Shade 4 Vegetables (SAVE) Project Baseline Report
Farmers in the SAVE restoration sites are highly willing to plant more trees (96% have space and are willing), but their agroforestry knowledge is low (78% report little knowledge) and 74% say agroforestry income is low or extremely low compared with other farm income.
Overview
Baseline study for the Shade 4 Vegetables (SAVE) project (2024-2029), funded by TerraFund for AFR100, which aims to restore 250 ha of degraded catchments in Oljororok and Ndaragwa sub-counties, Nyandarua County, Kenya, by integrating 160,000 trees into the vegetable farming systems of 2,000 smallholder horticulture farmers. Fieldwork ran from 20 June to 4 July 2024 across three wards. The study set baseline values for the project KPIs and described farmer, household and farm characteristics, land management, agroforestry practices, income, knowledge, and attitudes towards tree planting.
Key findings
- Of the farmers profiled, 56% were female, 90% were aged over 35 and only 5% were under 30; 96% had access to a mobile phone (46% smartphones) but only 44% of phone users had used the internet in the last three months.
- Average plot size was 0.75 acres (median 0.52 acres); main crops were maize (61% of plots) and horticulture (25%), and only 53% of farmers belonged to a cooperative, group or association.
- About 80% of farmers saw soil erosion, water management and pests and diseases as problems on their farms, and 95% reported drought cycles and increased low temperatures as the main climate events affecting production.
- Farmers had on average 227 trees on their farms (median 100), mostly cypress (60% of farmers) and eucalyptus (20%), and had planted an average of 66 trees in the last 2-3 years (median 20).
- Only 13% of farmers said agroforestry income was higher than other household income, while 74% said it was low or extremely low; 79% kept no farm cost and revenue records.
- 78% of farmers reported little agroforestry knowledge, 7% none and 4% high; 38% had never received agroforestry training, and 71% named lack of awareness and knowledge as the main barrier to adoption.
- 96% of farmers had space and were willing to plant more trees (average 0.5 acres available), preferring avocado (97%) and apple (85%), and 95% said they would plant more trees even without project support.
In figures
96 % of farmers
78 % of farmers
74 % of farmers
38 % of farmers
Data table
| Item | % of farmers |
|---|---|
| Have space and are willing to plant more trees | 96 |
| Report little agroforestry knowledge | 78 |
| Say agroforestry income is low or extremely low | 74 |
| Never received agroforestry training | 38 |
Recommendations
- Set up robust monitoring of planted trees and farmer practices to raise uptake and tree survival.
- Provide comprehensive training and capacity building for trainers of trainers and farmers on agroforestry design, management and adoption, with refresher training where needed.
- Link farmers to quality tree seedlings suitable for integration with their farming, and train them to choose suitable species.
- Maintain continuous engagement with stakeholders and partners, including county stakeholders and ministries, to support uptake and sustainability after project closure.
- Use an adaptive approach so that shifts not captured at baseline do not undermine the intervention.
- Plan follow-up research: impact assessments, tree survival studies, M&E studies and success stories.
Methodology
Mixed-methods baseline: structured household questionnaires on ODK with about 400 purposively and randomly sampled farmers across three wards (sample size from Cochran's formula against a frame of 2,300 farmers), plus key informant interviews with project staff and one FGD; analysis in Python with triangulation.
Limitations
- Data collected by enumerators is prone to human error, inconsistency and bias, and needed extensive validation and outlier removal.
- The baseline may not have captured some relevant data points or variables.
- No control groups were used, limiting the ability to generalise findings across wards or attribute change to the project.
- Resource constraints (time, funding, expertise) may have limited the depth of the assessment.
- External factors and natural changes over time (baseline drift) may complicate later attribution of change to the project.
