Use of Extant Populations of Scaled Chrysophytes for the Inference of Lakewater pH

Abstract

Abundance of living populations of scaled chrysophytes were used to develop multiple regression models for inferring lakewater pH. Until now, all such inference models had been prepared with surface sediment remains and used to reconstruct historical (down-core) changes. We demonstrate that highly significant models can be prepared from living populations of scaled-chrysophytes which could be valuable for monitoring chronic, episodic and/or long-term changes in lakewater pH. Average weighted-mean pH and a cluster analysis technique were used to divide 33 taxa found in 26 Connecticut lakes into groups according to their distribution along a pH gradient. Two calculations of average weighted-mean pH were made; one based on data from this study and one from literature records. Inference models were developed using a single sample from each lake as well as for multiple samples collected throughout the year. The best model based on a single discrete sample yielded an R² = 0.58 (p < 0.05); multiple samples from each lake yielded significantly higher R² values, (between 0.75 and 0.83). Scaled chrysophytes appear to be a very valuable assemblage of indicator organisms for the long-term monitoring of lakes.