格尔木河流域生态功能-敏感性识别及生态修复分区研究

Identification of ecosystem services and ecological sensitivity and ecological restoration zoning in the Golmud River catchment

关键词:  主导生态功能  典型生态问题  修复分区  保护修复策略  格尔木河流域

Key words:  dominant ecosystem services  typical ecological problems  restoration regionalization  conservation and restoration strategies  Golmud River catchment

摘要:

针对格尔木河流域生态修复分区体系缺失及生态修复策略针对性不足的问题, 文章基于自然立地条件、主导生态功能、典型生态问题三维视角, 搜集遥感资料并结合实测数据, 运用GIS空间分析, 引入生态重要性、敏感性评价模型, 构建分区指数, 并对其进行精度评定, 构建了“自然本底-功能导向-问题识别”的分区框架。结果表明: (1) 分区指数精度验证R²约为0.62, 能够反映流域生态敏感性空间梯度特征; (2) 全域划分为5个一级修复大区, 8个二级修复亚区, 5类三级修复区, 研究区总面积为33712.12 km², 其中, 优先区占总面积的5.29%, 重点区占10.50%, 预防区占9.83%, 维护提升区占54.48%, 保护保育区占19.92%; (3) 提出了采取自然修复为主, 人工干预为辅的生态修复策略。该生态分区及生态修复策略为实现干旱区生态系统保护与修复提供了典型的案例。

Abstract:

Background, aim, and scope Exploring the ecological restoration zoning system is of great significance for guaranteeing ecological security and realizing the construction of beautiful China. This paper tackles the absence of a systematic restoration zoning framework and generalized strategies in the Golmud River catchment via a three-dimensional perspective analysis, i.e. natural land conditions, dominant ecosystem services and typical ecological problems. The entire Golmud River catchment selects as the research region. Materials and methods Land use, land cover data and elevation data, and field-measured total soil salinity data collected in 2023. Remotely sensing information such as vegetation indices, MODIS 13Q1 product data, and meteorological data gathered from 2017 to 2023. Utilizing GIS spatial analysis techniques, an ecological importance assessment model and an ecological sensitivity evaluation model merged together. Then, a zoning framework based on the “natural context, function orientation and problem identification” is constructed to evaluate the accuracy of the zoning index through correlation analysis. Results The results show that: (1) The accuracy of the zoning index validation R² is 0.62, which reflects the characteristics of spatial gradient of ecological sensitivity in the catchment effectively. The zoning results are reasonably interpretable. (2) The total area is divided into five primary restoration areas, eight secondary restoration areas and five types of tertiary restoration areas. Specifically, those five tertiary restoration areas, i.e. the priority zones, key zones, prevention zones, maintenance and enhancement zones and conservation zones account for 5.29%, 10.50%, 9.83%, 54.48% and 19.92% of the total catchment area, respectively. (3) Differentiated ecological restoration strategies are proposed for different zones: areas with relatively mild ecological degradation should focus on natural recovery measures such as consolidating existing achievements. Whereas in priority and key zones, comprehensive remediation and intensive restoration strategies need to be adopted. Discussion On the spatial perspective, the zoning index exhibits significant spatial heterogeneity. In theory, ecologically highly sensitive areas are typically found in regions with high rainfall intensity. However, this study found that the ecologically highly sensitive areas are mainly concentrated in the central and northern parts of the catchment, where annual rainfall is only 42.2 mm. This indicates that rainfall induced erosion is not the primary factor determining the sensitivity assessment of this region. Additionally, this study only considered natural factors and neglected socio-economic factors, which may lead to certain limitations. Conclusions The “natural context, function-oriented and problem identification” ecological zoning framework and corresponding ecological restoration strategy is developed. And it provides a typical case for realizing ecosystem protection and restoration in the arid zones. Recommendations and perspectives The protection and restoration of arid areas ecosystems is of irreplaceable strategic significance in ensuring sustainable development in the region. There are deficiencies in the aspects considered in this paper. Subsequently, it is recommended to integrate multi-source data from remote sensing monitoring and actual surveys. The study should comprehensively consider natural factors, population activities and socio-economic factors, etc., further improve the zoning methodology, optimize the evaluation index system, determine the main influencing factors of ecological vulnerability, so as to provide a more accurate direction for ecological restoration.