東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Decision Support Tools to Enhance th...

Guerrero Pineda, Maria Camila,

Linked to FindBook

Google Book

Amazon

博客來

Decision Support Tools to Enhance the Efficiency of Conservation Practices /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Decision Support Tools to Enhance the Efficiency of Conservation Practices // Maria Camila Guerrero Pineda.
Author:	Guerrero Pineda, Maria Camila,
Description:	1 electronic resource (196 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
Contained By:	Dissertations Abstracts International86-05A.
Subject:	Conservation biology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31564148
ISBN:	9798342716505

Decision Support Tools to Enhance the Efficiency of Conservation Practices /
Guerrero Pineda, Maria Camila,

Decision Support Tools to Enhance the Efficiency of Conservation Practices /Maria Camila Guerrero Pineda. - 1 electronic resource (196 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: A.

The UN's Sustainable Development Goals aim to ensure sustainable human development and biodiversity conservation, but biodiversity loss is accelerating due to human activities. Scarcity of monetary resources in conservation creates challenges that highlight the need to increase the efficiency of conservation interventions to reduce species threats while meeting human goals. In this dissertation, I develop a set of decision support tools (DSTs) to help address some of these challenges and apply each DST in the context of specific cases. In chapter one, I provide an overview of three of some of the challenges that conservation faces. In chapter two, I contribute to the call for standardized methods to report costs and outcomes of conservation management interventions to improve decision-making. In particular, I develop a data management tool for tracking expenses and outcomes of conservation interventions and demonstrate the use of this tool within the red spiny lobster fishery in the Galapagos Marine Reserve. This data management tool enables the conservation community to efficiently use knowledge of past experiences to inform future decisions. In chapter three, I develop a prioritization approach to examine how it can guide decisions about what species can benefit most from interventions. I apply this approach to address the risk assessment bottleneck in the pesticide and review process in the U.S., and test it with terrestrial endangered species in the state of California. Results suggests that prioritizing the assessment of a small group of species could potentially result in high conservation benefits. In chapter four, I develop an optimization framework to quantify conservation outcomes from threat abatement actions accounting for species-specific threats and species heterogeneity in threat level. I illustrate this framework using data on Red List birds in the Peruvian Amazon and an intervention consisting of transitioning from conventional agriculture to agroforestry. Here, conservation planning using the optimization framework shows higher benefits in Red List birds than more traditional approaches, namely return-on-investment or species richness. Overall, my dissertation research contributes to the conservation field by developing three DSTs and demonstrating how they can be used to increase efficiency in conservation decision-making.

English

ISBN: 9798342716505Subjects--Topical Terms:

535736
Conservation biology.
Subjects--Index Terms:

Conservation

Decision Support Tools to Enhance the Efficiency of Conservation Practices /
LDR:06814nmm a22004573i 4500 001 2434477
005 20250912102025.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798342716505
035 $a (MiAaPQD)AAI31564148
035 $a AAI31564148
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Guerrero Pineda, Maria Camila, $e author. $3 3824472
245 1 0 $a Decision Support Tools to Enhance the Efficiency of Conservation Practices / $c Maria Camila Guerrero Pineda.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (196 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: Dissertations Abstracts International, Volume: 86-05, Section: A.
500 $a Advisors: Gerber, Leah R.; Iacona, Gwenllian D. Committee members: Kroetz, Kailin; Sefair, Jorge A.
502 $b Ph.D. $c Arizona State University $d 2024.
520 $a The UN's Sustainable Development Goals aim to ensure sustainable human development and biodiversity conservation, but biodiversity loss is accelerating due to human activities. Scarcity of monetary resources in conservation creates challenges that highlight the need to increase the efficiency of conservation interventions to reduce species threats while meeting human goals. In this dissertation, I develop a set of decision support tools (DSTs) to help address some of these challenges and apply each DST in the context of specific cases. In chapter one, I provide an overview of three of some of the challenges that conservation faces. In chapter two, I contribute to the call for standardized methods to report costs and outcomes of conservation management interventions to improve decision-making. In particular, I develop a data management tool for tracking expenses and outcomes of conservation interventions and demonstrate the use of this tool within the red spiny lobster fishery in the Galapagos Marine Reserve. This data management tool enables the conservation community to efficiently use knowledge of past experiences to inform future decisions. In chapter three, I develop a prioritization approach to examine how it can guide decisions about what species can benefit most from interventions. I apply this approach to address the risk assessment bottleneck in the pesticide and review process in the U.S., and test it with terrestrial endangered species in the state of California. Results suggests that prioritizing the assessment of a small group of species could potentially result in high conservation benefits. In chapter four, I develop an optimization framework to quantify conservation outcomes from threat abatement actions accounting for species-specific threats and species heterogeneity in threat level. I illustrate this framework using data on Red List birds in the Peruvian Amazon and an intervention consisting of transitioning from conventional agriculture to agroforestry. Here, conservation planning using the optimization framework shows higher benefits in Red List birds than more traditional approaches, namely return-on-investment or species richness. Overall, my dissertation research contributes to the conservation field by developing three DSTs and demonstrating how they can be used to increase efficiency in conservation decision-making.
520 $a Los Objetivos de Desarrollo Sostenible de las Naciones Unidas tienen como objetivo garantizar el desarrollo humano sostenible y la conservacion de la biodiversidad, pero la perdida de biodiversidad se esta acelerando debido a actividades humanas. La escasez de recursos monetarios en conservacion crea desafios que resaltan la necesidad de aumentar la eficiencia de las intervenciones de conservacion para reducir las amenazas a las especies y, al mismo tiempo, cumplir con objetivos humanos. En esta disertacion, desarrollo un conjunto de herramientas de apoyo a la toma de decisiones (DST, por sus siglas en ingles) para ayudar a abordar algunos de estos desafios y aplicar cada DST en el contexto de casos especificos. En el capitulo uno, proporciono una descripcion general de tres de algunos de los desafios que enfrenta la conservacion. En el capitulo dos, contribuyo al llamado a metodos estandarizados para informar los costos y los resultados de las intervenciones de gestion de la conservacion para mejorar la toma de decisiones. En particular, desarrollo una herramienta de gestion de datos para rastrear los gastos y los resultados de las intervenciones de conservacion y demuestro el uso de esta herramienta dentro de la pesqueria de langosta roja en la Reserva Marina de Galapagos. Esta herramienta de gestion de datos permite a la comunidad de conservacion utilizar de manera eficiente el conocimiento de experiencias pasadas para informar decisiones futuras. En el capitulo tres, desarrollo una estrategia de priorizacion para examinar como puede guiar las decisiones sobre que especies pueden beneficiarse mas de intervenciones. Aplico esta estrategia para abordar el cuello de botella de la evaluacion de riesgos en el proceso de revision y control de pesticidas en los EE. UU., y lo pruebo con especies terrestres en peligro de extincion en el estado de California. Los resultados sugieren que priorizar la evaluacion de un pequeno grupo de especies podria potencialmente resultar en altos beneficios de conservacion. En el capitulo cuatro, desarrollo un marco de optimizacion para cuantificar los resultados de conservacion de acciones de reduccion de amenazas que tiene en cuenta las amenazas especificas de las especies y la heterogeneidad de las especies en el nivel de amenaza. Ilustro este marco utilizando datos sobre aves de la Lista Roja en la Amazonia peruana y una intervencion que consiste en la transicion de la agricultura convencional a la agroforesteria. Aqui, la planificacion de la conservacion utilizando el marco de optimizacion muestra mayores beneficios en las aves de la Lista Roja que los enfoques mas tradicionales, a saber, el retorno de la inversion o la riqueza de especies. En general, mi disertacion contribuye al campo de la conservacion al desarrollar tres DST y demostrar como se pueden utilizar para aumentar la eficiencia en la toma de decisiones de conservacion.
546 $a English
590 $a School code: 0010
650 4 $a Conservation biology. $3 535736
650 4 $a Computer engineering. $3 621879
650 4 $a Statistics. $3 517247
650 4 $a Systems science. $3 3168411
650 4 $a Sustainability. $3 1029978
653 $a Conservation
653 $a Conservation planning
653 $a Decision making
690 $a 0408
690 $a 0464
690 $a 0640
690 $a 0463
690 $a 0790
710 2 $a Arizona State University. $b Biology. $e degree granting institution. $3 3824473
720 1 $a Gerber, Leah R. $e degree supervisor.
720 1 $a Iacona, Gwenllian D. $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-05A.
790 $a 0010
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31564148