Climate-smart forestry: an AI-enabled sustainable forest management solution for climate change adaptation and mitigation

适应(眼睛) 气候变化 可持续森林管理 森林经营 适应气候变化 林业 环境资源管理 业务 农林复合经营 环境科学 地理 生态学 心理学 生物 神经科学
作者
G. Geoff Wang,Deliang Lu,Tian Gao,Jinxin Zhang,Yirong Sun,Dexiong Teng,Fengyuan Yu,Jiaojun Zhu
出处
期刊:Journal of Forestry Research [Springer Nature]
卷期号:36 (1) 被引量:1
标识
DOI:10.1007/s11676-024-01802-x
摘要

Abstract Climate change is the most severe ecological challenge faced by the world today. Forests, the dominant component of terrestrial ecosystems, play a critical role in mitigating climate change due to their powerful carbon sequestration capabilities. Meanwhile, climate change has also become a major factor affecting the sustainable management of forest ecosystems. Climate-Smart Forestry (CSF) is an emerging concept in sustainable forest management. By utilizing advanced technologies, such as information technology and artificial intelligence, CSF aims to develop innovative and proactive forest management methods and decision-making systems to address the challenges of climate change. CSF aims to enhance forest ecosystem resilience (i.e., maintain a condition where, even when the state of the ecosystem changes, the ecosystem functions do not deteriorate) through climate change adaptation, improve the mitigation capabilities of forest ecosystems to climate change, maintain high, stable, and sustainable forest productivity and ecosystem services, and ultimately achieve harmonious development between humans and nature. This concept paper: (1) discusses the emergence and development of CSF, which integrates Ecological Forestry, Carbon Forestry, and Smart Forestry, and proposes the concept of CSF; (2) analyzes the goals of CSF in improving forest ecosystem stability, enhancing forest ecosystem carbon sequestration capacity, and advocating the application and development of new technologies in CSF, including artificial intelligence, robotics, Light Detection and Ranging, and forest digital twin; (3) presents the latest practices of CSF based on prior research on forest structure and function using new generation information technologies at Qingyuan Forest, China. From these practices and reflections, we suggested the development direction of CSF, including the key research topics and technological advancement.

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