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

Fouquet, Roger; Mangubhai, Sangeeta; Jagadish, Arundhati; Tabunakawai-Vakalalabure, Margaret; Tawake, Alifereti; Govan, Hugh; Mills, Morena

doi:10.1038/s41893-023-01123-7

Cited by 8 publications

(2 citation statements)

References 68 publications

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“…For example, repeating our approach with alternative fisheries interventions -such as a pay-to-release by-catch intervention [26] -could help anticipate which measure is more likely to be widely taken up. Such projects could be combined with evidence from impact evaluations, such as the national scale evaluation of the FLMMA network by O'Garra, Mangubhai [44], to calculate the relative cumulative impact of different measures. Furthermore, such forecasts are useful when engaging with decision-makers [34].…”

Section: Discussionmentioning

confidence: 99%

Forecasting the adoption and spread of a community-based marine management initiative using agent-based models

Jørgensen,

Pienkowski,

Clark

et al. 2024

Preprint

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While many successful initiatives for conserving nature exist, efforts to take them to scale have been inadequate. Moreover, conservation science currently lacks a systematic methodology for determining if or when interventions will reach effective scales and how programmatic decisions will affect the scaling process. This paper presents a modelling framework that aims to address both issues by operationalizing Diffusion of Innovations theory and local knowledge using agent-based modelling and Bayesian inference. By applying our framework to existing data on the spatiotemporal adoption of a community-based marine management initiative in Fiji, we demonstrate that our approach can identify the mechanisms that govern the observed adoption patterns. In this case, the relative advantage of the intervention, village social networks, and perceived knowledge stand out as important drivers of adoption. Using the identified causal processes, our approach can forecast business-as-usual and counterfactual future scenarios and hence inform conservation policy. Finally, we highlight the importance of spatiotemporal data for making detailed scaling predictions. We structure the paper as a step-by-step guide, highlighting our modelling decisions and possible limitations. Thus, besides presenting a case study, this paper serves as a template for practitioners and researchers to better model the scaling process of other conservation interventions.

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Section: Discussionmentioning

confidence: 99%

Forecasting the adoption and spread of a community-based marine management initiative using agent-based models

Jørgensen,

Pienkowski,

Clark

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Each LMMA is uniquely designed to meet local needs with support from partners, building on customary tenure and fishing rights 2 . A comprehensive study of Fijian coastal villages by O'Garra et al 3 in Nature Sustainability, shows that although community-based marine management can create the mechanisms to deliver conservation benefits, this does not always translate into positive social and ecological outcomes. Worldwide, four out of ten small-scale fishers are women, but they can be marginalized in fisheries decision-making.…”

Section: Involving Locals In Marine Conservation and Management Has B...mentioning

confidence: 99%