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Retrospective stable isotope analysis reveals ecosystem responses to river regulation over the last century

  • University of New Mexico
  • Western Kentucky University

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Disruption of natural flow regimes, nutrient pollution, and other consequences of human population growth and development have impacted most major rivers of the world. Alarming losses of aquatic biodiversity coincide with human-caused river alteration, but effects of biotic homogenization on aquatic ecosystem processes are not as well documented. This is because unaltered systems for comparison are scarce, and some ecosystem-wide effects may take decades to manifest. We evaluated aquatic ecosystem responses to extensive riverfloodplain engineering and nutrient addition in the Rio Grande of southwestern North America as revealed by changes in trophic structure of, and resource availability to, the fish community. Stable Isotope Analysis (SIA) was conducted on museum-preserved fishes collected over a 70-year period of intensive river management and exponential human population growth. Trophic complexity and resource heterogeneity for fish consumers (measured as "isotopic niche breadth") decreased following sediment deprivation and channelization, and these effects persist into the present. Increased nutrient inputs led to δ15N enrichment in the entire fish community at all affected sites, and a shift to autochthonous sources of carbon at the most proximal site downstream of wastewater release, probably via bottom-up transfer. Overall, retrospective SIA of apex consumers suggests radical change and functional impairment of a floodplain river ecosystem already marked by significant biodiversity loss.

Original languageEnglish
Pages (from-to)3213-3226
Number of pages14
JournalEcology
Volume96
Issue number12
DOIs
StatePublished - Dec 2015

Keywords

  • Ecosystem size
  • Food web
  • Heterogeneity
  • Isotopic niche
  • Rio Grande
  • Stable isotope analysis (SIA)
  • Time series

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