Mass coral mortality under local amplification of 2 °C ocean warming.
A 2 °C increase in global temperature above pre-industrial levels is considered a reasonable target for avoiding the most devastating impacts of anthropogenic climate change. In June 2015, sea surface temperature (SST) of the South China Sea (SCS) increased by 2 °C in response to the developing Pacific El Niño. On its own, this moderate, short-lived warming was unlikely to cause widespread damage to coral reefs in the region, and the coral reef "Bleaching Alert" alarm was not raised. However, on Dongsha Atoll, in the northern SCS, unusually weak winds created low-flow conditions that amplified the 2 °C basin-scale anomaly. Water temperatures on the reef flat, normally indistinguishable from open-ocean SST, exceeded 6 °C above normal summertime levels. Mass coral bleaching quickly ensued, killing 40% of the resident coral community in an event unprecedented in at least the past 40 years. Our findings highlight the risks of 2 °C ocean warming to coral reef ecosystems when global and local processes align to drive intense heating, with devastating consequences.
Massachusetts Institute of Technology/Woods Hole Oceanographic Institution Joint Program in Oceanography/Applied Ocean Science and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.
Thomas M
TM
DeCarlo
Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.
Anne L
AL
Cohen
Research Center for Environmental Changes, Academia Sinica, 128 Academia Road Section 2, Nankang, Taipei 115, ROC, Taiwan.|Old Dominion University, Norfolk, VA, USA.
George T F
GT
Wong
University of California, Irvine, California, USA.
Kristen A
KA
Davis
Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA.
Pat
P
Lohmann
National Sun Yat-sen University, Kaohsiung, ROC, Taiwan.
Keryea
K
Soong
D000818:Animals; D037421:Anthozoa / Q000502:physiology*; D002681:China; D002980:Climate; D057894:Coral Reefs; D017753:Ecosystem; D059000:El Nino-Southern Oscillation; D006358:Hot Temperature; D015233:Models, Statistical; D010140:Pacific Ocean; D012623:Seawater; D013312:Stress, Physiological