To explore impact on marine habitats caused by coastal pollution, predictive models of the Indo-Pacific humpback dolphin (Sousa chinensis) distribution were generated using the Maxent modelling approach, based on dolphin occurrence data in Sanniang Bay and its adjacent waters in Guangxi Province during 2006-2007, the independent oceanographic parameters derived from Google Earth Digital Elevation Model (DEM) and Landsat images, and the water environmental data from the marine investigation in 2012. Results indicated that the distance to the major river mouths was the strongest predictors, and water nutrition and persistent pollutants were the important factors for the dolphin distribution in both wet and dry seasons. Based on the results, habitat selection strategies of the dolphin were discussed: the dolphin tended to select estuaries with abundant prey and avoid highly polluted areas, which could be useful in designing Marine Protected Areas (MPAs) and formulating management strategies.

The aim of the current study is to construct the Remote Associates Test (RAT) in Chinese version, which is based on the theory of associative creativity. Item response theory (IRT) with Binary Logistic Models was used for item selection. Participants were 2659 middle-school students from Guangdong, Gansu, and Hubei Province. Based on the principle of Criterion-Referenced Test, the item difficulty was limited between ?3.00 and 3.00, the item discrimination was limited between 0.30 and 2.50, and the item information was above 0.20. In addition, the RAT scores were positively correlated with scores on the Torrance Test of Creativity, Runco Test, and Raven’s Standard Progressive Matrices. Results of RAT were also positively correlated with teachers’ evaluations of creativity and could significantly predict middle-school academic performance. Potential applications of RAT are also discussed.