Modelling and forecasting the effects of increasing sea surface temperature on coral bleaching in the Indo-Pacific region. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Khalil, Idham; Muslim, Aidy M.; Hossain, Mohammad Shawkat; Atkinson, Peter M.
• Is Part Of: International journal of remote sensing. Volume 44:Issue 1(2023)
• Page Start: 194
• Page End: 216
• Publication Date: 2023-01-02
• Subjects: SST -- space-time -- coral bleaching -- Coral Triangle -- South China Sea; Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2022.2161850
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: The Coral Triangle (CT) and the South China Sea (SCS) are the world's great tropical seas, located in the Indo-Pacific (IP) region. It is home to the richest marine ecosystem on Earth, with a total of 76% reef-building coral species as well as 37% coral reef fish species. Unfortunately, this sensitive area is now vulnerable to Sea Surface Temperature (SST) warming. This research explored the possible consequences of SST warming on the rich ecosystems of the IP region, specifically on bleaching of its coral reefs. Reefbase provided coral bleaching records together with the daily NOAA AVHRR Optimum Interpolation (OI) SST V2 dataset (OISSTv2) were used to explore the relationship between coral bleaching and SST in the IP region. Three different categories of monthly mean SST were tested as potential covariates: minimum SST, mean SST and maximum SST, obtained from the OISSTv2. The fitted logistic regression (LR) model revealed a significant and large correlation between coral bleaching and annual maximum monthly mean SST in the study area using the bleaching data from an online database and the time-series of AVHRR images. Predicted maps of coral bleaching based on the LR model were highly consistent with NOAA Coral Reef Watch (CRW) Degree heating Weeks (DHW) maps. However, some important discrepancies resulted from the more specific local fitting used in the LR model. The maximum SST was forecasted from 2020 to 2100 based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset under the Representative Concentration Pathways (RCP2.6) scenario. The fitted logistic regression model was employed to transform the forecasted maximum SST values into maps of the probability of coral bleaching from 2020 to 2100. The results provide considerable cause for concern, including the likelihood of widespread coral bleaching in many places in the IP region over the next 30 years.