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Date Permissions Signed

5-30-2014

Date of Award

2014

Document Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Environmental Sciences

First Advisor

Landis, Wayne G.

Second Advisor

Stahl, Ralph G., 1953-

Third Advisor

Matthews, Robin A., 1952-

Abstract

Ecological managers often implement one or more management options to manage risk without the direct integration of a quantitative risk assessment and evaluation of management alternatives. Throughout the decision making process a manager should consider multiple stressors as well as stressor interactions and the resulting effects. In my study, I used Bayesian networks in a relative risk assessment model framework (BN-RRM) to integrate two management options into existing risk assessment models for biotic endpoints and water quality endpoints in the mercury contaminated site, South River, VA. The two management options assessed were agricultural best management practices (BMPs) and bank stabilization. The primary management goal expressed by managers is "no regrets." In other words, managers do not want to make the site worse in any way, such as reducing mercury levels at the detriment of habitat, loss of other species, degradation of water quality, or other environmental parameters. The Bayesian networks represent the expected effects of a management option and the potential for unintended consequences. Agricultural BMPs did not change the skew of the risk distributions, but aligns with the "no regrets" management focus because risk did not increase. Bank stabilization management shifted the risk distribution for smallmouth bass so that there was greater likelihood of zero risk. The risk distribution for the water quality-fishing endpoint changed because likelihood of medium and high risk increased. If bank stabilization is implemented without consideration of Belted Kingfisher nests, there was 100% likelihood of high risk to the Kingfisher. My research provides South River managers with a tool that describes how management options are expected to change risk to biotic and water quality endpoints. Adaptive management for the South River is a long-term process. The BN-RRM models can be updated with new monitoring data to inform future management decisions.

Type

Text

Publisher

Western Washington University

OCLC Number

881242065

Digital Format

application/pdf

Geographic Coverage

South River Watershed (Augusta County and Rockingham County, Va.)

Genre/Form

Academic theses

Language

English

Rights

Copying of this thesis in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this thesis for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.

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