Forests, Volume 15, Issue 6 (June 2024) – 88 articles

Diversified soil microbiomes are the key drivers of carbon fixation and plant residue decomposition in forest ecosystems. Revealing the elevation patterns of soil microbial carbon cycling in forests is essential for utilization of forest ecological resources. However, the soil microbial diversity and carbon cycle processes in Platycladus orientalis plantations across different elevations are still unclear. Here, we established a gradient with three elevations (118 m, 300 m, and 505 m) on the Beijing Ming Dynasty Tombs Forest Farm, which is located in Changping District, Beijing. The metagenomics method was applied to study the soil microbiome, with a special focus on the carbon cycle process at each elevation. We found the diversity and composition of the soil microbiomes significantly varied across the elevation gradients. The structure of bacteria and archaea was mainly driven by soil total potassium, pH and NH₄⁺, but the eukaryota had no significant relationship with the environmental factors. The relative abundance of genes involved in microbial carbon fixation and decomposition of organic carbon were also significantly impacted by elevation, with the former showing increasing, u-shaped, or hump trends with increasing elevation, but the latter only showing hump trends. The rTCA cycle and 3-hydroxypropionate pathway were the dominant carbon fixation pathways in the Platycladus orientalis plantations. The elevation gradient shaped the microbial decomposition of plant-derived organic carbon by changing soil properties and, furthermore, led to soil organic carbon stock losses. These findings increase our understanding of soil microbial diversity and the carbon cycle across different elevations and provide a theoretical basis for the utilization of forest ecological resources to promote carbon sequestration. Full article

This study introduced a novel two-step treatment to enhance the waterproofing, dimensional stability, and self-cleaning capabilities of ancient architectural wood. The process was initiated with the immersion of wood in an organic hybrid sol, composed of an acidic methyltrimethoxysilane (MTMS)-based silica sol and polyvinyl alcohol (PVA), which effectively sealed the wood’s inherent pores and cracks to mitigate degradation effects caused by aging, fungi, and insects. Subsequently, the treated wood surface was modified with an alkaline MTMS-based silica sol to form a functional superhydrophobic protective layer. The modification effectiveness was meticulously analyzed using advanced characterization techniques, including scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), Fourier-transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). The results demonstrated substantial improvements: the modified wood’s water contact angle (WCA) reached 156.0°, and the sliding angle (SA) was 6.0°. Additionally, the modified wood showed a notable reduction in water uptake and moisture absorption, enhancing its dimensional stability. The superhydrophobic surface endowed the wood with excellent self-cleaning properties and robust resistance to pollution. Enhanced mechanical durability of superhydrophobic surface was observed under rigorous testing conditions, including sandpaper abrasion and tape peeling. Furthermore, the modification improved the thermal stability, compressive strength, and storage modulus of the wood. Collectively, these enhancements render this modification a potent methodology for the preservation and functional augmentation of historic architectural woodwork. Full article

Diameter at breast height (DBH) is a unique attribute used to characterize forest growth and development for forest management planning and to understand forest ecology. Forest managers require an array of DBHs of forest stands, which can be reconstructed using selected probability distribution functions (PDFs). However, there is a lack of practices that fit PDFs of sub-dominating species grown in natural mixed forests. This study aimed to fit PDFs and develop predictive models for PDF parameters, so that the predicted distribution would represent dynamic forest structures and compositions in mixed forest stands. We fitted three of the simplest forms of PDFs, log-normal, gamma, and Weibull, for the DBH of eight tree species, namely balsam fir (Abies balsamea [L.] Mill.), eastern white pine (Pinus strobus L.), paper birch (Betula papyrifera Marshall), red maple (Acer rubrum L.), red pine (Pinus resinosa Aiton), trembling aspen (Populus tremuloides Michx), and white spruce (Picea glauca [Moench] Voss), all grown in natural-origin mixed forests in Ontario province, Canada. We estimated the parameters of the PDFs as a function of DBH mean and standard deviation for these species. Our results showed that log-normal fit the best among the three PDFs. We demonstrated that the predictive model could estimate the recovered parameters unbiasedly for all species, which can be used to reconstruct the DBH distributions of these tree species. In addition to prediction, the cross-validated R² for the DBH mean ranged between 0.76 for red maple and 0.92 for red pine. However, the R² for the regression of the standard deviation ranged between 0.00 for red pine and 0.69 for sugar maple, although it produced unbiased predictions and a small mean absolute bias. As these mean and standard deviations are regressed with dynamic covariates (such as stem density and stand basal area), in addition to climate and static geographic variables, the predicted DBH distribution can reflect change over time in response to management or any type of disturbance in the regime of the given geography. The predictive model-based DBH distributions can be applied to the design of appropriate silviculture systems for forest management planning. Full article

To address issues of detail loss, limited matching datasets, and low fusion accuracy in infrared/visible light fire image fusion, a novel method based on the Generative Adversarial Network of Wavelet-Guided Pooling Vision Transformer (VTW-GAN) is proposed. The algorithm employs a generator and discriminator network architecture, integrating the efficient global representation capability of Transformers with wavelet-guided pooling for extracting finer-grained features and reconstructing higher-quality fusion images. To overcome the shortage of image data, transfer learning is utilized to apply the well-trained model to fire image fusion, thereby improving fusion precision. The experimental results demonstrate that VTW-GAN outperforms the DenseFuse, IFCNN, U2Fusion, SwinFusion, and TGFuse methods in both objective and subjective aspects. Specifically, on the KAIST dataset, the fusion images show significant improvements in Entropy (EN), Mutual Information (MI), and Quality Assessment based on Gradient-based Fusion (Q_abf) by 2.78%, 11.89%, and 10.45%, respectively, over the next-best values. On the Corsican Fire dataset, compared to data-limited fusion models, the transfer-learned fusion images enhance the Standard Deviation (SD) and MI by 10.69% and 11.73%, respectively, and compared to other methods, they perform well in Average Gradient (AG), SD, and MI, improving them by 3.43%, 4.84%, and 4.21%, respectively, from the next-best values. Compared with DenseFuse, the operation efficiency is improved by 78.3%. The method achieves favorable subjective image outcomes and is effective for fire-detection applications. Full article

The accurate estimation of forest above-ground biomass (AGB) is crucial for sustainable forest management and tracking the carbon cycle of forest ecosystem. Machine learning algorithms have been proven to have great potential in forest AGB estimation with remote sensing data. Though many studies have demonstrated that a single machine learning model can produce highly accurate estimations of forest AGB in many situations, efforts are still required to explore the possible improvement in forest AGB estimation for a specific scenario under study. This study aims to investigate the performance of novel ensemble machine learning methods for forest AGB estimation and analyzes whether these methods are affected by forest types, independent variables, and spatial autocorrelation. Four well-known machine learning models (CatBoost, LightGBM, random forest (RF), and XGBoost) were compared for forest AGB estimation in the study using eight scenarios devised on the basis of two study regions, two variable types, and two validation strategies. Subsequently, a hybrid model combining the strengths of these individual models was proposed for forest AGB estimation. The findings indicated that no individual model outperforms the others in all scenarios. The RF model demonstrates superior performance in scenarios 5, 6, and 7, while the CatBoost model shows the best performance in the remaining scenarios. Moreover, the proposed hybrid model consistently has the best performance in all scenarios in spite of some uncertainties. The ensemble strategy developed in this study for the hybrid model substantially improves estimation accuracy and exhibits greater stability, effectively addressing the challenge of model selection encountered in the forest AGB forecasting process. Full article

Afforestation is an effective approach for restoring degraded ecological functions in the dry-hot valleys of southwest China. Afforestation can affect soil carbon and nitrogen storage; however, how it affects soil P fractions, and their driving factors. is poorly understood in this region. To address these questions, we conducted a field study of Leucaena leucocephala plantations at three different stand age sites (3, 10, and 20 years) and an adjacent natural shrub-grass community control site to investigate changes in soil total phosphorus (Pt), Pi (inorganic phosphorus), Po (organic phosphorus), and phosphorus (P) fractions and their driving factors. Soil Pt, Po, labile P, and moderately labile P significantly increased in the Leucaena leucocephala plantation compared with the natural shrub grass site, and the Leucaena leucocephala plantation increased soil Pt content by significantly increasing soil Po. Soil Pt, Po, Pi, labile P, moderately labile P and non-labile P were not significantly different among the different stages of the Leucaena leucocephala plantation, and soil Pt and its fractions were all significantly higher in the middle-age forest stage of the Leucaena leucocephala plantation. These results indicate that Leucaena leucocephala plantations increased the soil P transformation ability, and soil Po played a critical role in sustaining soil P availability. The middle-age forest stage of Leucaena leucocephala plantations had the best conditions for P stocks and P conversion capacity. The abundance of actinomycetes and fungi showed significant positive relationships with soil Pi fractions (NaHCO₃-Pi, NaOH-Pi, and NaOH_u.s.-Pi); soil Pt and moderately labile P were significantly and directly influenced by fungal abundance. Soil organic carbon (SOC), NH₄⁺-N, and NO₃⁻-N showed significant and positive relationships with the soil Pi fractions (NaHCO₃-Pi, NaHCO₃-Po, and HCl-Po). SOC and NO₃⁻-N were the key drivers of soil Pt, labile P, moderately labile P and non-labile fractions. These results indicate that abiotic and biotic factors differently affected the soil P fractions and Pt in Leucaena leucocephala plantations in the dry-hot valley. Full article

Road construction and strip mining in mountainous regions inevitably causes the destruction of vegetation and soil, leading to large ranges of exposed slopes. Although soil spray-sowing has become a promising method to accelerate community assembly in humid regions, the application of microbial fertilizers and shading in slope recovery during soil spray-sowing are rarely reported in dry-hot valleys. This study compared the effectiveness among artificial seeding, arch column + planting bags, and soil spray-sowing by slope restoration trials in the Yuanjiang dry-hot valley, southwest China. Additionally, we explored the effect of slope degrees, shade, and microbial fertilizers on seedling survival and growth after soil spray-sowing. Results indicated that soil spray-sowing displayed better species survival and growth performance than artificial seeding and arch column + planting bags. The richness, density, and height of seedlings dropped dramatically with the increasing of slope degrees after soil spray-sowing, especially when the slope degree was greater than 1. Although shading observably improved the species density, it inhibited the growth of Albizia julibrissin and Crotalaria pallida. Moreover, microbial fertilizers Penicillium chrysogenum and Bacillus aryabhattai markedly enhanced the density and growth of species Azadirachta Indica, Cajanus cajan, Indigofera cassioides, and Sophora xanthanth. Soil spray-sowing, combined with shading and microbial fertilizers, contributes to species survival and growth when the slope degree is less than 1.73 and the soil spray-sowing process coincides with the rainy season, which provides the theoretical basis and technical support for ecological restoration in the dry-hot river valley. Full article

As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the “cooler” Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions. Full article

Bamboo and wood-mixed forests are management models that remarkably enhance the balance and productivity of bamboo ecosystems. However, the effects of this model on soil nutrients and enzyme activities remain largely unknown. This study compared the soil organic carbon, nitrogen, phosphorus, and enzyme activity, along with the characteristics of fine roots in pure Moso bamboo plantations (CK) and those mixed with Liriodendron chinense (ML), Sassafras tzumu (MS), Cunninghamia lanceolata (MC), and Pseudolarix amabilis (MP). The results showed that mixed forests improve carbon pools in 0–40 cm soil layers, increasing the total organic C(TOC), free particulate organic C (fPOC), occluded particulate organic C (oPOC), hot-water-extractable organic C (DOC), and mineral-associated organic C (MOC). They also increase soil total N, total P, available N, available P, NH₄⁺-N, NO₃⁻-N, inorganic P, organic P, and microbial biomass N. Bacterial and fungal abundances, along with enzyme activities (urease, acid phosphatase, polyphenol oxidase, peroxidase, and β-glucosidase), also improved. MP and MS were the most effective. Moreover, MS and MP supported a higher biomass and length of fine root and increased the nitrogen and phosphorus uptake of Moso bamboo. In conclusion, Sassafras tzumu and Pseudolarix amabilis are optimal for mixed planting, offering substantial benefits to soil nutrient dynamics and preventing soil quality decline in Moso bamboo forests, thereby supporting better nutrient cycling and carbon sequestration. This research offers insights into enhancing soil quality through diversified Moso bamboo forestry. Full article

With more and more loss caused by forest biological disasters (FBDs) in China, forest farmers, as one of the most important stakeholders, are participating in the control. In this study, the ordinary least squares model, simultaneous equation model, and propensity score matching method were used with the data from 818 surveys conducted in the typical FBD outbreak provinces, to reveal the FBD control behaviors of forest farmers and their differences between western and eastern regions of China. The results indicated the following. (1) Household factors: forest farmers could timely take control measures. An increase of 1 ha in the area of occurrence would increase the control measures by 3.26 ha. However, the control measures can only reduce 50% of the economic loss caused by FBDs and cannot effectively control the spread trend of FBDs. There are issues, including an insufficient and old labor force, insufficient technology support, and low consciousness of ecology protection. (2) External factors: forest farmers would increase control when the temperature rises, and reduce control when rainfall increases. After village committees unify organizing the control, their participation enthusiasm would increase, which would have a substitution relationship with the household investment. (3) Regional difference: the eastern region of China has higher figures than the western in terms of outbreak area, economic losses, control measures, and pesticide cost. If the western forest farmers have the control funds as the eastern forest farmers have, and the eastern forest farmers have the control intensity as the western forest farmers have, the overall FBD control effect would be better. Full article

Visits to forests can improve human health and well-being through various mechanisms. They can support the immune system, promote physical activity, and restore stress and attention fatigue. Questions remain about how perceived qualities in forests important to support such salutogenic, i.e. health-promoting, benefits can be represented in forest simulation tools to allow quantitative analyses, e.g., long-term projections or trade-off analyses with other forest functions, such as biodiversity conservation, wood production, etc. Questions also remain about how different forest management regimes might impact such perceived qualities in forests. Here, we defined three types of salutogenic forest characteristics (SFCs), referred to as Deep, Spacious, and Mixed forest characteristics, respectively. We did so by using the perceived sensory dimension (PSD) model, which describes and interrelates more fundamental perceived qualities of recreational outdoor environments that are important to support people’s health and well-being. We identified proxy variables for the selected PSD models in boreal forest stands and compared the effect of five different management regimes on both individual PSD models and the derived SFCs when projecting a forest landscape 100 years into the future. Our results suggest combinations of protection (set-aside) and variations of continuous cover forestry as the most promising strategies to achieve these salutogenic properties in the long-term future. Depending on the SFC in focus and the specific management regime used, between 20% and 50% of the landscape could support associated properties in the long term (100 years). This might impact how forests should be managed when salutogenic outcomes are considered alongside, e.g., wood production and other forest contributions. Full article

Forest road planning incorporates crucial strategies essential for sustainable timber extraction, minimizing environmental impacts and ensuring safe access to forest regions. This paper presents a literature review conducted to examine publications related to forest roads to ultimately filter and evaluate the information on the incorporation of classification systems in the planning strategies for forest roads. Using the Scopus database to gather publications, various data points were mapped, such as temporal distribution of publications, citation metrics, keyword inputs and other bibliometric markers. Through the bibliometric visualization software VOSviewer 1.6.19, this study determined that over the years, the forest road research subject has gained increasing attention with different shifts in focus. However, upon investigating the application of systems of classification implemented on forest road networks, it became evident that this approach is not a recent innovation and there is scarce documentation and development regarding this planning strategy. The information collected also reveals that this type of classification can be found more in technical documents, like design manuals. This outcome suggests that the subject under study is not relevantly covered in forest-related journals, but rather by institutions aiming to identify region-specific needs and develop corresponding systems accordingly. Full article

Forest fires are sudden and difficult to extinguish, so early risk assessment is crucial. However, there are currently a lack of suitable knowledge-mining algorithms for forest fire risk assessment. This article proposes an improved continuous Apriori algorithm to mining forest fire rules by introducing prior knowledge to classify input data and enhance its ability to process continuous data. Meanwhile, it constructs an ontology to provide a standardized expression platform for forest fire risk assessment. The improved continuous Apriori algorithm cooperates with ontology and applies the mining rules to the forest fire risk assessment results. The proposed method is validated using the forest fire data from the Bejaia region in Algeria. The results show that the improved continuous Apriori algorithm is superior to the raw Apriori algorithm and can mine the rules ignored by the raw Apriori algorithm. Compared to the raw Apriori algorithm, the number of generated rules increased by 191.67%. The method presented here can be used to enhance forest fire risk assessments and contribute to the generation and sharing of forest-fire-related knowledge, thereby alleviating the problem of insufficient knowledge in forest fire risk assessment. Full article

This study conducted a comprehensive analysis of functional substances and explored their biological activities using colorimetric and chromatographic techniques to identify high-value materials from 14 species of forest plants native to Korea. Comparative analysis between plant species included calculating the total polyphenol and flavonoid contents and qualitative and quantitative analysis of the phytochemical compounds caffeic acid (1), p-coumaric acid (2), and quercetin (3) using HPLC, and antioxidant activity tests (DPPH and ABTS⁺) and menopausal symptom relief tests (E-screen assay) to investigate their biological activities. The results highlighted Cercidiphyllum japonicum (FR 4), Aruncus dioicus (FR 6), and Pseudocydonia sinensis (FR 8) as excellent forest plant resource materials among the 14 forest plant resources. Notably, FR 4 exhibited significant activity in the E-screen assay. On the basis of these findings, we propose the use of FR 4 as a valuable material. Further analysis identified the phytochemical compounds maltol (4), chlorogenic acid (5), ellagic acid (6), and quercitrin (7) in FR 4 and analyzed their biological activities. Compounds 2–6 found in FR 4 were confirmed to possess strong antioxidant activity, and an E-screen assay revealed an excellent cell proliferation rate for quercitrin (7). This suggests that quercitrin (7) in FR 4 may be a significant indicator of the alleviation of menopausal symptoms. Full article

This study aimed to streamline the determination of chlorophyll content in Cunninghamia lanceolate while achieving precise measurements of canopy chlorophyll content. Relative chlorophyll content (SPAD) in the Cunninghamia lanceolate canopy were assessed in the study area using the SPAD-502 portable chlorophyll meter, alongside spectral data collected via onboard multispectral imaging. And based on the unmanned aerial vehicle (UAV) multispectral collection of spectral values in the study area, 21 vegetation indices with significant correlation with Cunninghamia lanceolata canopy SPAD (CCS) were constructed as independent variables of the model’s various regression techniques, including partial least squares regression (PLSR), random forests (RF), and backpropagation neural networks (BPNN), which were employed to develop a SPAD inversion model. The BPNN-based model emerged as the best choice, exhibiting test dataset coefficients of determination (R²) at 0.812, root mean square error (RSME) at 2.607, and relative percent difference (RPD) at 1.942. While the model demonstrated consistent accuracy across different slope locations, generalization was lower for varying slope directions. By creating separate models for different slope directions, R² went up to about 0.8, showcasing favorable terrain applicability. Therefore, constructing inverse models with different slope directions samples separately can estimate CCS more accurately. Full article

This study characterized important environmental factors that contribute to plant invasion in the forested riparian zones surrounding stream restoration sites. We sampled vegetation and environmental variables (light availability, soil physiochemistry, and site age) across invasion gradients at multiple sites in Virginia, USA. Data analysis involved a multimetric statistical approach combining correlation and Canonical Correspondence Analysis (CCA) to arrive at a plausible model for invasion risk by species. We targeted three of the most problematic invaders in these systems: Lespedeza cuneata (sericea lespedeza), Lonicera japonica (Japanese honeysuckle), and Microstegium vimineum (Japanese stiltgrass). Our analysis revealed species-specific environmental drivers of invasion, with certain factors consistently important across all targeted invaders—notably, canopy cover, nitrogen availability, soil texture, and bioavailable phosphorus, as indicated by the importance of certain proxies (e.g., metal cations). The results of this research have been used to develop a suite of best practices that can be implemented at the outset of a stream restoration project to reduce the risk of invasion in the riparian forests surrounding these sites. Full article

This study provides a detailed investigation of archaeological wood samples from the Luoyang Canal No. 1 site, focusing on wood species identification, physical properties, mechanical property analyses, and morphological examination. The identified wood species, belonging to the Ulmus genus, exhibited a 43% decline in compressive strength in waterlogged environments. Further, the wood exhibited increased moisture content, higher porosity, reduced basic density, and elevated shrinkage rates, indicating a mild level of degradation. X-ray diffraction was employed for the observation of cellulose structure, and Fourier transform infrared spectroscopy (FT-IR) demonstrated significant removal of cellulose and hemicellulose components. These findings emphasize the importance of understanding wood degradation mechanisms to evaluate structural integrity and durability in guiding the development of effective preservation strategies for archaeological wood artifacts. Continued research and conservation are crucial to deepen our knowledge of wood deterioration processes and enhance the implementation of preservation techniques. Full article

The management of understory vegetation and anthropogenic nitrogen (N) deposition has significantly resulted in a nutrient imbalance in forest ecosystems. However, the effects of canopy nitrogen addition and understory vegetation removal on N transformation processes (mineralization, nitrification, ammonification, and leaching) along with seasonal variations (spring, summer, autumn, and winter) remain unclear in subtropical forests. To fill this research gap, a field manipulation experiment was conducted with four treatments, including: (i) CK, control; (ii) CN, canopy nitrogen addition (25 kg N ha⁻¹ year⁻¹); (iii) UR, understory vegetation removal; and (iv) CN+UR, canopy nitrogen addition plus understory vegetation removal. The results revealed that CN increased net mineralization and nitrification by 294 mg N m⁻² month⁻¹ in the spring and 126 mg N m⁻² month⁻¹ in the winter, respectively. UR increased N mineralization and nitrification rates by 618 mg N m⁻² month⁻¹ in the summer. In addition, CN effectively reduced N leaching in the spring, winter, and autumn, while UR increased it in the spring and winter. UR increased annual nitrification rates by 93.4%, 90.3%, and 38.9% in the winter, spring, and summer, respectively. Additionally, both net N ammonification and annual nitrification rates responded positively to phosphorus availability during the autumn. Overall, UR potentially boosted nitrification rates in the summer and ammonification in the spring and winter, while CN reduced N leaching in the spring, winter, and autumn. Future research should integrate canopy nitrogen addition, understory vegetation removal, and phosphorus availability to address the global N deposition challenges in forest ecosystems. Full article

Recently, an outbreak of Ips sexdentatus (Börner, 1776) has caused considerable damage in the pine forests of the Czech Republic. As historical data on the biology of this pest are scarce due to its rare occurrence in recent decades, our work focused on monitoring flight activity and voltinism and investigating methods for monitoring its activity during the growing season. Observations were conducted from March to September 2021 and 2022 at three sites using 12 Theysohn traps with four types of pheromone lures (ACUMIPROTECT, ACUWIT, SEXOWIT and Pheagr IAC) together with data loggers to record weather conditions. The first beetles occurred in early May (daily mean temperatures above 13 °C). After the first egg laying stage, females re-emerged to establish a sister brood. The maximum flight activity appeared between late June and mid-July (daily mean temperatures about 20 °C), and the offspring occurred at the turn of June/July and in the first half of August. Since then, flight activity had a downward trend and quietened in September. According to the data, monitoring of I. sexdentatus should be conducted between May and September using the ACUMIPROTECT pheromone bait exhibiting the highest capturing efficacy. In future, however, the behavior of I. sexdentatus might alter due to climate change. Full article

Phenotypic variation analysis and comprehensive evaluation are important tools for selecting provenances of forest trees, which, in turn, is crucial for genetic improvement of forest trees. The study analyzed eight needle-leaf and fourteen tracheid trait indexes of ten provenances of Qinghai spruce forest stands. Multiple comparisons, correlation analysis, cluster analysis, and principal component analysis were used to evaluate the differences in needle-leaf and tracheid traits among the different provenances. The study found significant differences in the needle-leaf and tracheid traits among the provenances. All traits included 50 pairs of positive and 26 pairs of negative correlations. The coefficient of variation for the tracheid trait (18.86%) was higher than that for the needle-leaf trait (17.20%). A comprehensive evaluation of needle-leaf and tracheid traits was conducted using principal component analysis. The study demonstrated that the degree of variation in needle-leaf and tracheid traits among the provenances of Qinghai spruce was extensive, with a multitude of sources of variation. Therefore, it is crucial to strengthen the selection of good provenances in the early seed selection process. The results of the comprehensive evaluation can be utilized as a foundation for the selection of good provenances for carbon sequestration and timber properties. Full article

The ecosystem of the water level fluctuation (WLF) zone of the Three Gorges Reservoir (TGR) is highly vulnerable and sensitive due to its unique cyclical flooding and drought conditions. The ecological impact of biological invasion in this area is particularly severe, making it crucial to study the differences in resource utilization strategies between invasive plants (IPs) and native plants (NPs) using functional traits to explore the mechanisms of invasion. We selected the WLF zone of Pengxi River in the TGR area and conducted a multi-scale study along the elevation gradient. The results reveal that at the regional scale, IPs have a larger height and specific leaf area, smaller leaf tissue density, and specific root length compared to NPs, showing a preference for enhancing aboveground resource acquisition over leaf defense capabilities. They allocate more tissue construction resources to their roots to withstand environmental pressures, which may be the key to their successful intrusion, highlighting the role of niche differentiation. On the community scale, the H and SLA of IPs and NPs are positively correlated with elevation, while the LTD of IPs shows a negative correlation. At elevations of 175 m and below, IP and NP exhibit functional convergence, while above 175 m, functional divergence was observed. This indicates that although the different resource utilization strategies are crucial for successful IP invasion, the environmental filtering from periodic floods and drought pressures play a significant role in community assembly in the WLF zone, allowing IP to integrate into habitats with similar functional characteristics already inhabited by NP and establish their own communities. Full article

We aimed to clarify the nutrient allocation strategies of Cunninghamia lanceolata (CL) and Schima superba (SS) and their differences in N uptake and utilization under acidic stress and heterogeneous allocation of N. One-year-old seedlings of CL and SS were cultured in sands with three pH levels (pH rate 4.5, 5.5, and 6.5) and five different N form ratios (NH₄⁺-N to NO₃⁻-N ratios 10:0, 7:3, 5:5, 3:7, and 0:10) in the greenhouse. The C, N, and P contents and C:N:P stoichiometry in leaves, total biomass, and NH₄⁺-N and NO₃⁻-N contents in the cultivation substrate were analyzed after 160 days. At the pH rate of 4.5, the N contents of CL and SS significantly decreased. However, the N contents of SS increased at the pH rate of 5.5. At the pH rate of 5.5, the N content of CL and SS increased under the cultivation substrate, with ratios of 10:0 and 7:3, and 3:7 and 0:10, respectively. The N content of CL was significantly positively correlated with its P content. The C:P ratios of CL and SS were significantly positively correlated with their C:N ratios and N:P ratios. Under the same treatment, the differences in C:N:P stoichiometry were more significant between CL and SS at the pH rate of 5.5. The NH₄⁺-N content of the cultivation substrate in CL and SS was higher than the NO₃⁻-N content. At the ratio of 7:3, the C:N stoichiometric ratio of CL and C:N:P stoichiometric ratio of SS were negatively correlated with total biomass. At the pH rate of 5.5, cultivation environments with high NH₄⁺-N and NO₃⁻-N amount respectively increased the N content of CL and SS. The CL is susceptible to N limitation, and SS is susceptible to N and P limitation. Full article

The Sphagnum habitat is a ”miniature forest” to the mites, of which the layers offer different microenvironmental conditions. We studied the vertical distribution of the Oribatida, Mesostigmata, and Prostigmata groups in four layers (0–5 cm, 5–10 cm, 10–15 cm, and 15–20 cm) of a forest bog on Neshalvøya, Norway, to improve the knowledge of the ecology of these mites. The sampled bog was grazed by farm animals; thus, another aim was to investigate the vertical distribution of the oribatid species, which are intermediate hosts of tapeworms. The selected study site is known for its valuable yet increasingly endangered nature, so our aim was also to contribute to the knowledge on its diversity. We collected Sphagnum samples in four replicates and extracted them in the laboratory in modified Berlese funnels. In total, 16.880 mites were studied, including 16.384 Oribatida, 466 Mesostigmata, and 30 Prostigmata. The total abundance of mites, the Oribatida and Mesostigmata groups, was the highest in the upper layer of Sphagnum and decreased with depth, while the abundance of the Prostigmata did not follow any pattern. Among the Oribatida, at deeper layers, significant declines in abundance were observed in adults, but not in juveniles. Most oribatid species, e.g., Nothrus pratensis, preferred the upper layer of Sphagnum, whereas some preferred deeper layers. For example, Suctobelbella acutidens and Carabodes femoralis preferred the 5–10 cm layer, Quadroppia maritalis the 10–15 cm layer, and Ceratozetes gracilis and Eulohmannia ribagai preferred the deepest layer of Sphagnum. Adults and juveniles of the same species showed a preference for the same layer. In total, 62 species of the Oribatida were recorded, including 11 species that are known to be intermediate hosts of tapeworms. Most of them occurred in the upper layer of Sphagnum. Over 20% of the species were found exclusively in deeper layers, so sampling these layers is important for a better evaluation of the mites’ diversity. Studying the vertical distribution of the mites in bogs helps us to understand their ecology, including their role as intermediate hosts of tapeworms, as well as their diversity. Full article

In June 2020, needle blight symptoms on Pinus thunbergii were discovered in Bazhong City, Sichuan Province, China. Fungal isolates were obtained from the pine needles of P. thunbergii. After examining morphological characteristics and conducting multi-locus (ITS, ACT, TUB2 and RPB2) phylogenetic analyses, the isolates SC1–SC5 were determined to be a new species, Biscogniauxia sinensis. Genealogical Concordance Phylogenetic Species Recognition with a pairwise homoplasy index test was used to further verify the results of the phylogenetic analyses. The morphology and phylogenetic relationships between this new species and other related Biscogniauxia species were discussed. To our knowledge, this is also the first report of Biscogniauxia sinensis associated with pine needle blight on P. thunbergii in China. The needle damage of P. thunbergii associated with Biscogniauxia sinensis will detrimentally affect the carbon absorption and photosynthetic efficiency of P. thunbergii, further reduce the absorption of nutrients by Japanese black pine and may lead to the imbalance of pine forest conditions, which will have a negative impact on the forest ecological system. Full article

Arhopalus rusticus is a significant forestry pest known for its destructive impact on various host plants. This species, commonly found in coniferous forests across the Northern Hemisphere, has successfully spread to regions like New Zealand, Australia, and South America. This research is based on the known distribution sites of A. rusticus. Projections are made for the potential global distribution of A. rusticus under historical climatic conditions (1970–2000) and future climatic conditions (2081–2100) for the four forcing scenarios of the Coupled Model International Comparison Program 6 (CMIP6). The aim was to analyze the effects of climate change on the distribution range of this pest and its invasion trend in the southern hemisphere, and to support relevant departments in enhancing the effectiveness of forestry pest control strategies. The study utilized the Biomod2 software package in R to compare six models: generalized linear models (GLMs), generalized additive models (GAMs), multivariate adaptive regression splines (MARSs), artificial neural networks (ANNs), classification and regression trees (CTAs), and random forests (RFs) for modeling species distributions. The optimal model was selected based on evaluation indexes such as AUC and TSS. Projections of A. rusticus distribution under historical and future climate scenarios were created. The prediction results were visualized using ArcGIS software (version 10.2) to classify fitness levels and calculate distribution areas. Based on evaluation metrics, random forests (RFs) demonstrated the highest average assessment index scores, indicating high prediction accuracy (AUC = 0.99, TSS = 0.91, Kappa = 0.93). Model predictions revealed that, under historical climatic conditions, A. rusticus was predominantly found in northern Europe, eastern Asia, eastern and southwestern coastal regions of North America, and there were also highly suitable regions in parts of the southern hemisphere, including central and southwestern Argentina, southern Australia, New Zealand, and South Africa. Among these models, each of the CMIP6’s different climate prediction scenarios had a significant impact on the predicted distribution of A. rusticus. The SSP126 scenario depicted the broadest range of suitability, while the SSP585 scenario presented the narrowest and, overall, the extent of highly suitable regions was contracting. Multi-model predictions suggested that the potential distribution area of A. rusticus during the period of 2081–2100 would likely expand compared to that of 1970–2000, ranging from an increase of 1.13% (SSP126) up to 6.61% (SSP585), positively correlating with the level of radiative forcing. Notably, the most substantial growth was observed in potentially low-suitability region, escalating from 1.17% (SSP126) to 5.55% (SSP585). The distribution of A. rusticus shows decreasing trends from coastal areas to inland areas and from high to low level suitability of regions, and further expansion into the southern hemisphere under future climate conditions. Therefore, quarantine efforts at ports of entry should be strengthened in areas that are not currently infested but are at risk of invasion, and precise preventive measures should be strengthened in areas that are at risk of further expansion under future climatic conditions to prevent its spread to inland areas. Full article

Functional traits are pivotal for understanding the functional niche within plant communities. Yet, the relationship between the functional niches of typical forest plant communities across different climatic zones, as defined by functional traits, and their association with community and phylogenetic structures remains elusive. In this study, we examined 215 woody species, incorporating 11 functional traits spanning leaf economy, mechanical support, and reproductive phenology, gathered from forests in four climatic zones from tropical, subtropical, warm-temperate to cold-temperate zones in China and supplemented by the literature. We quantified the functional niche hypervolume (FNH), reflecting the multidimensional functional niche variability. We then probed into the correlation between the FNH and community and phylogenetic structures of forests. Our findings reveal that species richness significantly influences the geographic variance of functional niche space in forest vegetation across different climatic zones. Specifically, a community’s species richness correlates positively with the functional niche breadth occupied by the community species. The FNH of woody plants across diverse forest types shows significant associations with both the mean phylogenetic distance (MPD) and the mean nearest phylogenetic taxon distance (MNTD) of the communities. There is a progressive increase in tropical rainforest (TF), subtropical evergreen deciduous broad-leaved mixed forest (SF), and warm-temperate coniferous broad-leaved mixed forest (WF), followed by a decline in the cold-temperate coniferous forest (CF). This pattern suggests potential environmental filtering in CF, which may constrain the spatial extent of plant functional niches. Our research underscores the substantial variability in the FNH across China’s typical forest vegetation, highlighting the complex interplay between functional traits, community richness, and phylogenetic distance. Full article

Seed orchards are important seed resources for producing improved tree crops for future plantations, forest restoration, and forestry practices (i.e., gene conservation) and for transmitting current gene diversity to future generations. Seed orchards are a major sub-division in forest science. The establishment and management of a seed orchard involves many steps, from the selection of superior trees to the harvesting of a seed crop. Studying the trends and future directions of seed orchards using different analysis methods is critically important, especially to establish resistant forests via the production of climate-smart, biotic/abiotic-stress-resistant seedling materials. Published papers related to seed orchards should be analyzed to determine the current trends in this field and to contribute to its future directions. Bibliometric analysis has been used for different purposes in various scientific fields. However, it has not been performed for publications in seed orchards. This study was carried out to analyze the current trends of research on seed orchards and to determine the future directions of these orchards based on published papers. For these purposes, 1018 published papers were obtained from the Science Citation Index, Science Citation Index Expanded, and citation index databases of “Web of Science” using the keyword “seed orchard”. The papers were published between 1980 and 2022 and were subjected to bibliometric analysis based on the most prolific contributors, references, countries, and keywords. CiteSpace software 6.1 R6 was applied to visualize information about seed orchard research. The average number of citations per publication was 13.05, and the 4 H-Index of the publication set was 48. The most prolific contributors with the strongest citation bursts, the highest centrality, and the greatest numbers of published papers were from Canada, Sweden, South Korea, Finland, and Czech Republic, while Canada (186 published articles), the USA (140), and Sweden (115), together with China, Brazil, and Germany, were active countries, especially based on citations from recent years. The “keywords” of the papers were the core of the research. “Mating pattern”, “Swedish forestry”, “fertility variation”, “Hymenoscyphus fraxineus”, “threatened Pacific sandalwood”, “outbreeding depression”, “climate change”, “management”, and “growth”, together with others such as “genetic improvement” and “effective size”, were active study areas and keywords, based on results of the analysis. They also guided the literature search and inventory and classification of early studies and served as predictors for future studies. The results of this study are discussed based on the trends and future directions of the research and development of seed orchards. Full article

Phytophthora nicotianae is a global and polyphagous pathogen with a wide host range. P. nicotianae can infect Areca catechu, Durio zibethinus L., Psidium guajava L., Hevea brasiliensis, and other tree species. The pathogen is capable of inducing butt rot and affecting aerial parts, including stems, leaves, and fruits. Compared to other Phytophthora species, P. nicotianae is more adaptable to abiotic stress. In this study, recombinase polymerase amplification (RPA) in combination with the CRISPR/Cas12a system was used for the detection of P. nicotianae, and achieved rapid and efficient detection of P. nicotianae. The assay was highly specific to P. nicotianae. All 4 tested isolates of P. nicotianae yielded positive results, whereas 30 isolates belonging to 17 other Phytophthora species, 8 fungal species, and 4 Bursaphelenchus xylophilus vermicules lacked detection. Under the conditions of 37 °C, after 20 min of RPA reaction and 25 min of Cas12a cleavage, a DNA concentration as low as 10 pg·μL⁻¹ could be detected. In addition, it detected P. nicotianae from artificially inoculated leaves of Fatsia japonica. In this study, a novel method was established for the efficient and accurate detection of P. nicotianae based on the combination of RPA and the CRISPR/Cas12a system. Full article

In civil construction, one of the primary challenges associated with wood application is its high flammability and low durability during fires. Although chemical treatment with fire-retardant properties exists, they are expensive and of non-renewable origin. Tannin, a wood extractive, being a phenolic compound, holds promise for enhancing the thermal properties of wood. This study aimed to assess the efficacy of tannin as a fire retardant and compare it with a commercial product, as well as comparing different application techniques for these products. Wood samples from the Simarouba amara Aubl. species were utilized. Tannin and a commercial flame retardant were applied via immersion, vacuum impregnation, brushing, and a treatment of tannin incorporated into water-based wood varnish. Alongside the burning test performance, assessments of the wood’s physical properties, such as colorimetry, thermal stability, and mass retention, were conducted. The application of tannin altered the wood’s color and reduced the spread of fire; its presence significantly reduced the flame duration and maintained the wood’s structural integrity. However, tannin retention was lower compared to commercial flame retardant, leading to reduced fire retardancy. Among the methods tested, immersion proved to be the most effective in enhancing the wood’s resistance to flame contact. Full article

Agroforestry is known to significantly improve long-term land productivity, potentially enhancing the ability to cope with climate stress. However, there is limited information regarding the accurate monitoring of greenhouse gases (GHGs) in rubber-based agroforestry systems. Before GHGs can be accurately estimated, the diurnal variations and suitable sampling times must be studied to reduce the uncertainty of the manual static chamber method. In this study, the soil GHGs emitted from conventional single-row (SR) and improved double-row (DR) rubber plantations were compared across the dry and wet seasons in Hainan, China. A total of 1728 GHG samples from a field trial were collected, analyzed, and related to environmental factors. The results demonstrated that the diurnal fluxes of CO₂ in rubber plantations were likely to remain fluctuating, with the maximum typically occurring during the night-time and daytime hours of the dry and wet seasons, respectively. A clearer double-peak (around 2:00 and 14:00) during the dry season and a daytime peak (14:00) during the wet season of the N₂O were recorded. In addition to the commonalities, different seasons and different types of GHGs and rubber plantations also differed in their detailed fluctuation times and ranges; therefore, the determination of suitable sampling times should not ignore these factors in certain cases. Based on this study, it was determined that the late afternoon (16:00–18:00) was the suitable sampling time of soil GHGs in rubber plantations, instead of the most common morning times (with an underestimation of 25% on average). In addition, the air humidity during the dry season and the soil temperature during the wet season were both positively correlated with GHGs (p < 0.05). This study highlights the significance of accurately monitoring soil GHGs in rubber-based agroforestry systems, providing a basic reference for the development and management of climate-smart land use practices in rubber plantations. Full article