Integrating ecosystem services (ESs) into ecological security patterns (ESPs) provides a comprehensive framework for recognizing critical conservation areas and enhancing regional ecological security. However, previous studies are predominantly based on ES supply, while often not fully considering the supply-demand balance and its dynamic trends. This study proposed a comprehensive framework including comprehensive supply-demand ratio (CSDR), CSDR trend, total supply trend, and trade-off to revise ecological source recognition. Subsequently, ecological resistance surfaces were revised using land use and nighttime light data. Finally, corridors and strategic nodes were further recognized according to circuit theory to establish a comprehensive ESP. Selecting Three Gorges Reservoir Area as a research case, the results show that the ecological sources (18,232.59 km²) are predominantly situated in the eastern regions and parts of the southern bank of the Yangtze River with high supply and low ecological risks and trade-off levels. The low value of the resistance surfaces is distributed consistently with ecological sources, and the high value of the resistance surfaces is distributed near the cities with high population density and demand. Two hundred sixty-six key ecological corridors and 195 pinch points connected the regions into an organic whole and barrier points, with an area of 285.96 km² overlapping with the potential corridors. These findings offer guidance for regional planning and sustainable development.

Terricolous mosses and epilithic mosses are often used to indicate atmospheric nitrogen (N) deposition, while terricolous mosses also absorb N from soils. How to use N isotopes (δ¹⁵N) of terricolous mosses to trace the levels and sources of atmospheric N deposition accurately is an urgent problem to resolve. Based on the N contents (N_moss) and isotopes (δ¹⁵N_moss) of terricolous and epilithic mosses collected in Mount Qilian in 2022, we established a bottom-up method to calculate local atmospheric N deposition levels and source contributions. No significant difference was found in N_moss between soils and bare rocks, whil terricolous mosses had significantly higher δ¹⁵N_moss than epilithic mosses. Thus, the effects of soil N sources on δ¹⁵N_moss of terricolous mosses should be excluded before they are used to tuace emission surrces of atmospheric N deposition. The flux of total inorganic N deposition in Mount Qilian was 15.0 ± 2.3 kg N ha⁻¹ year⁻¹, with nitrate-N deposition being dominant. According to analyses of emission sources, it was volatilization-related ammonia (61.9% ± 19.8%; mainly from fertilizer application and wastes) rather than combustion-related ammonia (38.1% ± 19.8%) that dominated atmospheric ammonium-N deposition. It was fossil fuel N oxides (51.5% ± 19.6%; mainly from oil and coal combustion) rather than non-fossil fuel N oxides (48.5% ± 19.6%; mainly from biomass burning and microbial N cycles) that dominated nitrate-N deposition in this region. The Mount Qilian region holds an important position as a crucial ecological barrier in western China. Therefore, it is important to reduce reactive N emissions based on the above source apportionments to protect the fragile ecosystems of Mount Qilian.

Rapid urban development has led to the anthropogenic disruption of natural river connectivity, posing unprecedented threats to aquatic biological communities. Understanding how river connectivity influences the structure of these communities is crucial, particularly in urban mountainous regions where this topic remains underexplored. Here, we assessed river connectivity in the Mother River of Beijing, one of the world's largest megacities, and analyzed its effects on the biodiversity, dominant species, and biomass of benthic fauna, zooplankton, phytoplankton, and fungi. Our results showed that the river connectivity index (RCI) ranged from 0.0003 to 0.3978, with higher connectivity observed in the middle reaches of the river. RCI values were distinctly categorized into 2 types: high connectivity and low connectivity. Organisms at different trophic levels exhibited varying responses to river connectivity, with the composition of dominant benthic species differing by 62.5% between connectivity conditions, a higher variation than that observed in other taxa. Notably, diatom richness displayed significant spatial heterogeneity and was strongly negatively correlated with RCI. Our findings demonstrate that river connectivity exerts taxon-specific effects across multiple trophic levels, underscoring the need to consider both faunal diversity gains and potential diatom losses when designing urban river restoration and conservation strategies.

The interplay of extreme precipitation and high temperature markedly diminishes the carbon sink capacity of China's terrestrial ecosystems. Although the spatiotemporal evolution characteristics of these extreme events have been initially identified, their impacts on gross primary production (GPP) remain inadequately quantified. With the multisource data (1981 to 2100) of 4 shared socioeconomic pathways (SSPs), the Mann-Kendall test, empirical orthogonal function, and center of gravity shift models were used to identify the spatiotemporal evolution of GPP, and the structural equation model was used to elucidate the pathways and contributions of extreme events to GPP changes. GPP increased nationwide (0.02 to 0.07 kg C m⁻² a⁻¹ decade⁻¹, P < 0.05), with growth varying by scenario and there is regional heterogeneity; the first principal mode of GPP was positive in most areas (59.55% to 100%), with the same increasing and decreasing characteristics; the spatial centroid of GPP exhibited a shift from the east and south toward the west and north, accompanied by marked ecosystem greening; extremely high temperature exerted the most -substantial negative influence on GPP under SSP5-8.5 (standardized path coefficients: −0.580), whereas extreme precipitation duration in SSPs 1-2.6 and 3-7.0, and intensity in SSP2-4.5. The total effect of extreme events on GPP change shifts from a positive to a negative effect (0.966 → −0.655, −167.81%) with increasing carbon emissions. Negative effects are concentrated in Northeast China, East China shows alternating positive and negative effects, and the other regions shift from positive to negative effects. This study emphasizes the importance of differentiated climate change adaptation capacity building.