“Bright spots” and Effectively Communicating the Ecological and Social Outcomes of Protected and Conserved Areas in Canada
Notice bibliographique
Résumé
Healthy and resilient protected and conserved areas are the foundation of biodiversity conservation, improve livelihoods, and drive sustainable development. Protected lands and seascapes radiate life sustaining ecosystem services and provide important places for nature connection, rejuvenation, and inspiration. Although escalating human pressures and climate change-related risks continue to place many protected and conserved areas under increasing threat, “conservation bright spots” have emerged as a key communications strategy to illustrate where and how biodiversity and the social benefits it provides is performing relatively well. Given the crucial need to educate the public about biodiversity-related issues and amplify solution-centric approaches to support ambitious targets to protect 30 percent of terrestrial, freshwater, and marine area by 2030, the ‘bright spots lens’ is a useful way to learn about and share conservation success information. Because bright spots in conservation are context-specific, with unique goals and values systems, they are defined and applied differently within conservation scholarship literature and in public discourse. There is limited research assessing how conservation bright spots are perceived, defined, and applied in the protected and conserved areas space. To address this scholarly knowledge gap, expert practitioners and researchers in Canada were surveyed to understand the ways in which they characterize bright spots in their work, with special focus on conservation objectives and the communication of outcomes related to protected and conserved areas. Results reveal that while positive biodiversity values underpin bright spot emergence, outcome-factors and themes reference human-nature relationships, Indigenous leadership, knowledge sharing, inspiration and storytelling, and recognition of special conservation milestones along the way. The survey results also captured implications for protected and conserved areas when conservation success knowledge and information is communicated, such as through “success stories” or the profiling of “conservation bright spot” case studies. I conclude by providing recommendations on how protected and conserved area organizations can more effectively mainstream bright spots in education, interpretation, and outreach activities, with a focus on elevating “success” with meaningful narratives and stories. These recommendations can be used to support the effective communication of protected and conserved area goals and objectives and related successes in planning and management. The results can also be used to support the monitoring of progress towards the achievement of the goals and targets of the Kunming-Montreal Global Biodiversity Framework (K-M GBF) (see specifically Targets 3 and 21) as well as biodiversity’s contributions to sustainable development more broadly. While this survey focused on the Canadian context, the results can help managers and decision-makers globally to consider, more holistically, the ways in which “bright spots” can be used to boost awareness and strengthen communication and education efforts related to the benefits of biodiversity and the conservation thereof.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,023 | 0,008 |
| Communication savante | 0,007 | 0,002 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».