Towards a classification of vulnerability of small-scale fisheries
Environmental Science and Policy
; 134:1-12, 2022.
Article
Dans Anglais
| EMBASE | ID: covidwho-20237206
ABSTRACT
Vulnerability of small-scale fisheries (SSF) results from complex interactions amongst various threats and stressors, including biophysical risks, environmental variability, unstable political situations, and weak governance, to name a few. SSF vulnerability has become more evident, with increased severity, during the COVID-19 pandemic. Knowledge about what makes SSF vulnerable is limited, which impedes appropriate policy responses and intervention. As a first step to rectifying the situation, a classification approach is proposed to better describe and differentiate types of vulnerability to SSF and to guide data collection and dissemination about SSF vulnerability. The classification system is developed based on a narrative review of case studies worldwide, published in scientific journals in the past 20 years. The case studies cover SSF in diverse aquatic environments, including river, floodplain, reservoir, river delta, lake, atoll, estuaries, lagoon mangrove, coral reefs, seagrass ecosystem, islands, coastal and marine environment. Similar to the five pillars of sustainability, SSF vulnerability is associated with five main factors, i.e., biophysical, social, economic, technological, and governance. Knowledge about SSF vulnerability helps inform tailored management strategies and policies to reduce SSF marginalization and promote viability, aligning, therefore, with the goal of the Voluntary Guidelines for Securing Sustainable Small-Scale Fisheries.Copyright © 2022 Elsevier Ltd
Classification system; Narrative review; Small-scale fisheries; SSF Guidelines; Sustainability; Vulnerability factors; aquatic environment; coral reef; ecosystem; estuary; fishery; floodplain; human; lagoon; mangrove; marine environment; narrative; nonhuman; practice guideline; review; river; seagrass; vulnerability
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
EMBASE
Type d'étude:
Étude pronostique
/
Révision
langue:
Anglais
Revue:
Environmental Science and Policy
Année:
2022
Type de document:
Article
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