For example, the NOOA Coral Reef Watch Program uses the Degree Heating Week (DHW) metric, which is a thermal stress algorithm based on satellite-derived sea surface temperature. The DHW higher than 4 °C predicts the occurrence of coral bleaching [10]. However, recent studies show that the use of the thermal tresshold variable alone is unable to predict the susceptibility of corals to bleaching [8, 11]. The high variability of thermal threshold had “relatively weak or no significant relationships with coral cover and susceptibility” [8]. In addition, researchs on coral bleaching model tends to ignore the significance of joint probability of multivariate dependent variables. Therefore, we propose the first effort ever to develop temporal and spatial models of coral bleaching susceptibility based on copula …show more content…
It expected that copula models in this research will perform well to forecast coral bleaching events and could help coral reef managers to predict its spatial susceptibility in local or regional scopes. Therefore, three major studies of the proposed research are 1) analysing the multivariate return period of coral bleaching, 2) developing the spatial susceptibility prediction for risk assessment and 3) evaluating the performance of the coral bleaching susceptibility models. The multivariate analysis shall follow the remarkable work by De Michele et al. in 2013 [25], which introduce the concept of dynamic return period based on copula and calculated via Survival Kendall’s approach. Meanwhile, the spatial susceptibility prediction will develop through the spatial vine copula procedure by Gräler and Pebesma [26, 27]. Any form of modification could be applied under the investigation. Both of studies require the determination of the suitable variables, the availability of a good time series data, as well as the selection of appropriate copula families and