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"Community Forests" in the United States – How Do we Know One When we See One?

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Title: "Community Forests" in the United States – How Do we Know One When we See One?
Authors: Frey, Gregory E.1 (AUTHOR) gregory.e.frey@usda.gov, Hajjar, Reem2 (AUTHOR), Charnley, Susan3 (AUTHOR), McGinley, Kathleen4 (AUTHOR), Schelhas, John5 (AUTHOR), Tarr, Nathan A.6 (AUTHOR), McCaskill, Lauren2 (AUTHOR), Cubbage, Frederick W.6 (AUTHOR)
Source: Society & Natural Resources. Aug2024, Vol. 37 Issue 8, p1240-1252. 13p.
Subject Terms: *Forest management, *Community forestry, *Community forests, Historical literature, Decision making
Abstract: Community forests (CFs) involve communities in decision-making about, management of and access to forests, and have potential to benefit both communities and forests. However, they lack a single definition, clear distinction from related topics, or method for identification. This perspectives article explores historical and current literature on CFs and proposes a conceptual framework for understanding CFs and related concepts in the U.S. context. Through that exploration, we propose a conceptual framework for understanding their meaning and relationship. We propose three potential pathways for identifying CFs in the U.S., each with advantages and disadvantages. CFs can be identified by using a criteria and indicators approach; by participation in programs or networks designated for CFs; or by their own self-identification as a CF. We suggest that using a hybrid of these approaches will produce the most robust process for knowing a community forest when we see one. [ABSTRACT FROM AUTHOR]
Copyright of Society & Natural Resources is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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An: 178807642
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PubType: Academic Journal
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  Data: "Community Forests" in the United States – How Do we Know One When we See One?
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  Data: <searchLink fieldCode="JN" term="%22Society+%26+Natural+Resources%22">Society & Natural Resources</searchLink>. Aug2024, Vol. 37 Issue 8, p1240-1252. 13p.
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  Data: *<searchLink fieldCode="DE" term="%22Forest+management%22">Forest management</searchLink><br />*<searchLink fieldCode="DE" term="%22Community+forestry%22">Community forestry</searchLink><br />*<searchLink fieldCode="DE" term="%22Community+forests%22">Community forests</searchLink><br /><searchLink fieldCode="DE" term="%22Historical+literature%22">Historical literature</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink>
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  Data: Community forests (CFs) involve communities in decision-making about, management of and access to forests, and have potential to benefit both communities and forests. However, they lack a single definition, clear distinction from related topics, or method for identification. This perspectives article explores historical and current literature on CFs and proposes a conceptual framework for understanding CFs and related concepts in the U.S. context. Through that exploration, we propose a conceptual framework for understanding their meaning and relationship. We propose three potential pathways for identifying CFs in the U.S., each with advantages and disadvantages. CFs can be identified by using a criteria and indicators approach; by participation in programs or networks designated for CFs; or by their own self-identification as a CF. We suggest that using a hybrid of these approaches will produce the most robust process for knowing a community forest when we see one. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Society & Natural Resources is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/08941920.2024.2361413
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        Text: English
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              Text: Aug2024
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