Spatio-temporal variation of periphyton biomass and accumulation in a temperate spring-fed stream

Casey M. Godwin, Hunter J. Carrick

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27 Scopus citations

Abstract

Spatio-temporal variation of plant populations often can demonstrate synchronous patterns, particularly within highly connected landscapes. Periphyton biomass (chlorophyll a) and net accumulation were measured at five sites in a spring-fed fourth-order stream located in central Pennsylvania with a mixed land-uses watershed (Spring Creek, USA) to characterize longitudinal variation within the stream. Samples were collected at three-week intervals over one year to describe seasonal patterns of periphyton biomass and net production (n = 17 per site). Spring Creek periphyton biomass and net accumulation increased dramatically from the headwaters to downstream (range 10-1,000 mg/m2). The downstream reaches had exceptionally large algal biomass (chlorophyll a > 300 mg/m2) and potential for rapid turnover. Varying degrees of seasonality were observed among the sites, with upstream sites showing more temporal variation but no distinct seasonal pattern. Despite this, large-scale disturbances within the watershed seem to promote synchrony among sites throughout the stream as reflected by close correlations in chlorophyll values (Pearson correlation coefficient r > 0.50).

Original languageEnglish (US)
Pages (from-to)583-595
Number of pages13
JournalAquatic Ecology
Volume42
Issue number4
DOIs
StatePublished - Dec 2008

Bibliographical note

Funding Information:
Acknowledgements This work was funded by grants from the United States Geological Survey 01-HQGR-00-99 US Environmental Protection Agency IE060031 to H. Carrick. We thank R. Carline and D. DeWalle for reviewing a previous version of the manuscript. M. Johnston-Greenwald and C. Rilk assisted with field work and laboratory processing. The research was conducted in partial completion of a M.S. in Ecology by C. Godwin at Penn State University.

Keywords

  • Chlorophyll a
  • Hurricane Ivan
  • Periphyton
  • Spatio-temporal variation
  • Stream

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