Environmental Concerns and Stewardship Behaviors Among Rural Landowners: What Supports Farmers and Non-farmers in Being Good Stewards?
Notice bibliographique
Résumé
Intensive agriculture is a main factor of biodiversity and ecosystem services loss globally. It is therefore of great importance to understand how rural landowners are managing their lands and how environmental stewardship behaviors could be strengthened. Farming and non-farming rural landowners are often considered a homogenous group. In reality, however, they vary by their histories, attitudes, interests, and resources. While many rural landowners manage their lands with environmental values in mind, others may struggle to do so. Ignoring this diversity poses the risk that planning and policy for sustainable agriculture are less effective than they could be. Hence, it is of interest to understand the variety of environmental perceptions and stewardship behaviors across these varied groups. To help addressing this knowledge gap, we conducted a survey of 1,200 farming and non-farming rural landowners, using Ontario as a case study. We specifically investigated whether farming landowners differed from non-farming landowners in expressed environmental concerns and stewardship behaviors, as well as what the roles are of participation in conservation incentive programs, demographic factors, and landholding characteristics. We analyzed survey answers with logistic regression and text analysis. Our results suggest that farming landowners are generally less environmentally concerned than non-farming landowners. However, it appears that this difference may be less driven by farm ownership than by contextual factors, such as landowner age and participation in conservation programs. Participation in conservation programs was more pronounced for non-farming landowners and was associated with higher likelihood of environmental concerns and engaging with stewardship behaviors. In contrast, higher age emerged as predictor of lower environmental concerns. In addition, we found that cost factors and knowledge needs were important barriers for stewardship behaviors across farming and non-farming rural landowners. Based on our results, we are making recommendations for increasing the effectiveness of agricultural sustainability planning and policy in Ontario, focusing on reducing financial and knowledge barriers to pro-environmental land management behaviors.
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 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 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 ».