Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool for water management planning, especially in terms of requirements of the Water Framework Directive. Therefore, model verification studies, which investigate the accuracy and reliability of the results generated, are essential. An electrofishing survey was conducted in September 2014 on the Stura di Demonte River located in north-western Italy. One hundred and sixteen bullhead—Cottus gobio L.—were captured in 80 pre-exposed area electrofishing (PAE) grids. Observations of bullhead distribution in various habitats were used to validate MesoHABSIM model predictions created with inductive and deductive habitat suitability indices. The inductive statistical models used electrofishing data obtained from multiple mountainous streams, analyzed with logistic regression. The deductive approach was based on conditional habitat suitability criteria (CHSC) derived from expert knowledge and information gathered from the literature about species behaviour and habitat use. The results of model comparison and validation show that although the inductive models are more precise and reflect site- and species-specific characteristics, the CHSC model provides quite similar results. We propose to use inductive models for detailed planning of measures that could potentially impair riverine ecosystems at a local scale, since the CHSC model provides general information about habitat suitability and use of such models is advised in pre-development or generic scale studies. However, the CHSC model can be further calibrated with localized electrofishing data at a lower cost than development of an inductive model.
Habitat Suitability Modelling of Endangered Kashmir Grey Langur (Semnopithecus ajax) in North Kashmir, India
