Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin

There is no single methodology toward freshwater conservation planning, and few analytical tools exist for summarizing ecological risks at a landscape scale. I constructed a relative risk model, the Ecological Risk Index (ERI), to combine the frequency and severity of human-induced stressors with m...

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Main Author: Mattson-Hansen, Kimberly M.
Other Authors: Fisheries and Wildlife Science
Format: Others
Published: Virginia Tech 2017
Subjects:
Online Access:http://hdl.handle.net/10919/78611
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-786112020-09-29T05:36:03Z Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin Mattson-Hansen, Kimberly M. Fisheries and Wildlife Science Angermeier, Paul L. Wolfe, Mary Leigh Prisley, Stephen P. Hallerman, Eric M. Brewster, Carlyle C. risk assessment freshwater ecology mollusk mussel conservation landscape ecology There is no single methodology toward freshwater conservation planning, and few analytical tools exist for summarizing ecological risks at a landscape scale. I constructed a relative risk model, the Ecological Risk Index (ERI), to combine the frequency and severity of human-induced stressors with mappable land and water use data to evaluate impacts to five major biotic drivers: energy sources, physical habitat, flow regime, water quality, and biotic interactions. It assigns 3 final risk rankings based on a user-specified spatial grain. In a case study of the 5 major drainages within the upper Tennessee River basin (UTRB), U.S.A, differences in risk patterns among drainages reflected dominant land uses, such as mining and agriculture. A principal components analysis showed that localized, moderately severe threats accounted for most of the threat composition differences among watersheds. Also, the relative importance of threats is sensitive to the spatial grain of the analysis. An evaluation of the ERI procedures showed that the protocol is sensitive to how extent and severity of risk are defined, and threat frequency-class criteria strongly influenced final risk rankings. Multivariate analysis tested for model robustness and assessed the influence of expert judgment by comparing my original approach to a quantile-based approach. Results suggest that experts were less likely to assign catchments to high-risk categories than was the quantile approach, and that 3 final risk rankings were appropriate. I evaluated the influence of land use on freshwater ecosystems by studying the relationship between land cover changes and the persistence of freshwater mussels. First, historical species data were collected and the Upper Tennessee River Mussel Database (UTRMD) was constructed. The UTRMD contains >47,400 species records from 1963-2008 distributed across nearly 2,100 sampling sites. My study suggests that 30 years of land cover change does not explain observed freshwater mussel declines. Quantitative surveys are recommended basin-wide to provide more accurate information about mussel distribution and abundance. Lastly, results suggest that streams with repeated mussel surveys have increasing populations, including active recruitment in several beds. Additional quantitative surveys since 2004 have probably provided more accurate species and population counts, although actual population sizes are still uncertain. Ph. D. 2017-08-02T06:00:11Z 2017-08-02T06:00:11Z 2016-02-08 Dissertation vt_gsexam:6791 http://hdl.handle.net/10919/78611 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic risk assessment
freshwater ecology
mollusk
mussel conservation
landscape ecology
spellingShingle risk assessment
freshwater ecology
mollusk
mussel conservation
landscape ecology
Mattson-Hansen, Kimberly M.
Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
description There is no single methodology toward freshwater conservation planning, and few analytical tools exist for summarizing ecological risks at a landscape scale. I constructed a relative risk model, the Ecological Risk Index (ERI), to combine the frequency and severity of human-induced stressors with mappable land and water use data to evaluate impacts to five major biotic drivers: energy sources, physical habitat, flow regime, water quality, and biotic interactions. It assigns 3 final risk rankings based on a user-specified spatial grain. In a case study of the 5 major drainages within the upper Tennessee River basin (UTRB), U.S.A, differences in risk patterns among drainages reflected dominant land uses, such as mining and agriculture. A principal components analysis showed that localized, moderately severe threats accounted for most of the threat composition differences among watersheds. Also, the relative importance of threats is sensitive to the spatial grain of the analysis. An evaluation of the ERI procedures showed that the protocol is sensitive to how extent and severity of risk are defined, and threat frequency-class criteria strongly influenced final risk rankings. Multivariate analysis tested for model robustness and assessed the influence of expert judgment by comparing my original approach to a quantile-based approach. Results suggest that experts were less likely to assign catchments to high-risk categories than was the quantile approach, and that 3 final risk rankings were appropriate. I evaluated the influence of land use on freshwater ecosystems by studying the relationship between land cover changes and the persistence of freshwater mussels. First, historical species data were collected and the Upper Tennessee River Mussel Database (UTRMD) was constructed. The UTRMD contains >47,400 species records from 1963-2008 distributed across nearly 2,100 sampling sites. My study suggests that 30 years of land cover change does not explain observed freshwater mussel declines. Quantitative surveys are recommended basin-wide to provide more accurate information about mussel distribution and abundance. Lastly, results suggest that streams with repeated mussel surveys have increasing populations, including active recruitment in several beds. Additional quantitative surveys since 2004 have probably provided more accurate species and population counts, although actual population sizes are still uncertain. === Ph. D.
author2 Fisheries and Wildlife Science
author_facet Fisheries and Wildlife Science
Mattson-Hansen, Kimberly M.
author Mattson-Hansen, Kimberly M.
author_sort Mattson-Hansen, Kimberly M.
title Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
title_short Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
title_full Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
title_fullStr Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
title_full_unstemmed Modeling Ecological Risks at a Landscape Scale: Threat  Assessment in the Upper Tennessee River Basin
title_sort modeling ecological risks at a landscape scale: threat  assessment in the upper tennessee river basin
publisher Virginia Tech
publishDate 2017
url http://hdl.handle.net/10919/78611
work_keys_str_mv AT mattsonhansenkimberlym modelingecologicalrisksatalandscapescalethreatassessmentintheuppertennesseeriverbasin
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