Chao Long

Chao Long


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 March 2022 in Climate
Verified
Journal Article
Open access
PDF file
KFKalifi Ferretti-Gallon
Kalifi Ferretti-Gallon
JLJames Langston
James Langston
Guangyu WangGuangyu Wang
Guangyu Wang
KHKEBIAO HUANG
KEBIAO HUANG
CLChao Long
Chao Long
HZHongbo Zhai
Hongbo Zhai
Forest restoration is increasingly becoming a priority at international and national levels. Identifying forest degradation, however, is challenging because its drivers are underlying and site-specific. Existing frameworks and principles for identifying forest degradation are useful at larger scales, however, a framework that includes iterative input from local knowledge-holders would be useful at smaller scales. Here, we present a new mechanism; a framework for developing criteria and indicators that enables an approach for the identification of forest degradation and opportunities for restoration in landscapes that is free from failures that are often inherent to project cycles. The Degradation and Restoration Assessment Mechanism (DReAM) uses an iterative process that is based on local expertise and established regional knowledge to inform what is forest degradation and how to monitor restoration. We tested the mechanism’s utility at several sites in the Lancang-Mekong Region (Cambodia, Laos, Myanmar, Thailand, and Vietnam). The application of this mechanism rendered a suite of appropriate criteria and indicators for use in identifying degraded forests which can help inform detailed guidelines to develop rehabilitation approaches. The mechanism is designed to be utilized by any individual or group that is interested in degradation identification and/or rehabilitation assessment.