Assessing Nonlinearity in Fish Habitat Preference of Japanese Medaka (Oryzias latipes) Using Genetic Algorithm ^|^ndash; Optimized Habitat Prediction Models

Abstract

present study assessed nonlinearity in habitat preferences of Japanese medaka (Oryzias latipes) using genetic algorithm-optimized fuzzy habitat preference models incorporating the environmental fac- tors of water depth (depth), current velocity (velocity), lateral cover ratio (cover), and percent vegetation coverage (vegetation). A linear relationship appeared between habitat preferences for cover and vegeta- tion, which suggest the independent relationship between two factors. The habitat preference for veloc- ity was found to have a nonlinear relationship with those for cover and vegetation, which appeared as different preference curves evaluated by the single-factor model. The habitat preference curves were affected by interactions between the environmental factors, especially those with nonlinear relation- ships, which resulted in different predictions of spatial distribution of the fish. Based on the present results, the use of a multiplex modeling approach, as applied in this study, would be appropriate to achieve better prediction accuracy, thus leading to more reliable habitat evaluation.