This study aims to explore the evolution of the pattern of ecological environment quality and its driving factors in the Beijing-Tianjin-Hebei (BTH) region, providing a basis for developing regional ecological protection policies. Based on remote sensing image data, the study developed a remote-sensing eco-environmental index (REI) from two dimensions, namely ecological quality and environmental quality, and evaluated the spatiotemporal changes of the eco-environment quality in the BTH region from 2000 to 2020. The main factors affecting the eco-environment quality and the changing trend of the eco-environment quality were subsequently analyzed using the geographic detector model and the GM1.1 model. The results show that the eco-environmental quality of the BTH region shows a fluctuating downward trend and distinct regional differences during the study period. The Yanshan Mountain in the north and the Taihang Mountain in the west have high ecological quality, while the Zhangjiakou area in the northwestern part of Hebei Province and the urban center in the southeastern part of Hebei Province suffer low ecological quality. Natural factors played a dominant role in influencing eco-environmental factors, but the proportion of economic and social factors increased over time. It is predicted that the number of counties in the region with poor eco-environmental factors will increase significantly. Therefore, the comprehensive assessment of regional ecological quality can be effectively achieved based on REI, thus providing a reference for the green and high-quality development of the regional social economy.

Assessing the response of soil heterotrophic and autotrophic respiration to climate change is critical for forecasting terrestrial carbon cycle behavior in the future. In the present study, we conducted a drought experiment in Vitexnegundo var. heterophylla shrub ecosystem of the Middle Taihang Mountain. Three precipitation manipulation treatments (natural conditions/ambient precipitation (CK), reduced precipitation by 30% (PE30), and reduced precipitation by 60% (PE60)) were used to study the impact of different levels of precipitation exclusion on total soil respiration (R_s) and its heterotrophic (R_h) and autotrophic (R_a) components. Our results showed that the rates of R_s and its components were significantly decreased under the precipitation exclusion treatments. The proportion of R_h in R_s reduced from 72.6% for CK to 71.9% under PE60. The annual cumulative C fluxes of R_s decreased by 47.8 g C m⁻² in PE30 and 106.0 g C m⁻² in PE60, respectively. An exponential relationship was observed between the rate of each soil respiration component and soil temperature in all treatments ( p < 0.01). Moreover, each soil respiration component rate was better represented by a quadratic model which included soil moisture ( p < 0.01). However, including both of soil temperature and soil moisture did not explain more variation in soil respiration components compared than the regression model with soil moisture only. In addition, excluding precipitation increased the temperature sensitivity (Q₁₀ values) of R_s and its R_a and R_h components compared to the control. Collectively, our findings suggest that increased drought will inhibit the release of carbon from the soil to the atmosphere, and will likely decrease the contribution of R_h to R_s in this semiarid shrubland ecosystem.

In response to global climate change, future precipitation changes are expected to profoundly influence soil respiration in arid and semiarid areas. However, few studies focus on CO₂ emissions from soils undergoing precipitation changes in semiarid mountain shrublands in winter. A precipitation-manipulation experiment with three levels of precipitation (30% decreased precipitation (DP), ambient precipitation (AP), and 30% increased precipitation (IP)) was performed to examine the effects of variable precipitation on soil respiration (SR) and wintertime contributions to annual SR emissions in Vitex negundo var. heterophylla shrub ecosystems located on the Middle Taihang Mountain in Hebei Province, northern China. The results showed that the average annual SR rates and winter SR rates ranged from 1.37 to 1.67 μmol m⁻² s⁻¹ and 0.42 to 0.59 μmol m⁻² s⁻¹ among the different precipitation treatments. The model based on soil moisture better represented the soil-respiration rates, suggesting that the variable precipitation extended the water’s limitation of the soil’s CO₂ emissions. The cumulative annual soil CO₂ emissions were 523, 578, and 634 g C m⁻² in response to the DP, AP, and IP treatments, respectively. The ratio of the soil CO₂ emissions in winter to the annual CO₂ emissions varied from 7.6 to 8.8% in response to the different precipitation treatments. Therefore, ignoring the soil CO₂ emissions in winter leads to the underestimation of the carbon losses in semiarid shrublands. Our results highlight that variable precipitation significantly influences soil-respiration rates, and soil CO₂ emissions in winter must not be ignored when predicting the future feedback between SR and climate change in semiarid regions.

Large-scale tree planting programs that store carbon provided by wood and non-wood products are being promoted to mitigate climate change. Assessing the biomass pool of plantations is thus an essential task in forest ecology. This study investigated biomass allocation and allometric equations for above- and belowground components along an age-sequence of Pinus tabuliformis plantations (8, 18, 32, and 46 years old) in northern Hebei Province, China. The biomass of each tree component (root, stem, branch, foliage) was quantified by destructive harvesting. Allometric equations and biomass conversion and expansion factors (BCEFs) were subsequently developed for each tree component. The mean above- and belowground biomass was 5.86, 20.05, 41.26, and 135.28 kg tree⁻¹ and 1.73, 3.42, 11.39, and 27.30 kg tree⁻¹ in the 8-, 18-, 32-, and 46-year-old stands, respectively. The proportion of stem biomass to total tree biomass increased from 28.7% for the 8-year-old stand to 55.8% for 46-year-old stand. In contrast, the contributions of foliage and branch decreased along the chronosequence. The root contribution to total tree biomass also showed a declining trend with stand age. Allometric models based on diameter at breast height showed a good fit (p < 0.001) and incorporating stand age as an additional variable improved the fit of allometric equations (higher R² and lower ACI) for branch, aboveground, root, and total tree biomass. BCEFs decreased for all tree components as stand age increased. These findings indicate that changes in tree biomass allocation and allometry across stand development must be considered to improve estimates of plantation biomass and carbon stocks at regional and national scales.

Little information is available about the ecosystem carbon (C) storage among coniferous and broadleaved plantations with similar stand ages in North China. The aim of the present research was to estimate the C storages of the components of plants, litter, and soil in two coniferous plantations (Pinus tabulaeformis and Larix principis-rupprechtii) and two broadleaved plantations (Betula platyphylla and Populus davidiana) on Yanshan Mountain, North China. Allometric equations of diameter at breast height (DBH) and height (H) were used to quantify the biomass of the tree organs. The C storage of trees, herbs, litter, and soil were estimated based on the measured C contents. The C storage varied from 24.0 to 51.9 Mg ha⁻¹, 0.3 to 0.7 Mg ha⁻¹, and 1.9 to 4.0 Mg ha⁻¹ in the tree, herbs, and litter layers, respectively. The ecosystem C storages were as follows: B. platyphylla (164.1 Mg ha⁻¹) > P. davidiana (150.4 Mg ha⁻¹) > L. principis-rupprechtii (122.3 Mg ha⁻¹) > P. tabulaeformis (106.7 Mg ha⁻¹), 65.7%–75.6% of which was stored in the soil layer. Broadleaf plantations stored higher C than coniferous plantations in this study. These results indicate that ecosystem C storage varied among various plantation types, and broadleaf plantations had considerable ecosystem C sequestration potential with even-aged plantation stands.

Urban expansion directly reduces vegetation via impervious surface growth, though indirect urban environmental effects may partially offset these losses. This study examines the Beijing–Tianjin–Hebei (BTH) region from 2000 to 2025 by integrating multi-source remote sensing and socioeconomic data to investigate the effects of urban expansion on vegetation greenness (NDVI) and productivity (NPP). The results show that impervious surfaces expanded from 21,747 km² to 33,688 km². Yet NDVI and NPP did not decline in tandem. Instead, they responded differently. NDVI exhibited broad increases—particularly in the northwest ecological zones. NPP was more sensitive to impervious surface expansion. Further analysis reveals that impervious surface coverage is the primary driver of NPP, while per capita GDP dominates NDVI. Correlation analysis confirms these relationships are consistent in direction. The combined contribution of socio-economic variables (GDP, per capita GDP, and population) substantially exceeds that of impervious surface area. This suggests that economic development, as a whole, is the dominant force shaping vegetation greenness in the region. These findings challenge the conventional trade-off narrative between urban growth and vegetation health. They demonstrate that urban expansion and ecological improvement can advance in parallel. This requires sustained greening investments and coordinated regional planning. The results offer actionable insights for carbon-sensitive land-use regulation in rapidly urbanizing regions.