| 基于贝叶斯网络的生态系统服务权衡协同关系强度及其空间格局优化：以汾河流域为例 |
| 摘要点击 392 全文点击 58 投稿时间：2023-05-23 修订日期：2023-07-20 |
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| 中文关键词 生态系统服务（ESs） 权衡协同指数（TSI） 贝叶斯网络 区域优化 汾河流域 |
| 英文关键词 ecosystem services （ESs） trade-off synergy index （TSI） Bayesian network regional optimization Fenhe River Basin |
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| 中文摘要 |
| 了解生态系统服务（ESs）间权衡协同关系强度对于汾河流域地区的生态环境管理和恢复至关重要,然而,迄今为止,对该地区ESs间关系强度变化的驱动变量和空间格局优化仍然缺乏足够的研究.在定量评估汾河流域2000年和2020年6种生态系统服务的基础上,引入了生态系统服务权衡协同指数（TSI）定量衡量两两ES间权衡协同关系的强度,同时构建了贝叶斯生态系统服务权衡协同关系强度网络,识别了权衡协同强度的驱动变量,通过敏感度分析确定了关键变量对权衡协同关系强度的影响程度,并在空间格局上刻画了ESs权衡协同关系强度的优化区.结果表明：①2000年和2020年汾河流域6种ESs时空差异较为显著,在时间尺度上,产水量、净初级生产力、粮食供给、土壤保持和碳储量均呈现波动上升的趋势,在空间尺度上,6种生态系统服务在20年里空间分布变化较小.②碳储量与生境质量、土壤保持以及净初级生产力的TSI在空间上呈现出四周高中部低的格局；与产水量有关的5对服务中TSI最大的地区均分布在流域西部和南部；粮食供给与其他服务之间的TSI自北向南呈现“高-中-高”的分布特征.③敏感性分析发现,产水量与土壤保持和生境质量的强度均受到降水、根系限制性深度和降雨侵蚀等的显著影响,且根据关键变量不同状态的条件概率,发现汾河流域中部的文水县、清徐县和祁县等是权衡协同强度的高值区,可作为生态修复重点区域.研究结果对于认识多种生态系统服务间权衡与协同强度的复杂关系及其驱动变量,对后续提出生态环境可持续治理和政策制定具有重要的理论和实践意义. |
| 英文摘要 |
| Understanding the strength of trade-off and synergistic relationships among ecosystem services (ESs) is crucial for ecological management and restoration in the Fenhe River Basin. However, there is still a lack of sufficient research on the driving variables and spatial pattern optimization of the strength of ESs relationships in this area. Based on the quantitative assessment of six ESs in the Fenhe River Basin in 2000 and 2020, the ecosystem services trade-off synergy index (TSI) was introduced to quantitatively measure the strength of trade-off and synergistic relationships between each pair of ESs. A Bayesian network was constructed to identify the driving variables of trade-off and synergistic relationships, and sensitivity analysis was conducted to determine the degree of influence of key variables on the strength of these relationships. The optimization area of the strength of ESs trade-off and synergistic relationships was characterized in spatial patterns. The results showed that:① There were significant spatiotemporal differences in the six ESs in the Fenhe River Basin in 2000 and 2020. In terms of time scale, water yield, net primary productivity, crop productivity, soil conservation, and carbon storage all showed a trend of fluctuating increase. In terms of spatial scale, the spatial distribution changes in the six ESs were relatively small over the 20 years. ② The TSI of carbon storage was high in the surrounding area and low in the middle, showing a four-high and four-low pattern. The areas with the highest TSI between grain supply and other services were distributed from north to south. ③ Sensitivity analysis found that the strength of water yield, soil conservation, and habitat quality were significantly affected by precipitation, plant root depth restriction, and rainfall erosion. According to the conditional probability of different states of key variables, Wenshui County, Qingxu County, and Qi County in the central part of the Fenhe River Basin were identified as high-value areas for trade-off and synergistic relationships, which could be used as key areas for ecological restoration. These findings have important theoretical and practical significance for understanding the complex relationship between multiple ESs trade-off and synergistic relationships and their driving variables and for proposing sustainable ecological environment management policies. |
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