Forestry work involves scientific management and the effective utilization of forest land resources, and finding economical, efficient and accurate acquisition methods for forest land resource information. In previous land-use classification research, machine learning algorithms have achieved good results, and Sentinel public data have been used in various remote sensing applications. However, there is a paucity of research using these data to evaluate the performance of machine learning algorithms in the extracting of complex forest land resource information. Using the Sentinel-2 satellite multispectral image data, the spectral reflectance, vegetation index characteristics and image texture characteristics of different forest land resources in the study area were calculated and compared. Then, based on three groups of features, the performances of the Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), decision trees (DT) and Multi-layer Perceptron (MLP) were examined and compared to identify and classify forest land resource types. The research indicates the following: (1) The SVM algorithm achieved the highest OA (95.8%). The average accuracy of the SVM algorithm was much higher than other algorithms (SVM 88.3%, KNN 87.5, RF 85.3%, MLP 85.00% and DT 77.5%). (2) The classification accuracies of each algorithm for coniferous forests were relatively high, and the recognition accuracy was above 95%, whereas the classification accuracies of the other categories varied greatly. (3) Adding texture features can improve the accuracy of the five algorithms. This study reports new references for the qualitative methods of forest land resource distribution. It has also produced more efficient and accurate acquisitions of forest land resource information, scientific management and effective use of forest land resources.

As the primary secondary tree species in Northeast China, Quercus mongolica possesses significant ecological and economic value. This study employed the Biomod2 platform in conjunction with ArcGIS spatial analysis to assess the potential suitable habitat distribution area of Q. mongolica under current climatic conditions. Furthermore, it forecasted the distribution range and niche changes of potentially suitable habitats for Q. mongolica from 2022 to 2090 and pinpointed the key environmental factors influencing its distribution. The findings reveal that the total potential suitable area for Q. mongolica covers 74,994.792 km², predominantly spread across Inner Mongolia, Heilongjiang, Jilin, and other regions. The primary determinants of suitable area distribution were peak temperature of hottest month, lowest temperature of coldest month, and altitude. Under future climate scenarios, the potentially suitable habitats of Q. mongolica are anticipated to diminish to varying extents, with the distribution center exhibiting a tendency towards northward migration. Concurrently, the overlap among different climate scenarios is predicted to expand over time. This investigation facilitates a comprehensive understanding of Q. mongolica’s adaptation to climate change, enabling informed adjustments and serving as a valuable reference for the preservation and sustainable management of Q. mongolica populations.

In the Mu Us Sandy Land, vegetation is closely related to soil microorganisms and nutrients. However, research on the relationship between soil microbial communities and nutrients in Pinus sylvestris var. mongolica plantations of different densities is still imperfect. This study selected Pinus sylvestris var. mongolica plantations with high, medium, and low densities, as well as bare sandy land, to analyze the relationship between vegetation density and soil nutrients, microbial community structure, and diversity indices. The results show that the following: (1) Medium-density plantations significantly increased soil organic matter, total nitrogen, and total potassium content, which were 4.3 times that of bare sandy land and 1.7 times that of high-density plantations; (2) In high-density plantations, the relative abundance of bacterial phyla Actinobacteriota and fungal phylum Ascomycota was higher; as plantation density decreased, the relative abundance of bacterial phyla Proteobacteria and Acidobacteriota and fungal phylum Basidiomycota increased, with different density plantations significantly affecting soil microbial community structure; (3) High-density plantations significantly increased the abundance of bacterial and fungal genera but also reduced bacterial diversity indices, while medium-density plantations were outstanding in enhancing fungal species richness and diversity, with the highest fungal Shannon index, indicating that medium density is conducive to fungal diversity enhancement; (4) Soil organic matter, total nitrogen, total phosphorus, total potassium, and pH value were the main environmental factors affecting soil microbial community structure. High-density plantations significantly affected soil microbial community structure by changing these soil nutrients and physicochemical properties, especially related to changes in total potassium and pH value. This study clarified the effects of Pinus sylvestris var. mongolica plantation density on soil nutrients and microbial community structure, revealing the intrinsic connection between soil nutrients and microbial communities, providing a theoretical basis for vegetation restoration in the Mu Us Sandy Land ecosystem, and helping to formulate scientific management strategies for Pinus sylvestris var. mongolica plantations to improve sandy land soil quality and promote the sustainable development of sandy land ecosystems.

Sustainable forest management requires a comprehensive understanding of how stand density regulates soil ecological processes. We examined a Larix principis-rupprechtii plantation under three thinning retention densities (High—HD; Medium—MD; Low—LD) and an unthinned control (CK), with soil samples collected from four depth layers (0–10, 10–20, 20–30, and 30–40 cm). This study investigated the effects of stand density on soil properties and microbial communities in a Larix principis-rupprechtii plantation by combining high-throughput sequencing with soil physicochemical analysis to identify the optimal density regime for maintaining soil health. Results demonstrated the following: (1) Moderate-density (MD) management best balanced the stability of soil ecosystem structure, showing superior water retention, organic carbon content, and microbial diversity in the 0–30 cm soil layer. The mechanism underlying these improvements can be attributed to the moderately open canopy structure in MD stands, which facilitated efficient litter decomposition and drove functional complementarity between Basidiomycota (enhancing cellulose degradation capacity) and Acidobacteriota (adapted to oligotrophic conditions). (2) Redundancy analysis revealed that soil pH and available nutrients (AK, AP) were key environmental factors driving microbial community restructuring: Actinobacteriota dominated in neutral, phosphorus-rich environments, while Acidobacteriota thrived under acidic, phosphorus-limited conditions. Fungal communities showed high sensitivity to management intensity, with significant shifts between Ascomycota and Basidiomycota, whereas bacterial communities remained relatively stable due to functional redundancy. We recommend the adoption of moderate-density management as a sustainable practice to enhance soil nutrient cycling and maintain microbial diversity, thereby providing scientific support for sustainable plantation management.

As the primary secondary tree species in Northeast China, Quercus mongolica possesses significant ecological and economic value. This study employed the Biomod2 platform in conjunction with ArcGIS spatial analysis to assess the potential suitable habitat distribution area of Q. mongolica under current climatic conditions. Furthermore, it forecasted the distribution range and niche changes of potentially suitable habitats for Q. mongolica from 2022 to 2090, and pinpointed the key environmental factors influencing its distribution. The findings reveal that the total potential suitable area for Q. mongolica covers 74,994.792 km², predominantly spread across Inner Mongolia, Heilongjiang, Jilin, and other regions. The primary determinants of suitable area distribution were peak temperature of hottest month, lowest temperature of coldest month and altitude. Under future climate scenarios, the potentially suitable habitats of Q. mongolica are anticipated to diminish to varying extents, with the distribution center exhibiting a tendency towards northward migration. Concurrently, the overlap among different climate scenarios is predicted to expand over time. This investigation facilitates a comprehensive understanding of Q. mongolica's adaptation to climate change, enabling informed adjustments and serving as a valuable reference for the preservation and sustainable management of Q. mongolica populations.

Sustainable forest management requires a comprehensive understanding of how stand density regulates soil ecological processes. This study investigated the effects of stand density on soil properties and microbial communities in a Larix principis-rupprechtii plantation by combining high-throughput sequencing with soil physicochemical analysis to identify the optimal density regime for maintaining soil health. Results demonstrated that moderate-density (MD) management best balanced the stability of soil ecosystem structure, showing superior water retention, organic carbon content, and microbial diversity in the 0-30 cm soil layer. The mechanism underlying these improvements can be attributed to the moderately open canopy structure in MD stands, which facilitated efficient litter decomposition and drove functional complementarity between Basidiomycota (enhancing cellulose degradation capacity) and Acidobacteriota (adapted to oligotrophic conditions). Redundancy analysis revealed that soil pH and available nutrients (AK, AP) were key environmental factors driving microbial community restructuring: Actinobacteriota dominated in neutral, phosphorus-rich environments, while Acidobacteriota thrived under acidic, phosphorus-limited conditions. Fungal communities showed high sensitivity to management intensity, with significant shifts between Ascomycota and Basidiomycota, whereas bacterial communities remained relatively stable due to functional redundancy. We recommend the adoption of moderate-density management as a sustainable practice to enhance soil nutrient cycling and maintain microbial diversity, thereby providing scientific support for sustainable plantation management.