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India has different bioclimatic zones and supports diverse aquatic habitats rich in biodiversity. For effective conservation of the endangered species in its habitat, it is essential to know the distribution of fish species in the environmental range, and for this, species distribution models are the efficient and innovative tools. The present study used the MaxEnt modeling technique for developing probability distribution models highlighting the distribution of fish species by analyzing the known occurrence records of Denison barb under genus Sahyadria (Sahyadria denisonii Day 1865 and Sahyadria chalakkudiensis (Menon et al., Rec Zool Surv India 97:61–63, 1999)) in relation to environmental variables typically incorporating seasonal and temporal variability. AUC of the models for Sahyadria species depicted good fitness. Both species were found sensitive to "solar radiation," "temperature seasonality," and "temperature annual range" and assessed as significant predictors. The sensitivity and distribution of both species to these environmental variables were found correlated with their breading and spawning seasons. "Precipitation" was determined as one of the significant climatic envelopes influencing the distribution of the species associated with river flow. The models showed the distribution of S. denisonii in the higher precipitation areas compared to S. chalakkudiensis. The probability distribution model with respect to the distribution of both species indicates a lineage barrier at Palghat Gap supporting the earlier studies. At the latitudinal scale, prediction of the suitable ecological habitat provides a detailed insight into the distribution of all genetic lineages of the genus Sahyadria. Evidently, the findings of this study can assist in determining ecological niches for endangered species of other areas and may aid in field surveys as well as developing conservation plans. [ABSTRACT FROM AUTHOR]

In order to assess the distribution pattern and understand the prevailing factors for predicting further expansion of an exotic fish Oreochromis niloticus, this study was undertaken in the Ganga river flowing through the state of Uttar Pradesh using MaxEnt model. The authors report the distribution pattern of O. niloticus and prevailing causative factors mounting the expansion of O. niloticus in the Ganges based on MaxEnt modeling technique. The presence only occurrence data-set for this invasive species was prepared from the field data and also from data collated from the authenticated publications of different fisheries researchers. The data-set was analyzed with environmental and topographical variables typically incorporating seasonal and temporal variability using MaxEnt, a maximum entropy algorithm which showed that the area under curve was much closer to 1 (0.999). The model predicted elevation as the most influential predictor variable with permutation importance of 69.2% followed by slope_steepness (10.1%), Tmax_1 (7.3%) and Srad_5 (6.8%). The findings from the results suggest that invasive O. niloticus tend to spread in rivers where elevation is lower as well as slope_steepness of the river is higher and thus indicated that invasion might be higher in the downstream of the river. The model suggests that topography and its derived variable are the most significant predictors for distribution of invasive O. niloticus. The results of this study also confirm that the water qualities of the Ganga river are suitable for O. niloticus and if the model is supplemented with water quality variables data, the influential predictor variable in water quality can be well investigated with permutation importance. [ABSTRACT FROM AUTHOR]