Human Dimensions of Large-scale Marine Protected Areas: Advancing Research and Practice
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Notice bibliographique
Résumé
This special issue of Coastal Management focuses on the human dimensions of large-scale marine protected areas (LSMPAs), those MPAs that are typically larger than 250,000 km2.11. Toonen et al. (2013 Toonen, R. J., T. A. Wilhelm, S. M. Maxwell, D. Wagner, B. W. Bowen, C. R. C. Sheppard, S. M. Taei, T. Teroroko, R. Moffitt, C. F. Gaymer, et al. 2013. One size does not fit all: The emerging frontier in large-scale marine conservation. Marine Pollution Bulletin 77:7–10.[Crossref], [PubMed], [Web of Science ®], [Google Scholar]) and the Big Ocean network of LSMPA managers define LSMPAs as those larger than 250,000 km2. Other authors have defined LSMPAs as larger than 30,000 km2 (de Santo 2013 de Santo, E. M. 2013. Missing marine protected area (MPA) targets: How the push for quantity over quality undermines sustainability and social justice. Journal of Environmental Management 124:137–46.[Crossref], [PubMed], [Web of Science ®], [Google Scholar]) or 100,000 km2 (Spalding et al. 2013 Spalding, M. D., I. Meliane, A. Milam, C. Fitzgerald, and L. Z. Hale. 2013. Protecting marine spaces: Global targets and changing approaches. Ocean Yearbook 27:213–48.[Crossref], [Google Scholar]; Gruby et al. 2016 Gruby, R. L., N. J. Gray, L. M. Campbell, and L. Acton. 2016. Toward a social science research agenda for large marine protected areas. Conservation Letters 9 (3):153–63.[Crossref], [Web of Science ®], [Google Scholar]). View all notes We define ‘human dimensions’ as the cultural, social, economic, political, and institutional factors that affect and are affected by large-scale marine conservation efforts. While human dimensions of marine conservation and coastal management have long been a focus of research, they have not yet received sustained and systematic consideration in relation to LSMPAs specifically. Although there is an emerging body of scholarship focused on the human dimensions of LSMPAs (e.g. de Santo 2013 de Santo, E. M. 2013. Missing marine protected area (MPA) targets: How the push for quantity over quality undermines sustainability and social justice. Journal of Environmental Management 124:137–46.[Crossref], [PubMed], [Web of Science ®], [Google Scholar]; Harris 2014 Harris, P. 2014. A Political Trilemma? International Secruity, Environmental Protection and Human Rights in the British Indian Ocean Territory. International Politics 51 (1):87–100.[Crossref], [Web of Science ®], [Google Scholar]; Wilhelm et al. 2014 Wilhelm, T. A., C. R. C. Sheppard, A. L. S. Sheppard, C. F. Gaymer, J. Parks, D. Wagner, and N. Lewis. 2014. Large marine protected areas – advantages and challenges of going big: Considerations when going big in MPAs. Aquatic Conservation: Marine and Freshwater Ecosystems 24:24–30.[Crossref], [Web of Science ®], [Google Scholar]; Richmond and Kotowicz 2015 Richmond, L., and D. Kotowicz. 2015. Equity and access in marine protected areas: The history and future of ‘traditional indigenous fishing’ in the Marianas Trench Marine National Monument. Applied Geography 59:117–24.[Crossref], [Web of Science ®], [Google Scholar]; Gruby et al. 2016 Gruby, R. L., N. J. Gray, L. M. Campbell, and L. Acton. 2016. Toward a social science research agenda for large marine protected areas. Conservation Letters 9 (3):153–63.[Crossref], [Web of Science ®], [Google Scholar]; Ban et al. 2017 Ban N. C., T. E. Davies, S. E. Aguilera, C. Brooks, M. Cox, G. Epstein, L. S. Evans, S. M. Maxwell, and M. Nenadovic. 2017. Social and ecological effectiveness of large marine protected areas. Global Environmental Change 43:82–91.[Crossref], [Web of Science ®], [Google Scholar]; Alger and Dauvergne 2017 Alger, J., and P. Dauvergne. 2017. The global norm of large marine protected areas: Explaining variable adoption and implementation. Environmental Policy and Governance 27 (4):298–310. doi:10.1002/eet.1768.[Crossref], [Web of Science ®], [Google Scholar]; Christie et al. 2017 Christie P., N. J. Bennett, N. J. Gray, T. A. Wilhelm, N. Lewis, J. Parks, N. C. Ban, R. L. Gruby, L. Gordon, J. Day, et al. 2017. Why people matter in ocean governance: Incorporating human dimensions into large scale marine protected areas. Marine Policy 84:273–284.[Crossref], [Web of Science ®], [Google Scholar]), this is the first collection of papers devoted to their analysis. The purpose of this special issue is to showcase the diversity of human dimensions of LSMPAs, illustrating the range of contexts in which LSMPAs function, the variety of social science tools that can be used to analyze LSMPAs, the ways that human dimensions considerations can be integrated into LSMPA management, and the diverse human dimensions outcomes that are associated with LSMPAs. We suggest this special issue is timely and valuable for several reasons.
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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 | 0,001 | 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,007 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle