Academy of Sciences (XDA13010400)

Data Citation:

CHEN Zhike, SU Fenzhen, ZUOXiuling*. Thermal Stress Prediction Dataset of Coral Reefs in South China Sea Islands (1982-2100)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020. https://doi.org/10.3974/geodb.2020.09.07.V1.

References:

[1] Hoegh-Guldberg, O. Climate change, coral bleaching and the future of the world's coral reefs [J]. Marine and freshwater research, 1999, 50: 839-866.
     [2] Hooidonk, R. V., Maynard, J. A., Planes, S. Temporary refugia for coral reefs in a warming world [J]. Nature Climate Change, 2013, 3: 508-511.
     [3] Sheppard, C., Sheppard, A., Mogg, A., et al. Coral bleaching and mortality in the Chagos Archipelago [J]. Atoll Research Bulletin, 2017: 1-26
     [4] Selig, E. R., Casey, K. S., Bruno, J. F. New insights into global patterns of ocean temperature anomalies: implications for coral reef health and management [J]. Global Ecology & Biogeography, 2010, 19: 397–411.
     [5] Liu, G., Strong, A. E., Skirving, W. Remote sensing of sea surface temperatures during 2002 Barrier Reef coral bleaching [J]. Eos, Transactions American Geophysical Union, 2003, 84: 137.
     [6] Magris, R. A., Heron, S. F., Pressey, R. L. Conservation planning for coral reefs accounting for climate warming disturbances [J]. Plos One, 2015, 10: e0140828.
     [7] Hooidonk, R. V., Huber, M. Quantifying the quality of coral bleaching predictions [J]. Coral Reefs, 2009, 28: 579-587.
     

Data Product:

ID Data Name Data Size Operation
1 ThermalStressCoralReefs_SCSIs.rar 12342.74KB
Co-Sponsors
Superintend