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National-level evaluation of a community-based marine management initiative

Nature Sustainability volume 6, pages 908–918 (2023)Cite this article

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Abstract

Community-based approaches to conservation and natural resource management are considered essential to meeting global conservation targets. Despite widespread adoption, there is little understanding about successful and unsuccessful community-based practices because of the challenges of designing robust evaluations to estimate impacts and analyse the underlying mechanisms to impact. Here we present findings from a national scale evaluation of the ‘locally managed marine areas’ network in Fiji, a marine community-based management initiative. Using data from 146 villages selected using matching methods, we show that engagement in the Fijian locally managed marine areas network leads to improvements in all mechanisms hypothesized to generate conservation outcomes (participation, knowledge, management and financial support). Yet these mechanisms translate to few social outcomes and have no effect on the perceived ecological health of a village’s fishing grounds. Our findings show that practitioners may need to carefully evaluate and adapt the mechanisms that they expect will generate impact from community-based projects to improve outcomes for people and the rest of nature.

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Fig. 1: Directed acyclic graphs (DAGs) of FLMMA impact on final outcomes and hypothesized mechanisms to impact.
Fig. 2: Estimates of the impact of FLMMA membership on key outcomes.
Fig. 3: Effects of FLMMA via mechanisms on subset of final outcomes found to be influenced by at least one mechanism, including the direct effect from FLMMA.

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Data availability

Summary data that support the findings of this study are available within the paper and Supplementary Information. FLMMA member village data are available upon request from the FLMMA Secretariat (email contact: info@lmmanetwork.org). Covariate data used for matching were provided by the Ministry of Lands and Mineral Resources and Fiji Roads Authority, with the exception of coral cover data, which are publicly available from the Millennium Coral Reef Mapping Project (available at https://oceancolor.gsfc.nasa.gov/cgi/landsat.pl). Raw data from the interviews are available on request from the corresponding author (T.O.) with reasonable restrictions, as respondents belong to the Indigenous iTaukei group and have additional protections under our ethical review process. Data and code used for the analysis will be made available no more than 2 weeks after the data use agreement has been agreed and signed.

Code availability

Stata code used for analysis in this study is available at the repository in the Open Science Framework (https://osf.io/g94ya/).

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Acknowledgements

This project was funded by the British Academy’s Knowledge Frontiers: International Interdisciplinary Research Projects Programme (award reference: KF2\100033) (T.O., S.M., H.G., A.T., M.T.-V. and M.M.). Additional funding was provided by John D. and Catherine T. MacArthur Foundation (grant no. 16-1608-151132-CSD) (A.J. and M.M.) and the Margaret A. Cargill Foundation (grant agreement no. JW55 for Alliance for Conservation Evidence and Sustainability) (S.M.). We thank the staff from the provincial offices of Ba, Bua, Cakaudrove, Kadavu, Lomaiviti, Macuata, Nadroga/Navosa, Ra, Rewa, Serua and Tailevu for supporting this research. We are grateful to the team leaders (E. Waqa, M. Lalawa and V. Tikoenavuli) and data collectors (N. Drose, A. N. Ratu, J. Ratuva, U. Navuni, U. Vuli, M. Radinimatai, L. Uluiburotu, T. Dradra, R. T. Rokoratu and O. Vosailagi) who administered the surveys. We acknowledge I. Qauqau (WCS) for assisting with organization of baseline data, and A. Bueno (Middlesex University) for programming the data entry platform. We acknowledge Y. Nand (WCS) for overseeing the management of data entry, and volunteers R. Audh, N. Bhan, N. N. Prasad and V. Duavakacagi who assisted with data entry. We acknowledge the valuable inputs of FLMMA representatives, A. Qorovarua, T. Seru, K. Ravonoloa, R. I. Baleirotuma and T. Veibi together with our partner organisations working on sites, WCS, World Wide Fund for Nature, Pacific Blue Foundation and Global Vision Initiative with the selection of sites. The FLMMA Secretariat coordinated all logistics for the surveys. Finally, we acknowledge the 146 Fijian communities, including the chiefs, Yaubula and women groups, fishers and youth groups whose goodwill, wisdom and shared experience on decades of LMMA implementation efforts become the basis of these analyses and the paper. The research contributed to the long-standing mission of the LMMA Network International to support learning of communities and partners about community based adaptive management and the Lessons Learned Initiative. This is contribution no. 6 from the ‘Insights for Catalyzing Conservation at Scale’ initiative.

Author information

Author notes

  1. Tanya O’Garra

    Present address: Institute for Environment and Sustainability, Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore

Authors and Affiliations

  1. Department of Economics, Middlesex University, London, UK

    Tanya O’Garra

  2. Wildlife Conservation Society Fiji, Suva, Fiji

    Sangeeta Mangubhai

  3. Talanoa Consulting, Suva, Fiji

    Sangeeta Mangubhai

  4. The Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA

    Arundhati Jagadish

  5. Fiji Locally Managed Marine Area Network, Suva, Fiji

    Margaret Tabunakawai-Vakalalabure & Alifereti Tawake

  6. World Wide Fund For Nature - Pacific, Suva, Fiji

    Margaret Tabunakawai-Vakalalabure

  7. Locally Managed Marine Area Network International Trust, Suva, Fiji

    Alifereti Tawake & Hugh Govan

  8. School of Law and Social Sciences, University of the South Pacific, Suva, Fiji

    Hugh Govan

  9. Centre for Environmental Policy, Imperial College London, London, UK

    Morena Mills

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Contributions

T.O., M.M., S.M., A.T. and M.T.-V. designed research. T.O., M.M., S.M., A.J., A.T. and M.T.-V. performed research. T.O. analysed data. T.O., M.M., S.M., H.G., A.J., A.T. and M.T.-V. wrote the paper.

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Correspondence to Tanya O’Garra.

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Extended data

Extended Data Fig. 1 Full set of SEM results depicting pathways from FLMMA to final outcomes via hypothesized mechanisms.

a. Causal model showing relationships to and between mechanisms (black pathways). Blue pathways vary by final outcome. b. Coefficients (standard errors in parentheses) for (blue) pathways (h, j, k, l, m) leading to final outcomes, listed as follows: (1) Village assets, (2) Household assets, (3) Diversity of income activities, (4) Non-dependence on fisheries for income, (5) Diversity food-gen activities, (6) Non-dependence on fisheries for food, (7) Satisfied with food from sea, (8) Fish catch, (9) Reef health good, (10) Mangrove not declined, (11) Subjective wellbeing, (12) Perceived management benefits. Coefficient of determination (CD) shows the fraction of variation (variance) explained by a model (higher values indicate better fit). The standardized root mean square residual (SRMR) describes the standardized difference between the observed correlation and the predicted correlation (values <0.08 indicate a good fit). †Missing observations are due to non-answers (refusal to answer or ‘don’t know’) except for outcomes (9) and (10) which only have responses from villages with reefs or mangroves. Level of significance: *p < 0.1, **p < 0.05, ***p < 0.001 (two-sided tests).

Extended Data Fig. 2 SEM results, participation operationalized in terms of women’s participation.

a. Causal model showing relationships to and between mechanisms (black pathways). Blue pathways vary by final outcome. b. Coefficients (standard errors in parentheses) for (blue) pathways (h, j, k, l, m) leading to final outcomes, listed as follows: (1) Village assets, (2) Household assets, (3) Diversity of income activities, (4) Non-dependence on fisheries for income, (5) Diversity food-gen activities, (6) Non-dependence on fisheries for food, (7) Satisfied with food from sea, (8) Fish catch, (9) Reef health good, (10) Mangrove not declined, (11) Subjective wellbeing, (12) Perceived management benefits. Coefficient of determination (CD) shows the fraction of variation (variance) explained by a model (higher values indicate better fit). The standardized root mean square residual (SRMR) describes the standardized difference between the observed correlation and the predicted correlation (values <0.08 indicate a good fit). †Missing observations are due to non-answers (refusal to answer or ‘don’t know’) except for outcomes (9) and (10) which only have responses from villages with reefs or mangroves. Level of significance: *p < 0.1, **p < 0.05, ***p < 0.001 (two-sided tests).

Extended Data Table 1 Indicators used to measure intermediate and final outcomes
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Supplementary Information 1–11, Tables 1–5 and Figs. 1–15.

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O’Garra, T., Mangubhai, S., Jagadish, A. et al. National-level evaluation of a community-based marine management initiative. Nat Sustain 6, 908–918 (2023). https://doi.org/10.1038/s41893-023-01123-7

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