Fig. 1. Map showing the Jingui River Basin located in the People’s Republic of China(a); The wet season(b). The normal season(c). The dry season(d).
Environmental factors
The water temperature (WT, °C), conductivity (Cond, μS/m), dissolved oxygen (DO, %), ammonia nitrogen (NH4+-N, mg/L), and Nitrogen (NO3--N, mg/L) were measured in situ using a portable multi-parameter probe water quality analyzer (YSI Professional Plus, USA). The turbidity (Tur, NTU) and pH value were measured on-site with a portable turbidimeter (Hach 2100Q, China) and a portable pH meter (Ohaus ST20, China), respectively. The water velocity (Vel, m/s) was measured by a portable velocity analyzer (LS-300A, China), and water depth and river width were measured using a graduated measuring rod and a laser rangefinder (Trueyard SP1500H, China). The integrated water samples were collected at each location and then stored in a cool box before arriving at the laboratory to determine the chemical compositions, including total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (CODMn).
The detrital and macrophyte cover in each site was investigated by wading and expressed as a percentage. Substratum composition was visually evaluated and expressed as a percentage based on the following categories: boulder (> 256 mm), cobbles (64 - 256 mm), pebbles (32 - 64 mm), gravel (2 - 32 mm), and sand and silt (< 2 mm)(Lin et al., 2022).
Data analysis
Parameters based on the macroinvertebrate data and identifications of three inter seasonal differences were subjected to the one-way analysis of variances (Tomanova et al.). The Pearson correlation analysis (PCA) was employed to analyze the relationship between macroinvertebrate abundance, biomass, and environmental factors of the Jingui River based on the International Business Machine (IBM) Statistic Package for Social Science (SPSS) 24.0. The species diversity indices included species richness (S ), the Shannon-Wiener diversity index (H’ )(Shannon, 1997), the Margalef’s richness index (dM )(Margalef, 1978), the Pielou’s evenness index (J )(Pielou, 1966), the Simpson’s diversity index (D )(Simpson et al., 1997) and dominance index (Y )(Yan et al., 2017). They all were calculated by using the PRIMER 6.0.
The functional diversity (FD) indices included functional richness (FRic), functional evenness (FEve), functional dispersion (FDis), and Rao, a secondary entropy (RaoQ index) in this work. FRic and FEve represent the amount and regularity of niche space occupied by the community, respectively, which were determined by the distribution of each species’ abundance through niche space. FDis is a multiple simulation of weighted average absolute deviation and is not affected by the species richness. RaoQ reflects the community diversity and distinction(Baker et al., 2021; Casanoves et al., 2011). The “dbFD” function from the functional diversity package in R (version 4.0.0) was selected to construct the functional diversity index system.
The relations among species diversity, physicochemical characteristics, and functional diversity were examined using the stepwise multiple regression analysis. Before analysis on the selected predictors, the potential collinear predictors were identified and removed (R≥0.70), and the significance level was set at 0.05(Xiang et al., 2022). The data that support the findings of this study are openly available in repository name “figshare” at http://doi.org/10.6084/m9.figshare.22277359.
Results
3.1 Environmental variables
Environmental factors of the Jingui River exhibited significant changes in wet season, normal season, and dry season (Table 1). Great differences were detected in WT, Vel, Cond, NH4+-N, NO3--N, TN, TP, and CODMn of the river in the three seasons (P <0.05). WT, Cond, NO3--N, TP, TN, and pH value reached peaks in wet season. By contrast, DO and NH4+-N were higher in dry season than those in wet season and normal season. The river bottom environments exhibited considerable variation among Cobble, Macrophytes, Moss, Woody debris, and leaf packs (P <0.05). The remaining environmental factors presented no significant differences.
Table 1 Environmental factors of the Jingui River in three different seasons.