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Large-scale land restoration improved drought resilience in Ethiopia’s degraded watersheds

Abstract

Anthropogenic land degradation, exacerbated by more frequent and intense weather shocks due to climate change, threatens the livelihoods of rural populations in developing economies. Development agencies have invested heavily in sustainable land management projects to overturn land productivity losses, but efforts to assess project impacts have been hampered by operational issues and by the high costs of gathering on-ground data. This study combines satellite observations (moderate-resolution imaging spectroradiometer-based Enhanced Vegetation Index and Orbiting Carbon Observatory-2-derived solar-induced chlorophyll fluorescence-based gross primary production) with quasi-experimental impact evaluation methods to examine the impacts of the Sustainable Land Management Project in Ethiopia, one of the world’s most ambitious restoration efforts to date. We find that over a five-year effective implementation period, gross primary production in treated locations grew by 13.5% on average in areas affected by severe droughts (those with a standard precipitation index lower than –2) and by 3.1% in areas that did not experience droughts, suggesting important drought-buffering effects. We provide empirical evidence about the effectiveness of sustainable land management projects in restoring land productivity and resilience to weather shocks, and show that remote-sensing technologies can be incorporated into impact evaluation models to assess ecosystem restoration programmes.

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Fig. 1: SLMP watershed map by implementation phase.
Fig. 2: Nonparametric regression over time: seasonal average EVI (1 km) and GOSIF-GPP (5 km).
Fig. 3: Event study: average 1 km EVI and GOSIF-GPP.
Fig. 4: SLMP1 impacts on land productivity.

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Data availability

All data necessary for replication will be available at Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/AXH2OU) to reproduce the results presented in this paper upon publication.

Code availability

All computer codes necessary for replication will be available at Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/AXH2OU) to reproduce the results presented in this paper upon publication.

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Acknowledgements

For feedback and insights on earlier drafts of this work, we thank M. A. Gizaw, D. Glandon, A. Mabiso, D. Monchuk, B. A. Shiferaw and other seminar participants at the International Fund for Agricultural Development (IFAD) and the 2021 Asian Evaluation Week. Any remaining errors are our own. The contributions of S.C.-V., Y.L., Y.S. and S.C. were supported by PROFOR, a multidonor partnership housed at the World Bank, under grant no. TF0B1259 to S.C., and funding from the CGIAR Research Program on Policies, Institutions, and Markets (PIM) to Y.L. J.W. and Y.S. also acknowledge support from NASA CMS (80NSSC21K1058). The contents are solely the authors’ responsibility and do not necessarily reflect the views of the World Bank, World Bank’s member countries, PIM, IFPRI or the CGIAR.

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Y.L. and S.C. conceived the idea for the study. Y.L. and S.C.-V. developed the methodology. S.C., Y.S. and J.W. provided key datasets for the analysis. S.C.-V. compiled, processed and analysed the data. S.C.-V. and Y.L. wrote the manuscript and the Supplementary Information. All authors edited the manuscript and advised on analysis and revisions.

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Correspondence to Yanyan Liu.

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Nature Sustainability thanks Wuletawu Abera, Athur Mabiso and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Note, Figs. 1–8, Tables 1–5 and refs. 1–6.

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Constenla-Villoslada, S., Liu, Y., Wen, J. et al. Large-scale land restoration improved drought resilience in Ethiopia’s degraded watersheds. Nat Sustain 5, 488–497 (2022). https://doi.org/10.1038/s41893-022-00861-4

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