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Enregistrement W4411729129 · doi:10.1016/j.envc.2025.101221

Small-scale fisherfolk in Papua New Guinea: Perspectives on climate variability and its impact on coastal fishing operations and activities

2025· article· en· W4411729129 sur OpenAlex

Pourquoi ce travail est dans la base

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Notice bibliographique

RevueEnvironmental Challenges · 2025
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMarine Bivalve and Aquaculture Studies
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesNational Science and Technology Council
Mots-clésNew guineaFishingScale (ratio)Fishing villageGeographyEnvironmental resource managementFisheryEnvironmental planningBusinessEnvironmental scienceHistoryBiologyCartographyEthnology

Résumé

récupéré en direct d'OpenAlex

This study aimed at exploring climate variability and small-scale fishers’ perspectives on how climate variability impacts fishing operations in Papua New Guinea. Climate data from 2000 to 2020 and participatory interactions with 80 fishers in three fishing villages of East New Britain (ENB) province were utilized. Findings revealed that traditionally, small-scale fisheries (SSFs) have sustained coastal and island communities' livelihoods of ENB for millennia. However, the projected impacts of climate change (CC) are posing significant challenges to fishers, yet limited research has explored the plight of SSFs, and fishers including their knowledge of CC variability. Coastal livelihoods and activities are dependent on fishing and fishing knowledge that is cross-generational. Women and renowned fishers (with unique fish harvesting skills) are critical actors, e.g., in the identifying historically rich fishing grounds, and helping fishers/community in fishing activities and community festivals. Fishing is a sociocultural identity, and this has led to emphasis on sustainable fishing practices, by fishers and some key stakeholders, including the utilization of eco-friendly gear and stone traps. However, the fishers population is ageing. During peak fishing seasons that last one week per month, and depending on the fishing method, fishers earn between 300 to 1500 Kina (72-259 USD) daily. Increasing socioecological shifts were reported, including reducing fish economic value, changing fishing locations, and declining catch. Since 2000, sea surface temperatures (SSTs) have increased by about 1°C and in December 2020, SST reached 30.20°C, with the northern and eastern coastal zones of PNG being greatly affected. Fishers reported four critical concerns that affect their livelihoods and which could increase their vulnerability to human-environmental risks. 65 percent of fishers are uncertain or have limited knowledge on CC, climate variability, drivers, and their impacts. Fishers emphasized fourteen perspectives that could mitigate the increasing socioecological shocks and vulnerabilities they face. Most of the perspectives cut across the socio-cultural, economic, institutional, and environmental domains of sustainable fishing practices. Five starting points for sustainability transformations for policy and research are recommended including: (1) education programs on ecological processes, fishers’ local socioecological knowledge and climate variability, (2) collaborative stakeholder engagements in CC-policy design and community adaptation and mitigation actions, (3) integrated socio-ecological approaches on marine resource management, cost-benefit sharing, and co-management, (4) capacity-building programs and initiatives, and (5) proactive national-level prioritization of coastal and island fishers’ rights. Although fishers in ENB are reportedly uncertain about CC knowledge and yet there is evidence of pronounced climate variability, ocean environmental parameters, threatened fishery and livelihoods vulnerabilities, collaborative and effective fisheries management approaches might mitigate it. This can be via proactive integration of CC adaptation, sustainable fisheries management, better governance within the existing institutional structures, and support for community-led resilience strategies.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,168
Score d'incertitude au seuil0,795

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,253
Écart entre enseignants0,238 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle