Ecological engineering is a widely used strategy to address environmental degradation and enhance human well-being. A quantitative assessment of the impacts of ecological engineering on ecosystem services (ESs) is a prerequisite for designing inclusive and sustainable engineering programs. In order to strengthen national ecological security, the Chinese government has implemented the world’s largest ecological project since 1999, the Grain for Green Program (GFGP). We used a professional model to evaluate the key ESs in Lvliang City. Scenario analysis was used to quantify the contribution of the GFGP to changes in ESs and the impacts of trade-offs/synergy. We used spatial regression to identify the main drivers of ES trade-offs. We found that: (1) From 2000 to 2018, the contribution rates of the GFGP to changes in carbon storage (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC) were 140.92%, 155.59%, −454.48%, and 92.96%, respectively. GFGP compensated for the negative impacts of external environmental pressure on CS and HQ, and significantly improved CS, HQ, and SC, but at the expense of WY. (2) The GFGP promotes the synergistic development of CS, HQ, and SC, and also intensifies the trade-off relationships between WY and CS, WY and HQ, and WY and SC. (3) Land use change and urbanization are significantly positively correlated with the WY–CS, WY–HQ, and WY–SC trade-offs, while increases in NDVI helped alleviate these trade-offs. (4) Geographically weighted regression explained 90.8%, 94.2%, and 88.2% of the WY–CS, WY–HQ, and WY–SC trade-offs, respectively. We suggest that the ESs’ benefits from the GFGP can be maximized by controlling the intensity of land use change, optimizing the development of urbanization, and improving the effectiveness of afforestation. This general method of quantifying the impact of ecological engineering on ESs can act as a reference for future ecological restoration plans and decision-making in China and across the world.

The degradation of ecosystem services (ES) poses a significant obstacle to regional sustainable development. Land-use change is widely recognized as a pivotal factor driving the spatio-temporal dynamics of ES supply and demand. However, the future impact of land-use changes on supply–demand risks remains largely unknown. To fill this knowledge gap, we conducted a study in the Gansu section of the Yellow River Basin. By integrating Cellular Automata (CA) and an enhanced Markov model within the GeoSOS-FLUS framework, we dynamically simulated land-use changes under three scenarios—the Normal Development Scenario (NDS), Ecological Protection Scenario (EPS), and Rapid Socio-economic Development Scenario (RDS)—spanning from 2020 to 2050. Furthermore, we employed the InVEST model to analyze the spatio-temporal pattern of supply, demand, supply-to-demand ratios, and supply–demand risks for water provision, carbon storage, and soil conservation under all scenarios. Firstly, all scenarios project an increase in built-up land, primarily from unused land, shrubland, grassland, and cropland. Forest land and water bodies remain stable. Secondly, water provision increases, but demand grows faster, leading to supply–demand imbalances, with high-risk areas in the north, central, and east. Soil conservation shows balanced supply and demand with high-risk areas in the north. Carbon storage remains stable, with high-risk areas in the central and east regions. Thirdly, high-risk areas for water provision increase under all scenarios, particularly under the Rapid Socio-economic Development scenario.

Ecological stoichiometry is an essential tool to understand carbon (C), nitrogen (N), and phosphorus (P) cycles and nutrient limitations. Plantations are usually managed to maintain specific age structures, but the impact of such management on microbial biomass and stoichiometric ratios remains unclear. We compared the stand ages of four Larix principis-rupprechtti Mayr. Plantations that were 15 years old, (young plantation, Lar15), 24 years old, (middle aged plantation, Lar24), 40 years old, (near-mature plantation, Lar40), and 50 years old, (mature plantation, Lar50), respectively, to determine the main factors that drive differences in the C:N:P stoichiometry of microorganisms. We demonstrated that the temperature, moisture, and nutrient concentrations in surface soil increased significantly with forest age. The stoichiometric ratios of elements in soil and microorganisms reached their maxima in the Lar40 and Lar50 plantations. Additionally, forest stand ages had a great influence on the biomass of microbial communities. Moreover, soil microbial community and soil abiotic factors are closely related to soil microorganisms’ C:N:P stoichiometric ratios. Specifically, changes in the microbial biomass C:N (MBC:MBN) were primarily correlated with bacteria, Gram-positive bacteria (G⁺), temperature, NH₄⁺-N, and moisture in soil. Shifts in G⁺, actinobacteria, soil temperature, and total phosphorus were primarily associated with variation in microbial biomass C:P (MBC:MBP). Alterations in microbial biomass N:P (MBN:MBP) were correlated with bacteria, NH₄⁺-N, water content, Gram-negative bacteria, and soil temperature. Overall, these results suggest that microbial elemental stoichiometric ratios could be affected by stand age and emphasize the importance of microbial communities and soil abiotic factors in shifting this dynamic change process.

The stoichiometric ratios of elements in microorganisms play an important role in biogeochemical cycling and evaluating the nutritional limits of microbial growth, but the effects of thinning treatment on the stoichiometric ratio of carbon, nitrogen, and phosphorus in microorganisms remain unclear. We conducted research in a Larix principis-rupprechtti Mayr. plantation to determine the main factors driving microbial carbon (C): nitrogen (N): phosphorus (P) stoichiometry following thinning and the underlying mechanisms of these effects. The plantation study varied in thinning intensity from 0% tree removal (control), 15% tree reduction (high density plantation, HDP), 35% tree reduction (medium density plantation, MDP), and 50% tree reduction (low density plantation, LDP). Our results indicated that medium density plantation significantly increased litter layer biomass, soil temperature, and other soil properties (e.g., soil moisture and nutrient contents). Understory vegetation diversity (i.e., shrub layer and herb layer) was highest in the medium density plantation. Meanwhile, thinning had a great influence on the biomass of microbial communities. For example, the concentration of phospholipid fatty acids (PLFA) for bacteria and fungi in the medium density plantation (MDP) was significantly higher than in other thinning treatments. Combining Pearson correlation analysis, regression modeling, and stepwise regression demonstrated that the alteration of the microbial biomass carbon: nitrogen was primarily related to gram-positive bacteria, gram-negative bacteria, soil temperature, and soil available phosphorus. Variation in bacteria, actinomycetes, gram-positive bacteria, gram–negative bacteria, and soil total phosphorus was primarily associated with shifts in microbial biomass carbon: phosphorus. Moreover, changes in microbial biomass nitrogen: phosphorus were regulated by actinomycetes, gram-negative bacteria, and soil temperature. In conclusion, our research indicates that the stoichiometric ratios of elements in microorganisms could be influenced by thinning management, and emphasizes the importance of soil factors and microbial communities in driving soil microbial stoichiometry.