Global meta-analysis for controlling factors on carbon stable isotope ratios of lotic periphyton

Naoto F. Ishikawa, Hideyuki Doi, Jacques C. Finlay

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Carbon stable isotope ratios (δ13C) are widely used to trace resource transfer pathways, yet δ13C variation in freshwater autotrophs is not yet fully understood. We have analyzed data from 42 published studies, supplemented with some unpublished data, to show the determinants of lotic periphyton δ13C. At large spatial scales, we observed broad differences in periphyton δ13C among biomes and consistent longitudinal variation related to watershed area. Longitudinal increases in δ13C indicate the importance of in-stream processes on lotic carbon cycles and autotroph δ13C variation. At local spatial scales, periphyton δ13C was negatively related to canopy cover and water current velocity and positively related to chlorophyll a density. Autotroph δ13C varied among taxonomic groups. Cyanobacteria and red algae had significantly higher and lower δ13C than other taxa, respectively. A hierarchical model across spatial scales showed that local controls for periphyton δ13C were nested by regional controls, which suggested that productivity and CO2 availability determine δ13C. Overall, our results reveal general patterns of periphyton δ13C and provide improved information for study design and the use of δ13C in isotopic mixing models in lotic food web studies.

Original languageEnglish (US)
Pages (from-to)541-549
Number of pages9
JournalOecologia
Volume170
Issue number2
DOIs
StatePublished - Oct 2012

Bibliographical note

Funding Information:
Acknowledgments We thank C.M. Godwin and A.W. Walters for providing their unpublished data for the meta-analysis. Comments from R.O. Hall and an anonymous reviewer greatly improved the early draft of this manuscript. H. Doi and N.F. Ishikawa were financially supported by the Japan Society for the Promotion of Science to conduct this study.

Keywords

  • Local control
  • Lotic ecosystem
  • Regional control
  • Structural equation modeling

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