Analysis of Farmers’ Perception on the Impact of Land Degradation Hazard on Agricultural Land Productivity in Jeldu District in West Shewa Zone, Oromia, Ethiopia
Notice bibliographique
Résumé
Land degradation is increasing in severity and extent in many parts of the world. Success in arresting land degradation entails an improved understanding of its causes, process, indicators and impacts. Various scientific methodologies have been employed to assess land degradation globally. However, the use of local community knowledge in elucidating the causes, process, indicators and effects of land degradation has seen little application by scientists and policy makers. Land degradation may be a physical process, but its underlying causes are firmly rooted in the socio-economic, political and cultural environment in which land users operate. Analyzing the root causes and effects of land degradation from local community knowledge, perception and adapting strategies perspective will provide information that is essential for designing and promoting sustainable land management practices. The main objective of this study was to analyze the perceptions of farmers’ on the impact of land degradation hazard on agricultural land productivity decline associated with soil erosion and fertility loss. The study used a multistage sampling procedure to select sample respondent households. The sample size of the study was 120 household heads and 226 farm plots managed by these farmers. The primary data of the study were collected by using semi-structured Interview, focus group discussions and field observation. Both descriptive statistics and econometric techniques were used for data analysis. Descriptive results show that 57percent of the respondents were perceived the severity and its consequence on agricultural land productivity. The following indicators of soil erosion and fertility loss were generally perceived and observed by farmers’ in the study area: gullies formations, soil accumulation around clumps of vegetation, soil deposits on gentle slopes, exposed roots, muddy water, sedimentation in streams and rivers, change in vegetation species, increased runoff, and reduced rooting depth. The direct human activities which were perceived to be causing land degradation in the study area include: deforestation and clearing of vegetation, overgrazing, steep slope cultivation and continuous cropping. The farmers’ possibility of perceiving the impact of land degradation hazard on agricultural land productivity was primarily determined by institutional, psychological, demographic and by bio-physical factors. Farmers who perceive their land as deteriorating and producing less than desired, tend to adopt improved land management practices. On the other hand, farmers who perceive their land to be fertile tend to have low adoption of conservation practices. In order to overcome this land degradation and its consequent effects, the study recommended a need for the government to enforce effective policies to control and prevent land degradation and these policies should be community inclusive /participatory founded up on indigenous and age-honored knowledge and tradition of farmers' natural resource management as well as introduced scientific practices.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».