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Fish communities as indicators of ec...

Anderson, Alison M.

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Fish communities as indicators of ecological health in West Virginia rivers.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Fish communities as indicators of ecological health in West Virginia rivers./
作者:	Anderson, Alison M.
面頁冊數:	180 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
Contained By:	Dissertation Abstracts International76-12B(E).
標題:	Aquatic sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3718395
ISBN:	9781321981902

Fish communities as indicators of ecological health in West Virginia rivers.
Anderson, Alison M.

Fish communities as indicators of ecological health in West Virginia rivers. - 180 p.

Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.

Thesis (Ph.D.)--West Virginia University, 2015.

Anthropogenic altered landscapes from the extraction of natural resources, urbanization, agricultural development, dam construction, and general conversion from forested to non-forested landscape have resulted in the loss of biodiversity and changes in ecosystem function for aquatic environments. Throughout this research, we have used detailed landscape data and a large fish community dataset to develop management tools and analyses in order to evaluate the condition of rivers and streams in West Virginia.

ISBN: 9781321981902Subjects--Topical Terms:

3174300
Aquatic sciences.

Fish communities as indicators of ecological health in West Virginia rivers.
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100 1 $a Anderson, Alison M. $3 3190160
245 1 0 $a Fish communities as indicators of ecological health in West Virginia rivers.
300 $a 180 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
500 $a Adviser: J. Todd Petty.
502 $a Thesis (Ph.D.)--West Virginia University, 2015.
520 $a Anthropogenic altered landscapes from the extraction of natural resources, urbanization, agricultural development, dam construction, and general conversion from forested to non-forested landscape have resulted in the loss of biodiversity and changes in ecosystem function for aquatic environments. Throughout this research, we have used detailed landscape data and a large fish community dataset to develop management tools and analyses in order to evaluate the condition of rivers and streams in West Virginia.
520 $a For Chapter 1, we developed a fish-based Index of Biotic Integrity (IBI), a common ecological tool for assessing the health of fish communities, in order to inform state and federal regulatory agencies of the impairment status of warm water, wadeable stream and rivers in West Virginia. Based on fish distributions and assemblage metrics within reference sites, we identified 5 distinct biomonitoring regions for which we constructed separate warm water IBIs. Final lists consisting of 7 -- 9 metrics were retained within each region for the inclusion into a final IBI. Common metrics retained in the final IBIs included measures of benthic associated species, total species richness, clean-gravel spawning species, tolerance to stressors, feeding classification (e.g., invertivores, omnivore-herbivores) and taxonomic group membership (e.g., Family Cyprinidae, Family Cottidae, darters, and madtoms).
520 $a In the remaining chapters, we evaluated alternative methods for portions of IBI development and relationships of the final IBI and metrics to both natural and anthropogenic landscape characteristics. Specifically for Chapter 2, we used a modeling framework (i.e., boosted regression tree modeling) in order to generate an anthropogenic condition gradient based on currently defined reference sites. We used the reference condition probabilities to locate additional reference sites that span a gradient of natural environmental conditions to be used in bioassessment development as well as define regions of high quality for future sampling or conservation efforts. We then used this larger sample of reference sites to model the expected condition of trait-based fish community metrics using a variety of natural landscape variables (i.e., drainage area, elevation, and distance from a source river) in chapter 3. In order to generate predictive models, we used a boosted regression tree (BRT) framework in which we also analyzed the effectiveness of BRT models by developing thresholds of model use using Monte Carlo simulations. Overall, the metrics analyzed for chapter 3 showed distinct regional difference in their natural condition BRT models as well as their correlations with anthropogenic stressors within each biomonitoring region.
520 $a Finally, for Chapter 4, we recognized the importance of the hierarchical nature of aquatic systems in determining local fish community structure. We evaluated different measures of fish community assembly (species richness, diversity, WV IBI scores, and proportion of tolerant individuals) and how local and neighborhood level landscape structure in additional to natural variables, can impact stream community health in Central Appalachian watersheds. In order to account for the nested structure of our data, we employed a mixed-effects modeling approach, which has the ability to incorporate non-independent sampling locations by establishing a fixed-effect grouping variable. For our analysis, we used neighborhood (HUC 12 watershed) as a grouping variable. Generally, each community variable, with exception of % tolerant individuals, was responsive to local landscape structure. These variables demonstrated decreases with increase in measures of surface mining intensity. However, they also demonstrated increases with increases in residential development indicating that residential development in the Central Appalachians may serve as a refuge from mining related stressors by providing increased levels of nutrients and release from degraded water quality. (Abstract shortened by UMI.).
590 $a School code: 0256.
650 4 $a Aquatic sciences. $3 3174300
650 4 $a Ecology. $3 516476
690 $a 0792
690 $a 0329
710 2 $a West Virginia University. $b Davis College of Argriculture, Natural Resources, & Design. $3 2098241
773 0 $t Dissertation Abstracts International $g 76-12B(E).
790 $a 0256
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3718395