東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Modeling Individual Variability in Growth and Its Importance : = an Application for Lake Trout (Salvelinus namaycush) in Lake Superior.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling Individual Variability in Growth and Its Importance :/
Reminder of title:	an Application for Lake Trout (Salvelinus namaycush) in Lake Superior.
Author:	Stebbins, Elizabeth.
Description:	1 online resource (109 pages)
Notes:	Source: Masters Abstracts International, Volume: 84-02.
Contained By:	Masters Abstracts International84-02.
Subject:	Aquatic sciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29326885click for full text (PQDT)
ISBN:	9798841767374

Modeling Individual Variability in Growth and Its Importance : = an Application for Lake Trout (Salvelinus namaycush) in Lake Superior.
Stebbins, Elizabeth.

Modeling Individual Variability in Growth and Its Importance :an Application for Lake Trout (Salvelinus namaycush) in Lake Superior. - 1 online resource (109 pages)

Source: Masters Abstracts International, Volume: 84-02.

Thesis (M.S.)--Michigan State University, 2022.

Includes bibliographical references

Correctly characterizing growth of fish within a population is a crucial component of fish biology and fishery management because, among other things, it informs population dynamics that affect management decisions. Size-at-age is a common metric of fish growth and is often measured at the population level with the assumption that, on average, all fish of a given age are a given size. Over time, several studies have shown that ignoring individual variability in growth can influence population parameter estimates and these inaccuracies can be propagated in population models that are used to calculate reference points for management. In the first chapter we develop a hierarchical, mixed-effects statistical growth model that measures individual variability in growth model parameters and partitions it into two sources. We fit this model to length-at-age data of lake trout (Salvelinus namaycush) from six populations in Lake Superior and show that individual-level variability exceeds population-level variability for this system, and persistent error contributes more to variability in length-at-age. In our second chapter, we simulate a population of fish and predict biological reference points, yield-per-recruit, and spawning stock biomass-per-recruit curves from the population using a 'standard' method that ignores individual variability and a 'true' method that accounts for size-selective mortality and its interaction with individual fish. We show that ignoring individual variability in these models results in overestimation of yield-per-recruit and the biological reference points F0.1 and FMAX. Further, spawning stock biomass-per-recruit is underestimated at low levels of fishing intensity and overestimated at high levels of fishing intensity when individual variability is ignored.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841767374Subjects--Topical Terms:

3174300
Aquatic sciences.
Subjects--Index Terms:

FishIndex Terms--Genre/Form:

542853
Electronic books.

Modeling Individual Variability in Growth and Its Importance : = an Application for Lake Trout (Salvelinus namaycush) in Lake Superior.
LDR:03239nmm a2200409K 4500 001 2354916
005 20230505090458.5
006 m o d
007 cr mn ---uuuuu
008 241011s2022 xx obm 000 0 eng d
020 $a 9798841767374
035 $a (MiAaPQ)AAI29326885
035 $a AAI29326885
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Stebbins, Elizabeth. $3 3695290
245 1 0 $a Modeling Individual Variability in Growth and Its Importance : $b an Application for Lake Trout (Salvelinus namaycush) in Lake Superior.
264 0 $c 2022
300 $a 1 online resource (109 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 84-02.
500 $a Advisor: Bence, James R.; Brenden, Travis O.
502 $a Thesis (M.S.)--Michigan State University, 2022.
504 $a Includes bibliographical references
520 $a Correctly characterizing growth of fish within a population is a crucial component of fish biology and fishery management because, among other things, it informs population dynamics that affect management decisions. Size-at-age is a common metric of fish growth and is often measured at the population level with the assumption that, on average, all fish of a given age are a given size. Over time, several studies have shown that ignoring individual variability in growth can influence population parameter estimates and these inaccuracies can be propagated in population models that are used to calculate reference points for management. In the first chapter we develop a hierarchical, mixed-effects statistical growth model that measures individual variability in growth model parameters and partitions it into two sources. We fit this model to length-at-age data of lake trout (Salvelinus namaycush) from six populations in Lake Superior and show that individual-level variability exceeds population-level variability for this system, and persistent error contributes more to variability in length-at-age. In our second chapter, we simulate a population of fish and predict biological reference points, yield-per-recruit, and spawning stock biomass-per-recruit curves from the population using a 'standard' method that ignores individual variability and a 'true' method that accounts for size-selective mortality and its interaction with individual fish. We show that ignoring individual variability in these models results in overestimation of yield-per-recruit and the biological reference points F0.1 and FMAX. Further, spawning stock biomass-per-recruit is underestimated at low levels of fishing intensity and overestimated at high levels of fishing intensity when individual variability is ignored.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Aquatic sciences. $3 3174300
650 4 $a Ecology. $3 516476
650 4 $a Natural resource management. $3 589570
653 $a Fish
653 $a Growth
653 $a Individual variation
653 $a Methods
653 $a Modeling
653 $a Salvelinus namaycush
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0792
690 $a 0329
690 $a 0528
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Michigan State University. $b Fisheries and Wildlife - Master of Science. $3 2049737
773 0 $t Masters Abstracts International $g 84-02.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29326885 $z click for full text (PQDT)