Mansourian.org, Mont d'eau, 1276, Gingins, Switzerland.
University of Geneva, 24 rue du Général-Dufour, 1211, Geneva, Switzerland.
Environ Manage. 2020 Dec;66(6):941-951. doi: 10.1007/s00267-020-01295-4. Epub 2020 May 1.
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.
从实地实施中吸取经验教训会产生新知识，在最近开发的方法、流程和具有有限历史和高度不确定性的复杂系统背景下，这些知识尤为重要。森林景观恢复（FLR）就是这样一种方法。尽管它根植于多个学科（例如保护生物学、景观生态学、恢复生态学），但 FLR 仍然非常灵活，可以根据不同利益相关者的需求进行调整，从地方到全球。如今，许多国家或组织承诺实施 FLR。全球承诺，特别是在 2011 年建立的森林景观恢复《波恩挑战》之后，旨在扩大 FLR 的规模，以实现社会、生物多样性和碳效益。然而，FLR 方法相对较新（<20 年），由于其多方面的性质，它很复杂，并且长期的实地经验和结果仍然有限。这使得从过去、正在进行的和相关方法中吸取经验教训变得尤为紧迫。我们在这里提出了一个在 FLR 中进行经验教训学习的框架的首次尝试，该框架可以为迄今为止的实地经验提供实践和政策基础。
