Analysis of Multitrophic Biodiversity Patterns in the Irtysh River Basin Based on eDNA Metabarcoding

In freshwater ecosystems, cross-trophic interactions among biological communities underpin ecosystem stability and functionality. In arid and semi-arid rivers, however, hydrological fluctuations, invasive species, and other perturbations exacerbate the complexity of biological processes. To systematically assess the community structure of fish, eukaryotic plankton, and prokaryotic microorganism in the Irtysh River basin, this study employed environmental DNA (eDNA) metabarcoding for monitoring. High-throughput sequencing of taxa within the study area was conducted via eDNA metabarcoding, coupled with random forest and linear mixed models to dissect the effects of community structure. The eDNA approach effectively unraveled spatial patterns of biodiversity and identified taxon-specific diversity hotspots: invasive fish exerted a facilitative effect on algae and suppressed the richness of protozoa, fungi, and heterotrophic microorganisms, yet had minimal impact on the dominant structure of autotrophic microorganisms. These findings provide a scientific basis for basin-scale ecological management, emphasizing the necessity of balancing habitat preservation and invasive-species control to safeguard ecosystem functionality.

Authors

Institutions

Publication Details

Journal
Biology
Published
2025-11-24
DOI
https://doi.org/10.3390/biology14121661
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Multitrophic Biodiversity Patterns in the Irtysh River Basin Based on eDNA Metabarcoding

Tianjian Song, Yuna Zhang, Yu Liu, Jiang Chang et al.
Biology
Environmental DNA in Biodiversity Studies
article

Analysis of Multitrophic Biodiversity Patterns in the Irtysh River Basin Based on eDNA Metabarcoding

Tianjian Song, Yuna Zhang, Yu Liu, Jiang Chang, Hongyang Zhou, Fangze Zi, Ye Chen, Lei Fang, Yuxin Huang
article en

Abstract

In freshwater ecosystems, cross-trophic interactions among biological communities underpin ecosystem stability and functionality. In arid and semi-arid rivers, however, hydrological fluctuations, invasive species, and other perturbations exacerbate the complexity of biological processes. To systematically assess the community structure of fish, eukaryotic plankton, and prokaryotic microorganism in the Irtysh River basin, this study employed environmental DNA (eDNA) metabarcoding for monitoring. High-throughput sequencing of taxa within the study area was conducted via eDNA metabarcoding, coupled with random forest and linear mixed models to dissect the effects of community structure. The eDNA approach effectively unraveled spatial patterns of biodiversity and identified taxon-specific diversity hotspots: invasive fish exerted a facilitative effect on algae and suppressed the richness of protozoa, fungi, and heterotrophic microorganisms, yet had minimal impact on the dominant structure of autotrophic microorganisms. These findings provide a scientific basis for basin-scale ecological management, emphasizing the necessity of balancing habitat preservation and invasive-species control to safeguard ecosystem functionality.

BiologyVol. 14(12)
Beijing Normal University (CN), Chongqing Academy of Environmental Science (CN), Chinese Research Academy of Environmental Sciences (CN), Anhui Normal University (CN), Beijing University of Chemical Technology (CN), Lanzhou University (CN)
Openalex Percentile: Top 65%
Environmental DNA in Biodiversity Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.