4.7 Article

Stable isotopes reveal effects of natural drivers and anthropogenic pressures on isotopic niches of invertebrate communities in a large subtropical river of China

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 27, Issue 29, Pages 36132-36146

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-020-09252-8

Keywords

East River; Layman metrics; SIBER; MixSIAR; Functional feeding group; Nitrogen pollution; Biological indicator

Funding

  1. National Natural Science Foundation of China [51909107, U1501235]
  2. China Postdoctoral Science Foundation [2019 M653284]
  3. Science and Technology Program of Guangzhou [201704020158]
  4. China Innovation & Entrepreneurship Competition for Undergraduate [S201910559065, CX2019040]
  5. National Science and Technology Major Project for Water Pollution Control and Treatment [2012ZX07206-006]
  6. Knowledge Innovation Program of Shenzhen [JCYJ20160526162154729]

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Isotopic niches reflect the basic structure and functioning of river food webs; however, their response to riverine environments remains unclear. We used stable isotope analysis and community-wide metrics to quantify how invertebrate niches vary with environmental changes along a large subtropical river in China. Eight niche metrics, which had higher values in the wet than in the dry season, increased from headwaters to the middle river and decreased sharply near the estuarine industrial zones. The delta C-13 value of > - 23.8 parts per thousand, which indicated consumption of epilithic diatoms, separated the invertebrates between the upper and mid-lower reaches. The delta N-15 values > 9.4 parts per thousand identified site-specific nitrogen sources from manure (e.g., animal effluent) and domestic sewage in agricultural area. The output of mixing models showed a downstream shift in carbon utilization by invertebrates from autochthonous periphyton and submerged hydrophytes to allochthonous C3 plants. Principle component (PC) and cluster analysis decomposed and grouped 40 environmental variables into 4 PCs that explained 84.5% of the total variance. Hierarchical partitioning revealed that the second and first PCs, which were driven mainly by biological indicators and habitat characteristics, had the highest explanatory power for niche ranges and areas (e.g., Bayesian ellipse), respectively. Our results suggest that reducing anthropogenic pressures (e.g., habitat loss and water pollution) on river ecosystems through measures, such as protecting diatom-dominated biofilms in riffles and controlling nitrogen loading in rural regions, may produce the greatest impact for river management.

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