乌梁素海流域生态脆弱性时空变化及其成因分析

doi:10.12082/dqxxkx.2023.230212

地球信息科学学报 ›› 2023, Vol. 25 ›› Issue (10): 2039-2054.doi: 10.12082/dqxxkx.2023.230212

• 地理空间分析综合应用 • 上一篇下一篇

乌梁素海流域生态脆弱性时空变化及其成因分析

李云帆¹^,²(), 李彩霞¹^,², 贾翔¹^,², 吴晶¹^,², 张晓丽¹^,²^,^*(), 梅晓丽³, 朱若柠³, 王冬³

1.北京林业大学森林培育与保护教育部重点实验室，北京 100083
2.北京林业大学精准林业北京市重点实验室，北京 100083
3.中建一局集团第三建筑有限公司，北京 100161

收稿日期:2023-04-21 修回日期:2023-07-13 出版日期:2023-10-25 发布日期:2023-09-22
通讯作者: * 张晓丽（1967—），北京人，博士，教授，博士生导师，研究方向为资源环境遥感。E-mail: zhangxl@bjfu.edu.cn
作者简介:李云帆（1999—），山西长治人，硕士生，研究方向为资源环境遥感。E-mail: lilichin@bjfu.edu.cn
基金资助:
中建股份科技研发计划项目(CSCEC-2020-Z-5);中欧科技合作“龙计划”五期项目(59257);中欧对地观测合作森林监测技术与示范应用(2021YFE0117700)

Spatiotemporal Changes and Causes of Ecological Vulnerability in Ulansuhai Basin

LI Yunfan¹^,²(), LI Caixia¹^,², JIA Xiang¹^,², WU Jing¹^,², ZHANG Xiaoli¹^,²^,^*(), MEI Xiaoli³, ZHU Ruoning³, WANG Dong³

1. The Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China
2. Precision Forestry Key Laboratory of Beijing, Beijing 100083, China
3. The Third Construction Co., Ltd. of China Construction First Bureau Group, Beijing 100161, China

Received:2023-04-21 Revised:2023-07-13 Online:2023-10-25 Published:2023-09-22
Contact: * ZHANG Xiaoli, E-mail: zhangxl@bjfu.edu.cn
Supported by:
CSCEC Science and Technology Research and Development Program(CSCEC-2020-Z-5);China-Europe Science and Technology Cooperation "Dragon Plan" Phase V Project(59257);Cooperation project between China and Europe in Earth Observation on forest monitoring technology and demonstration applications(2021YFE0117700)

摘要/Abstract

摘要：

面对“碎片化”生态治理的挑战，全面了解流域生态系统的脆弱性及其演变规律成为生态环境综合治理的关键。乌梁素海流域作为全国示范意义的生态保护修复工程试点，经历了传统“治理湖泊”到系统“治理流域”的转变。本研究选择乌梁素海流域作为研究对象，构建了“敏感-恢复-压力”生态脆弱性评价指标体系，并以Google Earth Engine (GEE)云平台为基础，采用Mann-Kendall突变检验、Sen+Mann-Kendall趋势分析和变换轨迹等方法，对2000—2020年乌梁素海流域生态脆弱性时空演变进行分析，最后通过地理探测器进一步探讨了乌梁素海流域生态脆弱性的成因，并揭示了其主要驱动因子。研究结果表明：乌梁素海流域的生态脆弱性表现为“中间低、两边高”的格局。其中，西部乌兰布和沙漠以及东部乌拉山区生态脆弱性较高，而中部河套灌区则相对较低。2000—2020年，流域的生态脆弱性分级指数从2.44上升至2.59，揭示了生态脆弱性的轻微恶化趋势。2000、2009、2013、2017和2020年为突变节点，约59.82%的区域在评估期间生态脆弱性等级保持稳定，变化轨迹法显示2013年为显著下降的节点，2017年后下降趋势减缓。此外，地表干度是乌梁素海流域生态脆弱性的核心驱动因子，多个因素相互作用时对生态脆弱性的解释力超过单一因素。土地覆盖类型解释力最为显著，其次是气象类型、经济类型。本研究对长时序流域生态脆弱性的时空变化及成因进行了分析，为同类型的生态脆弱区域评估和生态保护与修复工程治理提供科学依据。

关键词: 生态脆弱性, 乌梁素海流域, Google Earth Engine, 时间序列分析, 地理探测器, 时空变化

Abstract:

To meet the challenges posed by the "fragmented" nature of ecological governance, it is crucial to have a holistic understanding of the vulnerability of basin ecosystems and the underlying patterns of their evolution for comprehensive ecological management. The Ulansuhai Basin, serving as a pilot site for a representative ecological conservation and restoration project, has experienced a shift from traditional "lake management" to a more systemic "basin management". This study selected the Ulansuhai Basin as the study area and established a "Sensitivity-Recovery-Pressure" index system for ecological vulnerability assessment. Using the Google Earth Engine cloud platform, methods including Mann-Kendall test, Sen+Mann-Kendall trend analysis, and transformation trajectory were applied to analyse the spatiotemporal evolution of ecological vulnerability in the Ulansuhai Basin from 2000 to 2020. Moreover, geographical detectors were utilized to further investigate the causes of ecological vulnerability in the Ulansuhai Basin, and to identify the primary driving factors. The results indicated that the ecological vulnerability of the Ulansuhai Basin exhibited a “low in the middle, high on both sides” pattern, e.g., the western region of the Ulan Buh Desert and the eastern Ula Mountain region had relatively higher ecological vulnerability, while the central Hetao irrigation area had lower ecological vulnerability. From 2000 to 2020, the basin’s ecological vulnerability grading index increased from 2.44 to 2.59, indicating a slight decline in ecological vulnerability. Abrupt changes of vulnerability were observed in 2000, 2009, 2013, 2017, and 2020, with approximately 59.82% of the basin area maintaining stable ecological vulnerability grades throughout the assessment period. The transformation trajectory method showed that the decline of vulnerability peaked in 2013 and then began to slow after 2017. Additionally, surface aridity was identified as a key driving factor of ecological vulnerability in the Ulansuhai Basin, and the interaction of multiple factors showed a stronger explanatory power for ecological vulnerability than a single factor. Generally, land cover type exhibited the most significant explanatory power, followed by meteorological and economic types. This study analyzed the long-term spatiotemporal changes and causes of ecological vulnerability in basin ecosystems, providing a scientific basis for the assessment and governance of ecological conservation and restoration projects in ecologically vulnerable regions.

Key words: ecological vulnerability, Ulansuhai Basin, Google Earth Engine, time series analysis, Geodetector, spatiotemporal change

李云帆, 李彩霞, 贾翔, 吴晶, 张晓丽, 梅晓丽, 朱若柠, 王冬. 乌梁素海流域生态脆弱性时空变化及其成因分析[J]. 地球信息科学学报, 2023, 25(10): 2039-2054.DOI:10.12082/dqxxkx.2023.230212

LI Yunfan, LI Caixia, JIA Xiang, WU Jing, ZHANG Xiaoli, MEI Xiaoli, ZHU Ruoning, WANG Dong. Spatiotemporal Changes and Causes of Ecological Vulnerability in Ulansuhai Basin[J]. Journal of Geo-information Science, 2023, 25(10): 2039-2054.DOI:10.12082/dqxxkx.2023.230212

图/表 15

图1

图2

表1

表2

表3

表4

交互探测器结果类型

判断依据	交互作用
$q X 1 ⋂ X 2 < M i n q X 1, q X 2$	非线性减弱
$M i n q X 1, q X 2 < q X 1 ⋂ X 2 < M a x q X 1, q X 2$	单线性减弱
$q X 1 ⋂ X 2 > M a x q X 1, q X 2$	双线性增强
$q X 1 ⋂ X 2 = q X 1 + q X 2$	相互独立
$q X 1 ⋂ X 2 > q X 1 + q X 2$	非线性增强

表4

图3

图4

图5

图6

图7

表5

乌梁素海流域2000—2020年生态脆弱性指数变化统计

Sen斜率	$Z$	变化状况	研究区占比/%
>0.000 5	≥ 1.96	显著上升	4.15
>0.000 5	< 1.96	不显著上升	2.77
-0.000 5~0.000 5	< 1.96	稳定不变	9.55
<-0.000 5	< 1.96	不显著下降	48.59
<-0.000 5	≥ 1.96	显著下降	34.93

表5

图8

表6

图9

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要素层	指标层	指标性质	空间分辨率	原始数据来源
生态敏感性 (Sensitivity)	高程	正向	90 m	SRTM^[32]
	地形起伏度	正向	90 m	SRTM
	景观干扰度	正向	1 km	Zendo^[33]
	年均降雨量	正向	1 km	中国科学院环境数据中心
	大气温度	正向	1 km	Zendo^[34]
	地表温度	正向	1 km	MODIS
	地表湿度	负向	30 m	Landsat
	地表干度	正向	30 m	Landsat
生态压力度 (Pressure)	人口密度	正向	1 km	GPW v4^[35]
生态恢复力 (Recovery)	植被覆盖度	负向	30 m	Landsat
生态恢复力 (Recovery)	经济密度	负向	1 km	中国科学院环境数据中心^[36]

传感器名称	B	G	R	NIR	SWIR₁	SWIR₂
TM	0.031 5	0.202 1	0.301 2	0.159 4	-0.680 6	-0.610 9
ETM+	0.262 6	0.214 1	0.092 6	0.065 6	-0.762 9	-0.538 8
OLI	0.151 1	0.197 3	0.328 3	0.340 7	-0.711 7	-0.455 9

脆弱性等级	生态脆弱性指数范围	脆弱程度	生态特征解释
Ⅰ	0≤ EVI<0.2	潜在脆弱	生态功能完整，对各类干扰敏感性弱，承受生态压力小，自我恢复能力强，无生态异常出现
Ⅱ	0.2≤ EVI<0.4	微度脆弱	生态功能较为完整，对各类干扰敏感性较弱，承受生态压力较小，自我恢复能力强，存在潜在的生态异常
Ⅲ	0.4≤ EVI<0.6	轻度脆弱	生态功能尚可维持，对各类干扰敏感性中等，承受生态压力接近阈值，自我恢复能力较弱，存在少量的生态异常
Ⅳ	0.6≤ EVI<0.8	中度脆弱	生态功能部分退化，对各类干扰敏感性较强，承受生态压力较大，受损后恢复难度较大，生态异常较多
Ⅴ	0.8≤ EVI ≤1	重度脆弱	生态功能退化严重，对各类干扰敏感性强，承受生态压力大，受损恢复难度大，生态异常集中连片出现

生态脆弱性因子	q统计值	p值
地形起伏度	0.135 6	2.93E-10
高程	0.515 2	6.12E-10
地表湿度	0.417 5	3.37E-10
大气温度	0.472 6	1.20E-10
年均降雨量	0.560 0	6.66E-10
人口密度	0.000 0	1
地表干度	0.561 3	5.19E-10
地表温度	0.214 9	9.49E-10
经济密度	0.200 9	3.98E-10
景观干扰度	0.237 9	5.29E-10
植被覆盖度	0.063 7	5.94E-10

乌梁素海流域生态脆弱性时空变化及其成因分析

Spatiotemporal Changes and Causes of Ecological Vulnerability in Ulansuhai Basin

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