横断山区产水服务空间异质性及归因分析

doi:10.11821/dlxb202003012

地理学报 ›› 2020, Vol. 75 ›› Issue (3): 607-619.doi: 10.11821/dlxb202003012

• 土地利用与生态系统服务 • 上一篇下一篇

横断山区产水服务空间异质性及归因分析

戴尔阜^1,², 王亚慧^1,²()

^1. 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室拉萨高原生态系统研究站,北京 100101
^2. 中国科学院大学,北京 100049

收稿日期:2018-12-20 修回日期:2019-12-16 出版日期:2020-03-25 发布日期:2020-05-25
作者简介:戴尔阜(1972-), 男, 甘肃平凉人, 博士, 研究员, 主要从事土地利用与气候变化对生态系统的影响研究。E-mail: daief@igsnrr.ac.cn
基金资助:
国家重点基础研究发展计划(2015CB452702);国家自然科学基金项目(41571098);国家自然科学基金项目(41530749);国家重点研发计划(2017YFC1502903);中国科学院科技战略咨询研究院重大咨询项目(Y02015003)

Spatial heterogeneity and driving mechanisms of water yield service in the Hengduan Mountain region

DAI Erfu^1,², WANG Yahui^1,²()

^1. Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
^2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2018-12-20 Revised:2019-12-16 Published:2020-03-25 Online:2020-05-25
Supported by:
National Basic Research Program of China(2015CB452702);National Natural Science Foundation of China(41571098);National Natural Science Foundation of China(41530749);National Key R&D Program of China(2017YFC1502903);Major Consulting Project of Strategic Development Institute, Chinese Academy of Sciences(Y02015003)

摘要/Abstract

摘要：

包括产水服务在内的生态系统服务已被纳入区域土地利用规划以及可持续发展决策中,识别其空间分异特征及影响因素是进行决策的基础,而空间分异的定量归因研究仍需进一步加强。以空间异质性明显的中国横断山区为研究区,借助InVEST模型模拟产水服务空间分布,选择气候、地形、土壤、植被、土地利用等因子,采用地理探测器开展产水服务空间异质性归因分析。结果表明,① 气候类因子是产水服务空间异质性的主要控制因子,其中以降水量和蒸散量为主。② 在不同地貌及气候分区中,各因子对产水的空间分异的解释能力存在显著差异：平缓地区,蒸散量解释能力远高于降水量,随着起伏度的增大,降水量解释能力逐步增强,最终成为主要因子;在高原气候区,以蒸散量解释能力最强,而在中亚热带气候区,降水量为主要的控制因子。③ 值得注意的是,平缓地区土地利用类型因子的解释能力较为突出,在山区发展中应注意土地利用的合理规划,以减轻土地利用变化对产水服务空间变化的影响。④ 风险探测识别的产水服务重要区主要为初育土及人为土分布区、灌木林区以及坡度在≤ 5°和25°~35°区域,而其对应的高程值则在不同区域之间存在差异,因此,在横断山区产水服务的维持与保护工作中应充分考虑不同分区的具体情况。

关键词: 产水服务, InVEST模型, 地理探测器, 归因分析, 横断山区

Abstract:

Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in Southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the InVEST software was used to simulate the spatial distribution of water yield. Also, quantitative attribution analysis was conducted for various geomorphologic and climatic zones in the Hengduan Mountain region by using the geographical detector method. Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First, water yield spatial heterogeneity are influenced most by climate-related factors, among which precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphologic and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most important factor. Evapotranspiration is the most important factor in a plateau climatic zone, while in the mid-subtropical zone, precipitation is the main controlling factor. Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slopes <5° and 25°-35° should be recognized as water yield important zones, while the corresponding elevation values are different in different geomorphologic and climatic zones. Therefore, the spatial heterogeneity and influencing factors in different zones should be fully considered in planning the maintenance and protection of water supply services in the Hengduan Mountain region.

Key words: water yield service, InVEST software, geographical detector, attribution analysis, the Hengduan Mountain region

戴尔阜, 王亚慧. 横断山区产水服务空间异质性及归因分析[J]. 地理学报, 2020, 75(3): 607-619.

DAI Erfu, WANG Yahui. Spatial heterogeneity and driving mechanisms of water yield service in the Hengduan Mountain region[J]. Acta Geographica Sinica, 2020, 75(3): 607-619.

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类型	指标	数据类型	类型	指标	数据类型
气候	年均温	连续	土地利用	土地利用类型	离散
	年总降水量	连续		SHDI	连续
	年总辐射	连续		CONTAG	连续
	年实际蒸散量	连续		MESH	连续
地形地貌	高程	连续		PLAND(耕地)	连续
地形地貌	坡度	连续		PLAND(林地)	连续
土壤	土壤类型	离散		PLAND(草地)	连续
植被	NDVI	连续

分区	主要交互作用
整个山区	降水∩蒸散降水∩土地利用类型降水∩土壤类型
平原	降水∩蒸散降水∩土地利用类型蒸散∩土壤类型/蒸散∩高程
台地	降水∩蒸散降水∩土地利用类型蒸散∩MESH指数
丘陵	降水∩蒸散蒸散∩高程降水∩土地利用类型
小起伏山地	降水∩蒸散降水∩土地利用类型降水∩土壤类型
中起伏山地	降水∩蒸散降水∩土地利用类型降水∩土壤类型
大起伏山地	降水∩蒸散降水∩土地利用类型降水∩土壤类型
极大起伏山地	降水∩蒸散降水∩土地利用类型降水∩PLAND(草地)
昌都区	降水∩蒸散蒸散∩其他因子
波密—川西区	降水∩蒸散降水∩土地利用类型蒸散∩其他因子
四川区	降水∩蒸散蒸散∩土地利用类型
金沙江—楚雄、玉溪区	降水∩蒸散蒸散∩土地利用类型
滇北区	降水∩蒸散降水∩土地利用类型降水∩土壤类型

分区	高程(m)	坡度(°)	土壤类型	NDVI	土地利用类型
整个山区	1591~2484	25~35	初育土	0.78~0.94	灌木林
平原	2069~2484			0.72~0.78	灌木林
台地	2069~2484		初育土	0.78~0.94	灌木林
丘陵	3377~3797		初育土	0.78~0.94	疏林地、灌木林
小起伏山地	2069~2484	25~35	初育土	0.78~0.94	灌木林
中起伏山地	2069~2484	25~35	初育土	0.78~0.94	灌木林
大起伏山地	2069~2484		初育土	0.78~0.94	灌木林
极大起伏山地	2924~3377	25~35		0.78~0.94	灌木林
昌都区	3797~6808	0~5	初育土	0.78~0.94	灌木林
波密—川西区	347~1591	0~5	初育土、人为土	0.78~0.94	灌木林
四川	347~1591	0~5	初育土、人为土		灌木林、其他林地
金沙江—楚雄、玉溪区	1591~2069	0~5	初育土	0.72~0.78	灌木林
滇北区	3797~4548	25~35	初育土	0.78~0.94	低覆盖度草地

横断山区产水服务空间异质性及归因分析

Spatial heterogeneity and driving mechanisms of water yield service in the Hengduan Mountain region

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