東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Stock Status and Management in Tuna ...

Pons, Maite.

FindBook

Google Book

Amazon

博客來

Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor./
作者:	Pons, Maite.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	186 p.
附註:	Source: Dissertation Abstracts International, Volume: 80-03(E), Section: B.
Contained By:	Dissertation Abstracts International80-03B(E).
標題:	Natural resource management. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10846859
ISBN:	9780438523432

Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor.
Pons, Maite.

Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 186 p.

Source: Dissertation Abstracts International, Volume: 80-03(E), Section: B.

Thesis (Ph.D.)--University of Washington, 2018.

Tunas and billfishes are large migratory species managed by Regional Fisheries Management Organizations (tRFMOs). The current status of these species is well known, and most of the large commercial tuna stocks are managed at sustainable levels. We found that most of the overfished tuna and billfish populations are showing signs of rebuilding as a consequence of the implementation of strong management measures such as fishing quotas. However, management performance among tRFMOs is highly variable among oceans and it is mainly correlated with the overall economic dependence of individual members of the tRFMOs on tuna fisheries. When countries with low governance capacity account for the greatest proportion of total tuna catches, management controls are, on average, harder to implement. On the other hand, some non-commercial valuable tuna stocks, such as mackerels and bonitos, managed under the umbrella of tRFMOs remain unassessed, mainly because of insufficient quantitative data, particularly total catch. Preliminary assessments for these stocks based only on length composition data from the catch, showed that some of these stocks are experiencing overfishing. These results should encourage the management body in the Atlantic Ocean to take management actions to protect these stocks from overfishing as well as improve data collection programs. When comparing the performance of some length-based and catch-based data limited assessment methods, we found that in many cases, length-based assessments performed as well as other catch-based models. Nevertheless, the performance of different data-limited methods depended not only on the type of data available, but on prior knowledge about the exploitation history of the stock and the biology of each species. We hope that this dissertation helps to improve the current management system for data-rich tuna stocks by highlighting successful management strategies, as well as to improve the estimation of stock status for data-poor tuna fisheries.

ISBN: 9780438523432Subjects--Topical Terms:

589570
Natural resource management.

Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor.
LDR:02962nmm a2200301 4500 001 2200300
005 20181214130638.5
008 201008s2018 ||||||||||||||||| ||eng d
020 $a 9780438523432
035 $a (MiAaPQ)AAI10846859
035 $a (MiAaPQ)washington:19155
035 $a AAI10846859
040 $a MiAaPQ $c MiAaPQ
100 1 $a Pons, Maite. $3 3427046
245 1 0 $a Stock Status and Management in Tuna Fisheries: From Data-rich to Data-poor.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 186 p.
500 $a Source: Dissertation Abstracts International, Volume: 80-03(E), Section: B.
500 $a Adviser: Ray Hilborn.
502 $a Thesis (Ph.D.)--University of Washington, 2018.
520 $a Tunas and billfishes are large migratory species managed by Regional Fisheries Management Organizations (tRFMOs). The current status of these species is well known, and most of the large commercial tuna stocks are managed at sustainable levels. We found that most of the overfished tuna and billfish populations are showing signs of rebuilding as a consequence of the implementation of strong management measures such as fishing quotas. However, management performance among tRFMOs is highly variable among oceans and it is mainly correlated with the overall economic dependence of individual members of the tRFMOs on tuna fisheries. When countries with low governance capacity account for the greatest proportion of total tuna catches, management controls are, on average, harder to implement. On the other hand, some non-commercial valuable tuna stocks, such as mackerels and bonitos, managed under the umbrella of tRFMOs remain unassessed, mainly because of insufficient quantitative data, particularly total catch. Preliminary assessments for these stocks based only on length composition data from the catch, showed that some of these stocks are experiencing overfishing. These results should encourage the management body in the Atlantic Ocean to take management actions to protect these stocks from overfishing as well as improve data collection programs. When comparing the performance of some length-based and catch-based data limited assessment methods, we found that in many cases, length-based assessments performed as well as other catch-based models. Nevertheless, the performance of different data-limited methods depended not only on the type of data available, but on prior knowledge about the exploitation history of the stock and the biology of each species. We hope that this dissertation helps to improve the current management system for data-rich tuna stocks by highlighting successful management strategies, as well as to improve the estimation of stock status for data-poor tuna fisheries.
590 $a School code: 0250.
650 4 $a Natural resource management. $3 589570
650 4 $a Aquatic sciences. $3 3174300
690 $a 0528
690 $a 0792
710 2 $a University of Washington. $b Aquatic and Fishery Sciences. $3 2093042
773 0 $t Dissertation Abstracts International $g 80-03B(E).
790 $a 0250
791 $a Ph.D.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10846859