IDEAS home Printed from https://ideas.repec.org/a/eee/forpol/v125y2021ics1389934121000095.html
   My bibliography  Save this article

Stochastic simulation of restoration outcomes for a dry afromontane forest landscape in northern Ethiopia

Author

Listed:
  • Tamba, Yvonne
  • Wafula, Joshua
  • Whitney, Cory
  • Luedeling, Eike
  • Yigzaw, Negusse
  • Negussie, Aklilu
  • Muchiri, Caroline
  • Gebru, Yemane
  • Shepherd, Keith
  • Aynekulu, Ermias

Abstract

Forest and Landscape Restoration (FLR) is carried out with the objective of regaining ecological functions and enhancing human well-being through intervention in degrading ecosystems. However, uncertainties and risks related to FLR make it difficult to predict long-term outcomes and inform investment plans. We applied a Stochastic Impact Evaluation framework (SIE) to simulate returns on investment in the case of FLR interventions in a degraded dry Afromontane forest while accounting for uncertainties. We ran 10,000 iterations of a Monte Carlo simulation that projected FLR outcomes over a period of 25 years. Our simulations show that investments in assisted natural regeneration, enrichment planting, exclosure establishment and soil-water conservation structures all have a greater than 77% chance of positive returns. Sensitivity analysis of these outcomes indicated that the greatest threat to positive cashflows is the time required to achieve the targeted ecological outcomes. Value of Information (VOI) analysis indicated that the biggest priority for further measurement in this case is the maturity age of exclosures at which maximum biomass accumulation is achieved. The SIE framework was effective in providing forecasts of the distribution of outcomes and highlighting critical uncertainties where further measurements can help support decision-making. This approach can be useful for informing the management and planning of similar FLR interventions.

Suggested Citation

  • Tamba, Yvonne & Wafula, Joshua & Whitney, Cory & Luedeling, Eike & Yigzaw, Negusse & Negussie, Aklilu & Muchiri, Caroline & Gebru, Yemane & Shepherd, Keith & Aynekulu, Ermias, 2021. "Stochastic simulation of restoration outcomes for a dry afromontane forest landscape in northern Ethiopia," Forest Policy and Economics, Elsevier, vol. 125(C).
  • Handle: RePEc:eee:forpol:v:125:y:2021:i:c:s1389934121000095
    DOI: 10.1016/j.forpol.2021.102403
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1389934121000095
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.forpol.2021.102403?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nkonya, Ephraim M. & Mirzabaev, Alisher & von Braun, Joachim, 2015. "Synopsis, Economics of land degradation and improvement: A global assessment for sustainable development:," Issue briefs 90, International Food Policy Research Institute (IFPRI).
    2. Edward Wilson, 2015. "A Practical Guide to Value of Information Analysis," PharmacoEconomics, Springer, vol. 33(2), pages 105-121, February.
    3. Stålhammar, Sanna & Pedersen, Eja, 2017. "Recreational cultural ecosystem services: How do people describe the value?," Ecosystem Services, Elsevier, vol. 26(PA), pages 1-9.
    4. James C. Felli & Gordon B. Hazen, 1998. "Sensitivity Analysis and the Expected Value of Perfect Information," Medical Decision Making, , vol. 18(1), pages 95-109, January.
    5. Grieshop, Andrew P. & Marshall, Julian D. & Kandlikar, Milind, 2011. "Health and climate benefits of cookstove replacement options," Energy Policy, Elsevier, vol. 39(12), pages 7530-7542.
    6. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    7. Renato Crouzeilles & Michael Curran & Mariana S. Ferreira & David B. Lindenmayer & Carlos E. V. Grelle & José M. Rey Benayas, 2016. "A global meta-analysis on the ecological drivers of forest restoration success," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
    8. Munialo Sussy & Hall Ola & Francisca Archila Bustos Maria & Boke-Olén Niklas & Onyango M. Cecilia & Oluoch-Kosura Willis & Marstorp Håkan & Göran Djurfeldt, 2019. "Micro-Spatial Analysis of Maize Yield Gap Variability and Production Factors on Smallholder Farms," Agriculture, MDPI, vol. 9(10), pages 1-23, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Newbold, Stephen C. & Johnston, Robert J., 2020. "Valuing non-market valuation studies using meta-analysis: A demonstration using estimates of willingness-to-pay for water quality improvements," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    2. James Love-Koh & Susan Griffin & Edward Kataika & Paul Revill & Sibusiso Sibandze & Simon Walker & Jessica Ochalek & Mark Sculpher & Matthias Arnold, 2019. "Economic analysis for health benefits package design," Working Papers 165cherp, Centre for Health Economics, University of York.
    3. Mayuran Sivapalan & Jerome Bowen, 2020. "Decision frameworks for restoration & adaptation investment–Applying lessons from asset-intensive industries to the Great Barrier Reef," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.
    4. Nasuh C. Buyukkaramikli & Peter Wigfield & Men Thi Hoang, 2021. "A MEA is a MEA is a MEA? Sequential decision making and the impact of different managed entry agreements at the manufacturer and payer level, using a case study for an oncology drug in England," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(1), pages 51-73, February.
    5. Alexis Laurent & Bo P. Weidema & Jane Bare & Xun Liao & Danielle Maia de Souza & Massimo Pizzol & Serenella Sala & Hanna Schreiber & Nils Thonemann & Francesca Verones, 2020. "Methodological review and detailed guidance for the life cycle interpretation phase," Journal of Industrial Ecology, Yale University, vol. 24(5), pages 986-1003, October.
    6. Ian Wadsworth & Lisa V. Hampson & Thomas Jaki & Graeme J. Sills & Anthony G. Marson & Richard Appleton, 2020. "A quantitative framework to inform extrapolation decisions in children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 515-534, February.
    7. Lee, Alice J. & Ames, Daniel R., 2017. "“I can’t pay more” versus “It’s not worth more”: Divergent effects of constraint and disparagement rationales in negotiations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 141(C), pages 16-28.
    8. Hussain, Hadia & Murtaza, Murtaza & Ajmal, Areeb & Ahmed, Afreen & Khan, Muhammad Ovais Khalid, 2020. "A study on the effects of social media advertisement on consumer’s attitude and customer response," MPRA Paper 104675, University Library of Munich, Germany.
    9. A. G. Fatullayev & Nizami A. Gasilov & Şahin Emrah Amrahov, 2019. "Numerical solution of linear inhomogeneous fuzzy delay differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 315-326, September.
    10. Arun Advani & William Elming & Jonathan Shaw, 2023. "The Dynamic Effects of Tax Audits," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 545-561, May.
    11. MacCarty, Nordica A. & Bryden, Kenneth Mark, 2016. "An integrated systems model for energy services in rural developing communities," Energy, Elsevier, vol. 113(C), pages 536-557.
    12. Philippe Aghion & Ufuk Akcigit & Matthieu Lequien & Stefanie Stantcheva, 2017. "Tax Simplicity and Heterogeneous Learning," NBER Working Papers 24049, National Bureau of Economic Research, Inc.
    13. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    14. Chuangen Gao & Shuyang Gu & Jiguo Yu & Hai Du & Weili Wu, 2022. "Adaptive seeding for profit maximization in social networks," Journal of Global Optimization, Springer, vol. 82(2), pages 413-432, February.
    15. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    16. Annette Alstadsæter & Wojciech Kopczuk & Kjetil Telle, 2019. "Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1291-1328, December.
    17. Sebastian Kaumanns, 2019. "“Some fuzzy math”: relational information on debt value adjustments by managers and the financial press," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 755-794, December.
    18. Samuel J Gershman, 2015. "A Unifying Probabilistic View of Associative Learning," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-20, November.
    19. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    20. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:forpol:v:125:y:2021:i:c:s1389934121000095. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/forpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.