Functional Trait Analysis and the Multi-metric Integrity Model, Based on Stream Fish Indicators, and Their Relations to Chemical Water Quality

Abstract

Functional trait and biological integrity approaches in stream ecology enable the determination and prediction of aquatic community responses to a variety of environmental stressors, such as chemical pollution, habitat disturbance, and biological invasion. Here, we used multi-trait based functional groups (FGs) to predict the functional responses of fish assemblages to the physicochemical and ecological health gradients in a temperate stream. The multi-metric biological integrity model (mIBI model) was used to evaluate stream ecological health. The FGs were derived from the distance matrix of trophic, tolerance, and physical habitat traits among fish species. The leading water quality indicators (conductivity [EC], total suspended solids [TSS], and chlorophyll-a [CHL-a]) varied conspicuously with the stream gradient and anthropogenic pollution. The multi-metric water-pollution index (mWPI) showed differences in chemical health from upstream to downstream. Monsoon precipitation may have affected the variations in fish species and associated changes linked to irregular chemical health. The fish FGs varied more by space (longitudinal) than by season (premonsoon and postmonsoon). Functional metrics, which reflected trophic and tolerance traits, as well as vertical position preference, were strongly correlated with water quality degradation downstream. Changes were evident in FG (II, III, and IV) combinations from the upstream to downstream reaches. Furthermore, the structure of the fish assemblages from FG-II and FG-III was significantly correlated with chemical (R² = 0.43 and 0.35, p < 0.001) and ecological health (R² = 0.69 and 0.66, p < 0.001), as well as the metrics of mWPI. In conclusion, the results indicate significant variations in both trait-based FGs and biological integrity among stream-fish communities, influenced by chemical water quality gradients. The causes included longitudinal zones and intensifying degradation of water quality downstream. Therefore, multi-trait based FGs can facilitate ecological health assessment and develop the mIBI model based on fish assemblages by reflecting the prevailing chemical health status of streams and rivers.