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1000 Titel
  • Agroforestry governance for operationalising the landscape approach: connecting conservation and farming actors
1000 Autor/in
  1. Zinngrebe, Yves |
  2. Borasino, Elena |
  3. Chiputwa, Brian |
  4. Dobie, Philip |
  5. Garcia, Edwin |
  6. Gassner, Anja |
  7. Kihumuro, Phillip |
  8. Komarudin, Heru |
  9. Liswanti, Nining |
  10. Makui, Permutia |
  11. Plieninger, Tobias |
  12. Winter, Etti |
  13. Hauck, Jennifer |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-08-09
1000 Erschienen in
1000 Quellenangabe
  • 15(5):1417-1434
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s11625-020-00840-8 |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The expansion and intensification of agriculture as well as the associated land clearing are threatening both biodiversity and human wellbeing in tropical areas. Implementing agroforestry systems through a landscape approach has a strong potential for integrating nature conservation objectives into agricultural systems. A key challenge for implementing the landscape approach is that political processes and conservation initiatives operate in ‘silos’, being largely disconnected from farmers and local key agents responsible for tree governance. In this study we brought together different stakeholders in facilitated, structured focus discussions to analyse the role of actor groups in tree governance. We used social network analysis to quantitatively and qualitatively analyse agroforestry governance networks and actor interactions related to information exchange, finance flows, and regulation. The analyses were conducted at national, sub-national and local levels in four countries: Honduras, Peru, Indonesia, and Uganda. Using trees on farms as a boundary object enabled all participants to bridge common interests and illuminate some of the constraints and opportunities of local governance systems while overcoming institutional and ideological barriers. The quantitative results of the social network analysis identify a strong density of actor linkages. Despite this density, results indicate incoherent and fragmented actor networks undermining the support for agroforestry on all levels. Nevertheless, existing processes related to finance, information, and regulation can be better aligned to ensure an effective implementation and mainstreaming of agroforestry for biodiversity conservation. Building social capital among key actors on both national and local levels can reveal a strong potential for adaptive learning processes mainstreaming agroforestry as essential component of “good farming” and integrating incentive systems for a coherent and effective agroforestry governance. We conclude that redirecting both public and private funding towards continuous seed-funding for the facilitation of these integrated learning processes can transform landscape management and at the same time reduce transaction costs.
1000 Sacherschließung
lokal Net-Map
lokal Social capital
lokal Special Feature: Agroforestry for Sustainable Landscape Management
lokal Social network analysis
lokal Biodiversity
lokal Aichi target 7
lokal Adaptive capacity
lokal Special Feature: Original Article
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-1731-2222|https://frl.publisso.de/adhoc/uri/Qm9yYXNpbm8sIEVsZW5h|https://frl.publisso.de/adhoc/uri/Q2hpcHV0d2EsIEJyaWFu|https://frl.publisso.de/adhoc/uri/RG9iaWUsIFBoaWxpcA==|https://frl.publisso.de/adhoc/uri/R2FyY2lhLCBFZHdpbg==|https://frl.publisso.de/adhoc/uri/R2Fzc25lciwgQW5qYQ==|https://frl.publisso.de/adhoc/uri/S2lodW11cm8sIFBoaWxsaXA=|https://frl.publisso.de/adhoc/uri/S29tYXJ1ZGluLCBIZXJ1|https://frl.publisso.de/adhoc/uri/TGlzd2FudGksIE5pbmluZw==|https://frl.publisso.de/adhoc/uri/TWFrdWksIFBlcm11dGlh|https://frl.publisso.de/adhoc/uri/UGxpZW5pbmdlciwgVG9iaWFz|https://frl.publisso.de/adhoc/uri/V2ludGVyLCBFdHRp|https://frl.publisso.de/adhoc/uri/SGF1Y2ssIEplbm5pZmVy
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1000 Erstellt am 2023-11-18T13:47:28.572+0100
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1000 Zuletzt bearbeitet 2024-04-04T09:22:45.809+0200
1000 Objekt bearb. Thu Apr 04 09:22:45 CEST 2024
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