How to Learn Lessons from Field Experience in Forest Landscape Restoration: A Tentative Framework

A Correction to this article was published on 13 July 2020

This article has been updated

Abstract

Lesson learning from field implementation generates new knowledge that is particularly important in the context of recently developed approaches, processes and complex systems with limited history and much uncertainty. One such approach is forest landscape restoration (FLR). Although grounded in a number of disciplines (e.g., conservation biology, landscape ecology, restoration ecology), FLR has remained very fluid and molded to suit different stakeholders, from local to global. Today, many countries or organizations pledge to implement FLR. Global commitments, especially following the Bonn Challenge on FLR (established in 2011), aim to upscale FLR to achieve social, biodiversity, and carbon benefits. However, the FLR approach is relatively new (<20 years), complex due to its multifaceted nature, and long-term field experience and results are still limited. That makes lesson learning from past, ongoing and related approaches particularly urgent. We propose here a first attempt at a framework for lesson learning in FLR that can serve to ground both practice and policy in field experiences to date.

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Change history

  • 13 July 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

We wish to thank PJ Stephenson and Gretchen Walters for their feedback and suggestions on an earlier draft of this article as well as two anonymous reviewers whose feedback helped us improve the article. We also acknowledge Bertrand Dubois’ support in refining the graphics.

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Correspondence to Stephanie Mansourian.

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Mansourian, S., Vallauri, D. How to Learn Lessons from Field Experience in Forest Landscape Restoration: A Tentative Framework. Environmental Management 66, 941–951 (2020). https://doi.org/10.1007/s00267-020-01295-4

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Keywords

  • Lessons learned
  • Learning
  • Knowledge
  • Conservation
  • FLR
  • Restoration