Identification of Ecosystem Service Bundles and Functional Zoning in the Dongjiang River Basin Based on Self-Organizing Map Neural Network

doi:10.16258/j.cnki.1674-5906.2026.02.012

Ecology and Environmental Sciences ›› 2026, Vol. 35 ›› Issue (2): 289-297.DOI: 10.16258/j.cnki.1674-5906.2026.02.012

• Environmental Science • Previous Articles Next Articles

Identification of Ecosystem Service Bundles and Functional Zoning in the Dongjiang River Basin Based on Self-Organizing Map Neural Network

HAN Nianlong(), ZHANG Zhenlin, GAO Haojia, PENG Anqi, JI Jiahui

School of Geography and Tourism, Huizhou University, Huizhou 516007, P. R. China

Received:2025-06-17 Revised:2026-01-22 Accepted:2026-01-26 Online:2026-02-18 Published:2026-02-09

基于自组织映射神经网络的东江流域生态服务簇识别与功能分区

韩念龙(), 张镇林, 高浩嘉, 彭安琪, 纪家慧

惠州学院地理与旅游学院，广东惠州 516007

作者简介:韩念龙（1983年生），男，副教授，主要从事土地资源管理研究。E-mail: 94432715@qq.com
基金资助:
广东省哲学社会科学规划项目(GD25YDXZYJ05);海南省自然科学基金项目(421RC1034);惠州学院科研启动基金项目(2022JB080);广东省大学生创新创业训练计划项目(S202410577081)

Abstract

Abstract:

Understanding the relationships among ecosystem services and implementing functional zoning are crucial foundations for socio-ecological sustainable development. This study focuses on the Dongjiang River Basin, assessing the spatiotemporal evolution characteristics and trade-off/synergy relationships of five key ecosystem services—water yield (WY), habitat quality (HQ), net primary productivity (NPP), soil conservation (SC), and food production (FP)—from 2000 to 2020. Clustering and functional zoning of ecosystem service bundles were conducted using the Self-Organizing Map (SOM) algorithm. The results indicate: 1) All five ecosystem services in the basin showed declining trends during 2000-2020, with reductions of WY (24%), FP (24%), SC (14%), NPP (2%), and HQ (1.7%). 2) Trade-offs dominated inter-service relationships, particularly a highly significant trade-off between WY and HQ (r= −0.66), while a significant synergy existed between HQ and SC (r=0.48), with trade-offs intensifying over time. 3) SOM clustering divided the basin into four functional zones: ecological core area, main crop production area, ecological conservation area, and urban functional area. From 2000 to 2020, the ecological core area and urban functional area increased by 3.9% and 62.6%, respectively, whereas the main crop production area and ecological conservation area decreased by 12.5% and 20.2%. The study reveals the spatial differentiation patterns and dynamic change mechanisms of ecosystem services in the Dongjiang River Basin, providing a scientific basis for differentiated ecological management and sustainable development of the basin.

Key words: ecosystem services, trade-offs and synergies, self-organizing map (SOM), functional zoning, Dongjiang River Basin

摘要：

流域生态系统服务关系解析与功能分区是实现流域生态可持续发展的重要基础。以东江流域为对象，评估2000－2020年产水量（WY）、生境质量（HQ）、净初级生产力（NPP）、土壤保持（SC）和粮食生产（FP）等5项关键生态系统服务的时空演变特征及其权衡协同关系，并基于自组织映射神经网络（SOM）算法进行生态系统服务簇聚类与功能分区。结果表明：1）2000－2020年，东江流域5项生态系统服务均呈下降趋势，WY、FP、SC、NPP和HQ降幅依次为24%、24%、14%、2%和1.7%；2）生态系统服务之间以权衡关系为主，WY与HQ呈极显著权衡（r= −0.66），而HQ与SC则呈显著协同（r=0.48），且权衡效应随时间增强；3）通过SOM聚类将流域划分为生态核心区、作物主产区、生态保育区和城镇功能区等4类，2000－2020年生态核心区与城镇功能区面积分别增长3.9%和62.6%，作物主产区与生态保育区面积分别减少12.5%和20.2%。该研究揭示了东江流域生态系统服务的空间分异规律与动态变化机制，可为流域差异化生态管理提供科学依据。

关键词: 生态系统服务, 权衡协同, 自组织映射, 功能分区, 东江流域

CLC Number:

HAN Nianlong, ZHANG Zhenlin, GAO Haojia, PENG Anqi, JI Jiahui. Identification of Ecosystem Service Bundles and Functional Zoning in the Dongjiang River Basin Based on Self-Organizing Map Neural Network[J]. Ecology and Environmental Sciences, 2026, 35(2): 289-297.

韩念龙, 张镇林, 高浩嘉, 彭安琪, 纪家慧. 基于自组织映射神经网络的东江流域生态服务簇识别与功能分区[J]. 生态环境学报, 2026, 35(2): 289-297.

Figures/Tables 8

References 27

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数据类型	内容	数据来源
土地利用栅格数	CLCD土地利用数据（2000/2020）	武汉大学（https://zenodo.org/records/8176941）
气象栅格数据	降水、潜在蒸散量、平均气温、日照时数等（2000－2020）	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/home）
土壤栅格数据	土层深度/植物可利用含水率	世界土壤数据库（HWSD）、第二次全国土壤调查 1꞉100万土壤数据（http://vdb3.soil.csdb.cn/）
遥感数据	东江流域NDVI（2000/2020）	地球资源数据云（http://gis5g.com/home）
统计数据	东江流域粮食总产值（包括稻谷、小麦、玉米和薯类）	广东省统计年鉴/江西省统计年鉴（https://www.stats.gov.cn/）
高程数据	东江流域DEM	中国科学院资源环境科学与数据中心（https://www.resdc.cn/）
流域地理数据	基于DEM的东江流域边界提取	中国科学院资源环境科学与数据中心（https://www.resdc.cn/）
流域地理数据	水系数据	Open Street Map

数据类型	内容	数据来源
土地利用栅格数	CLCD土地利用数据（2000/2020）	武汉大学（https://zenodo.org/records/8176941）
气象栅格数据	降水、潜在蒸散量、平均气温、日照时数等（2000－2020）	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/home）
土壤栅格数据	土层深度/植物可利用含水率	世界土壤数据库（HWSD）、第二次全国土壤调查 1꞉100万土壤数据（http://vdb3.soil.csdb.cn/）
遥感数据	东江流域NDVI（2000/2020）	地球资源数据云（http://gis5g.com/home）
统计数据	东江流域粮食总产值（包括稻谷、小麦、玉米和薯类）	广东省统计年鉴/江西省统计年鉴（https://www.stats.gov.cn/）
高程数据	东江流域DEM	中国科学院资源环境科学与数据中心（https://www.resdc.cn/）
流域地理数据	基于DEM的东江流域边界提取	中国科学院资源环境科学与数据中心（https://www.resdc.cn/）
流域地理数据	水系数据	Open Street Map

权衡协同关系	相关性程度	取值范围[−1, 1]	显著性水平
协同关系	正相关	0<r≤1	*//*
无关系	不相关	r=0	*//*
权衡关系	负相关	−1≤r<0	*//*

权衡协同关系	相关性程度	取值范围[−1, 1]	显著性水平
协同关系	正相关	0<r≤1	*//*
无关系	不相关	r=0	*//*
权衡关系	负相关	−1≤r<0	*//*

年份	水源涵养（WY）	生境质量（HQ）	粮食生产（FP）	净初级生产力（NPP）	土壤保持（SC）	生态系统服务
2000	1	−0.60^***	0.48^***	−0.21^*	−0.20^*	WY
		1	−0.69^***	0.53^***	0.51^***	HQ
			1	−0.42^***	−0.47^***	FP
				1	0.79^***	NPP
					1	SC
2020	1	−0.66^***	0.12	−0.51^***	−0.14	WY
		1	−0.44^***	0.39^***	0.48^***	HQ
			1	0.11	−0.32^***	FP
				1	0.35^***	NPP
					1	SC

Identification of Ecosystem Service Bundles and Functional Zoning in the Dongjiang River Basin Based on Self-Organizing Map Neural Network

基于自组织映射神经网络的东江流域生态服务簇识别与功能分区

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