Analysis of Farmers’ Perception on the Impact of Land Degradation Hazard on Agricultural Land Productivity in Jeldu District in West Shewa Zone, Oromia, Ethiopia
Why this work is in the frame
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it