Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city

Abstract

Summary Aquatic ecological rehabilitation is increasingly attracting considerable public and research attention. An effective method that requires less data and expertise would help in the assessment of rehabilitation potential and in the monitoring of rehabilitation activities as complicated theories and excessive data requirements on assemblage information make many current assessment models expensive and limit their wide use. This paper presents an assessment model for restoration potential which successfully links hydrologic, physical and chemical habitat factors to fish assemblage attributes drawn from monitoring datasets on hydrology, water quality and fish assemblages at a total of 144 sites, where 5084 fish were sampled and tested. In this model three newly developed sub-models, integrated habitat index (IHSI), integrated ecological niche breadth (INB) and integrated ecological niche overlap (INO), are established to study spatial heterogeneity of the restoration potential of fish assemblages based on gradient methods of habitat suitability index and ecological niche models. To reduce uncertainties in the model, as many fish species as possible, including important native fish, were selected as dominant species with monitoring occurring over several seasons to comprehensively select key habitat factors. Furthermore, a detrended correspondence analysis (DCA) was employed prior to a canonical correspondence analysis (CCA) of the data to avoid the “arc effect” in the selection of key habitat factors. Application of the model to data collected at Jinan City, China proved effective reveals that three lower potential regions that should be targeted in future aquatic ecosystem rehabilitation programs. They were well validated by the distribution of two habitat parameters: river width and transparency. River width positively influenced and transparency negatively influenced fish assemblages. The model can be applied for monitoring the effects of fish assemblage restoration. This has large ramifications for the restoration of aquatic ecosystems and spatial heterogeneity of fish assemblages all over the world.