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 神经科学 生物
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
图雄争霸完成签到 ,获得积分10
刚刚
姿势完成签到,获得积分10
刚刚
1秒前
共享精神应助沧海青州采纳,获得10
2秒前
2秒前
2秒前
3秒前
定格完成签到,获得积分10
3秒前
ymu发布了新的文献求助30
3秒前
笨笨三问发布了新的文献求助10
3秒前
4秒前
大模型应助有风的地方采纳,获得10
5秒前
6秒前
6秒前
SciGPT应助迅速的丑采纳,获得10
8秒前
marchon发布了新的文献求助30
8秒前
9秒前
9秒前
9秒前
曹曹完成签到,获得积分20
10秒前
欠收拾小孩完成签到,获得积分10
10秒前
定格发布了新的文献求助10
10秒前
昵称发布了新的文献求助10
11秒前
江月年发布了新的文献求助10
12秒前
LL666完成签到 ,获得积分10
13秒前
梁静宇完成签到 ,获得积分10
14秒前
14秒前
布坎南发布了新的文献求助10
15秒前
dreamflower完成签到,获得积分10
15秒前
16秒前
努力完成签到,获得积分10
17秒前
轻松不愁应助bobo采纳,获得10
17秒前
hhh发布了新的文献求助10
18秒前
老毛桃完成签到,获得积分10
18秒前
18秒前
SciGPT应助小全采纳,获得30
18秒前
彪壮的短靴关注了科研通微信公众号
19秒前
19秒前
佳宝(不可以喝但能吃完成签到,获得积分10
19秒前
Robin发布了新的文献求助10
21秒前
高分求助中
Востребованный временем 2500
The Three Stars Each: The Astrolabes and Related Texts 1500
Classics in Total Synthesis IV: New Targets, Strategies, Methods 1000
Les Mantodea de Guyane 800
Mantids of the euro-mediterranean area 700
The Oxford Handbook of Educational Psychology 600
有EBL数据库的大佬进 Matrix Mathematics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 内科学 物理 纳米技术 计算机科学 遗传学 化学工程 基因 复合材料 免疫学 物理化学 细胞生物学 催化作用 病理
热门帖子
关注 科研通微信公众号,转发送积分 3412654
求助须知:如何正确求助?哪些是违规求助? 3015273
关于积分的说明 8869601
捐赠科研通 2703053
什么是DOI,文献DOI怎么找? 1482000
科研通“疑难数据库(出版商)”最低求助积分说明 685102
邀请新用户注册赠送积分活动 679771