Forests are exposed to changing climatic conditions reflected by increasing drought and heat waves that increase the risk of wildfire ignition and spread. Climatic variables such as rain and wind as well as vegetation structure, land configuration and forest management practices are all factors that determine the burning potential of wildfires. The assessment of emissions released by vegetation combustion is essential for determining greenhouse gases and air pollutants. The estimation of wildfire-related emissions depends on factors such as the type and fraction of fuel (i.e., live biomass, ground litter, dead wood) consumed by the fire in a given area, termed the burning efficiency. Most approaches estimate live burning efficiency from optical remote sensing data. This study used a data-driven method to estimate live burning efficiency in a Mediterranean area. Burning severity estimations from Landsat imagery (dNBR), which relate to fuel consumption, and quantitative field data from three national forest inventory data were combined to establish the relationship between burning severity and live burning efficiency. Several proxies explored these relationships based on dNBR interval classes, as well as regression models. The correlation results between live burning efficiency and dNBR for conifers (R = 0.63) and broad-leaved vegetation (R = 0.95) indicated ways for improving emissions estimations. Median estimations by severity class (low, moderate-low, moderate-high, and high) are provided for conifers (0 .44 − 0.81) and broad-leaves (0.64 − 0.86), and regression models for the live fraction of the tree canopy susceptible to burning (< 2 cm, 2 − 7 cm, > 7 branches, and leaves). The live burning efficiency values by severity class were higher than previous studies.

Climate change has an impact on forest fire patterns. In the context of global warming, it is important to study the possible effects of climate change on forest fires, carbon emission reductions, carbon sink effects, forest fire management, and sustainable development of forest ecosystems. This study is based on MODIS active fire data from 2001–2020 and the influence of climate, topography, vegetation, and social factors were integrated. Temperature and precipitation information from different scenarios of the BCC-CSM2-MR climate model were used as future climate data. Under climate change scenarios of a sustainable low development path and a high conventional development path, the extreme gradient boosting model predicted the spatial distribution of forest fire occurrence in China in the 2030s (2021–2040), 2050s (2041–2060), 2070s (2061–2080), and 2090s (2081–2100). Probability maps were generated and tested using ROC curves. The results show that: (1) the area under the ROC curve of training data (70%) and validation data (30%) were 0.8465 and 0.8171, respectively, indicating that the model can reasonably predict the occurrence of forest fire in the study area; (2) temperature, elevation, and precipitation were strongly correlated with fire occurrence, while land type, slope, distance from settlements and roads, and slope direction were less strongly correlated; and, (3) based on future climate change scenarios, the probability of forest fire occurrence will tend to shift from the south to the center of the country. Compared with the current climate (2001–2020), the occurrence of forest fires in 2021–2040, 2041–2060, 2061–2080, and 2081–2100 will increase significantly in Henan Province (Luoyang, Nanyang, Sanmenxia), Shaanxi Province (Shangluo, Ankang), Sichuan Province (Mianyang, Guangyuan, Ganzi), Tibet Autonomous Region (Shannan, Linzhi, Changdu), Liaoning Province (Liaoyang, Fushun, Dandong).

The COVID-19 pandemic posed challenges to the tourism sector globally. We investigated changes in visitor demographics, satisfaction level, and its determinants pre- and peri-COVID-19. Data were collected using questionnaire surveys in 2019 and 2021 within Banff National Park (BNP). The data analyses were based on a sample size of 1183 respondents by conducting factor analysis, correlation analysis and stepwise regression analysis. Results highlight that there were fewer international visitors and more local and domestic visitors during the pandemic. Park attributes were evaluated at a higher satisfaction level peri-COVID-19. The quality of the Park facilities and services were the most important satisfaction determinants pre- and peri-COVID-19, and all the Park COVID-19 measures and actions received positive experience from visitors. This research fills this knowledge gap by developing a better understanding in the change of visitor demographics and satisfaction level in BNP under the context of the pandemic. It also provides implication for both scholars and practitioners to understand the impacts of the pandemic on Park visitation. The study can provide insights for utilizing the pandemic as a transformative strength and for mitigating its negative impact on tourism industry.

Experiencing urban green and blue spaces (GBSs) can be a nature-based solution to improve mental well-being and cope with negative moods for people exposed to PM_2.5 pollution. In this study, a total of 1257 photos were collected to recognize their posted emotions of Sina Weibo users from 38 parks in 22 cities in Northeast China in 2021, when atmospheric PM_2.5 and landscape metrics were evaluated for GBSs of each park. Autumn and winter had heavy atmospheric PM_2.5 pollutions in resource-dependent cities of Liaoning. Net positive emotions (happy minus sad scores) decreased in larger green spaces. The perception of blue space countered the presentation of sadness only for a limited period over four seasons. High elevation decreased the level of happiness presented in winter. Overall, this study confirms that visiting large urban green spaces at low elevations can benefit the perception of positive sentiments for people exposed to PM_2.5 in autumn. For planning urban forests in Northeast China, more green spaces should be constructed in cities in southern Jilin province to alleviate air PM_2.5 pollution and gain better well-being of local people.

Worldwide, forests are vital in the regulation of the water cycle regulation and in water balance allocation. Knowledge of ecohydrological responses of production forests is essential to support management strategies, especially where water is already scarce. Shifting climatological patterns are expected to impact thermopluviometric regimes, water cycle components, hydrological responses, and plant physiology, evapotranspiration rates, crop productivity and land management operations. This work (1) assessed the impacts of different predicted climate conditions on water yield; (2) inferred the impacts of climate change on biomass production on eucalypt-to-eucalypt succession. To this end, the widely accepted Soil and Water Assessment Tool (SWAT) was run with the RCA, HIRHAM5 and RACMO climate models for two emission scenarios (RCP 4.5 and 8.5). Three 12-year periods were considered to simulate tree growth under coppice regime. The results revealed an overall reduction in streamflow and water yield in the catchment in line with the projected reduction in total annual precipitation. Moreover, HIRHAM5 and RACMO models forecast a slight shift in seasonal streamflow of up to 2 months (for 2024–2048) in line with the projected increase in precipitation from May to September. For biomass production, the extreme climate model (RCA) and severe emission scenario (RCP 8.5) predicted a decrease up to 46%. However, in the less extreme and more-correlated (with actual catchment climate conditions) climate models (RACMO and HIRHAM5) and in the less extreme emission scenario (RCP 4.5), biomass production increased (up to 20%), and the growth cycle was slightly reduced. SWAT was proven to be a valuable tool to assess climate change impacts on a eucalypt-dominated catchment and is a suitable decision-support tool for forest managers.

Studies on fertilization management of species native to the Amazon for energy plantations contribute to the diversity of species use and reduce biological risk due to the excessive use of clones or hybrids of Eucalyptus. This study evaluates the effect of precipitation seasonality and phosphorus and potassium fertilization on gas exchange in a Tachigali vulgaris plantation. Three levels of P (zero, 65.2, 130.4 kg ha⁻¹) and three of K (zero, 100.0, 200.0 kg ha⁻¹) were applied in a 3 × 3 factorial randomized block design. Gas exchange measurements were conducted in April and November 2018. In low rainfall, high irradiance period, photosynthetic rates were up to four times higher than in the high rainfall period, reaching 20.3 μmol m⁻² s⁻¹ in the treatment with 130.4 g kg⁻¹ of P and 100.0 g kg⁻¹ of K. Factor analysis and principal component analysis reduced the initial eight gas exchange variables to two and three principal components in periods of high and low rainfall, respectively. The multivariate method used in this study readily identified variations in the variables as a function of rainfall, with high reliability in explaining the data set.

Historical and current climate impacts reshape the evolutionary trajectory and ecological dynamics of entire vegetative communities, which can drive insect species distribution. Understanding the spatial distribution of insects can enhance forest management effectiveness. The effects of historical and current climates in the spatial distribution of herbivorous tree insects in China were explored. A species distribution model simulated insect spatial distribution based on 596 species and the distribution probability and richness of these species were assessed in forest ecoregions. The explanatory power of the historical climate was stronger than that of the current climate, particularly historical annual precipitation and annual mean temperatures, for the distribution of herbivorous insects. Under both historical and current climatic conditions, herbivorous tree insects were and are mainly distributed in the North China Plain and the middle and lower reaches of the Yangtze River Plain, namely in the Huang He Plain mixed forests, Changjiang Plain evergreen forests, and Sichuan Basin evergreen broadleaf forests. The Yunnan–Guizhou Plateau and northeast China are regions with large impact differences between historical and current climates. The findings of this study provide valuable insights into herbivorous insect responses to sustained climate change and may contribute to long-term biodiversity conservation activities.

Arboricultural research focusing on transport land use was lacking in Hong Kong. Some highway slopes were registered in the Systematic Identification of Maintenance Responsibility of Slopes in the Territory (SIMAR), abbreviated as SIMAR slopes. We aimed to analyze patterns in the structure and species composition of the tree stock along a highway in Hong Kong and examined how a slope registration system could help explain the characteristics of urban forests. The 53 slopes and 52 verges along San Tin Highway, Hong Kong were randomly selected. The trees on each slope and verge were collectively sampled as a tree stand. Six variables, namely tree abundance, species richness, maximum tree height, Shannon–Wiener diversity, Simpson’s dominance, and Pielou’s evenness were measured for each stand. In addition, a limited visual tree risk assessment was performed. The 7,209 trees in 23 species were recorded. Species richness was low, ranging from one to eight species per stand. SIMAR and non-SIMAR slopes were compared. SIMAR slopes had significantly higher species richness, diversity, evenness but lower dominance, with mean difference of 1.41 species, 0.17, 0.17 and − 0.28 respectively. SIMAR slopes were associated with lower tree risk rating. When training regression models, boosting as an ensemble method arbitrarily raised the explanatory power and the predictive accuracy of some models. Slope height, length, angle and area could be significant predictors of the biodiversity-related variables. Future research can sample more habitat characteristics related to the structure and species composition of slopes and verges which were important components of urban forestry.

Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification, it has not been widely used over large areas. A comprehensive process based on multi-flightline airborne hyperspectral data is lacking over large, forested areas influenced by both the effects of bidirectional reflectance distribution function (BRDF) and cloud shadow contamination. In this study, hyperspectral data were collected over the Mengjiagang Forest Farm in Northeast China in the summer of 2017 using the Chinese Academy of Forestry’s LiDAR, CCD, and hyperspectral systems (CAF-LiCHy). After BRDF correction and cloud shadow detection processing, a tree species classification workflow was developed for sunlit and cloud-shaded forest areas with input features of minimum noise fraction reduced bands, spectral vegetation indices, and texture information. Results indicate that BRDF-corrected sunlit hyperspectral data can provide a stable and high classification accuracy based on representative training data. Cloud-shaded pixels also have good spectral separability for species classification. The red-edge spectral information and ratio-based spectral indices with high importance scores are recommended as input features for species classification under varying light conditions. According to the classification accuracies through field survey data at multiple spatial scales, it was found that species classification within an extensive forest area using airborne hyperspectral data under various illuminations can be successfully carried out using the effective radiometric consistency process and feature selection strategy.

Selective logging is well-recognized as an effective practice in sustainable forest management. However, the ecological efficiency or resilience of the residual stand is often in doubt. Recovery time depends on operational variables, diversity, and forest structure. Selective logging is excellent but is open to changes. This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms. The function maximizes remaining stand diversity, merchantable logs, and the inverse of distance between trees for harvesting and log landings points. The Brazilian rainforest database (566 trees) was used to simulate our 216-ha model. The log landing design has a maximum volume limit of 500 m³. The nondominated sorting genetic algorithm was applied to solve the main optimization problem. In parallel, a sub-problem (p-facility allocation) was solved for landing allocation by a genetic algorithm. Pareto frontier analysis was applied to distinguish the gradients α-economic, β-ecological, and γ-equilibrium. As expected, the solutions have high diameter changes in the residual stand (average removal of approximately 16 m³ ha⁻¹). All solutions showed a grouping of trees selected for harvesting, although there was no formation of large clearings (percentage of canopy removal < 7%, with an average of 2.5 ind ha⁻¹). There were no differences in floristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting. This implies a lower impact on the demographic rates of the remaining stand. The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.

Current techniques of forest inventory rely on manual measurements and are slow and labor intensive. Recent developments in computer vision and depth sensing can produce accurate measurement data at significantly reduced time and labor costs. We developed the ForSense system to measure the diameters of trees at various points along the stem as well as stem straightness. Time use, mean absolute error (MAE), and root mean squared error (RMSE) metrics were used to compare the system against manual methods, and to compare the system against itself (reproducibility). Depth-derived diameter measurements of the stems at the heights of 0.3, 1.4, and 2.7 m achieved RMSE of 1.7, 1.5, and 2.7 cm, respectively. The ForSense system produced straightness measurement data that was highly correlated with straightness ratings by trained foresters. The ForSense system was also consistent, achieving sub-centimeter diameter difference with subsequent measures and less than 4% difference in straightness value between runs. This method of forest inventory, which is based on depth-image computer vision, is time efficient compared to manual methods and less computationally and technologically intensive compared to Structure-from-Motion (SFM) photogrammetry and ground-based LiDAR or terrestrial laser scanning (TLS).

Crown development is closely related to the biomass and growth rate of the tree and its width (CW) is an important covariable in growth and yield models and in forest management. To date, various CW models have been proposed. However, limited studies have explicitly focused on additive and inherent correlation of crown components and total CW as well as the influence of competition on crown radius from the corresponding direction. In this study, two model systems were used, i.e., aggregation method system (AMS) and disaggregation method system (DMS), to develop crown width additive model systems. For calculating spatially explicit competition index (CI), four neighbor tree selection methods were evaluated. CI was decomposed into four cardinal directions and added into the model systems. Results show that the power model form was more proper for our data to fit CW growth. For each crown radius and total CW, height to the diameter at breast height (HDR) and basal area of trees larger than the subject tree (BAL) significantly contributed to the increase of prediction accuracy. The 3-m fixed radius was optimal among the four neighborhoods selection ways. After adding decomposed competition Hegyi index into model systems AMS and DMS, the prediction accuracy improved. Of the model systems evaluated, AMS based on decomposed CI provided the best performance as well as the inherent correlation and additivity properties. Our study highlighted the importance of decomposed CI in tree CW modelling for additive model systems. This study focused on methodology and could be applied to other species or stands.

Araucaria angustifolia is the dominant coniferous species in Brazil, a long-lived pioneer species and a supplier of valuable timber and non-timber products, which gives it key-species status. This study examines how A. angustifolia population structure affects the stand structure, and whether these relationships differ between protected and unprotected areas. The study was carried out on two protection status forests (national forest and urban forest) in a region of Atlantic mixed forest in Paraná State, southern Brazil. Skewness coefficient and the Weibull shape parameter described the population structure and its effects on species diversity and biomass stock. Population diameter distribution differed significantly between forests, with unbalanced structure in both, although regeneration was more abundant in the protected area. Skewness positively affected aboveground biomass whereas shape negatively affected it and species diversity. These relationships differed between protected and unprotected stands. The effect of A. angustifolia populations on stand structure was conditioned on protection status. Old-growth populations may have lower diversity and biomass stock even supporting large trees. Consequently, old-growth forests, can lead to wood loss through mortality, senescence, and declining populations, representing the waste of a valuable timber resource. These findings provide useful knowledge for forest management, species conservation, and the carbon market.

The exotic saltmarsh cordgrass, Spartina alterniflora (Loisel) Peterson & Saarela, is one of the important causes for the extensive destruction of mangroves in China due to its invasive nature. The species has rapidly spread wildly across coastal wetlands, challenging resource managers for control of its further spread. An investigation of S. alterniflora invasion and associated ecological risk is urgent in China’s coastal wetlands. In this study, an ecological risk invasive index system was developed based on the Driving Force-Pressure-State-Impact-Response framework. Predictions were made of ‘warning degrees’: zero warning and light, moderate, strong, and extreme warning, by developing a back propagation (BP) artificial neural network model for coastal wetlands in eastern Fujian Province. Our results suggest that S. alterniflora mainly has invaded Kandelia candel beaches and farmlands with clustered distributions. An early warning indicator system assessed the ecological risk of the invasion and showed a ladder-like distribution from high to low extending from the urban area in the central inland region with changes spread to adjacent areas. Areas of light warning and extreme warning accounted for 43% and 7%, respectively, suggesting the BP neural network model is reliable prediction of the ecological risk of S. alterniflora invasion. The model predicts that distribution pattern of this invasive species will change little in the next 10 years. However, the invaded patches will become relatively more concentrated without warning predicted. We suggest that human factors such as land use activities may partially determine changes in warning degree. Our results emphasize that an early warning system for S. alterniflora invasion in China’s eastern coastal wetlands is significant, and comprehensive control measures are needed, particularly for K. candel beach.

Fine roots (< 2 mm) play vital roles in water and nutrient uptake. However, intraspecific variations in their chemical traits and their controlling mechanisms remain poorly understood at a regional scale. This study examined these intraspecific variations in fine roots in Masson pine (Pinus massoniana Lamb.) plantations across subtropical China and their responses to environmental factors. Root nitrogen (N) and phosphorus (P) concentrations and their mass ratios (N:P) ranged from 3.5 to 11.7 g kg⁻¹, 0.2 to 0.9 g kg⁻¹, and 7.8 to 51.6 g kg⁻¹, respectively. These three chemical traits were significantly different between sites and in longitudinal patterns across subtropical China. Mean annual temperature was positively related to root N concentration but negatively related to root P concentration. There were significant, negative relationships between clay content and root P concentration and between pH and root N concentration. Available N had no significant relationship with root N concentration, while available P was a significantly positive relationship with root P concentration. The combined effects of altitude, climate (temperature and precipitation) and soil properties (pH, clay content, available N and P) explained 26% and 36% of the root N and P concentrations variations, respectively. These environmental variables had direct and indirect effects and exhibited disproportionate levels of total effects on root N and P concentrations. Root N and P concentrations explained 35% and 65% variations in their mass ratios, respectively. The results highlight different spatial patterns of chemical traits and various environmental controls on root N and P concentrations in these ecosystems. More cause-effect relationships of root chemical traits with abiotic and biotic factors are needed to understand nutrient uptake strategies and the mechanisms controlling intraspecific variations in plant traits.

As primary and secondary forests are being replaced by plantations across the globe, the soil macrofauna community structure is also affected, but little is known about the impact of mixed culture plantations compared with monocultures on the soil macrofauna. To determine the impact of forest conversion on soil macrofauna, we surveyed the soil macrofauna in two broad-leaved and three coniferous monoculture stands and four coniferous–broadleaved mixed stands, and in adjacent reserved secondary stands as a reference. Soil macrofauna community composition was significant affected by forest type, season and their interaction (P < 0.05). The abundance, taxa richness and diversity of soil macrofauna changed to different degrees depending on the plantation type. Broadleaved monoculture stands and secondary stands had similar macrofauna abundance and taxa richness, but values were lower in coniferous stands than in secondary stands. The Shannon index for macrofauna in coniferous stands was also the lowest, but the Pielou index did not differ between forest types. The negative effects of the conifer monoculture on soil macrofauna were not present in the mixed stands with broad-leaved trees. Forest conversion impacted soil properties; soil moisture, NO₃ ⁻, and pH were significant drivers of soil macrofauna community structure. The impact of forest conversion on soil macrofauna was closely dependent on tree species composition and diversity. The macrofauna community structure in the broadleaved and the mixed stands were relatively similar to that in the natural forest, and thus recommended for forest conversion in the study area.

Root-associated microbes play an essentialrole in mediating plant growth, health, and habitat adaptability. However, it is unknown which microbial taxa help develop host fitness and how habitats shape root-associated microbial assembly patterns. As an endemic species of subalpine forests in western Sichuan, China, Minjiang fir (Abies fargesii var. faxoniana) is dominant on cold-shaded northwestern slopes while absent on warm sunlit southwestern slopes. In this study, fungal and bacterial communities were investigated in three spatial compartments (endosphere, rhizosphere, and bulk soil) associated with Minjiang fir saplings on a cold-shaded northwestern slope and a warm sunlit southwestern slope. Habitats differentiated the microbial communities regardless of the spatial compartment and microbial taxa. Slope aspect variations caused shifts in root-associated (rhizosphere and endosphere) microbial compositions. Compared with the southwestern slope, the cold-shaded northwestern slope harbored a higher abundance of the growth-promoting bacteria Burkholderia and ectomycorrhizal fungi Cortinarius and Piloderma. The slope aspect had stronger effects on fungal diversity than bacterial diversity, with higher fungal endemism and lower bacterial endemism. Slope aspect variations were the dominant drivers of root-associated microbial communities, with lower contribution by soil properties and higher contribution by plant traits on the northwestern slope. Findings from this study could improve the understanding of plant habitat adaptability from the perspective of microbial community assembly. It is suggested that forest management should consider root-associated microbiomes for enhancing species fitness and habitat adaptability.

Zeyheria tuberculosa (Vell.) Bureau ex Verl. is among the Brazilian flora threatened with extinction. It has high-quality wood and can be used to recover herbicide-contaminated areas. However, abiotic stresses can harm seed germination and seedling development under adverse conditions and need to be understood to improve autochthonous or indigenous biodiversity conservation and strengthen reforestation projects. This study evaluated the effects of temperature, water and saline stress on Z. tuberculosa seed germination and water stress on seedling growth. Three laboratory experiments evaluated germination under: (1) different temperatures (20, 25, 30, 35 and 40 °C); (2) different water potentials simulated with polyethylene glycol (PEG 6000) at 25 and 30 °C; and, (3) different osmotic potentials simulated with NaCl at 25 and 30 °C. In addition, a greenhouse experiment subjected seedlings to five water regimes (20%, 35%, 50%, 65% and 80% of maximum substrate water holding capacity). In the laboratory, seedling biometry and germination were evaluated, while physiological and morphological parameters were assessed in the greenhouse. Physiological potential of seeds increased at 25 and 30 °C. Germination and vigor decreased as water and saline stresses increased. Germination tolerance thresholds for water and salt stresses were − 0.6 and − 0.4 MPa, respectively. In the greenhouse, the most restrictive water regimes reduced seedling physiological and morphological parameters. Seedling development was compromised at moisture levels below 50% field capacity.

Plant tolerance to aluminum (Al) toxicity can be enhanced by an ectomycorrhizal (ECM) fungus through biological filtering or physical blockage. To understand the roles of ECM colonization in Al absorption with regard to Al tolerance, Pinus massoniana seedlings were inoculated with either Lactarius deliciosus (L.:Fr.) Gray isolate 2 or Pisolithus tinctorius (Pers.) Coker et Couch isolate 715 and cultivated in an acid yellow soil with or without 1.0 mM Al³⁺ irrigation for 10 weeks. Biomass production, Al bioaccumulation and transport in seedlings colonized by the two ECM fungi were compared, and the three absorption kinetics (pseudo-first order, pseudo-second order and intraparticle diffusion) models used to evaluate variances in root Al³⁺ absorption capacity. Results show that both fungi increased aboveground biomass and Al tolerance of P. massoniana seedlings, but L. deliciosus 2 was more effective than P. tinctorius 715. Lower Al absorption capacity, fewer available active sites and decreased affinity and boundary layer thickness for Al³⁺, and higher Al accumulation and translocation contributed to the increased Al tolerance in the ECM-inoculated seedlings. These results advance our understanding of the mechanisms and strategies in plant Al-tolerance conferred by ECM fungi and show that inoculation with L. deliciosus will better enhance Al tolerance in P. massoniana seedlings used for forest plantation and ecosystem restoration in acidic soils, particularly in Southwest China and similar soils worldwide.

Chinese peony (Paeonia lactiflora Pall.) is both medicinally and aesthetically beneficial. Powdery mildew is a common fungal disease that seriously jeopardizes the value of numerous species, including peonies as a crop. In order to provide a basis for the prevention and treatment of peony powdery mildew, we examined the microbial diversity, the malondialdehyde (MDA) concentrations and antioxidant enzyme activities of peony leaves infected with three levels of powdery mildew to determine any modifications to the leaf's antioxidant enzyme systems and microbial community structure following the onset of disease. The results show that the MDA content rose as the degree of infection became worse. Antioxidant enzyme activity rose and then declined. Following the initiation of powdery mildew, fungal community diversity decreased, whereas there was not any appreciable change in bacterial communities according to microbial diversity sequencing. The relative abundance of more than half of fungal species decreased, with the bacterial genera displaying both abundant and diminished communities with less pronounced alterations in their community structure after the disease spread. Significant different taxa that were critical to the organization of each microbiome were found. Correlation analysis showed that the relative abundance of powdery mildew pathogenic fungal genus Erysiphe was correlated with those of 11 fungal genera and one bacterial genus. Among them, Aureobasidium, Neosetophoma and Sclerostagonospora showed significant positive correlations with Erysiphe and MDA.

Ontogenetic aging of tissues and the gradual decrease of adventitious rooting are known challenges for the clonal propagation of woody species, hampering clonal forestry programs. This study examined possible signatures of tissue rejuvenation/reinvigoration in different propagated materials of Eucalyptus microcorys by analyzing the total protein profile, peroxidase activity, macro- and micronutrient contents, and adventitious rooting of mini cuttings. The analyses were performed on E. microcorys shoots which were successfully obtained by seminal and grafting propagation, micropropagation with epicormic shoots, and indirect organogenesis. Among four mature trees used in the propagation, tissues from the one with the best propagation results were investigated for signs of tissue rejuvenation and/or reinvigoration. Five individuals from each technique were randomly selected and transferred to a semi-hydroponic “channel” system. After four weeks in the seedbed, the total protein, peroxidase activity, nutrient content and rooting of the mini cuttings were evaluated. SDS-PAGE enabled the differentiation of leaf samples obtained by grafting from the other propagation techniques, as revealed by two distinct bands. Materials obtained by micropropagation with epicormic shoots showed the highest peroxidase activity, while those obtained by seminal propagation and from the selected mature tree showed the lowest peroxidase activity. A portable X-ray fluorescence spectroscope (pXRF) identified adequate nutrient content in most of the nutrients tested in materials obtained by seminal and grafting propagation, and by indirect organogenesis. The analysis of adventitious rooting showed that the highest rooting percentage was observed in mini cuttings from seminal propagation (75%) followed by indirect organogenesis (35%). Based on principal component analysis, it was concluded that rooting of mini cuttings from both seminal propagation and indirect organogenesis was associated with phosphorous, sulphur, and potassium contents, which suggests a higher level of tissue rejuvenation/reinvigoration in these propagated plants. Further studies are recommended to search for other methods that present similarities with the responses to adventitious rooting in forest species and thus optimize the rescue and propagation of plants with distinct ontogenetic stages.

Allelopathy is an important mechanism in Eucalyptus plantations that causes detrimental impacts on understory diversity. Phenolic compounds are the main allelochemicals suppressing understory plants. However, the dynamic changes in phenolic allelochemicals and their relationship with understory diversity with increasing age of Eucalyptus plantations remain largely unclear. In this study, the understory plant diversity was assessed and phenolic compounds identified from leaf litter, roots, and rhizosphere soil samples in a Eucalyptus grandis plantation at two-year intervals for ten years using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The abundance and diversity of under story plant species were lowest in 4-year-old plantations and increased significantly with age. Seven phenolic acids and 10 flavonoids were identified from leaf litter, roots, and rhizosphere soils. Most of the potential phenolic allelochemicals, such as salicylic acid, gallic acid, 4-hydroxybenzoic acid, and epicatechin, were more abundant in younger plantations, especially at 4 years old. The concentrations of phenolic compounds in the rhizosphere zone were significantly lower than in litter and root samples and did not change significantly with an increase in age. Notably, phenolic compounds contributed more to the variation in the understory plants than soil factors. Hydroxyphenyllactic acid, ellagic acid, quercetin, salicylic acid, and 4-hydroxybenzoic acid were the main phenolic compounds explaining the variation in plant diversity with plantation age. These findings indicate that young E. grandis plantations, especially at four years of age, merit a greater focus because of their lower understory plant diversity and higher allelopathic potential.

Wetwood is an abnormal phenomenon in growing trees, which adversely affects growth, subsequent wood processing and economic values of wood products. In this study, the influences of factors such as clones, afforestation methods, site conditions and climate conditions on the characteristics of poplar wetwood were studied through field investigations in 27 clones from 48 sample plots in 28 counties. Results showed that the incidences of wetwood were almost 100% in all plots. Ratios of wetwood area among the 48 plots differed from 15.1 to 90.2%. Wetwood area ratios, moisture contents and pH differed significantly between the 27 clones. Wetwood area ratios of the clones ranged from 18.7 to 62.3%. Ratios of wetwood areas were positively correlated with wetwood moisture content and pH, tree age, and negatively correlated with pH of sapwood. The repeatability of wetwood area ratios was 0.52, moderately controlled by genetics. Wetwood moisture content and pH were highly controlled by genetics, indicated by the repeatability of 0.91 and 0.89, respectively. There were significant differences in wetwood area ratios, moisture content and pH between different site conditions, afforestation methods, and geographical regions. Sloping land had the lowest wetwood area ratios and moisture content among four types of sites. Afforestation by direct seeding and rooted cuttings had the lowest wetwood area ratios and moisture content, respectively. In the three geographical regions, the Yellow River Basin had the lowest wetwood values of all three factors.

Larix gmelinii var. principis-rupprechtii (Mayr.) Pilger is an important native tree species in North China with advantages of fast growth, straight trunk, and good wood properties. The multi-year and multi-site breeding research of families of the species has not been reported previously. Based on diameter at breast height (DBH), height and volume of 25 families on four experimental sites, we calculated variance components, genetic parameters, juvenile and mature trait correlations and made genotype main effect plus genotype × environment interaction effect (GGE) biplot based on the breeding values estimated using the method of best linear unbiased prediction (BLUP). Compared with height, DBH and volume had higher heritability and larger variation coefficients, making them the more suitable traits for family selection and evaluation. Based on these, GGE biplots containing 20 combinations of site × age were drawn using data at 13 to 17 years when the interactions between family and location were strong. Test sites classifications based on DBH, and volume were inconsistent, with two categories for DBH and one for volume. The Guyuan site was the most suitable with strong discriminating ability, high representativeness and stability among tree ages. Integrating the ranking results of DBH and volume, families 66, 76, 82 and 111 were high-yielding and stable, families 78 and 96 were high-yielding with above average stability, families 72 and 79 were high-yielding with below average stability, whereas stability of family 100 was inconsistent between DBH and volume. Early selection based on DBH was convenient and reliable, and can be made at seven years. This study provides support for the selection of Larix gmelinii var. principis-rupprechtii families in Hebei province and an example for the application of stem analysis data from multiple sites in tree breeding.