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Modeling the growth dynamics of Clad...

Higgins, Scott Neil.

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Modeling the growth dynamics of Cladophora in eastern Lake Erie.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling the growth dynamics of Cladophora in eastern Lake Erie./
Author:	Higgins, Scott Neil.
Description:	169 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-04, Section: B, page: 1851.
Contained By:	Dissertation Abstracts International66-04B.
Subject:	Biology, Ecology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR01254
ISBN:	0494012544

Modeling the growth dynamics of Cladophora in eastern Lake Erie.
Higgins, Scott Neil.

Modeling the growth dynamics of Cladophora in eastern Lake Erie. - 169 p.

Source: Dissertation Abstracts International, Volume: 66-04, Section: B, page: 1851.

Thesis (Ph.D.)--University of Waterloo (Canada), 2005.

Cladophora glomerata is a filamentous green alga that currently forms extensive blooms in nearshore areas of Lake Ontario, eastern Lake Erie, Lake Michigan, and isolated locations in Lake Huron. The biomass, areal coverage, algal bed characteristics, and tissue phosphorus concentrations of Cladophora glomerata were measured at 24 nearshore rocky sites along the northern shoreline of Lake Erie's eastern basin between 1995--2002. Midsummer areal coverage at shallow depths (≤5m) ranged from 4--100%, with a median value of 96%. Peak seasonal biomass ranged from <1 to 940 g m-2 dry mass (DM), with a median value of 171 g m -2 DM. Tissue phosphorus varied seasonally, with initial high values in early May (0.15 to 0.27% DM; median 0.23% DM) to midsummer seasonal low values during peak biomass (0.03 to 0.23% DM; median 0.06% DM). A numerical Cladophora growth model (CGM) was revised and field-tested at 5 sites in eastern Lake Erie during 2002. The CGM is useful for: (1) Predicting Cladophora growth, biomass, and tissue phosphorus concentrations under non-point source P loading with no depth restrictions; (2) providing estimates of the timing and magnitude of the midsummer sloughing phenomenon; (3) determining the contribution of Dreissena invasion to the resurgence of Cladophora in eastern Lake Erie; and (4) developing management strategies for Cladophora abatement. The CGM was applied to investigate how the spatial and temporal patterns of Cladophora growth were influenced by the natural variability in environmental parameters in eastern Lake Erie. Seasonal patterns in Cladophora growth were strongly influenced by temperature, and peak depth-integrated biomass was strongly influenced by both available light and phosphorus. The photosynthetic capacity of field collected Cladophora was a poor predictor of the mid-summer sloughing phenomenon. The CGM, however, predicted that self-shading within the dense Cladophora mats would have caused negative growth rates at the base of the dense mats for 14 days prior to the sloughing event. The metabolic imbalances at the base of the Cladophora mats were driven primarily by the availability of light and were exacerbated by intermediate water temperatures (&sim;23°C). The excellent agreement between model simulations and field data illustrates the ability of the CGM to predict tissue P and growth over a range of sites and depths in eastern Lake Erie and suggests potential for the model to be successfully applied in other systems.

ISBN: 0494012544Subjects--Topical Terms:

1017726
Biology, Ecology.

Modeling the growth dynamics of Cladophora in eastern Lake Erie.
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500 $a Source: Dissertation Abstracts International, Volume: 66-04, Section: B, page: 1851.
502 $a Thesis (Ph.D.)--University of Waterloo (Canada), 2005.
520 $a Cladophora glomerata is a filamentous green alga that currently forms extensive blooms in nearshore areas of Lake Ontario, eastern Lake Erie, Lake Michigan, and isolated locations in Lake Huron. The biomass, areal coverage, algal bed characteristics, and tissue phosphorus concentrations of Cladophora glomerata were measured at 24 nearshore rocky sites along the northern shoreline of Lake Erie's eastern basin between 1995--2002. Midsummer areal coverage at shallow depths (≤5m) ranged from 4--100%, with a median value of 96%. Peak seasonal biomass ranged from <1 to 940 g m-2 dry mass (DM), with a median value of 171 g m -2 DM. Tissue phosphorus varied seasonally, with initial high values in early May (0.15 to 0.27% DM; median 0.23% DM) to midsummer seasonal low values during peak biomass (0.03 to 0.23% DM; median 0.06% DM). A numerical Cladophora growth model (CGM) was revised and field-tested at 5 sites in eastern Lake Erie during 2002. The CGM is useful for: (1) Predicting Cladophora growth, biomass, and tissue phosphorus concentrations under non-point source P loading with no depth restrictions; (2) providing estimates of the timing and magnitude of the midsummer sloughing phenomenon; (3) determining the contribution of Dreissena invasion to the resurgence of Cladophora in eastern Lake Erie; and (4) developing management strategies for Cladophora abatement. The CGM was applied to investigate how the spatial and temporal patterns of Cladophora growth were influenced by the natural variability in environmental parameters in eastern Lake Erie. Seasonal patterns in Cladophora growth were strongly influenced by temperature, and peak depth-integrated biomass was strongly influenced by both available light and phosphorus. The photosynthetic capacity of field collected Cladophora was a poor predictor of the mid-summer sloughing phenomenon. The CGM, however, predicted that self-shading within the dense Cladophora mats would have caused negative growth rates at the base of the dense mats for 14 days prior to the sloughing event. The metabolic imbalances at the base of the Cladophora mats were driven primarily by the availability of light and were exacerbated by intermediate water temperatures (&sim;23°C). The excellent agreement between model simulations and field data illustrates the ability of the CGM to predict tissue P and growth over a range of sites and depths in eastern Lake Erie and suggests potential for the model to be successfully applied in other systems.
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