Motivation and harvesting behaviour of fishers in a specialized fishery targeting a top predator species at risk
Notice bibliographique
Résumé
Abstract Effective management of wildlife resources depends on understanding and cooperating with the human users of the resource, particularly as policies may be rejected if user satisfactions are not met. In Australia, recreational anglers can legally target a migratory top predator, the shortfin mako shark Isurus oxyrinchus , which is also a species at risk. It is assumed that most of the sharks are released and population remains minimally impacted; yet, the actual release rate of this species is unknown and little information is available about anglers that participate in this fishery. Fishing motivations and behaviours were ascertained by a web survey of recreational shark anglers from three south‐eastern Australian states. Respondents reported that ~70% of the captured makos were released, with significant geographic variation in release rates between states. Most anglers reported being motivated by the catch‐based objectives, the thrills and challenges, rather than harvest‐based motivations. However, there were significant differences in harvesting motivation among states. This could be attributed to the varying value assigned to shortfin mako as a sport fish and table fish among regions. Additionally, higher rates of release among anglers from New South Wales may be linked to increased opportunity for resource substitution (i.e. greater diversity of game fish species) and established norms driven by current catch‐and‐release fisheries in that region. Increased participation in catch‐and‐release fishing may be achieved by establishing behavioural norms by the provision of more desirable incentives to release sharks during fishing competitions. Data on regional variation in release rates yield important information for managers to target specialized fishers to incentivize catch‐and‐release fishing with an objective of changing behaviour. Many anglers understand that sharks are important to marine ecosystems and messaging may be important to deliver effective management given that most anglers are motivated by catch‐based objectives even though many enjoy harvesting makos. Information on natural resource user motivations and satisfactions, such as studied here, has the potential to guide management actions and the ways in which managers interact with resource users. A plain language summary is available for this article.
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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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».