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评估中亚地区的植被恢复潜力

Zhentao Lv¹, Shengyu Li¹, Xinwen Xu²

¹State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

Journal of environmental management

|January 10, 2025

概括

一个新的植被恢复潜力绘图 (VRPM) 模型为生态恢复提供了准确的评估. 这种机器学习方法可以改善干旱地区可持续生态系统发展的规划.

科学领域:

生态恢复生态恢复
环境科学环境科学
机器学习应用程序机器学习应用程序

背景情况:

生态恢复项目需要准确评估植被恢复潜力 (VRP).
现有的VRP模型由于依赖经验或未能考虑非线性环境关系而存在低效率,可复制性差或不准确的结果.
忽视环境承载能力可能导致无效的恢复或生态损害.

研究的目的:

开发和验证一种新的植被恢复潜力映射 (VRPM) 模型.
提高VRP评估的准确性和效率,用于生态恢复规划.
使用开发的模型评估中亚的VRP.

主要方法:

开发一个VRPM模型,整合息地相似性和机器学习算法的双变量离散方法.
该模型在VRP评估中应用于中亚.
在分辨率和精度方面验证模型的性能.

主要成果:

VRPM模型有效地生成高分辨率,高精度的植被恢复潜力地图.
中亚地区的平均VRP低,约为36%,大多数地区接近恢复能力.
较高的未实现植被恢复潜力 (VRPU) 集中在人类定居点附近;负的VRPU发生在沙漠绿洲边界和人工沙漠结构附近.

结论:

开发的VRPM模型为规划和实施有效的生态恢复项目提供了可靠的基础.
这些发现强调需要考虑局部化的环境承载能力,以实现干旱地区的可持续生态系统管理.
该模型有助于促进生态系统的健康和可持续发展,特别是在干旱和半干旱地区.

关键词:

中亚的中亚地区.土地退化土地退化机器学习是机器学习.类似的息地类似的息地植被恢复的潜力植物恢复的潜力

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