Assessing transferability of genetic algorithm-optimized fuzzy habitat preference models for Japanese medaka (Oryzias latipes)

The present study assessed the transferability of genetic algorithm-optimized fuzzy habitat preference models for Japanese medaka (Oryzias latipes), a freshwater fish dwelling in agricultural canals in Japan. By using three independent data sets from field surveys, three models were developed and evaluated with respect to model accuracy and transferability. As a result, all the habitat preference curves showed similar preference at deeper depth, lower velocity, larger cover and smaller vegetation. Despite this similar trend, the model accuracy and transferability differed among the models, which would be ascribed to site-specificity in physical environment and quality of data. Further studies would be necessary to reduce the effects of site-specificity and data quality for improving the present models.

[1]  Francisco Herrera,et al.  Genetic fuzzy systems: taxonomy, current research trends and prospects , 2008, Evol. Intell..

[2]  H. Van Dyck,et al.  Transferability of Species Distribution Models: a Functional Habitat Approach for Two Regionally Threatened Butterflies , 2007, Conservation biology : the journal of the Society for Conservation Biology.

[3]  Kazuaki Hiramatsu,et al.  Fuzzy neural network model for habitat prediction and HEP for habitat quality estimation focusing on Japanese medaka (Oryzias latipes) in agricultural canals , 2006, Paddy and Water Environment.

[4]  Kazuaki Hiramatsu,et al.  An information-theoretic approach for model selection in habitat preference evaluation of Japanese medaka (Oryzias latipes) , 2006 .

[5]  Kazuaki Hiramatsu,et al.  Prediction ability and sensitivity of artificial intelligence-based habitat preference models for predicting spatial distribution of Japanese medaka (Oryzias latipes) , 2008 .

[6]  Ari Huusko,et al.  Transferability of habitat suitability criteria of juvenile Atlantic salmon (Salmo salar) , 2002 .

[7]  Paul L. Angermeier,et al.  Factors influencing behavior and transferability of habitat models for a benthic stream fish , 1997 .

[8]  Matthias Schneider,et al.  Fuzzy based Models for the Evaluation of Fish Habitat Quality and Instream Flow Assessment , 2001 .

[9]  Matthias Schneider,et al.  Fish habitat modelling as a tool for river management , 2007 .

[10]  Shinji Fukuda,et al.  Assessing Nonlinearity in Fish Habitat Preference of Japanese Medaka (Oryzias latipes) Using Genetic Algorithm-Optimized Habitat Prediction Models , 2008 .

[11]  Shinji Fukuda,et al.  Consideration of fuzziness: is it necessary in modelling fish habitat preference of Japanese medaka (Oryzias latipes)? , 2009 .

[12]  Bernard De Baets,et al.  Prevalence-adjusted optimisation of fuzzy habitat suitability models for aquatic invertebrate and fish species in New Zealand , 2009, Ecol. Informatics.

[13]  B. Baets,et al.  Fuzzy rule-based macroinvertebrate habitat suitability models for running waters , 2006 .

[14]  Ari Huusko,et al.  Transferability of habitat preference criteria for larval European grayling (Thymallus thymallus) , 2004 .

[15]  Bernard De Baets,et al.  Interpretability-preserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study , 2007, Int. J. Approx. Reason..

[16]  A. Huusko,et al.  Changes in movement, range and habitat preferences of adult grayling from late summer to early winter , 2004 .

[17]  Peter Goethals,et al.  Fuzzy knowledge-based models for prediction of Asellus and Gammarus in watercourses in Flanders (Belgium) , 2006 .

[18]  Sovan Lek.  Uncertainty in ecological models , 2007 .

[19]  A. Huusko,et al.  Size-related changes in habitat selection by larval grayling (Thymallus thymallus L.) , 2003 .

[20]  Daniel Boisclair,et al.  Assessment of the transferability of biological habitat models for Atlantic salmon parr (Salmo salar) , 2003 .

[21]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[22]  William Silvert,et al.  Fuzzy indices of environmental conditions , 2000 .

[23]  Matthias Schneider,et al.  Optimisation of a fuzzy physical habitat model for spawning European grayling ( Thymallus thymallus L.) in the Aare river (Thun, Switzerland) , 2008 .

[24]  Bernard De Baets,et al.  Prevalence-adjusted optimisation of fuzzy models for species distribution , 2009 .