Larix gmelinii natural forests, which are of great ecological and economic importance, are mainly distributed in northeast China. Sustainable management of these forests play a vital role in ecological security in northeast China, especially in the context of climate change. Forest growth models, which support forest management decision-making, are lacking for Larix gmelinii natural forests, hampering the prescription of forest management strategies. In this study, we produced a climate-sensitive, transition-matrix model (CM) for Larix gmelinii natural forests. For comparison, a variable transition model without including climate change effects (NCM) and a fixed-parameter model (FM) were also built. We examined the performance of the CM, NCM, and FM by conducting short- (5 years) and long-term (100 years) simulations. The results showed that for short-term prediction, no significant difference was observed among the three predictive models. However, the long-term prediction ability of the CM under the three different RCPs was superior to that of the FM and NCM. The number of trees and basal area were predicted to increase under climate change, which might result in natural disasters, such as snow break, windthrow, and forest fire. Silvicultural practices, such as reducing the intermediate thinning interval and the enrichment planting of slow-growing trees, should be implemented to mitigate the deleterious effects of climate change.

Quantifying the dynamic changes and relationships between ecosystem services (ESs) and land use change is critical for sustainable ecosystem management and land use optimization. However, comprehensive discussions on the spatiotemporal variations of ESs and their relationships with land use intensity (LUI) are lacking, particularly in the context of significant climate warming. Systematic analyses of the forestry management unit scale are limited, leading to considerable uncertainty in sustainable ecosystem management, especially in alpine ecosystems of the Northern Hemisphere, where ESs have significantly degraded. The study focuses on the Daxing’anling forest area, Inner Mongolia (DFIAM), a representative sensitive alpine ecosystem and crucial ecological security barrier in Northern China. Utilizing the InVEST model, we analyzed the spatiotemporal variations in land use and four essential ESs, water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ), from 2013 to 2018. We also assessed the dynamic relationships between LUI and these ESs using a four-quadrant model. Our findings indicate the following: (1) Land use types in DFIAM remained relatively stable between 2013 and 2018, with forest being the dominant type (approximately 93%). During this period, areas of forest, cropland, impervious surfaces, and bare land increased, while areas of grassland, water, and wetland decreased. Although the overall change of LUI was gentle, a spatial pattern of “high in the southeast and low in the northwest” emerged, with low LUI areas showing slight expansion. (2) WY, SC, and HQ decreased, while CS increased from 2013 to 2018. The spatial distributions of these ESs showed higher values in the center and lower values at the edges, with forests demonstrating a strong capacity to provide multiple ESs. (3) The relationship between LUI and the four ESs from 2013 to 2018 was predominantly negative, primarily situated in Quadrant II, indicating that increased LUI inhibited ES supply capacity. Within Quadrant II, the distribution range of LUI, WY, and HQ decreased, while CS remained stable and SC increased. Furthermore, Quadrant III (positive correlation) accounted for a large proportion (19.23%~42.31%), highlighting the important role of non-anthropogenic factors in ES changes. Overall, most ESs in the DFAIM showed a decline while LUI remained relatively stable, with predominantly negative correlations between LUI and ESs. The increased LUI driven by human activities, and other non-human factors, may have contributed significantly to ES degradation. To improve ESs, we proposed implementing differentiated land use planning and management, systematic ecological protection and restoration strategies, a multi-level ecological early-warning monitoring and evaluation network, ecological corridors and buffer zones, and a collaborative management system with multiple participation. These results provide scientific guidance for the sustainable management of alpine ecosystems, enhancement of ESs, and formulation of land resource protection policies.