1.甘肃农业大学 草业学院, 甘肃 兰州 730070
2.草业生态系统教育部重点实验室,甘肃 兰州 730070
3.国家林业草原高寒草地鼠害防控工程技术研究中心, 甘肃 兰州 730070
何生申(2001—),女(汉族),甘肃省临夏市人,硕士研究生,研究方向为生态系统服务评估。Email:15120488650@163.com。
郝媛媛(1987—), 女(汉族),甘肃省白银市人,博士,副教授,主要从事草地生态遥感和生态恢复方面的研究。Email:haoyy@gsau.edu.cn。
收稿:2024-12-04,
修回:2025-03-17,
纸质出版:2025-08-20
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何生申, 郝媛媛, 孟哲, 等.中国首批国家公园产水能力时空格局及驱动力差异[J].水土保持通报,2025,45(4):392-401.
He Shengshen, Hao Yuanyuan, Meng Zhe, et al. Spatiotemporal patterns of water-yield capacity and driving-force differences of first group of China’s national parks [J]. Bulletin of Soil and Water Conservation,2025,45(4):392-401.
何生申, 郝媛媛, 孟哲, 等.中国首批国家公园产水能力时空格局及驱动力差异[J].水土保持通报,2025,45(4):392-401. DOI: 10.13961/j.cnki.stbctb.2025.04.003. CSTR: 32312.14.stbctb. 2025.04.003..
He Shengshen, Hao Yuanyuan, Meng Zhe, et al. Spatiotemporal patterns of water-yield capacity and driving-force differences of first group of China’s national parks [J]. Bulletin of Soil and Water Conservation,2025,45(4):392-401. DOI: 10.13961/j.cnki.stbctb.2025.04.003. CSTR: 32312.14.stbctb. 2025.04.003..
目的
2
分析中国首批5个国家公园产水能力,探索各公园关键产水驱动力,为优化国家公园生态保护及水资源管理提供科学依据。
方法
2
基于InVEST模型评估2000—2023年各国家公园的产水能力,结合变异系数(
C
v
)分析产水能力的稳定性,采用偏最小二乘路径模型(PLS-PM)定量探讨各公园关键驱动力的作用机制。
结果
2
①2000—2023年,首批国家公园的产水深度普遍呈波动上升趋势(除海南热带雨林国家公园)。其中,武夷山国家公园的产水深度(1 609.13 mm)和增幅(
k
=9.34)均最大;三江源国家公园的产水深度(133.89 mm)较小,且增幅(
k
=0.95)最为平缓。 ②各公园产水能力的稳定性大小顺序为:三江源国家公园
>
海南热带雨林国家公园
>
大熊猫国家公园
>
武夷山国家公园
>
东北虎豹国家公园。 ③不同公园的关键产水驱动力差异明显,表现出不同的影响模式。降水量是影响产水能力的主要正向因素,且三江源(0.987 9)和海南热带雨林国家公园(0.832 8)显著高于其他公园;潜在蒸散发对产水深度的影响普遍为负相关,在大熊猫(-0.458 1)和武夷山国家公园(-0.348 5)中表现尤为显著;植被覆盖度和地形因子的影响程度则在不同国家公园中存在差异。
结论
2
2000—2023年,中国首批5个国家公园产水能力时空格局变化明显且稳定性较高,其关键产水驱动力各有差异且空间异质性明显。
Objective
2
The water-production capacities of the first group of first five national parks in China were analyzed, and the key driving forces of each park were explored, in order to provide a scientific basis for optimizing the ecological protection and water-resource management of national parks.
Methods
2
Based on the InVEST model, the water-yielding capacities of each national park from 2000 to 2023 were assessed. The stability of the water-yielding capacities was analyzed in combination with the coefficient of variation(
C
v
). The partial least squares path model (PLS-PM) was used to explore the functioning mechanism of the key driving force at each park quantitatively.
Results
2
① From 2000 to 2023, the depths of the water-yields in the national parks generally demonstrated a fluctuating upward trend (excepte Hainan Tropical Rainforest National Park). Wuyishan National Park had the largest water-yield depth (1 609.13 mm) and the largest increase (
k
=9.34), while Sanjiangyuan National Park had the smallest water-yield depth (133.89 mm) and the most moderate increase (
k
=0.95). ② The stability of the water yield of each park was as follows: Sanjiangyuan National Park
>
Hainan Tropical Rainforest National Park
>
Giant Panda National Park
>
Wuyishan National Park
>
Northeastern Tiger and Leopard National Park. ③ The key driving forces of the water yields of the parks differed significantly, demonstrating varying patterns of influence. Precipitation was the primary positive factor affecting water yield, and was significantly higher in Sanjiangyuan National Park (0.987 9) and Hainan Tropical Rainforest National Park (0.832 8) than in the other parks. Potential evapotranspiration was generally negatively correlated with the depth of wa
ter yield and was seen to be particularly significant at Giant Panda National Park (-0.458 1) and Wuyishan National Park (-0.348 5). The impacts of vegetation cover and topography differed across the national parks.
Conclusion
2
From 2000 to 2023, the spatial and temporal patterns of water-yield capacities in the five first group national parks in China changed significantly and were relatively stable. The key driving forces of those patterns were shown to be different and spatially heterogeneous.
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