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Using ecosystem models to understand...

Vasslides, James Michael.

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Using ecosystem models to understand the faunal response to non-trophic impacts in an estuarine ecosystem.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Using ecosystem models to understand the faunal response to non-trophic impacts in an estuarine ecosystem./
作者:	Vasslides, James Michael.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	173 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
Contained By:	Dissertation Abstracts International77-09B(E).
標題:	Ecology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10095971
ISBN:	9781339601274

Using ecosystem models to understand the faunal response to non-trophic impacts in an estuarine ecosystem.
Vasslides, James Michael.

Using ecosystem models to understand the faunal response to non-trophic impacts in an estuarine ecosystem. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 173 p.

Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.

Thesis (Ph.D.)--Rutgers The State University of New Jersey - New Brunswick, 2016.

Ecosystem-based management requires a holistic view of the impacts of management activities, and a number of modelling techniques have been suggested as appropriate for the task at hand. In the first chapter I utilized fuzzy logic cognitive mapping to develop conceptual models of a Barnegat Bay, a lagoonal estuarine system, among four stakeholder groups. These findings suggest that while all of the stakeholders interviewed perceive the subject ecosystem as a complex series of social and ecological interconnections, there is a core set of components that are present in most of the groups' models that are viewed as crucial in managing the system towards some desired outcome. However, the variability in the connections between these core components and the rest of the categories influences the exact nature of these outcomes.

ISBN: 9781339601274Subjects--Topical Terms:

516476
Ecology.

Using ecosystem models to understand the faunal response to non-trophic impacts in an estuarine ecosystem.
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500 $a Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
500 $a Adviser: Olaf P. Jensen.
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520 $a Ecosystem-based management requires a holistic view of the impacts of management activities, and a number of modelling techniques have been suggested as appropriate for the task at hand. In the first chapter I utilized fuzzy logic cognitive mapping to develop conceptual models of a Barnegat Bay, a lagoonal estuarine system, among four stakeholder groups. These findings suggest that while all of the stakeholders interviewed perceive the subject ecosystem as a complex series of social and ecological interconnections, there is a core set of components that are present in most of the groups' models that are viewed as crucial in managing the system towards some desired outcome. However, the variability in the connections between these core components and the rest of the categories influences the exact nature of these outcomes.
520 $a In the second chapter I constructed a trophic-based ecosystem model for the same estuary and included mortality associated with a nuclear generating station. Under a scenario where the generating station substantially reduces its water withdrawals, the effect on the biomass of an individual species tended to be small (<3%), and the direction of the change varied by species. However, trophic interactions played an important role in determining the overall change in a species' biomass, as some species directly impacted by the generating station had a reduced biomass in the decommissioning scenario due to increased predation mortality.
520 $a In the third and fourth chapters I reviewed the available literature regarding incorporation of eutrophication and other anthropogenic impacts into the trophic-based model. I then reduced nutrient loads within models developed in the previous chapters to understand how they can be best utilized to meet the needs of resource managers. Both models responded to the nutrient load reduction in a similar fashion, despite the differences in data sources, approaches, and methodology. This suggests that in data-poor situations local ecological knowledge, collected in a stakeholder-based conceptual modelling framework, can be used to understand the patterns and relative magnitude of changes to an ecosystem that can be expected given proposed management actions. However, a more powerful approach would be to use the two models in combination, maximizing the strengths of each.
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