A diatom model for inferring sea level change in the coastal waters of Hong Kong

Diatoms were identified and enumerated from surface sediments of 25 sites in Double Haven, Hong Kong. The relationship between diatom species distribution and 14 environmental variables was examined using Detrended Correspondence Analysis (DCA) and Canonical Correspondence Analysis (CCA). Water depth was identified as the most important environmental variable influencing the distribution of diatoms in Double Haven. Subsequently a Weighted Average (WA) calibration model was developed to infer water depth. The reliability of the model was evaluated by the error of prediction (RMSEboot = 3.479) and the correlation (r(2) = 0.7342) between observed and diatom-inferred values. This predictive calibration model has the potential to infer past sea level change in Hong Kong and the adjacent coastal areas.