Zhan Yang, Wang Xu, Mao Yi-Xin, Yun Li-Li, Peng Xi
Liaoning Academy of Forestry Science, Shenyang 110032, China.
Liaoning Baishilazi Forest Ecosystem Research Station, Kuandian 118201, Liaoning, China.
Ying Yong Sheng Tai Xue Bao. 2025 Aug;36(8):2442-2454. doi: 10.13287/j.1001-9332.202508.026.
Integrated management of ecosystem services through ecosystem service bundles (ESBs) is increasingly recognized as one of the most promising approaches for optimizing ecosystem services. Understanding the spatiotemporal dynamics of ESBs is critical for developing precise and adaptive regional ecosystem management strategies. However, most existing studies focus on the static identification of ESBs, with limited attention to the long-term stability and underlying drivers. With Hunan Province as an example and based on the spatiotemporal evolution of six key ecosystem services from 1995 to 2020, we introduced the "dominant service cluster change frequency" indicator to quantify the spatiotemporal stability of ESBs, and established an explanatory framework for the stability dri-ving mechanism. The results showed that food production, carbon sequestration, and soil retention significantly increased, habitat quality remained relatively stable, while flood regulation and water yield declined. The spatial patterns of multiple service types also underwent significant change during 1995-2020. ESBs showed high spatial heterogeneity and temporal dynamics, with 58.2% of the area showing high transition frequency and only 41.8% remaining relatively stable. High stability regions were mainly located in plains and mountainous forest areas with high levels of agricultural intensification. Geographic detector analysis revealed that land-use factors (e.g., cropland and forest ratios) and climate variables (e.g., precipitation and temperature) were the primary drivers of ESB stability. The interaction effects between land use and climate were stronger than single-factor effects. Based on the stability classifications, we further proposed adaptive and region-specific ecosystem management strategies to provide a new path for improving the ability to sustain service supply and the timeliness of policy implementation. This study would expand the perspective of dynamic regulation in the study of ESBs, providing theoretical support and practical basis for the refined management of ecosystem multifunctionality in changing environments.
通过生态系统服务束（ESB）对生态系统服务进行综合管理，日益被视为优化生态系统服务最具前景的方法之一。了解ESB的时空动态对于制定精确且适应性强的区域生态系统管理策略至关重要。然而，大多数现有研究侧重于ESB的静态识别，对长期稳定性和潜在驱动因素的关注有限。以湖南省为例，基于1995年至2020年六种关键生态系统服务的时空演变，我们引入“主导服务簇变化频率”指标来量化ESB的时空稳定性，并建立了稳定性驱动机制的解释框架。结果表明，粮食生产、碳固存和土壤保持显著增加，栖息地质量保持相对稳定，而洪水调节和产水量下降。1995 - 2020年期间，多种服务类型的空间格局也发生了显著变化。ESB表现出高度的空间异质性和时间动态性，58.2%的区域显示出高转变频率，仅有41.8%保持相对稳定。高稳定性区域主要位于农业集约化程度高的平原和山区森林地区。地理探测器分析表明，土地利用因素（如耕地和森林比例）和气候变量（如降水和温度）是ESB稳定性的主要驱动因素。土地利用与气候之间的交互作用比单因素作用更强。基于稳定性分类，我们进一步提出了适应性和区域特定的生态系统管理策略，为提高服务供给维持能力和政策实施及时性提供了新途径。本研究将拓展ESB研究中动态调控的视角，为变化环境中生态系统多功能性的精细化管理提供理论支持和实践依据。
