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The Effect of Algal Blooms on Carbon Emissions in Western Lake Erie: An Integration of Remote Sensing and Eddy Covariance Measurements.
- Source :
- Remote Sensing; Jan2017, Vol. 9 Issue 1, p44, 19p
- Publication Year :
- 2017
-
Abstract
- Lakes are important components for regulating carbon cycling within landscapes. Most lakes are regarded as CO<subscript>2</subscript> sources to the atmosphere, except for a few eutrophic ones. Algal blooms are common phenomena in many eutrophic lakes and can cause many environmental stresses, yet their effects on the net exchange of CO<subscript>2</subscript> (F<subscript>CO2</subscript>) at large spatial scales have not been adequately addressed. We integrated remote sensing and Eddy Covariance (EC) technologies to investigate the effects that algal blooms have on F<subscript>CO2</subscript> in the western basin of Lake Erie--a large lake infamous for these blooms. Three years of long-term EC data (2012-2014) at two sites were analyzed. We found that at both sites: (1) daily F<subscript>CO2</subscript> significantly correlated with daily temperature, light, and wind speed during the algal bloom periods; (2) monthly F<subscript>CO2</subscript> was negatively correlated with chlorophyll-a concentration; and (3) the year with larger algal blooms was always associated with lower carbon emissions. We concluded that large algal blooms could reduce carbon emissions in the western basin of Lake Erie. However, considering the complexity of processes within large lakes, the weak relationship we found, and the potential uncertainties that remain in our estimations of F<subscript>CO2</subscript> and chlorophyll-a, we argue that additional data and analyses are needed to validate our conclusion and examine the underlying regulatory mechanisms. [ABSTRACT FROM AUTHOR]
- Subjects :
- ALGAL blooms
CARBON dioxide & the environment
REMOTE sensing
LAKE ecology
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 9
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 120987906
- Full Text :
- https://doi.org/10.3390/rs9010044