Developing policy instruments to tackle abandoned, lost, or discarded fishing gear problem in Thailand
Notice bibliographique
Résumé
Due to global concern over marine debris and plastic pollution, Thailand has become more conscious of abandoned, lost, or otherwise discarded fishing gear (ALDFG) issues. However, ALDFG management is not fully addressed in existing policies and roadmaps. Consequently, this research aims to examine ALDFG status, impacts, and existing international and national regulations. A systematic review (SR) was used to gather information, and a semi-structured interview with 23 key informants took place to investigate the root cause of ALDFG and explore suitable solutions to ALDFG problems in Thailand. Multi-criteria decision-making (MCDM) method was adopted to prioritize and assess proposed policy options regarding the effectiveness and impacts affecting stakeholders, including the challenges and limitations. The key finding shows that several international and regional seas conventions exist to handle the marine pollution problem. Comprehensive practice overcoming ALDFG mainly falls on non-binding bodies and agreements deterring IUU fishing explicitly prohibiting intentional discharge from fishing gear and banning the use of gear inappropriately marked. At the implementation level, developed countries such as Canada, Norway, The USA, Australia and the EU, have tackled ALDFG by relying on their national laws and having financial support from their states. The mixed combination of policy instruments used by these countries proved that no one solution fits all. In Thailand, many laws govern marine pollution from ships. However, ADLDF is not directly addressed in the existing laws and regulations, leading to ambiguity regarding the responsible agencies and a lack of ALDFG data collection. In terms of the root cause of ALDFG generated by Thai fishery, poor maintenance, severe weather, gear conflict, loss of flag buoy, sunlight and salinity of the sea, and low-quality net texture cause net damage and put a higher chance to become ALDFG. Fishermen who use dynamic gears have less chance of gear-losing events than those who use passive gears. The capacity of gear retrieval procedures by commercial fishery is better than artisanal fishery due to expertise. When fishing gear (FG) is no longer in use, it is taken to be sold at second-hand shops or reused as a henhouse. Unfortunately, some of them were burned. Based on the MCDM method, the prioritized solutions to tackle the ALDFG problem in Thailand are a voluntary program of ALDFG removal scheme and a government-subsidized program of Port Reception Facilities (PRF) for FG, and the Extended Producer Responsibility (EPR) model of FG. As a result, this study calls for relevant authorities to discuss and share responsibilities for dealing with ALDFG issues, starting with the use of FG through the period of fishing gear being ghost gear.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».