Use of Macroinvertebrate Predictive Models to Evaluate Stream Restoration Effect

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dc.contributor.advisorFelton, Gary Ken_US
dc.contributor.authorTsang, Yin-Phanen_US
dc.contributor.departmentBiological Resources Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2009-01-24T06:39:55Z
dc.date.available2009-01-24T06:39:55Z
dc.date.issued2008-09-03en_US
dc.description.abstractMultivariate analysis was used to build macroinvertebrate predictive models for stream assessment in Britain, Australia, and the west coast of the United States. The philosophy behind these predictive models was similar, but variations exist and have been adapted for different regions. The macroinvertebrate predictive model in Maryland has been improved using Region-style models, including the Assessment by Nearest Neighbour Analysis (ANNA), the Burn's Region of Influence (BROI), and the New Datum Region of Influence (NROI) predictive schemes. For better prediction precision, different parameter selection methods (stepwise AIC, exhaustive AIC, and exhaustive BIC) and rational multiple regression function checking have been used to prevent overfitting. Root mean squared error (RMSE) was used to select the final best model. The calibration results from the Region-Style models are better than those from previously built River InVertebrate Prediction And Classification System (RIVPACS)-style model. The different parameter selection criteria along with rational regression function checking discourage overfitting and improve the prediction results. Region-style methods can be alternative methods for building predictive model. GISHydro2000 is a GIS-based program for performing hydrologic analysis in Maryland. This tool was used to determine numerous hydrologic characteristics as potential predictors to be used in the macroinvertebrate predictive model. The best performing ANNA, BROI, and NROI predictive models can be automated in the GISHydro2000 environment. Theses multivariate analyses (i.e., Observed/Expected (O/E) scores), as well as multimetric analysis (i.e., Benthic Index of Biotic Integrity (IBI) metrics), were applied to evaluate the stream restoration sites in Montgomery County, Maryland. The evaluation results show most stream habitat conditions were still degraded after stream restoration projects. The environmental stressors at the stream site were not immediately alleviated by the restoration design, or the stressors overshadowed the restoration efforts. At many sites, the stream condition starts to recover at the 3rd- or 4th- year post-restoration. More time may be needed for monitoring the recovery of stream ecosystems. The benthic IBI metrics response to not only environmental stressor, but also other natural variances. The results suggested that O/E scores from multivariate analysis provides valuable supplemental information for evaluating stream health.en_US
dc.format.extent23314637 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/8757
dc.language.isoen_US
dc.subject.pqcontrolledEnvironmental Sciencesen_US
dc.subject.pqcontrolledEngineering, Environmentalen_US
dc.subject.pqcontrolledBiology, Entomologyen_US
dc.subject.pquncontrolledmacroinvertebrate predictive modelen_US
dc.subject.pquncontrolledmultivariate analysisen_US
dc.subject.pquncontrolledRegion-style macroinvertebrate predictive modelen_US
dc.subject.pquncontrolledstream restorationen_US
dc.titleUse of Macroinvertebrate Predictive Models to Evaluate Stream Restoration Effecten_US
dc.typeDissertationen_US

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