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Uniform global deforestation patterns — An empirical analysis

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  • Köthke, Margret
  • Leischner, Bettina
  • Elsasser, Peter

Abstract

The forest transition (FT) hypothesis implies that changes in a region's forest cover follow a determinable pattern of decline and later re-expansion over time, which is supposed to be similar across regions and countries. Such a uniform pattern – if empirically proven and quantified – might help in establishing REDD+ baselines (i.e., references against which reductions in the emissions from deforestation and forest degradation of developing countries could be measured, and subsequently be rewarded). REDD+ baselines are required to be based on a globally standardised method and also to consider country-specific circumstances. These requirements might be fulfilled by applying the concept of forest transition in a baseline setting.

Suggested Citation

  • Köthke, Margret & Leischner, Bettina & Elsasser, Peter, 2013. "Uniform global deforestation patterns — An empirical analysis," Forest Policy and Economics, Elsevier, vol. 28(C), pages 23-37.
  • Handle: RePEc:eee:forpol:v:28:y:2013:i:c:p:23-37
    DOI: 10.1016/j.forpol.2013.01.001
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    Cited by:

    1. de Jong, Wil & Liu, Jinlong & Youn, Yeo-Chang, 2017. "Land and forests in the Anthropocene: Trends and outlooks in Asia," Forest Policy and Economics, Elsevier, vol. 79(C), pages 17-25.
    2. Barbier, Edward B. & Tesfaw, Anteneh, 2015. "Explaining forest transitions: The role of governance," Ecological Economics, Elsevier, vol. 119(C), pages 252-261.
    3. Khuc, Quy Van & Tran, Bao Quang & Meyfroidt, Patrick & Paschke, Mark W., 2018. "Drivers of deforestation and forest degradation in Vietnam: An exploratory analysis at the national level," Forest Policy and Economics, Elsevier, vol. 90(C), pages 128-141.
    4. Wolfersberger, Julien & Delacote, Philippe & Garcia, Serge, 2015. "An empirical analysis of forest transition and land-use change in developing countries," Ecological Economics, Elsevier, vol. 119(C), pages 241-251.
    5. Salahodjaev, Raufhon, 2016. "Intelligence and deforestation: International data," Forest Policy and Economics, Elsevier, vol. 63(C), pages 20-27.
    6. Nguyen, Trung Thanh & Nghiem, Nhung, 2016. "Optimal forest rotation for carbon sequestration and biodiversity conservation by farm income levels," Forest Policy and Economics, Elsevier, vol. 73(C), pages 185-194.
    7. Rubén Ferrer Velasco & Margret Köthke & Melvin Lippe & Sven Günter, 2020. "Scale and context dependency of deforestation drivers: Insights from spatial econometrics in the tropics," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-32, January.
    8. Indarto, Jarot & Mutaqin, Dadang J., 2016. "An overview of theoretical and empirical studies on deforestation," MPRA Paper 70178, University Library of Munich, Germany.
    9. Tetsuya Michinaka, 2018. "Approximating Forest Resource Dynamics in Peninsular Malaysia Using Parametric and Nonparametric Models, and Its Implications for Establishing Forest Reference (Emission) Levels under REDD+," Land, MDPI, Open Access Journal, vol. 7(2), pages 1-1, June.
    10. Beygi Heidarlou, Hadi & Banj Shafiei, Abbas & Erfanian, Mahdi & Tayyebi, Amin & Alijanpour, Ahmad, 2020. "Armed conflict and land-use changes: Insights from Iraq-Iran war in Zagros forests," Forest Policy and Economics, Elsevier, vol. 118(C).
    11. Robin Matthews & Meine Noordwijk & Eric Lambin & Patrick Meyfroidt & Joyeeta Gupta & Louis Verchot & Kristell Hergoualc’h & Edzo Veldkamp, 2014. "Implementing REDD+ (Reducing Emissions from Deforestation and Degradation): evidence on governance, evaluation and impacts from the REDD-ALERT project," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(6), pages 907-925, August.

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