Factors affecting smallholder farmers’ local knowledge-based adaption to build resilience in Wolaita zone, Ethiopia

Abstract

This study aims to identify factors affecting local adaptation strategies smallholder farmers are practising to adapt multiple stresses. Primary data were collected from 400 randomly sampled households from six districts of Wolaita zone by face-to-face interviews, focus group discussions, and key informant interviews. Survey data were analyzed using both descriptive and inferential statistics. A binary logit model was employed to identify factors affecting smallholder farmers’ local adaptation strategies. A total of 15 explanatory variables, identified from relevant empirical literature, was included in the binary logit model to assess their relationship to the dependent variable – households’ decision to employ various local adaptations. The study found that eight of the explanatory variables such as age, farmland size, livestock owned, income, distance to market, extension agent visist, participation in the local organizations, and agro-ecology significantly influenced local adaption strategies. Additionally, qualitative data from focus group discussions and key informant interviews showed that the role and use of local adaptation have been ignored and marginalized. This study suggests the government should recognize the importance of local knowledge, multiple stakeholders should participate to enhance smallholders’ adaptabilities, interdisciplinary research is required, and communities should be supported to share their knowledge to build synergies between different knowledge systems.

Keywords:

• local adaptation strategies
• local knowledge
• resilience
• smallholder farmers

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical statement

Prior to the research being carried out and before data collection began, a full risk assessment and ethical review were conducted and approved by the University College Dublin Ethics Review Committee and Wolaita Sodo University Institutional Review Board (IRB).

Data availability statement

All the data underlying the findings described in the manuscript are fully available. The data are organized in the form of tables. There are six tables that embrace all the relevant data within three categories, including description of explanatory variables and expected signs (one table), local knowledge-based adaptation strategies and types (two tables), descriptive statistics for continuous explanatory variables and categorical variables (two tables), and binary logit model output (one table).

Notes

1 Focus group discussion with farmers on 9 June 2021 at Ampo Koysha kebele (Own translation).

2 Focus group discussion with farmers on 13 June 2021 at Damot Sore kebele (Own translation).

3 Interview with one of extension workers conducted on 10 June 2021 at Tora Sadebo kebele (Own translation).

4 Focus group discussion with farmers on 17 June 2021 at Zalla Shasha kebele (Own translation).

5 Focus group discussion with farmers on 15 June 2021 at Akabilo kebele (Own translation).

6 Focus group discussion with farmers on 14 June 2021 at Damot Sore kebele (Own translation).

7 Focus group discussion with farmers on 19 June 2021 at Duguna Boloso kebele (Own translation).

Additional information

Funding

This work was supported by Horizon 2020 Framework Programme: [Grant Number 778196].