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.