Abstract:

Aims: Taking the tributaries of the Qingyi River as the study site and using macroinvertebrates as indicator species, this study aims to investigate: (1) the extent of spatiotemporal beta diversity in this area and which components are dominant; (2) the primary environmental factors influencing spatiotemporal beta diversity; and (3) which species and sites are key species and key sites. 

Methods: Four surveys of biological and environmental factors were conducted in August 2023, May 2024, September 2024, and April 2025 at 16 sampling sites across five tributaries—Qingxi, Zhuxi, Machuan, Gufeng and Zhouhan River. Using abundance-based spatial beta diversity index (B_total) and temporal beta diversity index (TBI), methods such as Mantel test and variance partitioning were applied to explore the spatiotemporal beta diversity of macroinvertebrate communities and their environmental drivers. 

Results: (1) The average spatial beta diversity index (B_total) was 0.69, with turnover being the dominant factor (accounting for 55.8%). Across the entire study period (Summer 2023–Spring 2025), temporal beta diversity (TBI) did not reach statistical significance overall, although a significant increase in species richness was observed at a single site (S8). In the sub-period from Spring 2024 to Autumn 2024, species richness increased, and TBI reached a significant level overall. In the other two sub-periods (Summer 2023–Spring 2024 and Autumn 2024–Spring 2025), the overall change in TBI did not reach a significant level. (2) Spatial beta diversity (B_total) was primarily positively correlated with differences in substrate, river width and total phosphorus. Environmental factors collectively explained 19.0% of the variation in B_total, with substrate and water environment exhibiting relatively high explanatory power. Environmental factors collectively explained 5.9% of the variation in the turnover component (R_epl) and 5.1% of the variation in the nested component (Ab_diff), with substrate and water environment again exhibiting relatively high explanatory power. (3) Environmental factors collectively explained 21.8% of the variation in temporal beta diversity (TBI), primarily due to substrate, water environment, and their combined explanatory power. Environmental factors collectively explained 33.4% of the variation in beta diversity loss (B), with the water environment exhibiting a high explanatory power. Environmental factors collectively explained 20.4% of the variation in beta diversity gain (C), with substrate and water environment exhibiting high explanatory power. (4) Species with high species richness, such as those in the families Bithyniidae, Elmidae, Palaemonidae, Viviparidae, and Lymnaeidae, are key species influencing the spatiotemporal variation of regional macroinvertebrate communities. Sites in the lower reaches of tributaries such as S8 and S16, where human activity is frequent, the substrate is relatively homogeneous and species richness is relatively low, are key locations influencing the spatiotemporal variation of the regional community. 

Conclusion: The composition of macroinvertebrate communities in the tributaries of the Qingyi River basin exhibits significant spatial variation, with turnover being the dominant factor. Over the three-year period, there was a slight increase in community composition at all sampling sites, with the increase at S8 reaching statistical significance. However, the overall regional trend did not reach statistical significance. Substrate and water environment are the primary factors influencing the spatiotemporal variation in regional community composition. Species with high abundance are the key species influencing the spatiotemporal variation in regional communities. Sampling sites in the lower reaches of tributaries are the key locations influencing community spatiotemporal variation. The findings of this study can provide data support for the conservation of benthic invertebrate species diversity in regional rivers and also offer a theoretical reference for other similar regions.

Key words: macroinvertebrate, beta diversity, TBI, Mantel test, variance partitioning, Qingyi River