澜沧江-湄公河流域生态系统服务价值对土地利用变化的响应

doi:10.16258/j.cnki.1674-5906.2025.05.003

生态环境学报 ›› 2025, Vol. 34 ›› Issue (5): 688-698.DOI: 10.16258/j.cnki.1674-5906.2025.05.003

澜沧江-湄公河流域生态系统服务价值对土地利用变化的响应

赵志轩¹^,²^,³^,^*(), 魏芳菲¹^,², 吴皓天¹^,², 王怡宁¹^,², 王澎喆¹^,²

1.水文水资源与水利工程科学国家重点实验室，江苏南京 210029
2.南京水利科学研究院，江苏南京 210029
3.长江保护与绿色发展研究院，江苏南京 210098

收稿日期:2024-08-14 出版日期:2025-05-18 发布日期:2025-05-16
通讯作者: *
作者简介:赵志轩（1983年生），男，正高级工程师，博士，主要从事水文水资源和生态水文领域研究工作。E-mail: zxzhao@nhri.cn
基金资助:
国家重点研发计划项目(2022YFC3201702)

The Response of Ecological Service Value to Land Use Change in Lancang-Mekong River Basin

ZHAO Zhixuan¹^,²^,³^,^*(), WEI Fangfei¹^,², WU Haotian¹^,², WANG Yining¹^,², WANG Pengzhe¹^,²

1. State Key Laboratory of Hydrology and Water Resources and Hydraulic Engineering Science, Nanjing 210029, P. R. China
2. Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute (NHRI), Nanjing 210029, P. R. China
3. Yangtze Institute for Conservation and Development, Nanjing 210098, P. R. China

Received:2024-08-14 Online:2025-05-18 Published:2025-05-16

摘要/Abstract

摘要：

科学评估流域生态系统服务价值（ESV），揭示其随土地利用变化的时空响应规律，识别影响ESV空间异质性的关键驱动因子，对于制定合理开发和保护策略，促进区域可持续发展具有重要意义。以澜沧江-湄公河流域为研究对象，采用CV-Markov模型模拟流域未来不同发展情景下土地利用变化，采用修正的当量因子法评估ESV，基于空间统计分析方法分析揭示土地利用变化影响下的ESV时空演变规律，并利用地理探测器模型识别ESV空间分异的关键驱动因子。结果表明，1）1995－2020年间，流域ESV总量、空间分布发生相应变化，总体呈先减小、后增大的趋势；2040年3种发展情景下流域ESV存在显著的差异性和空间异质性，其中农业发展情景ESV值最低、生态保护情境ESV最高。2）未来不同情景下流域ESV均存在显著空间正相关性和空间集聚效应，但不同情景下的ESV冷点/热点区域规模及其空间格局存在显著差异。3）流域ESV的空间异质性受到自然-人类活动的双重影响，其中人类足迹是ESV空间格局的主导驱动因子，年均气温、高程、坡度3个因子也是ESV空间异质性的关键驱动因子，且任意双因子组合对ESV空间异质性的解释力均强于单一因子，其中解释力最高的双因子为人类足迹与年均气温的组合。

关键词: 土地利用变化, 生态服务价值, CV-Markov模型, 地理探测器, 澜沧江-湄公河

Abstract:

The Lancang-Mekong River (LMR) is the longest river in Southeast Asia. A broad variety of ecosystems is present in the river basin, including alpine grasslands, meadows, lakes, tropical rainforests, and mangroves, which provide local people with food, wood, and other important services. In recent years, in the context of jointly promoting high-quality development of the Belt and Road initiated by China, practical cooperation between China and the Association of Southeast Asian Nations (Asean) has been expanding. One of the important achievements was the implementation of the Lancang-Mekong Cooperation Action Plan (2023‒2027), which emphasized the cooperation of ecological protection and forestry. Under these circumstances, scientifically evaluating the ecosystem service value (ESV) of the river basin, revealing its temporal and spatial response patterns to land use changes, and identifying the key driving factors affecting the spatial heterogeneity of ESV have become of great significance for formulating reasonable development and protection strategies and promoting sustainable development in the region. This study focuses on the LMR Basin. First, a CV-Markov model was constructed to simulate future land-use changes in the basin under different development scenarios, and a modified equivalent factor method was introduced to evaluate the ESV of the basin. Second, the special-temporal patterns of ESV under different land-use scenarios were analyzed and revealed based on spatial analysis and statistical technologies. Finally, a geo-detector model was adopted to identify the key driving factors that determine the spatial heterogeneity of ESV. The results showed that: 1) From 1995 to 2020, the total ESV and its spatial distribution pattern differed as land use changed in the LMR basin, and the value of total ESV showed non-monotonic variation characteristics, which decreased from 1995 to 2015 and increased in 2020. There are significant differences and spatial heterogeneity in the three development scenarios in 2040, with the lowest ESV in the agricultural development scenario (ADS) and the highest ESV in the ecological protection scenario (EPS). 2) There are significant spatial positive correlations and spatial agglomeration effects of ESV in different scenarios in 2040, and the scale and spatial pattern of ESV cold/hotspots in each scenario are considerably different. 3) The spatial heterogeneity of ESV of the LMR is driven by both natural factors and human activities, in which the human footprint is the dominant driving factor of the ESV spatial pattern among the seven factors, and three factors including average annual temperature, elevation, and slope, are also the key driving factors of ESV spatial heterogeneity in the LMR. In addition, any combination of the two factors has stronger explanatory power for ESV spatial heterogeneity than a single factor. The two factors with the highest explanatory power were the interaction between the human footprint and average annual temperature.

Key words: land use change, ecological service value, CV-Markov model, Geo-detector, Lancang-Mekong River

中图分类号:

X196
Q149

赵志轩, 魏芳菲, 吴皓天, 王怡宁, 王澎喆. 澜沧江-湄公河流域生态系统服务价值对土地利用变化的响应[J]. 生态环境学报, 2025, 34(5): 688-698.

ZHAO Zhixuan, WEI Fangfei, WU Haotian, WANG Yining, WANG Pengzhe. The Response of Ecological Service Value to Land Use Change in Lancang-Mekong River Basin[J]. Ecology and Environmental Sciences, 2025, 34(5): 688-698.

图/表 13

参考文献 30

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分类	供给服务			调节服务				支持服务			文化服务
分类	食物生产	原料生产	水资源供给	气体调节	气候调节	净化环境	水文调节	土壤保持	维持养分循环	生物多样性	美学景观
农田	872	336	−341	693	369	104	588	834	123	134	61
林地	234	534	275	1754	5255	1567	3883	2140	162	1949	856
草地	218	317	177	1124	2968	978	2175	1368	104	1241	548
湿地	482	472	2447	1795	3401	3401	22893	2183	170	7436	4469
裸地	0	0	0	19	0	94	28	19	0	19	9
水体	726	209	7606	706	2099	5044	20453	844	64	2315	1719
建设用地	0	0	−64	489	909	488	790	196	45	296	287

分类	供给服务			调节服务				支持服务			文化服务
分类	食物生产	原料生产	水资源供给	气体调节	气候调节	净化环境	水文调节	土壤保持	维持养分循环	生物多样性	美学景观
农田	872	336	−341	693	369	104	588	834	123	134	61
林地	234	534	275	1754	5255	1567	3883	2140	162	1949	856
草地	218	317	177	1124	2968	978	2175	1368	104	1241	548
湿地	482	472	2447	1795	3401	3401	22893	2183	170	7436	4469
裸地	0	0	0	19	0	94	28	19	0	19	9
水体	726	209	7606	706	2099	5044	20453	844	64	2315	1719
建设用地	0	0	−64	489	909	488	790	196	45	296	287

土地利用类型	1995年	2000年	2005年	2010年	2015年	2020年	NDS	ADS	EPS
农田	25.85	26.48	26.95	27.18	27.27	27.02	27.67	35.11	21.30
林地	34.91	34.25	33.27	32.28	31.73	32.21	28.21	24.30	31.14
草地	18.20	18.22	18.63	19.26	19.56	19.33	22.10	18.70	25.11
湿地	0.68	0.71	0.80	0.87	0.87	0.85	1.17	1.11	1.27
裸地	0.03	0.03	0.04	0.03	0.03	0.05	0.03	0.03	0.03
水体	1.16	1.12	1.10	1.15	1.18	1.19	1.25	1.19	1.56
建设用地	0.05	0.07	0.11	0.13	0.24	0.25	0.45	0.43	0.47

土地利用类型	1995年	2000年	2005年	2010年	2015年	2020年	NDS	ADS	EPS
农田	25.85	26.48	26.95	27.18	27.27	27.02	27.67	35.11	21.30
林地	34.91	34.25	33.27	32.28	31.73	32.21	28.21	24.30	31.14
草地	18.20	18.22	18.63	19.26	19.56	19.33	22.10	18.70	25.11
湿地	0.68	0.71	0.80	0.87	0.87	0.85	1.17	1.11	1.27
裸地	0.03	0.03	0.04	0.03	0.03	0.05	0.03	0.03	0.03
水体	1.16	1.12	1.10	1.15	1.18	1.19	1.25	1.19	1.56
建设用地	0.05	0.07	0.11	0.13	0.24	0.25	0.45	0.43	0.47

土地利用类型	NDS		ADS		EPS
土地利用类型	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%
农田	27.67	34.21	35.11	43.42	21.30	26.34
林地	28.21	34.88	24.30	30.05	31.14	38.51
草地	22.10	27.33	18.70	23.12	25.11	31.04
湿地	1.17	1.44	1.11	1.38	1.27	1.56
裸地	0.03	0.03	0.03	0.03	0.03	0.03
水体	1.25	1.54	1.19	1.47	1.56	1.93
建设用地	0.45	0.55	0.43	0.53	0.47	0.58

澜沧江-湄公河流域生态系统服务价值对土地利用变化的响应

The Response of Ecological Service Value to Land Use Change in Lancang-Mekong River Basin

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参考文献 30

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情景	高程	坡度	年均降水	年均气温	与水体距离	人口密度	人类足迹
NDS	0.202^{** 1)}	0.163^**	0.048^**	0.214^**	0.047^**	0.085^**	0.363^**
ADS	0.211^**	0.161^**	0.044^**	0.228^**	0.055^**	0.072^**	0.346^**
EPS	0.190^**	0.144^**	0.043^**	0.202^**	0.033^**	0.078^**	0.288^**

情景	影响因子	高程	坡度	年均降水	年均气温	与水体距离	人口密度
NDS	人类足迹	0.449	0.399	0.418	0.452	0.379	0.371
ADS		0.427	0.380	0.390	0.439	0.360	0.353
EPS		0.394	0.338	0.352	0.398	0.308	0.301

情景	I	Z(I)	E(I)	Z(G)	G	E(G)
NDS	0.49	92.8	1×10⁻³	73.3	1×10⁻⁶	1×10⁻⁶
ADS	0.5	97.4	1×10⁻³	79.2	1×10⁻⁶	1×10⁻⁶
EPS	0.49	94.7	1×10⁻³	74.5	1×10⁻⁶	1×10⁻⁶

情景	TYPE	CA/km²	NP	MPS/km²	MSI	ED	MPI
NDS	热点区域	91368	77	1186.60	1.40	0.14	19.47
NDS	冷点区域	181359	29	6253.76	1.49	0.15	172.46
ADS	热点区域	47547	51	932.29	1.29	0.08	4.93
ADS	冷点区域	217566	28	7770.21	1.53	0.16	190.82
EPS	热点区域	145233	71	2045.54	1.48	0.19	70.68
EPS	冷点区域	149850	40	3746.25	1.43	0.15	235.58

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