## 1 Introduction  
The carbon cycle is fundamental to our understanding of Earth's ecological systems, offering essential insights into how ecosystems respond to climate change and highlighting the significant impact of anthropogenic activities on these dynamics [1, 2]. As such, carbon cycle research has become a pivotal theme in global climate change discourse, attracting extensive international focus [3, 4]. The role of terrestrial vegetation in the carbon cycle is particularly critical. Recent studies have extended beyond Gross Primary Productivity (GPP) [5, 6, 7] and Net Primary Productivity (NPP) [8, 9, 10] to broader aspects like estimating Net Ecosystem Productivity (NEP), determining regional carbon budgets, and assessing carbon sources and sinks comprehensively [4, 11]. Recent IPCC reports underscore the growing impact of climate change on the carbon cycle, underscoring the necessity for robust methods to assess carbon emissions at both regional and global scales, particularly to glean critical insights into the interplay between human activities and natural processes on carbon balance. Terrestrial ecosystems, recognized both domestically and internationally for their pivotal role in sequestering atmospheric CO2 and acting as significant carbon sinks [12], remain a major research focus. However, accurately estimating carbon sinks and their spatial distribution continues to pose significant challenges. NEP is a key metric in this context, quantifying an ecosystem's net carbon balance over a particular period [13]. The methodologies to estimate carbon sinks are diverse, incorporating field surveys [14], ecosystem flux measurements [15; 16], atmospheric inversion [17; 18], and model simulations [19; 20], among others. Each method has its advantages and limitations. Field surveys provide detailed, site-specific information on biomass, soil organic carbon, and vegetation characteristics but are limited in scope and require significant effort. Ecosystem flux measurements offer precise, real-time data on carbon flows within ecosystems but need lengthy data-collection periods for comprehensive analysis. Atmospheric inversion techniques estimate carbon sinks by monitoring atmospheric CO2 levels, covering large areas, but they are affected by atmospheric changes. Model simulations, using ecological models and meteorological data, allow for future predictions but depend on the accuracy and robustness of the models. Thus, selecting appropriate methods or their combination for carbon sink estimation largely depends on the research objectives and resources available, aiming for an all-encompassing dataset compilation without overstating the merits of one's own work. Located in the dry and semi-dry zones of Northern China, the Three Northern Protection Forest Project Area exemplifies China's efforts in aforestation and environmental restoration across its arid regions of the northwest, North China, and northeast. This comprehensive initiative supports environmental protection, ecological improvement, climate change mitigation, biodiversity conservation, and sustainability [21; 22; 23; 24]. Notably, the area has experienced an upward trend in annual, growing season, and non-growing season precipitation. Within the Three Northern Project Area, grasslands, as the dominant ecosystem, account for approximately 63.29% of the area, underscoring their importance in the regional ecosystem. This is followed by forested and agricultural lands, which constitute 16.33% and 13.99% of the area, respectively. Due to its significance, this study critically assesses the spatiotemporal dynamics of carbon sources and sinks within the Three Northern Protection Forest Project Area.