Abstract

The ecological heterogeneity created by river bends benefits the diversity of microorganisms, which is vital for the pollutant degradation and overall river health. However, quantitative tools capable of determining the interactions among different trophic levels and species are lacking, and research regarding ecological heterogeneity has been limited to a few species. By integrating the multi-species-based index of biotic integrity (Mt-IBI) and the structure equation model (SEM), an interactions-based prediction modeling framework was established. Based on DNA metabarcoding, a multi-species (i.e., bacteria, protozoans, and metazoans) based index of biotic integrity including 309 candidate metrics was developed. After a three-step screening process, eight core metrics were obtained to assess the ecological heterogeneity, quantitatively. The Mt-IBI value, which ranged from 2.08 to 7.17, was calculated as the sum of each single core metric value. The Mt-IBI revealed that the ecological heterogeneity of concave banks was higher than other sites. According to the result of the SEM, D90 was the controlling factor (r = −0.779) of the ecological heterogeneity under the influence of the river bends. The bend-induced redistribution of sediment particle further influenced the concentrations of carbon, nitrogen, and sulphur. The nitrogen group (r = 0.668) also played an essential role in determining the ecological heterogeneity, follow by carbon group (r = 0.455). Furthermore, the alteration of niches would make a difference on the ecological heterogeneity. This multi-species interactions-based prediction modeling framework proposed a novel method to quantify ecological heterogeneity and provided insight into the enhancement of ecological heterogeneity in river bends.

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