Agroforestry Community Forestry Adoption and Performance in Myanmar's Bago-Yoma Region

Myanmar's Bago-Yoma region is the focus of this dataset, which analyzes the adoption and performance of agroforestry-based community forests (ACFs) on agricultural encroachment land. It was created by Su Mon San of the University of Bonn and includes survey data from 291 farmers and inventory data from 42 sample plots. The study uses binary logistic regression, ANOVA, and correlation tests to evaluate factors influencing ACF adoption.

Use Cases

• Modeling farmer adoption likelihood based on factors like farmland size and perception of trees
• Comparing the performance of different agroforestry planting designs mentioned in the study
• Analyzing the gap between official registry participation and actual farmer engagement in ACFs
• Evaluating the influence of institutional factors, such as Forest Department decisions on species selection, on program outcomes

Strengths

• Includes primary data from a substantial survey of 291 farmers
• Combines survey responses with physical inventory data from 42 sample plots
• Analysis employs multiple statistical methods: binary logistic regression, one-way ANOVA, and non-parametric correlation tests

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect geographic bias inherent to the single-region study in Bago-Yoma

Provenance

Source

University of Bonn

Collection Method

Data gathered through farmer surveys (291 respondents) and field inventory of sample plots (42 plots).

Geography

Bago-Yoma region, Myanmar