The Huang-Huai-Hai Plain, a vital agricultural area in China with a significant amount of arable land, plays a pivotal role in influencing grain production, ecological carbon cycles, and global climate change through its shifts in land use. Within this research, we have employed the ArcGIS tool and the In-VEST-Geodetector-PLUS methodology to scrutinize the shifts in carbon storage from the year 2000 to 2020, determine the pivotal influences behind these shifts, and anticipate the projected carbon storage for 2030. Although there has been a slight increase in forested areas as a result of environmental policies, the conversion of cropland to impervious surfaces due to urbanization has led to a persistent decrease in carbon storage, with a cumulative loss of 272.79 million metric tons over the two decades. The Normalized Difference Vegetation Index (NDVI), Night-Time Lights (NTL), Gross Domestic Product (GDP), and Population (POP) are critical factors impacting carbon storage, reflecting the intricate connection between socio-economic development and natural ecosystems. The multi-scenario simulations for 2030 suggest that the least reduction in carbon storage would occur under the scenario of protecting arable land, while the most significant decrease would be under the urban expansion scenario, highlighting the impact of urbanization. The study’s results emphasize the critical need to harmonize agricultural land conservation with economic progress for the enduring growth of the Huang-Huai-Hai region.

In this research, we chose six indicators—soil conservation, water conservation, carbon sequestration, windbreak and sand fixation, biodiversity conservation, and forest recreation—to compute the forestland ecosystem service index for forestland within the study region, utilizing time series data. The outcomes reveal that the aggregate index of forestland ecosystem services exhibits a spatial distribution characterized by higher values in the northeastern part and lower values in the southwestern part, with an upward trend over time. Among these functions, windbreak and sand fixation, water conservation, carbon sequestration, and forest recreation all maintained relatively high growth rates. We selected 10 factors that are closely related to the natural environment and human activities and employed spatial principal component analysis to develop a comprehensive resistance surface. Based on the assessment results of forestland ecosystem functions, in conjunction with morphological spatial pattern analysis (MSPA) as well as landscape connectivity analysis, we optimized the method for identifying ecological source sites and extracted 38 ecological source sites. Subsequently, leveraging circuit theory, we extracted 91 ecological corridors and pinpointed 25 ecological nodes, ultimately constructing a forestland ecosystem security pattern (ESP) in the study area and proposing restoration strategies.

Heavy metal pollution poses a global environmental challenge, with lead (Pb) being particularly concerning due to its persistence and toxicity. This study investigated Xanthium strumarium L. from China’s Yellow River Sanmenxia section through hydroponic experiments (0–600 mg/L Pb²⁺, 1–11 d exposure) to elucidate its Pb²⁺ response mechanisms. Integrated analyses (EDX, FTIR, thermogravimetry, hyperspectral imaging) revealed a three-phase sequestration strategy: the roots immobilized 88.55% of Pb through pectin carboxyl de-esterification and lignin–Pb complexation, while the stems and leaves retained <11.14% and <0.31%, respectively. A critical threshold (300 mg/L) triggered nonlinear Pb accumulation escalation. Thermogravimetric analysis demonstrated enhanced cell wall stability under Pb stress (66.7% residual carbon increase at 600 mg/L). Hyperspectral features (1670 nm band intensity) effectively tracked physiological stress dynamics. The findings establish X. strumarium’s superior suitability for root-based immobilization rather than phytoextraction in Pb-contaminated sites, with its low translocation efficiency minimizing ecological risks. The identified concentration threshold and spectral biomarkers provide multi-scale insights for optimizing in situ phytostabilization strategies, advancing both theoretical understandings and practical applications in heavy metal remediation.

For tourist cities, coordination between tourism and socio-economic and natural environments is crucial for sustainable urban development. While the positive correlation between a Natural World Heritage (NWH) designation and local urban tourism growth has been validated, the interplay among tourism, the economy, and the environment remains underexplored. We conceptualize NWH cities as complex adaptive systems and establish an evaluation framework to assess the relationships among tourism, economic, and environmental subsystems. Using 34 NWH cities in China as case studies, we apply a coupling coordination degree model to evaluate the sustainability indices of the three subsystems and their interrelationships. Additionally, the obstacle degree model identifies specific obstacles in cities with suboptimal coordination, leading to targeted management recommendations. Our findings reveal that while tourism and economic sustainability indices have shown consistent upward trends, environmental sustainability has experienced a decline. The coupling coordination degrees among the three subsystems have generally increased, albeit with fluctuations in some cities. Environmental-related indicators are the main obstacle factors to imbalanced development in some cities from 2015 to 2020. Therefore, the primary challenge for sustainable management lies in the environmental subsystem. This study provides a relational perspective for evaluating the sustainability of NWH cities and offers targeted recommendations for enhancing their sustainable development, contributing to the broader discourse on heritage management and sustainable urban practices.