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Review
. 2025 Feb 21;11(4):e42796.
doi: 10.1016/j.heliyon.2025.e42796. eCollection 2025 Feb 28.

Evaluating the effects of Climate Smart Agricultural (CSA) practices on productivity, adaptation, and mitigation indicators in Ethiopia: A meta-analysis approach

Zenebe Adimassu  1 , Degefie Tibebe  1 , Lulseged Tamene  2 , Wuletawu Abera  3
Affiliations
Review

Evaluating the effects of Climate Smart Agricultural (CSA) practices on productivity, adaptation, and mitigation indicators in Ethiopia: A meta-analysis approach

Zenebe Adimassu et al. Heliyon. .

Abstract

Climate-smart agricultural (CSA) practices have been adopted in various agroecological zones in Ethiopia to enhance productivity, improve resilience to climate change, and reduce greenhouse gas emissions through carbon sequestration. However, the overall impact of different CSA practices on productivity, adaptation, and mitigation metrics has not been exhaustively evaluated. The study employed a meta-analysis approach based on data from 220 peer-reviewed articles to assess the effects of commonly used CSA practices on these indicators across Ethiopia's diverse agroecological regions. The analysis identified over 20 CSA practices, with most-except soil bunds, level Fanya juu, and deficit irrigation-showing positive effects on productivity, peaking with drip irrigation (effect size of 2.15). Almost all practices also effectively reduced runoff and soil erosion, particularly crop residue mulching, which had a remarkable effect size of 2.95. Additionally, the findings indicated that various CSA practices enhanced soil organic matter and carbon stocks. Water management practices, especially drip and deficit irrigation, demonstrated significantly higher water productivity than traditional flood irrigation, with an effect size of up to 2.6. This water use efficiency suggests that these methods could free up substantial water resources for irrigating additional land, thus boosting crop production in water-scarce areas. However, the analysis revealed a negative effect size of up to -0.74 for income derived from drip irrigation, primarily due to the high costs of the necessary equipment. This highlights the need for reforms in duty and tax exemptions to improve farmers' profitability from drip irrigation systems. Overall, this meta-analysis assesses the impact of various CSA practices on key performance indicators productivity, adaptation, and mitigation-providing insights that can guide the packaging and implementation of the most effective CSA strategies across Ethiopia's agroecological zones.

Keywords: Carbon sequestration; Climate-smart agriculture; Meta-analysis; Soil organic matter; Water productivity.

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Conflict of interest statement

As a corresponding author, I, on behalf of all the authors, declare that we have no known Competing financial and professional interests or personal relationships that could have Appeared to influence this research publication.

Figures

Fig. 1
Fig. 1
Steps in the meta-analysis of the effects of CSA practices (source: Authors' construction).
Fig. 2
Fig. 2
Distribution of publications over the years (1986–2022) regarding the effects of CSA practices on productivity, adaptation and mitigation pillars.
Fig. 3
Fig. 3
Distribution of CSA practices across various Agro-ecological zones (AEZs) of Ethiopia.
Fig. 4
Fig. 4
The proportion (%) of various CSA practices included in the meta-analysis.
Fig. 5
Fig. 5
The proportion (%) of publications reporting the three pillars of CSA practices. P: productivity, A: adaptation, M: mitigation, PA: productivity and adaptation, AM: adaptation and mitigation, PM: productivity and mitigation, and PAM: productivity, adaptation and mitigation all together.
Fig. 6
Fig. 6
Proportion of CSA practices studied across various Agro-ecological zones (AEZs) of Ethiopia.
Fig. 7
Fig. 7
Effect size of productivity (e.g. yield) for various climate-smart agricultural (CSA) practices studied in Ethiopia (1986–2022). Error bars represent 95 % confidence interval.
Fig. 8
Fig. 8
Effect size of income (productivity pillar) for five climate-smart agricultural (CSA) practices studied in Ethiopia (1986–2022). Error bars represent 95 % confidence interval.
Fig. 9
Fig. 9
Forest plot of the effect size of runoff (adaptation pillar) for various climate-smart agricultural (CSA) practices studied in Ethiopia (1986–2022). Error bars represent a 95 % confidence interval.
Fig. 10
Fig. 10
Forest plot of the effect size of soil loss (adaptation pillar) for various CSA practices studied in Ethiopia (1986–2022). Error bars represent 95 % confidence interval.
Fig. 11
Fig. 11
Forest plot of the effect size of irrigation water used and water productivity (adaptation pillar) for various CSA practices studied in Ethiopia (1986–2022). Error bars represent a 95 % confidence interval.
Fig. 12
Fig. 12
Forest plot of the effect size of soil organic matter (adaptation pillar) for various CSA practices studied in Ethiopia (1986–2022). Error bars represent a 95 % confidence interval.
Fig. 13
Fig. 13
Forest plot of the effect size of carbon stock (adaptation pillar) for various climate-smart agricultural (CSA) practices studied in Ethiopia (1986–2022). Error bars represent a 95 % confidence interval.
Fig. 14
Fig. 14
The effect size of various indicators across the three pillars of climate-smart agriculture (CSA) practices, including productivity (yield, income), adaptation (runoff, soil loss, irrigation water, water productivity), and mitigation (soil organic matter).
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References

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