Search Results (15)

Dioryctria Zeller, 1846 (Lepidoptera: Pyralidae) is a significant genus whose species primarily infest coniferous trees and are predominantly distributed across the Northern Hemisphere. To date, 17 species within this genus have been recorded in China. This study reports the discovery of Dioryctria simplicella (Heinemann, 1863) in China. During field surveys in forests of Heilongjiang Province, D. simplicella was observed infesting the cones and trunks of Pinus sylvestris var. mongolica Litv. as larvae. Comprehensive morphological descriptions and diagnostic characteristics of the adult, larva, pupa, and egg stages of D. simplicella are provided herein to facilitate accurate species identification within the genus. Molecular phylogenetic analysis based on mitochondrial cytochrome c oxidase subunit I (COI) DNA barcoding sequences was conducted to assess the phylogenetic position of D. simplicella within Dioryctria. These results strongly support its species identity and clarify its phylogenetic relationships with congeners. This discovery not only expands the known diversity of Lepidoptera in China but also provides new data supporting taxonomic and phylogenetic studies of the genus Dioryctria. Full article

Soil microorganisms are crucial in global biogeochemical cycles, impacting ecosystems’ energy flows and material cycling. This study, via high-throughput sequencing in four forests—the original Larix gmelinii (Rupr.) Kuzen. forest (LG), the conifer–broad-leaved mixed Pinus sylvestris var. mongolica Litv. forest (PS), the original pure Betula platyphylla Sukaczev forest (BP), and the original pure Populus L. forest (PL) in Shuanghe National Nature Reserve, Daxing’anling mountains—explored soil microbial community structures and diversities. The results indicated that the BP and PL forests had the lowest soil bacterial ACE and Chao1 indices, and the original pure birch forest’s Shannon index was higher than that of the poplar forest. The soil’s fungal Chao1 index of the birch forest was higher than that of the larch forests. Bradyrhizobium and Roseiarcus were the dominant soil bacterial genera; the dominant soil fungal genera were Podila, Russula, and Sebacina. RDA and mantel analyses indicated that soil microbial community structures varied across forest types mainly because of the effective phosphorous and pH levels, soil’s total nitrogen level, and available phosphorus level. This study offers a scientific foundation for cold-temperate-forest ecosystem management regarding soil microbial diversity and community structural changes in different forest types. Full article

Tree species are important factors affecting the carbon sequestration capacity of forests and maintaining the stability of ecosystems, but trees are widely distributed spatially and located in complex environments, and there is a lack of large-scale regional tree species classification models for remote sensing imagery. Therefore, many studies aim to solve this problem by combining multivariate remote sensing data and proposing a machine learning model for forest tree species classification. However, satellite-based laser systems find it difficult to meet the needs of regional forest species classification characters, due to their unique footprint sampling method, and SAR data limit the accuracy of species classification, due to the problem of information blending in backscatter coefficients. In this work, we combined Sentinel-1 and Sentinel-2 data to construct a machine learning tree classification model based on optical features, vegetation spectral features, and PolSAR polarization observation features, and propose a forest tree classification feature selection method featuring the Hilbert–Huang transform for the problem of mixed information on the surface of SAR data. The PSO-RF method was used to classify forest species, including four temperate broadleaf forests, namely, aspen (Populus L.), maple (Acer), peach tree (Prunus persica), and apricot tree (Prunus armeniaca L.), and two coniferous forests, namely, Chinese pine (Pinus tabuliformis Carrière) and Mongolian pine (Pinus sylvestris var. mongolica Litv.). In this study, some experiments were conducted using two Sentinel-1 images, four Sentinel-2 images, and 550 measured forest survey sample data points pertaining to the forested area of Fuxin District, Liaoning Province, China. The results show that the fusion model constructed in this study has high accuracy, with a Kappa coefficient of 0.94 and an overall classification accuracy of 95.1%. In addition, this study shows that PolSAR data can play an important role in forest tree species classification. In addition, by applying the Hilbert–Huang transform to PolSAR data, other feature information that interferes with the perceived vertical structure of forests can be suppressed to a certain extent, and its role in the classification of forest species, combined with PolSAR, should not be ignored. Full article

The accurate assessment of forest biomass is vital to climate change mitigation. Based on forest survey data, stand biomass models can effectively assess forest biomass carbon at large scales. However, traditional stand biomass models have ignored the potential effects of the climate on stand biomass estimation. There is still a lack of research on whether or not and in what ways the effects of the climate reduce uncertainty in biomass estimation and carbon accounting. Therefore, two types of stand biomass models, including basic stand biomass models (BBMs) and climate-sensitive stand biomass models (CBMs), were developed and tested using 311 plantation plots of Korean pine (Pinus koraiensis Siebold & Zucc.), Korean larch (Larix olgensisi A. Henry), and Mongolian pine (Pinus sylvestris var. mongolica Litv.) in Northeast China. The two types of models were developed by applying simultaneous equations based on nonlinear, seemingly unrelated, regression (NSUR) to ensure additivity of the stand total and components biomass (root, stem, branch, and needle). The results of fitting and leave-one-out cross-validation (LOOCV) indicated that the CBMs performed better than the corresponding BBMs. The RMSEs of the stand total biomass decreased by 3.5% to 10.6% for the three conifer species. The influence of temperature-related climate variables on the biomass of stand components was greater than that of precipitation-related climate variables. The sensitivity of the three conifer species to climate variables was ranked as Korean pine > Mongolian pine > Korean larch. This study emphasizes the importance of combining climate variables in stand biomass models to reduce the uncertainty and climate effects in forest biomass estimation, which will play a role in carbon accounting for forest ecosystems. Full article

Afforestation is conducive to improving ecosystem service functions and ecosystem diversity in the Mu Us Sandy Land, however, the important attribute of biomass for Mongolian pine (Pinus sylvestris var. mongolica Litv.) plantations has yet to be accurately evaluated. This study aimed to develop additive allometric biomass equations for the species and evaluate biomass partitioning patterns within tree components. A total of 131 trees were measured for stem, branch, and leaf biomass by destructively sampling and tree climbing, with the latter as a supplement. For each biomass component, we tested three equations with the diameter at breast (D) alone, height (H) as additional, and diameter in combination with height (D²H) as predictors using the weighted least squared method. Weighted nonlinear seemingly unrelated regression was adopted to fit a system of additive allometric biomass equations utilizing the selected equations. A leave-one-out cross-validation method (the jackknife procedure) was used to assess the predictive ability. The biomass partitioning pattern was evaluated by calculating the ratios. The results revealed that the diameter alone is a good predictor for branches and foliage biomass estimates, while the stem requires H included to improve estimation accuracy. Mongolian pine allocates relatively more biomass to the crown (51.4%) compared to the stem (48.6%). Branch biomass fraction increased monotonously with increasing tree size while a reverse trend was observed for foliage. In conclusion, the additive models developed in this study provide a robust biomass estimation and can be extensively used to estimate Mongolian pine forests biomass in Mu Us Sandy Land. Full article

Forest-canopy closure (FCC) reflects the coverage of the forest tree canopy, which is one of the most important indicators of forest structure and a core parameter in forest resources investigation. In recent years, the rapid development of UAV LiDAR and photogrammetry technology has provided effective support for FCC estimation. However, affected by factors such as different tree species and different stand densities, it is difficult to estimate FCC accurately based on the single-tree canopy-contour method in complex forest regions. Thus, this study proposes a method for estimating FCC accurately using algorithm integration with an optimal window size for treetop detection and an optimal algorithm for crown-boundary extraction using UAV LiDAR data in various scenes. The research results show that: (1) The FCC estimation accuracy was improved using the method proposed in this study. The accuracy of FCC in a camphor pine forest (Pinus sylvestris var. mongolica Litv.) was 89.11%, with an improvement of 6.77–11.25% compared to the results obtained from other combined conditions. The FCC accuracy for white birch (White birch platyphylla Suk) was about 87.53%, with an increase of 3.25–8.42%. (2) The size of the window used for treetop detection is closely related to tree species and stand density. With the same forest-stand density, the treetop-detection window size of camphor pine was larger than that of white birch. The optimal window size of camphor pine was between 5 × 5~11 × 11 (corresponding 2.5~5.5 m), while that of white birch was between 3 × 3~7 × 7 (corresponding 1.5~3.5 m). (3) There are significant differences in the optimal-canopy-outline extraction algorithms for different scenarios. With a medium forest-stand density, the marker-controlled watershed (MCW) algorithm has the best tree-crown extraction effect. The region-growing (RG) method has better extraction results in the sparse areas of camphor pine and the dense areas of white birch. The Voronoi tessellation (VT) algorithm is more suitable for the dense areas of camphor pine and the sparse regions of white birch. The method proposed in this study provides a reference for FCC estimation using high-resolution remote-sensing images in complex forest areas containing various scenes. Full article

The relationships between free shrinkage and actual shrinkage of different layers in Mongolian Scotch pine (Pinus sylvestris var. mongolica Litv.) were explored to provide basic data for the further study of drying shrinkage properties. The free shrinkage coefficients at different temperatures and the actual shrinkage strain of each layer were examined under conventional drying. The results showed high precision of free drying shrinkage of corresponding layers of thin small test strips in each layer of sawn timber. The free shrinkage increased linearly as moisture content declined. At the same temperature, the free shrinkage coefficient reached the largest values for the first layer (above 0.267%), while the smallest values were recorded for the ninth layer (below 0.249%). Except for the ninth layer, the free shrinkage coefficients in width directions of other representative layers decreased as temperature increased. At constant temperature, the difference in free shrinkage coefficient of test materials in the length direction of sawn timber was small for the first layer, but slightly larger and changed irregularly in the fifth and ninth layer direction. At the end of conventional drying, the plastic deformation of each layer in the early stage of drying showed a reducing trend or even reversal due to the effects of reverse stress and later damp heat. In sum, these findings look promising for future optimization of wood drying process. Full article

Background and Objectives: More frequent and severe droughts are occurring due to climate change in northern China. In addition to intensity and duration, the timing of droughts may be decisive for its impacts on tree growth, mortality, and the whole forest ecosystem. The aim of this study was to compare the effect of drought occurring in the early- and mid-growing season on the growth and physiology of Mongolian pine (Pinus sylvestris var. mongolica Litv.) saplings. Materials and Methods: Four-year-old container saplings that were about to sprout were exposed to three treatments: (i) regular irrigation throughout the growing season (CTRL), (ii) no irrigation in the early growing season (weeks 1–5) followed by regular irrigation (EGD), (iii) no irrigation in the mid growing season (weeks 5–10), and regular irrigation in the early and late growing season (MGD). We measured the root and shoot growth, sapling mortality, and the physiological changes in the roots and needles periodically. Results: Drought in the mid growing season was more harmful than in the early growing season in terms of chlorophyll fluorescence, electrolyte leakage of needles, needle length, stem diameter increment, and sapling mortality. The high mortality in the mid growing season might be attributed to the joint effect of drought and high temperature. Drought in the early growing season decreased root growth, and the starch and soluble sugars in roots as much as the drought in the mid growing season. Abscisic acid concentration increased in fine roots, but decreased in old needles after drought. Conclusions: Special attention should be paid on forest sites susceptible to drought during afforestation in the face of ongoing climate change. Full article

In this study, we developed dynamic top height growth models for the eight important Chinese tree species Larix gmelinii var. principis-rupprechtii, Pinus tabuliformis Carr., Pinus sylvestris var. mongolica Litv., Picea asperata Mast., Quercus mongolica Fisch. ex Ledeb, Betula platyphylla Suk., Betula dahurica Pall. and Populus davidiana Dode based on age-height relationships. For this purpose, commonly growth data from long-term observations of permanent experimental plots are used, which ideally cover all development stages from stand establishment to final harvest. As such data were not available in the research area of Hebei Province in Northeast China, we used stem analysis data as well as tree height and annual shoot length measurements. The dataset consisted of 72 stands, 233 dominant trees and 10,195 observations of stem discs and annual shoot length measurements. Five dynamic base-age invariant top height growth models were derived from four base models with the generalized algebraic difference approach and fitted to our age-height data using nested regression techniques. According to biological plausibility and model accuracy the Chapman–Richards model showed the best performance for Picea asperata. This selected model accounted for 99% of the total variance in age-height relationship with average absolute bias of 0.2322 m, root mean square error of 0.3337 m and ${\mathrm{R}}_{\mathrm{adj}}^2$ of 0.9979, respectively. The distribution of the residuals was scattered around 0 and without visible trends, indicating that the fitness of the models was good. All developed models are able to generate top height growth curves representing the analyzed height growth data and can be utilized for predicting height growth on the base of current height and age of dominant trees. Additionally, they are the base for calculating the development of other relevant stand attributes such as basal area and volume growth. The determination of potential site productivity by the use of top height growth curves is a practical and convenient method for a simplified presentation of complex growth processes in stands and helps to create growth models, which facilitate implementing sustainable forest management practices in Mulan Forest. Full article

Vegetation coverage is very important in terrestrial ecosystems and climate systems. However, the observational record of the normalized difference vegetation index (NDVI), which started in the 1980s when satellites became widely used, is too short to investigate the history of variation in vegetation coverage beyond the modern observation period. Here, we present a 189 y vegetation coverage series based on a total of 349 Mongolian pine (Pinus sylvestris var. mongolica Litv) cores from seven locations from the central–western Da Hinggan Mountains (CW–DHM), northeastern China. We found a significant relationship between tree-ring width and the regional cumulative normalized difference vegetation index (CNDVI). The correlation between the ring-width chronology and the regional June–July CNDVI (CNDVI_JJ) was significant, with r = 0.68 (n = 32, p < 0.001) and an explained variance of 45.8% (44.0% after the adjustment for the loss of the degree of freedom). On this basis, we designed a transfer function to reconstruct the CNDVI_JJ for the CW–DHM region from 1825 to 2013 CE (Common Era). During the last 189 years, there were 28 years with high CNDVI_JJ values, and another 28 years with low values. We also observed CNDVI_JJ fluctuations at the inter-annual and decadal time scales, including eight low value periods and nine high value periods. Based on our analysis, the variation in CNDVI is associated with climatic factors, such as temperature, precipitation and the Palmer Drought Severity Index (PDSI), which combines both temperature and precipitation. From 1950 to 2002 CE, the CNDVI showed a noticeable decreasing trend in the CW–DHM region, whereas after 2003 CE, the CNDVI exhibited an apparent increase, which has also been observed in southern Central Siberia, eastern Mongolia and northeastern and eastern China, indicating that the CNDVI change in the CW–DHM is related to climate change in the local region and in some parts of Asia. Full article

Sirex noctilio F. (Hymenoptera: Siricidae) is an invasive woodwasp from Europe and North Africa. Globalization has led to an expanding global presence in pine forests. S. noctilio has been previously introduced outside of its native range and now co-occurs in trees with native S. nitobei Matsumura (first discovered in 2016). Damage to Pinus sylvestris var. mongolica Litv in northeast China can be attributed to two types of woodwasp. To distinguish the two species by the traditional taxonomic morphology, we mainly differentiate the color of the male’s abdomen and the female’s leg. There remains intraspecific variation like leg color in the delimitation of related genera or sibling species of Sirex woodwasps. In this study, we used landmark-based geometric morphometrics including principal component analysis, canonical variate analysis, thin-plate splines, and cluster analysis to analyze and compare the wings, ovipositors, and cornus of two woodwasps to ascertain whether this approach is reliable for taxonomic studies of this group. The results showed significant differences in forewing venation and the shapes of pits in the middle of ovipositors among the two species, whereas little difference in hindwings and cornus was observed. This study assists in clarifying the taxonomic uncertainties of Siricidae and lays a foundation for further studies of the interspecific relationships of the genus Sirex. Full article

Determining plant–water relationships in response to drought events can provide important information about the adaptation of trees to climate change. The Mongolian Scots pine (Pinus sylvestris var. mongolica Litv), as one of the major tree species to control soil loss and desertification in northern China, has experienced severe degradation in recent decades. Here, we aimed to examine the impacts of a two-year consecutive drought and another year of drought on the radial growth, transpiration, and canopy stomatal conductance of Mongolian Scots pine over a five-year period, especially in terms of its recovery after drought. The study period during 2013–2017 consisted of a ‘normal’ year, a ‘dry year’, a ‘very dry’ year, a ‘wet’ year, and a ‘dry’ year, according to annual precipitation and soil moisture conditions. Based on measurements of the sap flow and diameters at breast height of 11 sample trees as well as the concurrent environmental factors, we quantified the reductions in tree radial growth, transpiration, and canopy stomatal conductance during the drought development as well as their recovery after the drought. The results showed that the tree radial growth, transpiration, and canopy stomatal conductance of Mongolian Scots pines decreased by 33.8%, 51.9%, and 51.5%, respectively, due to the two consecutive years of drought. Moreover, these reductions did not fully recover after the two-year drought was relieved. The minimum difference of these parameters between before and after the two-year consecutive drought period was 8.5% in tree radial growth, 45.1% in transpiration levels, and 42.4% in canopy stomatal conductance. We concluded that the two consecutive years of drought resulted in not only large reductions in tree radial growth and water use, but also their lagged and limited recoveries after drought. The study also highlighted the limited resilience of Mongolian Scots pine trees to prolonged drought in semi-arid sandy environmental conditions. Full article

Drought and topographic position are the most important factors influencing tree growth and survival in semiarid sandy regions of Northeast China. However, little is known about how trees respond to drought in combination with topographic position by modifying the depth of soil water extraction. Therefore, we identified water sources for 33-year-old Mongolian pine (Pinus sylvestris L. var. mongolica Litv.) trees growing at the top and bottom of sand dunes by comparing stable isotopes δ²H and δ¹⁸O in twig xylem water, soil water at various depths and groundwater during dry and wet periods. Needle carbon isotope composition (δ¹³C) was simultaneously measured to assess water use efficiency. Results showed that when soil moisture was low during the dry period, trees at the top used 40–300 cm soil water while trees at the bottom utilized both 40–300 cm soil water and possibly groundwater. Nevertheless, when soil moisture at 0–100 cm depth was higher during the wet period, it was the dominant water sources for trees at both the top and bottom. Moreover, needle δ¹³C in the dry period were significantly higher than those in the wet period. These findings suggested that trees at both the top and bottom adjust water uptake towards deeper water sources and improve their water use efficiency under drought condition. Additionally, during the dry period, trees at the top used shallower water sources compared with trees at the bottom, in combination with significantly higher needle δ¹³C, indicating that trees at the bottom applied a relatively more prodigal use of water by taking up deeper water (possibly groundwater) during drought conditions. Therefore, Mongolian pine trees at the top were more susceptible to suffer dieback under extreme dry years because of shallower soil water uptake and increased water restrictions. Nevertheless, a sharp decline in the groundwater level under extreme dry years had a strong negative impact on the growth and survival of Mongolian pine trees at the bottom due to their utilization of deeper water sources (possibly groundwater). Full article

The Mongolian pine (Pinus sylvestris L. var. mongolica Litv.) was first introduced to the southeastern Horqin sandy land in the mid-1950s. Since then, it has been widely planted and has become the most important conifer species in Northern China, providing significant ecological, economic and social benefits. However, its function in sequestering carbon at different developmental stages has been little studied. In this study, twenty plots inventory and destructive sampling of eight trees were conducted in 12-, 19-, 34-, 48- and 58-year-old Mongolian pine stands of China. Allometric biomass equations (ABEs) for tree components were established and used to determine the magnitude and distribution of tree biomass and carbon density. The carbon density of the understory, forest floor and soil was also determined. The ABEs with age as the second variable could simply and accurately determine the biomass of plantation tree branches, foliage and fruit, which were considerably influenced by age. With increasing stand age, the proportion of stem biomass to total tree biomass increased from 22.2% in the 12-year-old stand to 54.2% in the 58-year-old stand, and the proportion of understory biomass to total ecosystem biomass decreased, with values of 7.5%, 4.6%, 4.4%, 4.1% and 3.0% in the five stands. The biomass of the forest floor was 0.00, 1.12, 2.04, 6.69 and 3.65 Mg ha⁻¹ in the five stands. The ecosystem carbon density was 40.2, 73.4, 92.9, 89.9 and 87.3 Mg ha⁻¹ in the 12-, 19-, 34-, 48-, and 58-year-old stands, in which soil carbon density accounted for the largest proportion, with values of 67.4%, 76.8%, 73.2%, 63.4%, and 57.7% respectively. The Mongolian pine had the potential for carbon sequestration during its development, especially in the early stages, however, in the later growth stage, the ecosystem carbon density decreased slightly. Full article

Yeast extract, which is environmentally friendly, nutritious, and convenient to use, has advantages over common plant growth regulators and soil conditioners. It is worth verifying the effect of the application of yeast extract to afforestation in a semiarid chestnut soil area. This study was conducted through a wild field afforestation experiment in Inner Mongolia, northern China. We designed an orthogonal experiment of 25 treatments with 30 repetitions on Pinus sylvestris(Pinus sylvestris var. mongolica Litv.) sand Armeniaca sibirica（Armeniaca sibirica (L.) Lam）. Three factors with different levels were considered: application to rhizosphere soil with the amounts of 0 g, 10 g, 20 g, 30 g, and 40 g; foliar spraying with concentrations of 0%, 0.5%, 1%, 1.5%, and 2%; and spraying at three moments. The results showed that yeast extract could enhance the seedlings of Pinus sylvestris and Armeniaca sibirica. When applying 40 g of yeast extract, the survival rates and root parameters were significantly boosted. Foliar spraying plays an important role in promoting the growth of seedlings. It was most effective for the two species to be sprayed with a concentration of 2% after leafing of the seedlings. The data also revealed that the application of yeast extract improved the properties of the rhizosphere soil. The porosities and moisture contents were increased, and the bulk densities were reduced. Forty grams (40 g) was the best amount to apply, especially for the soil at 20–40 cm where the seedling roots are mainly located. The chemical properties were also improved, as there was a significant increase in the conductivities, organic matter, nitrogen, and phosphorus as well as a slight reduction in the calcium carbonate content and pH. Therefore, yeast extract has a beneficial effect on both seedling growth promotion and soil improvement. It is considered to be an environmentally efficient method for afforestation and ecological remediation in semiarid chestnut soil areas. Full article