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Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship./
作者:	Risley, Sarah Corinne.
面頁冊數:	1 online resource (214 pages)
附註:	Source: Masters Abstracts International, Volume: 84-04.
Contained By:	Masters Abstracts International84-04.
標題:	Collaboration. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29330416click for full text (PQDT)
ISBN:	9798351497556

Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship.
Risley, Sarah Corinne.

Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship. - 1 online resource (214 pages)

Source: Masters Abstracts International, Volume: 84-04.

Thesis (M.Sc.)--The University of Maine, 2022.

Includes bibliographical references

In the last two decades, there has been a shift towards more integrated, ecosystem-based approaches to marine management, including fisheries. At the same time, there have been calls for greater inclusion of diverse perspectives in conservation science and practice. For these reasons, there is renewed interest in the integration of indigenous and local knowledge into science, management, and environmental decision making. Despite these developments, local knowledge often is poorly integrated or treated as something of lesser value than knowledge generated or curated by professional researchers. Novel methods that integrate social and ecological data and prioritize local knowledge and community-based approaches are needed to meet this challenge. This thesis explores how linking local knowledge and community science approaches can bolster ecosystem-based management and coastal stewardship. Here I define community science as inquiry that is community-led, place-based, and aimed at improving governance processes with the goals of stewardship and social-ecological sustainability (after Charles et al., 2020). Together, local knowledge and community science can generate robust social and ecological data. I highlight the connections among these approaches and model how they can be applied to small-scale coastal fisheries. Using participatory mapping and interviews, I demonstrate how local knowledge can complement scientific knowledge by generating ecosystem hypotheses that can inform scientific inquiry and long-term monitoring. Local knowledge is critical because this holistic information is uniquely able to support actionable and responsive research and management by: (1) characterizing the social-ecological system at a fine spatial scale; (2) highlighting stakeholders' priorities and observations; and (3) generating hypotheses about how and why the system is changing, and what drivers may be influencing these changes. I explore how local knowledge can inform the development of community science initiatives and examine the community science process through a case study in the Damariscotta River estuary, Maine, USA. I use a typology to assess the conditions for community science and how it can generate ecosystem-level information. The assessment revealed two primary conclusions: (1) community science can be an effective approach to studying co-managed fisheries and (2) community science is, by its nature, an ecosystem-scale approach to research. Integrating diverse knowledges and community partners can contribute to holistic understandings of dynamic marine coastal systems. These approaches can be applied to fisheries locally and regionally and have the potential to support ecosystem-based approaches to stewardship and management in marine coastal environments in Maine and beyond.

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

Mode of access: World Wide Web

ISBN: 9798351497556Subjects--Topical Terms:

3556296
Collaboration.
Index Terms--Genre/Form:

542853
Electronic books.

Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship.
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245 1 0 $a Linking Local Knowledge & Community Science in Support of Coastal Marine Stewardship.
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300 $a 1 online resource (214 pages)
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500 $a Source: Masters Abstracts International, Volume: 84-04.
500 $a Advisor: Leslie, Heather; Stoll, Joshua.
502 $a Thesis (M.Sc.)--The University of Maine, 2022.
504 $a Includes bibliographical references
520 $a In the last two decades, there has been a shift towards more integrated, ecosystem-based approaches to marine management, including fisheries. At the same time, there have been calls for greater inclusion of diverse perspectives in conservation science and practice. For these reasons, there is renewed interest in the integration of indigenous and local knowledge into science, management, and environmental decision making. Despite these developments, local knowledge often is poorly integrated or treated as something of lesser value than knowledge generated or curated by professional researchers. Novel methods that integrate social and ecological data and prioritize local knowledge and community-based approaches are needed to meet this challenge. This thesis explores how linking local knowledge and community science approaches can bolster ecosystem-based management and coastal stewardship. Here I define community science as inquiry that is community-led, place-based, and aimed at improving governance processes with the goals of stewardship and social-ecological sustainability (after Charles et al., 2020). Together, local knowledge and community science can generate robust social and ecological data. I highlight the connections among these approaches and model how they can be applied to small-scale coastal fisheries. Using participatory mapping and interviews, I demonstrate how local knowledge can complement scientific knowledge by generating ecosystem hypotheses that can inform scientific inquiry and long-term monitoring. Local knowledge is critical because this holistic information is uniquely able to support actionable and responsive research and management by: (1) characterizing the social-ecological system at a fine spatial scale; (2) highlighting stakeholders' priorities and observations; and (3) generating hypotheses about how and why the system is changing, and what drivers may be influencing these changes. I explore how local knowledge can inform the development of community science initiatives and examine the community science process through a case study in the Damariscotta River estuary, Maine, USA. I use a typology to assess the conditions for community science and how it can generate ecosystem-level information. The assessment revealed two primary conclusions: (1) community science can be an effective approach to studying co-managed fisheries and (2) community science is, by its nature, an ecosystem-scale approach to research. Integrating diverse knowledges and community partners can contribute to holistic understandings of dynamic marine coastal systems. These approaches can be applied to fisheries locally and regionally and have the potential to support ecosystem-based approaches to stewardship and management in marine coastal environments in Maine and beyond.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
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650 4 $a Habitats. $3 3564192
650 4 $a Decision making. $3 517204
650 4 $a Fisheries management. $3 3558781
650 4 $a Aquatic sciences. $3 3174300
650 4 $a Biological oceanography. $3 2122748
650 4 $a Ecology. $3 516476
655 7 $a Electronic books. $2 lcsh $3 542853
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690 $a 0329
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710 2 $a The University of Maine. $3 1029373
773 0 $t Masters Abstracts International $g 84-04.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29330416 $z click for full text (PQDT)