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生态系统服务相互作用的时空空间异质性及其驱动因素在黄河流域的不同空间尺度

Qi Liu¹, Jiajun Qiao¹, Mengjuan Li¹

¹College of Geography and Environmental Science, Henan University, Kaifeng 475004, China.

The Science of the total environment

|November 12, 2023

概括

生态系统服务的协同作用主导着黄河流域的权衡. 管理层必须考虑生态系统服务 (ES) 的直接,间接和规模依赖的驱动因素,以实现有效的保护.

科学领域:

生态生态学生态生态学
环境科学环境科学
空间分析空间分析

背景情况:

有效的生态系统服务 (ES) 管理需要理解复杂的相互作用和多层次驱动因素.
黄河流域的生态健康对于区域可持续性至关重要.
之前的研究往往忽略了空间尺度在ES动态中的相互作用.

研究的目的:

分析黄河流域四个规模的ES相互作用的空间和时间变化.
确定影响生态系统服务的关键驱动因素和间接途径.
为多层次的ES管理策略提供科学基础.

主要方法:

利用极端梯度提升 (XGBoost) 来识别生态系统服务的关键驱动因素.
采用部分最小平方-结构方程建模 (PLS-SEM) 来阐明间接路径.
在多个尺度上分析了2000年至2020年的ES相互作用的空间和时间数据.

主要成果:

生态系统服务对之间的协同效应超过了权衡,ES捆绑的转换和规模不变的空间模式.
息地质量,碳封存和景观美学是由景观配置和生物物理条件驱动的.
粮食生产主要受到城市化的影响,而土壤保护和水产取决于气候.
驱动因素的间接影响是多样化的:当生物物理条件或城市化介导时是负面的,当景观配置介导时是混合的.

结论:

生态系统服务协同效应在黄河流域普遍存在,跨度尺度的空间模式不断演变.
不同的驱动因素影响着不同的生态系统服务,强调了有针对性的管理的必要性.
间接途径和规模依赖的效应对于理解ES动态和实施有效的管理策略至关重要.

关键词:

生态系统服务捆绑.间接影响的间接影响.机器学习模型机器学习模型规模效应是一个规模效应.权衡/协同作用

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