Spatial polychaeta habitat potential mapping using probabilistic models

Abstract

The purpose of this study was to apply probabilistic models to the mapping of the potential polychaeta habitat area in the Hwangdo tidal flat, Korea. Remote sensing techniques were used to construct spatial datasets of ecological environments and field observations were carried out to determine the distribution of macrobenthos. Habitat potential mapping was achieved for two polychaeta species, Prionospio japonica and Prionospio pulchra, and eight control factors relating to the tidal macrobenthos distribution were selected. These included the intertidal digital elevation model (DEM), slope, aspect, tidal exposure duration, distance from tidal channels, tidal channel density, spectral reflectance of the near infrared (NIR) bands and surface sedimentary facies from satellite imagery. The spatial relationships between the polychaeta species and each control factor were calculated using a frequency ratio and weights-of-evidence combined with geographic information system (GIS) data. The species were randomly divided into a training set (70%) to analyze habitat potential using frequency ratio and weights-of-evidence, and a test set (30%) to verify the predicted habitat potential map. The relationships were overlaid to produce a habitat potential map with a polychaeta habitat potential (PHP) index value. These maps were verified by comparing them to surveyed habitat locations such as the verification data set. For the verification results, the frequency ratio model showed prediction accuracies of 77.71% and 74.87% for P. japonica and P. pulchra, respectively, while those for the weights-of-evidence model were 64.05% and 62.95%. Thus, the frequency ratio model provided a more accurate prediction than the weights-of-evidence model. Our data demonstrate that the frequency ratio and weights-of-evidence models based upon GIS analysis are effective for generating habitat potential maps of polychaeta species in a tidal flat. The results of this study can be applied towards conservation and management initiatives for the macrofauna of tidal flats.