Effect of data quality on habitat preference evaluation for Japanese medaka (Oryzias latipes) using a simple genetic fuzzy system

This study compared the habitat preference curves (HPCs) and prediction ability of fuzzy habitat preference models (FHPM) for Japanese medaka (Oryzias latipes) so as to clarify the effect of two different types of data: log-transformed fish population density (LOG) and presence-absence (P/A) data. The results differed by the data sets used and types of data, in which LOG-based models were found to be better in calibration, while P/A-based models were better in validation. Each type of data has merits and demerits. Further studies would be needed to improve present models so that same conclusion could be derived in habitat evaluation using either LOG or P/A data.