The effects of nutrients and hydrology on periphyton and phytoplankton in Fraser River tributaries, British Columbia
type: CreativeWork
description: Physical and chemical variables were measured in riffle zones of 20 Fraser River tributaries, British Columbia, to examine which factors explain variation in algal biomass and taxonomic composition. July epilithic periphyton chlorophyll a was weakly correlated with TN, while October periphyton was significantly related to DP and conductivity. The phytoplankton biomass in July was best predicted by TP (r2 = 0.70, p &le; 0.001, n = 19), while October phytoplankton was best predicted by a multiple regression with conductivity, current velocity and TN. In terms of taxonomic composition in October, Bacillariophyta was most abundant, followed by Chlorophyta, Cyanobacteria and Phaeophyta. DP and current velocity explained 25% of the taxonomic variation among the rivers in a CCA. While changes in the relative abundance of specific diatom taxa were observed, shifts in division dominance were not. River algal biomass could be predicted from environmental variables, however the empirical models differed between July and October.
abstract: Physical and chemical variables were measured in riffle zones of 20 Fraser River tributaries, British Columbia, to examine which factors explain variation in algal biomass and taxonomic composition. July epilithic periphyton chlorophyll a was weakly correlated with TN, while October periphyton was significantly related to DP and conductivity. The phytoplankton biomass in July was best predicted by TP (r2 = 0.70, p &le; 0.001, n = 19), while October phytoplankton was best predicted by a multiple regression with conductivity, current velocity and TN. In terms of taxonomic composition in October, Bacillariophyta was most abundant, followed by Chlorophyta, Cyanobacteria and Phaeophyta. DP and current velocity explained 25% of the taxonomic variation among the rivers in a CCA. While changes in the relative abundance of specific diatom taxa were observed, shifts in division dominance were not. River algal biomass could be predicted from environmental variables, however the empirical models differed between July and October.
author: Kingsley, Marianne
language: en
keywords: Biology, Ecology., Hydrology., Biogeochemistry.
identifier: Source: Masters Abstracts International, Volume: 43-06, page: 2078.
date published: 2013-11-07T17:25:33Z
date modified: 2026-07-24T03:39:27Z
provider: University of Ottawa
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Ottawa (Canada)

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10393/26678

PropertyValue
property ID: DOI
value: 10.20381/ruor-9740