Abstract:

Driven by the rapid processes of urbanization and industrialization, the growing contradiction between increasing socioeconomic development demands and the limited supply of national land resources has progressively intensified global climate change. Against the backdrop of increasingly prominent environmental issues, China proposed a long-term strategic goal in 2020 to achieve peak carbon emissions by 2030 and carbon neutrality by 2060. As an essential component of territorial space, ecological spaces possess significant carbon sink capacity. However, under the dual pressures of abrupt land-use changes, such as agricultural production and urban construction, and global warming, the carbon storage capacity of these systems has gradually weakened. Therefore, the scientific identification and management of ecological spaces, rational territorial spatial planning, and enhancement of carbon sink capacity are of great practical significance for promoting regional sustainable development and exploring new models of ecological civilization. The Dongting Lake Ecological Economic Zone, an important part of China’s key ecological area in the middle reaches of the Yangtze River, plays a vital role in regional carbon storage and sequestration. However, under the combined influence of river-lake relationship adjustments, climate change, and human activities, the region faces severe ecological challenges, including the encroachment of ecological space, water shortages, biodiversity decline, and wetland function degradation, all of which have further weakened its carbon storage capacity. Consequently, there is an urgent need to explore new models of ecological civilization that integrate sustainable ecological spatial development with coordinated regional management. Despite the increasing recognition of the importance of ecological spaces, their inherent complexity has hindered the establishment of a comprehensive evaluation system, and few studies have focused on the identification and optimization of ecological spaces from the perspective of carbon sink enhancement. In this study, the Dongting Lake Ecological Economic Zone was used as a case study. Using land-use data from 2002 to 2022, we analyzed the spatiotemporal evolution of carbon storage over the past 20 years and identified key indicators of carbon sinks. Considering both the intrinsic functions of ecological patches and their interactions with the landscape environment, and drawing on existing research, we constructed a preliminary ecological space identification index system based on two dimensions: natural and anthropogenic factors. Natural indicators include elevation, slope, surface relief, precipitation, temperature, normalized difference vegetation index (NDVI), and composite habitat quality (CHEQ). Anthropogenic indicators included population distribution, nighttime light intensity, transportation network density, and gross domestic product (GDP). An optimal parameter-based geographical detector was applied to identify the driving factors behind the spatial differentiation of carbon storage, and the final natural and anthropogenic indicators were selected. The CRITIC weighting method was then employed to determine the weights of each indicator, forming an ecological space identification system oriented toward enhancing the carbon sinks. Finally, the natural breaks method was used to classify grid values from low to high into non-ecological, baseline ecological, auxiliary ecological, and core ecological spaces, yielding the spatial distribution of ecological space in the Dongting Lake Ecological Economic Zone from 2002-2022. K-means clustering was used for the multi-scale classification of county- and village-level spaces, forming the basis for the corresponding optimization strategies that followed. The results were as follows: 1) From 2002 to 2022, the total carbon storage in the Dongting Lake Ecological Economic Zone showed a continuous decline, decreasing from 621.78×10⁶ Mg to 550.70×10⁶ Mg. Aboveground carbon storage showed the most significant decrease, reaching 57.05×10⁶ Mg. The spatial distribution of carbon storage consistently exhibited a “high in the periphery and low in the center” pattern. High-value areas were mainly concentrated in forest land, water bodies, and wetlands, whereas low-value areas were mainly distributed in cultivated and built-up areas. Single-factor detection revealed that surface relief, DEM, population distribution, slope, and habitat quality were the dominant drivers of the spatial differentiation of carbon storage. 2) From 2002 to 2022, core ecological spaces were mainly located in the western and southeastern regions of the study area, dominated by forest land with high forest coverage and strong carbon sink capacity. Auxiliary ecological spaces were distributed around core ecological spaces, serving as buffer zones between core and baseline ecological spaces. Although connectivity was low, these areas showed significant potential for transformation into core ecological spaces. Baseline ecological spaces were primarily concentrated in the central part of the study area, accounting for the largest share among the three types of ecological spaces. By 2022, they occupied 49.31% of the total ecological space. However, driven by regional economic development, urban expansion, and changes in land use structure, their ecological functions and carbon sequestration capabilities have been severely impaired. 3) The multi-scale clustering results indicate that at both the county and village levels, high-potential carbon sequestration areas are the least numerous and spatially concentrated, medium-potential areas exhibit fluctuating degradation, and low-potential areas dominate and continue expanding. The regional carbon sequestration structure exhibits a degradation trend characterized by the reduction of high-potential areas and the expansion of low-potential areas, underscoring the urgent need to implement differentiated ecological restoration and spatial regulation strategies. On this basis, this study establishes an ecological space governance framework characterized by “county-level coordination, village-level implementation, graded measures, and synergistic effects”. High-potential areas should focus on strict protection, medium-potential areas on optimization and restoration, and low-potential areas on green transition and functional remediation. Furthermore, a county-village-linked ecological restoration system is proposed, along with mechanisms for ecological compensation and green industry development based on carbon sequestration values and the improvement of intelligent monitoring and early warning platforms, with the aim of systematically enhancing regional carbon sequestration capacity and supporting the achievement of “dual carbon” goals. These findings provide a scientific basis for differentiated ecological management at the county level and micro-scale restoration at the village level, thereby supporting the realization of regional carbon neutrality goals and promoting high-quality development. The Dongting Lake Ecological Economic Zone should actively implement ecological space classification and regulatory policies based on carbon sink functions to optimize spatial layouts aimed at enhancing carbon sequestration. This study also provides a replicable research framework and methodological reference for other ecologically sensitive regions in China, contributing to the coordinated development of ecological protection and carbon sink goals.

Key words: ecological space, carbon stock, multi-scale identification, zoning regulation, the Dongting Lake Ecological and Economic Zone

摘要：

碳储量及其空间分异是国土空间优化与生态保护的重要依据，从碳增汇视角识别生态空间对促进区域可持续发展与实现“双碳”目标具有重要意义。以洞庭湖生态经济区为例，基于InVEST模型与最优参数地理探测器等方法，分析2002－2022年碳储量时空演变特征与驱动机制，构建碳增汇目标下的生态空间识别指标体系，探讨县域与村域多尺度生态空间识别与分类，并提出差异化管控策略。结果表明：1）2002－2022年洞庭湖生态经济区碳储量总体呈下降趋势，共减少71.1×10⁶ Mg，空间上呈现“四周高、中部低”的格局，地表起伏度、高程、人口分布、坡度和生境质量是碳储量空间分异的主要影响因子；2）核心型生态空间主要分布在研究区的西部及东南部地区且20年间面积有所增加，辅助型略有回升但仍减少，底线型面积最大且波动上升；3）在县域与村域尺度分类结果中，高潜力类型数量少且分布集中，中潜力类型在村域尺度上退化明显，低潜力类型占主导并呈扩张趋势，反映出生态空间结构与碳汇功能整体有所退化。该研究可为县域差异化生态管控和村域微观修复提供科学依据，助力区域双碳目标实现与高质量发展。

关键词: 生态空间, 碳储量, 多尺度识别, 分区管控, 洞庭湖生态经济区