Contribution of wetland resources to household food security in Uganda
Bibliographic record
Abstract
In Uganda, nearly 1.4 million people are currently food insecure, with the prevalence of food energy deficiency at the country level standing at 37%. Local farmers are vulnerable to starvation in times of environmental stress, drought and floods because of dependence on rain-fed agriculture. Accordingly, the farmer’s means of increasing food production has always been an expansion of area under cultivation from virgin and fragile areas, especially wetlands. Consequently, Uganda has lost about 11,268 km 2 of wetland, representing a loss of 30% of the country’s wetlands from 1994 to 2009. While the environmental importance of wetland ecosystems is widely recognized, their contribution to household food security is still hardly explored. In this paper an assessment of the contribution of wetland resources to household food security and factors influencing use of wetland resources in Uganda are reported. A number of livelihood tools in food security assessment including focus group discussions, key informant interviews, direct observations and a household questionnaire survey, were used to collect the data. A total of 247 respondents from areas adjacent to wetlands were involved in the household questionnaire survey conducted in three agro-ecological zones that are frequently characterized as food insecure. The findings indicate that about 83% of the households experienced food insecurity. The main indicators of food insecurity were low harvest (30.9%) and when people buy locally grown food items (18%). Most households felt food secure when they had perennial crops (43.2%) in their gardens, or adequate money to buy food (23.9%). The prevalence of food insecurity was significantly lower among households with older and better educated household heads, but also among households located in Lake Victoria Crescent and South western farmlands agro-ecological zones, but significantly higher among households that were female headed, larger and participate in collection of wetland resources. Over 80% of the respondents reported that wetland resources provide products and services that contribute enormously to their household food security. Besides, they also indirectly contribute to food security by providing services that foster food production such as weather modifications and nutrient retention. Households with older heads and those that reside in the Lake Victoria Crescent agro-ecological zone when compared to counterparts in the Lake Kyoga agro-ecological zone are more likely to have a higher dependence on wetlands for food security. With increasing population around the wetlands, coupled with land shortage and weather variations, households with limited options will continue to generally rely on wetlands for food security and income for sustaining their livelihoods unless alternative livelihood options are provided. There is thus a need to design appropriate food production technologies that ensure sustainable use of wetland resources for food security.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".