An expanded weighted-averaging model for inferring past total phosphorus concentrations from diatom assemblages in eutrophic British Columbia (Canada) lakes

Euan D. Reavie, Roland I. Hall, John P. Smol

Research output: Contribution to journalArticlepeer-review

107 Scopus citations

Abstract

Eighteen lakes were added to a published training set of 46 British Columbia (BC) lakes in order to expand the original range of total phosphorus (TP) concentrations. Canonical correspondence analysis (CCA) was used to analyze the relationship between diatom assemblages and environmental variables. Specific conductivity and [TP] each explained significant (P≤0.05) directions of variance in the distribution of the diatoms. The relationship between diatom assemblages and [TP] was sufficiently strong to warrant the development of a weighted-averaging (WA) regression and calibration model that can be used to infer past trophic status from fossil diatom assemblages. The relationship between observed and inferred [TP] was not improved by the addition of more eutrophic lakes, however the [TP] range and the number of taxa used in the transfer function are now superior to the original model. Diatom species assemblages changed very little in lakes with TP concentrations greater than 85 μg 1-1, so we document the development of a model containing lakes with TP≤85 μg 1-1. The updated model uses 59 training lakes and covers a range of species optima from 6 to 41.9 μg 1-1 TP, and a total of 150 diatom taxa. The updated inference model provided a more realistic reconstruction of the anthropogenic history of a highly eutrophic BC lake. The model can now be used to infer past nutrient conditions in other BC lakes in order to assess changes in trophic status.

Original languageEnglish (US)
Pages (from-to)49-67
Number of pages19
JournalJournal of Paleolimnology
Volume14
Issue number1
DOIs
StatePublished - Jul 1 1995

Keywords

  • British Columbia
  • diatoms
  • eutrophication
  • lake management
  • lakes
  • paleolimnology
  • phosphorus
  • training sets

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