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Local knowledge enhances the sustainability of interconnected fisheries

Carine Emer Orcid Logo, Miguel Lurgi Rivera Orcid Logo, Sérgio Timóteo Orcid Logo, João Vitor Campos‐Silva Orcid Logo, Shai Pilosof Orcid Logo

Journal of Applied Ecology, Volume: 63, Issue: 1, Start page: e70213

Swansea University Author: Miguel Lurgi Rivera Orcid Logo

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DOI (Published version): 10.1111/1365-2664.70213

Abstract

Local knowledge (LK) refers to the ancestral understanding that Indigenous Peoples and local communities have developed over centuries through trial‐and‐error and hands‐on management of natural resources. LK may provide valuable insights for biodiversity conservation and human well‐being. However, i...

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Published in: Journal of Applied Ecology
ISSN: 0021-8901 1365-2664
Published: Wiley 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71271
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However, its effectiveness remains under&#x2010;explored at large scales, especially where multiple communities manage ecosystems. One example is fisheries, which form complex, interconnected networks where fish move across spatial boundaries between managed areas. Fisheries are critical for food security and income, yet face threats from overharvesting. Fisheries Co&#x2010;Management (FCM)&#x2014;a partnership between local communities and governments&#x2014;leverages LK. However, the value of LK in designing protection strategies remains unclear. Using a process&#x2010;based dynamical model parameterized with empirical data, we evaluated FCM strategies for pirarucu ( Arapaima gigas ) fisheries, which form a metapopulation network of protected and unprotected lakes in the Brazilian Amazon. 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spelling 2026-01-19T10:58:14.7516313 v2 71271 2026-01-19 Local knowledge enhances the sustainability of interconnected fisheries 947df89d116a1ab75515e421089e0443 0000-0001-9891-895X Miguel Lurgi Rivera Miguel Lurgi Rivera true false 2026-01-19 BGPS Local knowledge (LK) refers to the ancestral understanding that Indigenous Peoples and local communities have developed over centuries through trial‐and‐error and hands‐on management of natural resources. LK may provide valuable insights for biodiversity conservation and human well‐being. However, its effectiveness remains under‐explored at large scales, especially where multiple communities manage ecosystems. One example is fisheries, which form complex, interconnected networks where fish move across spatial boundaries between managed areas. Fisheries are critical for food security and income, yet face threats from overharvesting. Fisheries Co‐Management (FCM)—a partnership between local communities and governments—leverages LK. However, the value of LK in designing protection strategies remains unclear. Using a process‐based dynamical model parameterized with empirical data, we evaluated FCM strategies for pirarucu ( Arapaima gigas ) fisheries, which form a metapopulation network of protected and unprotected lakes in the Brazilian Amazon. We combined our metapopulation model with LK, fish biology and network theory to assess how lake protection, fishing quotas and illegal fishing impact pirarucu population abundance at the riverscape scale. By analysing 13 FCM‐protected lakes and 18 unprotected lakes, we contrasted six hypothesis‐driven management strategies against the current one, which is based on LK. In all strategies, protected lakes support higher pirarucu populations and buffer against increased fishing pressure, while unprotected lakes face population collapse due to the lack of fishing regulations. While a strategy that provides the best outcomes in terms of metapopulation persistence was based on pirarucu carrying capacity, the currently applied FCM strategy closely matched its efficacy. Synthesis and applications . Our modelling approach allows managers to compare alternative conservation strategies under different socio‐ecological scenarios, highlighting trade‐offs and guiding investment of effort and resources. While immediately valuable for pirarucu management in the Middle Juruá, the framework scales across tiers of applicability, each requiring progressively greater model adaptation: from supporting FCM in other Amazonian regions (with minimal adjustment), to adaptation for other riverine fisheries and ultimately to broader socio‐ecological systems. In this way, we provide both system‐specific insights and a flexible tool for advancing sustainable management of natural resources across contexts. Journal Article Journal of Applied Ecology 63 1 e70213 Wiley 0021-8901 1365-2664 conservation, ecosystem management, ecosystem services, fish ecology, metapopulation dynamics, socio-ecological systems, spatial networks 1 1 2026 2026-01-01 10.1111/1365-2664.70213 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University Another institution paid the OA fee The Pilot House; Fulbright Amazônia Program; Synchronicity Earth; Mulago Foundation; Fundação de Amparo à Pesquisa do Estado do Amazonas. Grant Number: 01.02.016301.04664/2022-03; Israel Science Foundation. Grant Number: 1281/20; Fundação para a Ciência e a Tecnologia. Grant Number: CEECIND/00135/2017/CP1460/CT0002; International Conservation Fund of Canada; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro. Grant Number: FAPERJ Proc. E-26/200.610/2022; National Geographic; Rolex Perpetual Planet Amazon Expedition; Gordon and Betty Moore Foundation. 2026-01-19T10:58:14.7516313 2026-01-19T10:51:20.5356681 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Carine Emer 0000-0002-1258-2816 1 Miguel Lurgi Rivera 0000-0001-9891-895X 2 Sérgio Timóteo 0000-0003-2417-3259 3 João Vitor Campos‐Silva 0000-0003-4998-7216 4 Shai Pilosof 0000-0003-0430-5568 5 71271__36043__5f48af3339764154a0e8ac0a06f114e7.pdf 71271.VOR.pdf 2026-01-19T10:56:08.4079264 Output 1032813 application/pdf Version of Record true © 2025 The Author(s). Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License. true eng http://creativecommons.org/licenses/by-nc/4.0/
title Local knowledge enhances the sustainability of interconnected fisheries
spellingShingle Local knowledge enhances the sustainability of interconnected fisheries
Miguel Lurgi Rivera
title_short Local knowledge enhances the sustainability of interconnected fisheries
title_full Local knowledge enhances the sustainability of interconnected fisheries
title_fullStr Local knowledge enhances the sustainability of interconnected fisheries
title_full_unstemmed Local knowledge enhances the sustainability of interconnected fisheries
title_sort Local knowledge enhances the sustainability of interconnected fisheries
author_id_str_mv 947df89d116a1ab75515e421089e0443
author_id_fullname_str_mv 947df89d116a1ab75515e421089e0443_***_Miguel Lurgi Rivera
author Miguel Lurgi Rivera
author2 Carine Emer
Miguel Lurgi Rivera
Sérgio Timóteo
João Vitor Campos‐Silva
Shai Pilosof
format Journal article
container_title Journal of Applied Ecology
container_volume 63
container_issue 1
container_start_page e70213
publishDate 2026
institution Swansea University
issn 0021-8901
1365-2664
doi_str_mv 10.1111/1365-2664.70213
publisher Wiley
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
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description Local knowledge (LK) refers to the ancestral understanding that Indigenous Peoples and local communities have developed over centuries through trial‐and‐error and hands‐on management of natural resources. LK may provide valuable insights for biodiversity conservation and human well‐being. However, its effectiveness remains under‐explored at large scales, especially where multiple communities manage ecosystems. One example is fisheries, which form complex, interconnected networks where fish move across spatial boundaries between managed areas. Fisheries are critical for food security and income, yet face threats from overharvesting. Fisheries Co‐Management (FCM)—a partnership between local communities and governments—leverages LK. However, the value of LK in designing protection strategies remains unclear. Using a process‐based dynamical model parameterized with empirical data, we evaluated FCM strategies for pirarucu ( Arapaima gigas ) fisheries, which form a metapopulation network of protected and unprotected lakes in the Brazilian Amazon. We combined our metapopulation model with LK, fish biology and network theory to assess how lake protection, fishing quotas and illegal fishing impact pirarucu population abundance at the riverscape scale. By analysing 13 FCM‐protected lakes and 18 unprotected lakes, we contrasted six hypothesis‐driven management strategies against the current one, which is based on LK. In all strategies, protected lakes support higher pirarucu populations and buffer against increased fishing pressure, while unprotected lakes face population collapse due to the lack of fishing regulations. While a strategy that provides the best outcomes in terms of metapopulation persistence was based on pirarucu carrying capacity, the currently applied FCM strategy closely matched its efficacy. Synthesis and applications . Our modelling approach allows managers to compare alternative conservation strategies under different socio‐ecological scenarios, highlighting trade‐offs and guiding investment of effort and resources. While immediately valuable for pirarucu management in the Middle Juruá, the framework scales across tiers of applicability, each requiring progressively greater model adaptation: from supporting FCM in other Amazonian regions (with minimal adjustment), to adaptation for other riverine fisheries and ultimately to broader socio‐ecological systems. In this way, we provide both system‐specific insights and a flexible tool for advancing sustainable management of natural resources across contexts.
published_date 2026-01-01T05:34:54Z
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