Economic Impact of Climate Change on Food Crop Production using Ricardina Approach: A Case of Kellem Wollega Zone, Ethiopia
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Background: Historical records and increased scientific consensus provide strong evidence that the global climate is changing. Future climate change would lead to an increase in climate variability and the frequency and intensity of extreme events. Agriculture that is dependent on climate conditions is inherently sensitive to climate changes. Today’s world agriculture has gone through challenges from population growth and has adapted to changing economic conditions, technology and resource availabilities. But uncertainty remains concerning the ability of agricultural systems to adapt to climate change. Thus, climate change adaptation of the essence for a resilient food crop production system requires economic transformation by arrangement of institutional and technology. Methods: This study uses the Ricardian model to examine the economic impact of climate change on agriculture in Kellem Wollega Zone, Ethiopia. The net farm revenue is regressed against climate variable (temperature and precipitation), soil and socio-economic variables to help determine the factors that influence variability in net farm revenues. The study was based on the data from a survey of 400 smallholder farming households interviewed across the zone. Result: The Ricardian model analysis shows the coefficients of summer, autumn and winter temperature are positive whereas the coefficient of spring temperature is negative. Regarding the precipitation, the coefficients of summer and spring precipitation are positive while coefficients of autumn and winter precipitation are negative. The marginal impact analysis results show an increase in summer and spring temperatures has mostly negative effects on net farm revenues implying that further temperature increases would be harmful to agricultural activities while increases in autumn temperatures increase net farm revenues in the study area. The summer and spring precipitation would increase the net farm revenue but the autumn precipitation reduces the farm revenue. The elasticity results show that net farm revenues are highly sensitive to changes in climate and the elasticity is relatively high for both summer temperature and precipitation. The impacts of climate change under the three special Reports on Emission Scenarios, (Canadian General Circulation Model, Hadley Centre for Climate Prediction and Research and Parallel Climate Model) predicted that by 2100 net farm revenues would decrease across all farms per hectare by US$ 942.83, US$ 1048.16 and US$ 1024.32 respectively. The finding suggests there is a great need for the concerned bodies to provide up-to-date information about climate change and rainfall patterns in the forthcoming season so that the farmers make informed decisions and develop adaptation strategies.
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.
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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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