Journal article
Use of local ecological knowledge in the management of algal blooms
Environmental Conservation, Vol.37(2), pp.210-221
2010
Abstract
More frequent and severe algal blooms are symptomatic of increasing ecosystem stress in coastal waters. Economic losses typically follow and local governments are forced to 'manage' this issue. Because many blooms are not monitored, local ecological knowledge (LEK) and oral history are the only practical tools to obtain data on bloom characteristics and identify their drivers. LEK was applied to outbreaks of brown algae on popular tourist beaches in south-east Queensland (Australia). Structured interviews with local citizens who had a close and frequent connection with the ocean provided 541 bloom records, which showed that blooms are regional (≥400 km) rather than local, and that they are a historical (≥40 years) rather than a recent phenomenon. LEK frequently cited that particular wind regimes coincided with the arrival of blooms, but this could not be verified by statistical cross-validation with empirical data. Harnessing LEK was valuable in engaging citizens, in generating testable hypotheses about plume causes, in providing a previously unrecognized historical perspective and in identifying the correct spatial scale of the issue. Multi-pronged approaches will be most effective in addressing blooms where local mitigation actions are combined with broader regional coastal environmental conservation efforts.
Details
- Title
- Use of local ecological knowledge in the management of algal blooms
- Authors
- Thomas Schlacher (Author) - University of the Sunshine Coast - Faculty of Science, Health and EducationStewart Lloyd (Author) - University of the Sunshine Coast - Faculty of Science, Health and EducationAaron Wiegand (Author) - University of the Sunshine Coast - Faculty of Science, Health and Education
- Publication details
- Environmental Conservation, Vol.37(2), pp.210-221
- Publisher
- Cambridge University Press
- DOI
- 10.1017/S0376892910000305
- ISSN
- 0376-8929
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science and Engineering - Legacy; School of Science, Technology and Engineering; Academic Support Unit
- Language
- English
- Record Identifier
- 99449735802621
- Output Type
- Journal article
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