Search Results (28)

Tomicus yunnanensis Kirkendall and Faccoli, a native bark beetle species and key pest of Pinus yunnanensis Franch. in southwestern China, relies on host-derived volatile organic compounds (VOCs) for host selection. To unravel these mechanisms, we collected VOCs from P. yunnanensis trunks across four infestation stages (healthy, early-infested, weakened, near-dead) using dynamic headspace sampling. Chemical profiling via gas chromatography–mass spectrometry (GC-MS) identified 51 terpenoids, with α-pinene as the most abundant component. VOC profiles differed markedly between healthy and early-infested trees, while gradual shifts in compound diversity and abundance occurred from the weakened to near-dead stages. Bioactive compounds were screened using gas chromatography–electroantennographic detection (GC-EAD) and a Y-tube olfactometer. Electrophysiological responses in T. yunnanensis were triggered by α-pinene, β-pinene, 3-carene, 2-thujene, and 4-allylanisole. Behavioral tests revealed that α-pinene, 3-carene, and 2-thujene acted as attractants, whereas β-pinene and 4-allylanisole functioned as repellents. These results indicate that infestation-induced VOC dynamics guide beetle behavior, with attractants likely promoting host colonization during early infestation and repellents signaling deteriorating host suitability in later stages. By mapping these chemical interactions, our study identifies potential plant-derived semiochemicals for targeted pest management. Integrating these compounds with pheromones could enhance the monitoring and control strategies for T. yunnanensis, offering ecologically sustainable solutions for pine ecosystems. Full article

Accurate prediction of individual tree mortality in Pinus yunnanensis Franch. is essential for sustainable forest management and ecological monitoring in southwest China. The aim of this study is to develop a tree mortality prediction model for Pinus yunnanensis based on resurvey data from the Cangshan area in Dali, Yunnan Province, using a stacked ensemble learning algorithm. After an initial evaluation of model performance, the classification thresholds were optimized using the Minimum Classification Error method, the Maximum Sensitivity and Specificity method, the Kappa coefficient method, and the Precision-Recall (PR) curve method to enhance classification results. The findings show that, compared to traditional statistical methods and individual machine learning models, the stacked ensemble learning model (Stacked-RSX) outperforms others in tree mortality classification tasks, which achieved an accuracy of 0.8947, recall of 0.9431, true negative rate of 0.9490, misclassification rate of 0.2289, and an area under the curve of 0.953. Through an exhaustive search for the best classification thresholds, the PR curve method demonstrated good adaptability across all models. All optimal thresholds, relative to the default threshold, significantly improved overall classification performance. Furthermore, feature importance analysis revealed that tree height, diameter at breast height (DBH), Hegyi competition index, and the ratio of DBH to stand basal area are key variables influencing mortality risk. These results indicate that the stacking ensemble learning algorithm effectively analyzes the complex relationships among different factors, significantly improving the prediction accuracy of tree mortality, and providing scientific insights for the management and health monitoring of Pinus yunnanensis forests. Full article

Nitrogen deposition can significantly impact soil biogeochemical cycling; however, its effects on the decomposition processes and nutrient release from leaf and twig litter in subtropical plantations remain inadequately understood. In this study, we focused on the Pinus yunnanensis Franch. forest in the central Yunnan Plateau, southwestern China, and explored how nitrogen addition influences litter decomposition nutrient release over two years, under four levels: control (CK, 0 g·m⁻²·a⁻¹), low nitrogen (LN, 10 g·m⁻²·a⁻¹), medium nitrogen (MN, 20 g·m⁻²·a⁻¹), and high nitrogen (HN, 25 g·m⁻²·a⁻¹). The results indicate that after 24 nitrogen application treatments, the rates of remaining mass in both leaf and twig litters followed the pattern: LN < CK = MN < HN. Under all nitrogen application treatments, the rate of remaining mass in leaf litters was significantly lower than that of twig litters (p < 0.05). Under LN, the mass retention in leaf and twig litters decreased by 3.96% and 8.41%, respectively, compared to CK. In contrast, under HN treatments, the rates of remaining mass in leaf and twig litters increased by 8.57% and 5.35%, respectively. This demonstrates that low nitrogen accelerates decomposition, whereas high nitrogen inhibits it. Significant differences in the remaining amounts of lignin and cellulose in both leaf and twig litters were observed when compared to CK (p < 0.05). Additionally, decomposition time and nitrogen deposition had significant effects on the remaining rates of nutrients (C, N, P) and their C/N, C/P, and N/P in litters (p < 0.05). Following nitrogen application, the C/N of the litters significantly reduced, while the N/P increased. The results suggest that nitrogen addition alleviates the nitrogen limitation on the litters while intensifying the phosphorus limitation. Full article

Subalpine shrubland is an important vegetation type in the Hengduan Mountains region of China, and its distribution has been substantially influenced by global warming. In this research, four subalpine shrub communities in the Hengduan Mountains were selected: Rhododendron heliolepis Franch. scrub, Rhododendron flavidum Franch. scrub, Quercus monimotricha (Hand.-Mazz.) Hand.-Mazz. scrub, and Pinus yunnanensis var. pygmaea (Hsueh ex C. Y. Cheng, W. C. Cheng & L. K. Fu) Hsueh scrub. A MaxEnt model was used to assess the suitable habitats and their primary drivers of four subalpine shrublands in China under different climate scenarios. Our results indicate the following: (1) The suitable habitat areas of the four subalpine shrublands exhibit a predominant distribution within the Hengduan Mountains region, with small populations in the Himalayas and Wumeng Mountain. Temperature and precipitation are identified as the primary drivers influencing the suitable habitat areas of the four subalpine shrublands, and the temperature factor is more influential than the precipitation factor. Furthermore, the contribution rate of slope to Quercus monimotricha scrub is 19.2%, which cannot be disregarded. (2) Under future climate scenarios, the total suitable habitats of the four subalpine shrublands show an expanding trend. However, the highly suitable areas of three shrublands (Rhododendron flavidum scrub, Quercus monimotricha scrub, and Pinus yunnanensis var. pygmaea scrub) show a contracting trend under the high-carbon-emission scenario (SSP585). (3) Driven by global warming, the suitable habitat areas of Rhododendron heliolepis scrub, Rhododendron flavidum scrub, and Pinus yunnanensis var. pygmaea scrub shift toward higher elevations in the northwest, while the distribution of Quercus monimotricha scrub varies under different carbon emission scenarios, with a much smaller shift range than the other three scrubs. Our study contributes valuable insights into the spatiotemporal dynamics of subalpine shrublands in China under climate change, providing scientific guidance for biodiversity conservation and ecosystem restoration. Full article

Pinus yunnanensis Franch. is a common woodland species in the southwest of China. Its trunk frequently twists during growth, affecting timber quality. The explanation for the twisted-trunk formation is unknown. In this work, we examined the variety of endophytes and metabolites by comparing the straight and twisted trunk types of P. yunnanensis. The results showed that the twisted trunk had a distinct endosymbiont composition compared to the straight trunk. Pseudomonas and Craurococcus bacteria, as well as the fungus taxa Phaeosphaeria and Epichloë, spread significantly more in the twisted trunk compared to the straight trunk. However, there was less Dechloromonas in the twisted trunk. Metabolomic analysis revealed differences in metabolites in the straight and twisted trunks, which were associated with four metabolic pathways: beta-alanine metabolism, metabolism of Jasmonic acid and trans-Zeatin metabolism, linoleic acid metabolism, and pentose phosphate pathway. The compounds were linked to certain endophyte bacteria species. Our findings suggested that the twisted trunk was subjected to more stress than the straight trunk because of endosymbionts. Moreover, we speculated that hormone signal transduction and the absorption, transport, and utilization of phosphorus elements and their interaction with microorganisms may be closely connected to the formation of twists. This is the first study to characterize the microbiome and metabolome in the twisted trunks of P. yunnanensis, and the results enhance our understanding of the underlying causes of twisted-trunk formation in P. yunnanensis. Full article

The effects of nutritional additions on the non-structural carbohydrates (NSCs) of Pinus yunnanensis Franch. following coppicing were examined in this work. Three levels of phosphorous (P) addition, namely P₀ (0 g/plant), P (2 g/plant), and P+ (4 g/plant), and two levels of nitrogen (N) additions, namely N0 (0 g/plant) and N+ (0.6 g/plant) The treatments consisted of D1 (N₀P), D2 (N+P₀), D3 (N₀P), D4 (N+P), D5 (N₀P), and D6 (N+P+), utilizing an orthogonal design to assess how these nutrients influence NSC levels and their components throughout many plant organs in P. yunnanensis. The findings showed that fertilization enhanced NSCs and their components’ contents in P. yunnanensis. P treatment greatly raised NSC levels in sprouts as well as starch (ST) content in stems and sprouts. N treatment greatly raised soluble sugar (SS) and NSC content in stems and greatly accelerated the contents of NSCs and their components in sprouts. The combined application of N and P further improved SS content in stems. Fertilization effects varied over time, with significant increases in NSC content observed at different stages: at 0 d, fertilization significantly raised NSCs and their components in needles; at 90 d, roots and stems showed increases in both NSCs and their components’ contents; at 180 d, stem ST content significantly increased; and at 270 d, NSCs and their components’ contents across all organs were significantly increased. Especially in roots, stems, and sprouts, the combined N (0.6 g/plant) and P (2.0 g/plant) treatment (D4) produced the highest NSC concentration among the treatments. This suggested that NSC formation in plants might be greatly promoted by a balanced N and P fertilization ratio acting in concert. Moreover, fertilizer, as part of a general management plan, has long-term and significant benefits on plant development, especially after coppicing, accelerating recovery, expanding growth potential, and thereby strengthening the plant’s capacity to adapt to environmental changes. Full article

Pinus yunnanensis Franch., one of the pioneer species of wild mountain afforestation in southwest China, plays an essential role in the economy, society and environment of Yunnan Province. Nonetheless, P. yunnanensis’ trunk twisting and bending phenomenon has become more common, which significantly restricts its use and economic benefits. In order to clarify the compositional differences between the straight and twisted trunk types of P. yunnanensis and to investigate the reasons for the formation of twisted stems, the present study was carried out to dissect the macroscopic and microscopic structure of the straight and twisted trunk types of P. yunnanensis, to determine the content of cell wall components (lignin, cellulose, hemicellulose), determine the content of endogenous hormones, and the expression validation of phytohormone-related differential genes (GA2OX, COI1, COI2) and cell wall-related genes (XTH16, TCH4). The results showed that the annual rings of twisted trunk types were unevenly distributed, eccentric growth, insignificant decomposition of early and late wood, rounding and widening of the tracheid cells, thickening of the cell wall, and reduction of the cavity diameter; the lignin and hemicellulose contents of twisted trunk types were higher; in twisted trunk types, the contents of gibberellin (GA) and jasmonic acid (JA) increased, and the content of auxin (IAA) was reduced; the GA2OX were significantly down-regulated in twisted trunk types, and the expressions of the genes associated with the cell wall, COI1, COI2, TCH4 and XTH16, were significantly up-regulated. In conclusion, the present study found that the uneven distribution of endogenous hormones may be an important factor leading to the formation of twisted trunk type of P. yunnanensis, which adds new discoveries to reveal the mechanism of the genesis of different trunk types in plants, and provides a theoretical basis for the genetic improvement of forest trees. Full article

The accurate mapping of age structure and access to spatially explicit information are essential to optimal planning and policy-making for forest ecosystems, including forest management and sustainable economic development. Specifically, surveying and mapping the age structure of forests is crucial for calculating the carbon sequestration capacity of forest ecosystems. However, spatial heterogeneity and limited accessibility make forest age mapping in mountainous areas challenging. Here, we present a new workflow using ICESat-2 LiDAR data integrated with multisource remote sensing imagery to estimate forest age in Shangri-La, China. Two methods—a climate-driven exponential model and a random forest algorithm—are compared to infer the age structure of the five dominant species in Shangri-La. The climate-driven model, with an R² of 0.67 and an RMSE of 12.79 years, outperforms the random forest model. The derived wall-to-wall forest age map at 30 m resolution reveals that nearly all forests in Shangri-La are mature or overmature, especially among the high-elevation species Abies fabri (Mast.) Craib and Picea asperata Mast., compared with Pinus yunnanensis Franch., Quercus aquifolioides Rehd. and E.H. Wils. and Pinus densata Mast., where the age structure is more evenly distributed across different elevation ranges. Younger forests are frequently found around human settlements and along the Jinsha River valley, whereas older forests are located in remote and high-elevation areas that are less disturbed. The combined use of active and passive remote sensing data has resulted in substantial improvements in the spatial detail and accuracy of wall-to-wall age mapping, which is expected to be a cost-effective approach for supporting forest management and carbon accounting in this important ecological region. The method developed here can be scaled to other mountain areas both to understand the age patterns and structure of mountain forests and to provide critical information for forestation, reforestation and carbon accounting in surface-to-high mountain areas, which are increasingly crucial for climate mitigation. Full article

Multiplatform fusion point clouds can effectively compensate for the disadvantages of individual platform point clouds in forest parameter extraction, maximizing the potential of LiDAR technology. However, existing registration algorithms often suffer from insufficient feature extraction and limited registration accuracy. To address these issues, we propose a ULS (Unmanned Aerial Vehicle Laser Scanning)-TLS (Terrestrial Laser Scanning) point cloud data registration method based on Similar Distance Search (SDS). This method enhances coarse registration by accurately retrieving points with similar features, leading to high overlap in the rough registration stage and further improving fine registration precision. (1) The proposed method was tested on four natural forest plots, including Pinus densata Mast., Pinus yunnanensis Franch., Pices asperata Mast., Abies fabri (Mast.) Craib, and demonstrated high registration accuracy. Both coarse and fine registration achieved superior results, significantly outperforming existing algorithms, with notable improvements over the TR algorithm. (2) In addition, the study evaluated the accuracy of individual tree parameter extraction from fusion point clouds versus single-platform point clouds. While ULS point clouds performed slightly better in some metrics, the fused point clouds offered more consistent and reliable results across varying conditions. Overall, the proposed SDS method and the resulting fusion point clouds provide strong technical support for efficient and accurate forest resource management, with significant scientific implications. Full article

Pinus yunnanensis (Franch), a species endemic to southwestern China, provides significant ecological and economic benefits. The quality of afforestation can be enhanced by promoting high-quality sprout growth. This study analyzed the effects of six fertilization treatments following top pruning: T1 (N: 0 g/plant⁻¹; P: 0 g/plant⁻¹), T2 (N: 0 g/plant⁻¹; P: 2 g/plant⁻¹), T3 (N: 0 g/plant⁻¹; P: 4 g/plant⁻¹), T4 (N: 0.6 g/plant⁻¹; P: 0 g/plant⁻¹), T5 (N: 0.6 g/plant⁻¹; P: 2 g/plant⁻¹), and T6 (N: 0.6 g/plant⁻¹; P: 4 g/plant⁻¹). The accumulation and allocation of aboveground biomass in roots, stems, and leaves of P. yunnanensis were measured, as well as changes in biomass per plant at 90 days (early stage), 180 days (middle stage), and 270 days (late stage) post-fertilization. At 90 days, root biomass accumulation in T3 was significantly higher, by 13.31%, compared to that in T1 (p < 0.05). The growth rates of stem and plant biomass followed the order T6 > T1 > T3 > T5 > T4 > T2. The biomass of sprouts and individual plants exhibited allometric growth under T1, T5, and T6 treatments. At 180 days, needle biomass allocation in T1 and T4 increased by 7.47% and 8.6%, respectively, compared to 90 days. Combined nitrogen–phosphorus fertilization significantly influenced aboveground biomass allocation, promoting growth more effectively than other treatments. By 270 days, the stem and individual biomass in T2 and T3 treatments showed significant differences (p < 0.01) compared to other treatments. Overall, root, stem, and sprouts were primarily influenced by phosphorus fertilization, while nitrogen fertilization notably promoted needle and leaf growth in later stages. The aboveground components were more affected by phosphorus fertilization. The combination of nitrogen and phosphorus fertilizers enhanced early-stage stem and sprouts, as well as late-stage root development. Full article

Southwestern China is a critical biodiversity hotspot area, and many large hydroelectric projects have been established in the valleys in the region. Tree growth in the valleys will be affected by both regional climate and reservoir impoundment. However, it remains unknown whether the radial growth of trees in the valleys has a common response pattern to the regional climate, and it is also unclear whether the response of radial growth to reservoir impoundment can be detected. In this study, we developed tree-ring width chronologies of Pinus yunnanensis Franch. collected at 11 sites with vertical and horizontal gradients to three hydroelectric reservoirs in three riverine valleys in southwestern China. We analyzed the radial growth responses to the regional climate from 1986 to 2017 by correlation with instrumental meteorological data. Tree growth responses to reservoir impoundment were investigated through spatial and temporal comparisons using the change in the Euclidean distance and difference test. We also distinguished their responses at tree-ring sites without influenced by reservoir impoundment including two sites in the valleys and seven sites at high elevations. The results showed that the climate conditions in May and the dry season before the growth season significantly limit the radial growth in the valleys, which is different to that at high-elevation areas in southwestern China. Growth variations in the valleys are related to elevations and the trees in similar slopes positions exhibit similar responses. For trees in the low slope positions, both variance and mean values of radial growth are affected by reservoir impoundment. Trees at relatively low sites (i.e., sites M2, R2, L2), rather than the trees close to the reservoirs (i.e., sites M1, R1, L1), respond more sensitively to reservoir impoundment. Full article

Prescribed burning is a widely used fuel management employed technique to mitigate the risk of forest fires. The Pinus yunnanensis Franch. forest, which is frequently prone to forest fires in southwestern China, serves as a prime example for investigating the effects of prescribed burning on the flammability of surface dead fuel. This research aims to establish a scientific foundation for managing dead fuel in forests, as well as fire prevention and control strategies. Field data was collected from P. yunnanensis forests located in central Yunnan Province in 2021 and 2022. The study implemented a randomized complete block design with two blocks and three treatments: an unburned control (UB), one year after the prescribed burning (PB1a), and three years after the prescribed burning (PB3a). These treatments were evaluated based on three indices: surface dead-bed structure, physicochemical properties, and potential fire behavior parameters. To analyze the stand characteristics of the sample plots, a paired t-test was conducted. The results indicated no significant differences in the stand characteristics of P. yunnanensis following prescribed burning (p > 0.05). Prescribed burning led to a significant decrease in the average surface dead fuel load from 10.24 t/ha to 3.70 t/ha, representing a reduction of 63.87%. Additionally, the average fire−line intensity decreased from 454 kw/m to 190 kw/m, indicating a decrease of 58.15%. Despite prescribed burning, there were no significant changes observed in the physical and chemical properties of dead fuels (p > 0.05). However, the bed structure of dead fuels and fire behavior parameters exhibited a significant reduction compared with the control sample site. The findings of this study provide essential theoretical support for the scientific implementation of prescribed burning programs and the accurate evaluation of ecological and environmental effects post burning. Full article

Pinus densata Mast. is considered a homoploid hybrid species that originated from the putative parent species Pinus tabuliformis Carr. and Pinus yunnanensis Franch., but the mechanism of the adaptive differentiation of P. densata and its parents in native habitats has not been reported. Therefore, the overlapping distribution areas between P. densata and P. yunnanensis in the heart of the Hengduan Mountains were chosen. The adaptive differentiation mechanism of the homoploid hybrids and their parents with respect to the elevational gradient was studied based on the morphological features and the different strategies of recruiting endophytic microbial communities from the rhizosphere soil. The results showed that (1) the height and diameter at breast height were the greatest at 2600 m and 2900 m, and from 2700 m to 2900 m, three-needle pines (P. yunnanensis-like type) transitioned into two-needle pines (P. densata-like type). (2) The recruitment of rhizosphere microbial communities was driven by the C, N, P and pH values which showed significant elevation features. (3) There was a significant difference in the recruitment strategies of endophytes between the P. yunnanensis-like type and P. densata-like type. Pinus densata mainly reduced the recruitment of Mucoromycota (fungi) and increased the recruitment of Proteobacteria (bacteria), which may be related to environmental adaptability, quorum sensing and the metabolism of auxiliary factors and vitamins at high elevations. (4) The root endophytic microbiome was enriched in the rare groups from the rhizosphere soil microbial pool. The results of this study provide new insights and new ideas for environmental adaptability and differentiation in homoploid hybrid speciation. Full article

Volatile oils in forest fuel can significantly affect forest fire behavior, especially extreme fire behavior, e.g., deflagration, fire storms, blowups, eruptive fires and crown fires. However, how these oils influence fire behavior remains unclear, as few qualitative studies have been performed globally. In the present study, we compared the volatile oil contents and components in live branches and surface dead fuel of Pinus yunnanensis Franch, which is widely distributed in Southwest China, to explore their potential effects on extreme fire behavior. Fifteen samples of live branches and fifteen samples of surface dead fuel were collected. Volatile oils were extracted from the samples using steam distillation, and their components were identified and analyzed using gas chromatography–mass spectrometry (GC-MS). The results show that the volatile oil content in live branches was as high as 8.28 mL·kg⁻¹ (dry weight) and was significantly higher than that in surface dead fuel (3.55 mL·kg⁻¹). The volatile oil content in the P. yunnanensis forest was 126.12 kg per hectare. The main volatile oil components were terpenoids, of which monoterpenes accounted for the highest proportion based on their content (62.63%), followed by sesquiterpenes (22.44%). The terpenoid compounds in live branches were more abundant than those in surface dead fuel. Monoterpenes and sesquiterpenes in volatile oils in forest fuel have low boiling points, high calorific values and a lower explosion limit (LEL; 38.4 g·m⁻³), which are important characteristics in the manifestation of extreme fire behavior such as deflagration. The analysis results indicate that when heated, the oily gases from P. yunnanensis forest could fill 3284.26 m³ per hectare, with a gas concentration reaching the LEL. We conclude that volatile oil in P. yunnanensis has an important influence on the manifestation of extreme fire behavior, and live branches have a greater effect than surface dead fuel. Full article

It remains challenging to control Tomicus spp., a pest with fast spreading capability, leading to the death of large numbers of Pinus yunnanensis (Franch.) and posing a severe threat to ecological security in southwest China. Therefore, it is crucial to effectively and accurately monitor the damage degree for Pinus yunnanensis attacked by Tomicus spp. at large geographical scales. Airborne hyperspectral remote sensing is an effective, accurate means to detect forest pests and diseases. In this study, we propose an innovative and precise classification framework to monitor the damage degree of Pinus yunnanensis infected by Tomicus spp. using hyperspectral UAV (unmanned aerial vehicle) imagery with machine learning algorithms. First, we revealed the hyperspectral characteristics of Pinus yunnanensis from a UAV-based hyperspectral platform. We obtained 22 vegetation indices (VIs), 4 principal components, and 16 continuous wavelet transform (CWT) features as the damage degree sensitive features. We classified the damage degree of Pinus yunnanensis canopies infected by Tomicus spp. via three methods, i.e., discriminant analysis (DA), support vector machine (SVM), and backpropagation (BP) neural network. The results showed that the damage degree detected from the BP neural network, combined with 16 CWT features, achieved the best performance (training accuracy: 94.05%; validation accuracy: 94.44%). Full article