Pinus massoniana is an important tree species for wind protection and timber forests in Southern China. In recent years, P. massoniana plantations have been developed on more than 11,300,000 hm2 in southern China, but numerous problems have been observed, such as soil degradation, biodiversity reduction, and ecological functional decline. Crop tree management impacts on fine root development, which can be explained by the variations in the root orders. In this study, a 36-year-old P. massoniana plantation located in Huaying, Sichuan Province, was selected as the research field. In 2015, crop tree management was initiated, with a crop tree intensity of 150 trees per hectare. After 3 years of growth, fine roots of crop and noncrop trees were collected by the sector method with an angle of 15 degrees and a radius of 2 meters. We analyzed the morphological characteristics and biomass in different root orders, and explored their carbon and nitrogen contents. The results were as follows: (1) The specific root length (SRL), root length density (RLD), and surface root area (SRA) of the crop trees were larger than those of the noncrop trees; the SRL increased significantly from 0–0.5 m to 1–1.5 m from the stem. (2) The fine root biomass of the crop trees was significantly larger than that of the noncrop trees. The fine root biomass of the crop and the noncrop trees increased with the horizontal distance from the stem from 0–0.5 m to 1–1.5 m. The morphological indexes of the noncrop trees at the distances of 1–1.5 m and 1.5–2 m were significantly different, while those of the crop trees at those distances were not. (3) The fine root C content of the crop trees was significantly higher than that of the noncrop trees and varied significantly along a vertical distribution. The fine root N content of the crop trees was significantly higher than that of the noncrop trees, and the N content of topsoil was higher than that of deeper soil. In conclusion, our results indicated that crop tree management increased the production of a large-diameter wood of P. massoniana, which might be attributed to the improvement of soil permeability and nutrient stock, and thus, the enhancement of fine root quantity and water/nutrient absorption ability.

Ectomycorrhizal (ECM) fungi can form symbioses with plant roots, which play an important role in regulating the rhizosphere microenvironment. As a broad-spectrum ECM tree species, Pinus massoniana forms symbiotic relationship called mycorrhiza with various ECM fungal species. In this study, four types of forests were selected from a 38-year-old Pinus plantation in eastern Sichuan, namely, pure P. massoniana forest (MC), P. massoniana mixed with Cunninghamia lanceolata forest (MS), P. massoniana–Cryptomeria fortunei forest (ML), and P. massoniana–broadleaved forest (MK), the species mixture ratio of all forests was 1:1. The ITS2 segment of ECM root tip sequenced by high-throughput sequencing using the Illumina MiSeq sequencing platform. (1) The ECM fungi of these four P. massoniana forests showed similar dominant genera but different relative abundances in community structure during the three seasons. (2) The alpha diversity index of ECM fungi was significantly influenced by season and forest type. (3) Soil pH, soil organic matter (SOM), total nitrogen (TN), C/N ratio, and total phosphorus (TP) influenced the ECM fungal community structure in different seasons. In summary, there were significant differences in ECM fungal communities among different forest types and different seasons; the colonization rate of ECM fungal in P. massoniana–Cunninghamia lanceolata was the highest, so we infer that Cunninghamia lanceolata is the most suitable tree species for mixed with P. massoniana in three mixture forests.

At present, many Deep Neural Network (DNN) methods have been widely used for hyperspectral image classification. Promising classification results have been obtained by utilizing such models. However, due to the complexity and depth of the model, increasing the number of model parameters may lead to an overfitting of the model, especially when training data are insufficient. As the performance of the model mainly depends on sufficient data and a large network with reasonably optimized hyperparameters, using DNNs for classification requires better hardware conditions and sufficient training time. This paper proposes a feature fusion and multi-layered gradient boosting decision tree model (FF-DT) for hyperspectral image classification. First, we fuse extended morphology profiles (EMPs), linear multi-scale spatial characteristics, and nonlinear multi-scale spatial characteristics as final features to extract both special and spectral features. Furthermore, a multi-layered gradient boosting decision tree model is constructed for classification. We conduct experiments based on three datasets, which in this paper are referred to as the Pavia University, Indiana Pines, and Salinas datasets. It is shown that the proposed FF-DT achieves better performance in classification accuracy, training conditions, and time consumption than other current classical hyperspectral image classification methods.

Thinning can significantly promote forest productivity and ecological function. Rhizosphere fungi play an indispensable role in regulating nutrient cycling between plants and the environment, and their community composition can positively respond to anthropogenic disturbance. However, the initial effects of thinning on rhizosphere fungal community assembly have seldom been reported. In this research, we studied the alterations in the rhizosphere fungal communities of 29-year-old Pinus massoniana in East Sichuan 2 years after three different thinning intensity treatments. In addition, the responses of fungal community and functional group composition to alterations in understory vegetation and soil physiochemical properties were analyzed. Three thinning intensities were set, which were 0 (CK), 25% (LIT), and 50% (HIT), respectively. The results suggested that the richness index and Shannon index of understory vegetation increased significantly with increasing thinning intensity. The alpha diversity indices of rhizosphere fungal community and soil physiochemical properties did not show significant differences among the three treatments. The relative abundances of 17 fungal indicator species varied regularly with increasing thinning intensity, and most of them belong to Hypocreales and Eurotiales, indicating that these two orders were potential indicators for different thinning treatments. Rhizosphere fungal community assembly was determined by deterministic process, and it was driven by the diversity of understory vegetation in the initial stage of thinning. The Simpson index and Pielou index of herbs were useful measures of the main environmental factors driving the differentiation of fungal functional group composition. Based on network analysis, thinning resulted in distinct co-occurrence patterns of rhizosphere fungal functional groups. This research elucidates the initial role of thinning in rhizosphere fungal community assembly of P. massoniana and has practical significance for the functional restoration and protection of local forest ecosystem.

As a special thinning method, crop tree release (CTR) has a beneficial effect on forest environments and structures by changing forest light, heat and water. However, the impact of CTR on underground biodiversity remains unclear. Therefore, we analyzed the composition, diversity and metabolic footprints of soil nematode communities under three CTR (100 trees/ha, 150 trees/ha and 200 trees/ha) treatments, as well as a non-CTR treatment, in a Pinus massoniana plantations. The results showed that CTR increased the density of soil nematodes (P < 0.05), the number of omnivore-predator nematodes (P < 0.05), and the diversity (H') of nematodes (P < 0.05) and enriched the food web structure of soil nematodes. In the medium CTR density treatment (150 trees/ha), the nematode density and diversity (H') were the highest (P < 0.05), the number of omnivore-predator nematodes was also the highest (P < 0.05), and the enrichment index and structure index values of the soil nematodes reached the maximum at the depth of 0-10 cm (P < 0.05). Our results indicated that the community structure of soil nematodes became more stable and mature after CTR, which may be attributed to the changes of soil condition, especially soil organic matter, and plant diversity indirectly.