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Evaluating Model Uncertainty to Info...

Third, Laura.

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Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada./
Author:	Third, Laura.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	76 p.
Notes:	Source: Masters Abstracts International, Volume: 82-06.
Contained By:	Masters Abstracts International82-06.
Subject:	Aquatic sciences. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27994203
ISBN:	9798698544760

Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada.
Third, Laura.

Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 76 p.

Source: Masters Abstracts International, Volume: 82-06.

Thesis (M.Sc.)--University of Toronto (Canada), 2020.

This item must not be sold to any third party vendors.

Ecological models allow resource managers to evaluate human impacts on fish and their habitat. However, quantitative methods that incorporate and assess uncertainty in these models are rare. These models require fish life history information, which is often uncertain, and can thus lead to uncertain predictions and pose risks to either the environment or proponent. I utilized a multispecies size spectrum model to evaluate uncertainty surrounding estimates of three fish life history traits: (1) asymptotic weight; (2) the von Bertalanffy growth coefficient; and (3) weight at maturity. I then applied an existing framework for quantifying compensation ratios to achieve "no net loss" (NNL) in the context of a theoretical development project. The results of this study show that asymptotic size and forage fishes have the greatest influence on predictive uncertainty. I recommend that sampling effort be prioritized for these and demonstrate how to account for uncertainty in a precautionary management framework.

ISBN: 9798698544760Subjects--Topical Terms:

3174300
Aquatic sciences.
Subjects--Index Terms:

Aquatic science

Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada.
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245 1 0 $a Evaluating Model Uncertainty to Inform Offset Ratios for the Protection of Freshwater Fish Productivity in Canada.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 76 p.
500 $a Source: Masters Abstracts International, Volume: 82-06.
500 $a Advisor: de Kerckhove, Dak;Chu, Cindy.
502 $a Thesis (M.Sc.)--University of Toronto (Canada), 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Ecological models allow resource managers to evaluate human impacts on fish and their habitat. However, quantitative methods that incorporate and assess uncertainty in these models are rare. These models require fish life history information, which is often uncertain, and can thus lead to uncertain predictions and pose risks to either the environment or proponent. I utilized a multispecies size spectrum model to evaluate uncertainty surrounding estimates of three fish life history traits: (1) asymptotic weight; (2) the von Bertalanffy growth coefficient; and (3) weight at maturity. I then applied an existing framework for quantifying compensation ratios to achieve "no net loss" (NNL) in the context of a theoretical development project. The results of this study show that asymptotic size and forage fishes have the greatest influence on predictive uncertainty. I recommend that sampling effort be prioritized for these and demonstrate how to account for uncertainty in a precautionary management framework.
590 $a School code: 0779.
650 4 $a Aquatic sciences. $3 3174300
650 4 $a Natural resource management. $3 589570
653 $a Aquatic science
653 $a Fish
653 $a Fisheries
653 $a Modeling
653 $a Offsetting
653 $a Uncertainty analysis
690 $a 0792
690 $a 0474
690 $a 0528
710 2 $a University of Toronto (Canada). $b Ecology and Evolutionary Biology. $3 3190014
773 0 $t Masters Abstracts International $g 82-06.
790 $a 0779
791 $a M.Sc.
792 $a 2020
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27994203