This paper introduces a new method of calculating crown projection area (CPA), the area of level ground covered by a vertical projection of a tree crown from measured crown radii through numerical interpolation and integration. This novel method and other four existing methods of calculating CPA were compared using detailed crown radius measurements from 30 tall trees of Eucalyptus pilularis variable in crown size, shape, and asymmetry. The four existing methods included the polygonal approach and three ways of calculating CPA as the area of a circle using the arithmetic, geometric and quadratic mean radius. Comparisons were made across a sequence of eight non-consecutive numbers (from 2 to 16) of measured crown radii for each tree over the range of crown asymmetry of the 30 trees through generalized linear models and multiple comparisons of means. The sequence covered the range of the number of crown radii measured for calculating the CPA of a tree in the literature. A crown asymmetry index within the unit interval was calculated for each tree to serve as a normative measure. With a slight overestimation of 2.2% on average and an overall mean error size of 7.9% across the numbers of crown radii that were compared, our new method was the least biased and most accurate. Calculating CPA as a circle using the quadratic mean crown radius was the second best, which had an average overestimation of 4.5% and overall mean error size of 8.8%. These two methods remained by and large unbiased as crown asymmetry increased, while the other three methods showed larger bias of underestimation. For the conventional method of using the arithmetic mean crown radius to calculate CPA as a circle, bias correction factors were developed as a function of crown asymmetry index to delineate the increasing magnitude of bias associated with greater degrees of crown asymmetry. This study reveals and demonstrates such relationships between the accuracy of CPA calculations and crown asymmetry and will help increase awareness among researchers and practitioners on the existence of bias in their CPA calculations and for the need to use an unbiased method in the future. Our new method is recommended for calculating CPA where at least four crown radius measurements per tree are available because that is the minimum number required for its use.

The addition of ectomycorrhizal fungi (ECMF), beneficial rhizosphere microorganisms, to the soil can promote plant growth and resistance. Here, Populus davidiana ×  Populus bolleana tissue culture seedlings were grown for 3 months in soils inoculated with one of the species, then seedlings were assessed for mycorrhizal colonization rate and growth, physiological and root traits. Suillus luteus and Populus involutus each formed ectomycorrhizal associations with the seedlings. Seedling height, ground diameter, biomass, and leaf area were significantly greater after treatment with ECMF than in the non-inoculated controls. Treatment improved all physiological and root variables assessed (chlorophylls and carotenoids, cellulose, and soluble sugars and proteins; root length, surface area, projected area, mean diameter, volume, number of root tips). Seedlings inoculated with S. luteus outperformed those inoculated with P. involutus.

In northern China, light and temperature are major limiting factors for plant growth, particularly during seed production and seedling establishment. While previous studies suggested a possible role for the MYB97 gene in cold-stress, confirmation through documented evidence was lacking. In this study, we transformed the MYB97 gene from Iris laevigata into tobacco, and discovered that the gene boosted photosynthesis, photoprotection and resilience to cold. The transgenic tobacco seeds exhibited enhanced germination and accelerated seedling growth. Moreover, these plants had decreased levels of MDA (Malondialdehyde) and relative conductance, coupled with elevated concentrations of proline and soluble sugars. This response was accompanied by heightened activity of antioxidant enzymes during periods of cold stress (4 and − 2 °C). Exposure to low temperatures (0–15 °C) also reduced heights but accentuated primary root growth in transgenic tobacco plants. Additionally, tobacco leaves showed an increased growth along with higher chlorophyll levels, net photosynthetic rates, stomatal conductance, transpiration rates and non-photochemical quenching coefficient. This study shows that IlMYB97 (The MYB97 genes in I. laevigata) improves cold-resistance, and enhances photosynthesis and photoprotective ability, and thus overall growth and development. These findings would offer the genetic resources to further study cold resistance and photosynthesis.

There is considerable interest devoted to old-growth forests and their capacity to store carbon (C) in biomass and soil. Inventories of C stocks in old-growth forests are carried out worldwide, although there is a lack of information on their actual potential for C sequestration. To further understand this, soil organic carbon (SOC) was measured in one of Italy’s best-preserved old-growth forests, the Sasso Fratino Integral Nature Reserve. This reserve is on the World Heritage List along with other ancient beech forests of Europe, and it is virtually untouched due to the steepness of the terrain, even before legal constraints were imposed. Although the sandstone-derived soils are often shallow, they are rich in organic matter. However, no quantification had been carried out. By systematically sampling the topsoil across the forest, we accurately determined the average amount of SOC (62.0 ± 16.9 Mg ha^–1) and nitrogen (4.0 ± 1.2 Mg ha^–1) in the top 20 cm. Using the CENTURY model, future dynamics of SOC stocks were predicted to 2050 according to two climate scenarios, A1F1 and B2, the first of high concern and the second more optimistic. The model projected an increase of 0.2 and 0.3 Mg ha^–1 a^–1 by 2030 under the A1F1 and B2 scenarios, respectively, suggesting that the topsoil in old-growth forests does not reach equilibrium but continues accumulating SOC. However, from 2030 to 2050, a decline in SOC accumulation is predicted, indicating SOC net loss at high altitudes under the worst-case scenario. This study confirms that soils in old-growth forests play a significant role in carbon sequestration. It also suggests that climate change may affect the potential of these forests to store SOC not only in the long term but also in the coming years.

For this study of long-term spatial patterns and trends of active fires in southern hemispheric Africa and on Madagascar from 2001 to 2020, active fire data from the MODIS FIRMS global fire data products were analyzed. The annual center of fire concentration tended to migrate toward the preserved rainforests and nature conservation areas in the Congo Basin and the mountain forests on the northeastern coast of Madagascar. Fire frequency varied seasonally at both study areas. We used geostatistical analysis techniques, such as measures of dispersion and emerging hot spot analysis, to reveal long-term trends in spatial patterns of fire events. In southern hemispheric Africa, the observed active fires tended to drift northward toward the Zambia-DRC border in the Congo basin. This northward migration progressed toward humid rainforests, which were better suited to sustaining repeated fire events. On Madagascar, the observed active fires tended to migrate toward the east coast in protected mountain forests. The spatial patterns of long-term trends showed a concentration of fires in the tropical regions of southern hemispheric Africa. Moreover, smaller clusters of new hot spots were located over eastern South Africa, overlapping with undifferentiated woodlands. On Madagascar, both hot and cold spots were identified and were separated by the highland region in the center of the island. Most of the eastern island was characterized by cold spots that received less precipitation than did the rest of the island. The presence of increasing hots spots in the densely vegetated areas highlights the urgent need for fire prevention and management in this region.

To study non-structural carbohydrate characteristics and nutrient utilization strategies of Pinus yunnanensis under continuous drought conditions, 2-year-old seedlings were planted in pots with appropriate water, light and moderate and severe drought treatments [(80 ± 5), (65 ± 5), (50 ± 5), and (35 ± 5)% of field water-holding capacity]. Non-structural carbohydrates, carbon (C), nitrogen (N), and phosphorus (P) concentrations were measured in each plant component. The results show that: (1) With increasing drought, non-structural carbohydrates gradually increased in leaves, stems, and coarse roots, while gradually decreased in fine roots; (2) C concentrations of all were relatively stable under different stress levels. Phosphorous utilization of each component increased under light and moderate drought conditions, while N and P utilization efficiency of each plant component decreased under severe drought. Growth was mainly restricted by N, first decreasing and then increasing with increased drought; (3) There was a correlation between the levels of non-structural carbohydrates and C, N, and P in each component. Changes in N concentration affected the interconversion between soluble sugar and starch, which play a regulatory role in the fluctuation of the concentration of non-structural carbohydrates; and, (4) Plasticity analysis showed that P. yunnanensis seedlings responded to drought mainly by altering starch concentration, the ratio of soluble sugar to starch in leaves and stems, and further by altering N and P utilization efficiencies. Overall, these results suggest that the physiological activities of all organs of P. yunnanensis seedlings are restricted under drought and that trade-offs exist between different physiological indicators and organs. Our findings are helpful in understanding non-structural carbohydrate and nutrient adaptation mechanisms under drought in P. yunnanensis seedlings.

This study comprehensively assessed long-term vegetation changes and forest fragmentation dynamics in the Himalayan temperate region of Pakistan from 1989 to 2019. Four satellite images, including Landsat-5 TM and Landsat-8 Operational Land Imager (OLI), were chosen for subsequent assessments in October 1989, 2001, 2011 and 2019. The classified maps of 1989, 2001, 2011 and 2019 were created using the maximum likelihood classifier. Post-classification comparison showed an overall accuracy of 82.5% and a Kappa coefficient of 0.79 for the 2019 map. Results revealed a drastic decrease in closed-canopy and open-canopy forests by 117.4 and 271.6 km², respectively, and an increase in agriculture/farm cultivation by 1512.8 km². The two-way ANOVA test showed statistically significant differences in the area of various cover classes. Forest fragmentation was evaluated using the Landscape Fragmentation Tool (LFT v2.0) between 1989 and 2019. The large forest core (> 2.00 km²) decreased from 149.4 to 296.7 km², and a similar pattern was observed in medium forest core (1.00–2.00 km²) forests. On the contrary, the small core (< 1.00 km²) forest increased from 124.8 to 145.3 km² in 2019. The perforation area increased by 296.9 km², and the edge effect decreased from 458.9 to 431.7 km². The frequency of patches also increased by 119.1 km². The closed and open canopy classes showed a decreasing trend with an annual rate of 0.58% and 1.35%, respectively. The broad implications of these findings can be seen in the studied region as well as other global ecological areas. They serve as an imperative baseline for afforestation and reforestation operations, highlighting the urgent need for efficient management, conservation, and restoration efforts. Based on these findings, sustainable land-use policies may be put into place that support local livelihoods, protect ecosystem services, and conserve biodiversity.

Forest hydrology, the study of water dynamics within forested catchments, is crucial for understanding the intricate relationship between forest cover and water balances across different scales, from ecosystems to landscapes, or from catchment watersheds. The intensified global changes in climate, land use and cover, and pollution that occurred over the past century have brought about adverse impacts on forests and their services in water regulation, signifying the importance of forest hydrological research as a re-emerging topic of scientific interest. This article reviews the literature on recent advances in forest hydrological research, intending to identify leading countries, institutions, and researchers actively engaged in this field, as well as highlighting research hotspots for future exploration. Through a systematic analysis using VOSviewer, drawing from 17,006 articles retrieved from the Web of Science Core Collection spanning 2000–2022, we employed scientometric methods to assess research productivity, identify emerging topics, and analyze academic development. The findings reveal a consistent growth in forest hydrological research over the past two decades, with the United States, Charles T. Driscoll, and the Chinese Academy of Sciences emerging as the most productive country, author, and institution, respectively. The Journal of Hydrology emerges as the most co-cited journal. Analysis of keyword co-occurrence and co-cited references highlights key research areas, including climate change, management strategies, runoff-erosion dynamics, vegetation cover changes, paired catchment experiments, water quality, aquatic biodiversity, forest fire dynamics and hydrological modeling. Based on these findings, our study advocates for an integrated approach to future research, emphasizing the collection of data from diverse sources, utilization of varied methodologies, and collaboration across disciplines and institutions. This holistic strategy is essential for developing sustainable approaches to forested watershed planning and management. Ultimately, our study provides valuable insights for researchers, practitioners, and policymakers, guiding future research directions towards forest hydrological research and applications.

Forest fires are frequent under a Mediterranean climate and have shaped the landscape of the region but are currently altered by human action and climate change. Fires have historically conditioned the presence of pine forests, depending on severity and forest regeneration. Regeneration of Mediterranean pine forests is not always successful, and a transition to shrublands or stands of resprouting species can occur, even after reforestation. This study analyses vegetation changes in two Mediterranean pine forests after severe fires and both reforested. The pines had difficulty to regenerate, even despite post-fire reforestation. The problem is the difficulty of young seedlings to survive, possibly due to increased summer drought. Problems are greater in pine species at the limit of their ecological tolerance: Pinus pinea had a much better recovery success while P. sylvestris and P. nigra virtually disappeared. Pinus pinaster had intermediate results but recovery was generally poor. A transition has taken place in many burnt areas to scrubland or to thickets of the resprouting Quercus rotundifolia, although it is not possible to know whether they will evolve into forests or remain in a sub climatic state. Resprouting species may increase fire severity but facilitates post-fire colonisation. Post-fire recovery difficulties are closely linked to issues of natural regeneration. Fire could initiate the disappearance of pine forests, but even in the absence of fire they may disappear in the long-term due to the lack of regeneration. Action is needed to increase the resilience of these forests, ensuring natural regeneration, and incorporating resprouting species in the understorey.

The reverse J-shaped diameter distribution is considered an inherent attribute of natural forests, crucial for forest resource utilization and community stability. However, in karst regions, intense habitat heterogeneity might alter species composition, spatial distribution, growth, biomass allocation, and mortality processes, yet its impact on diameter structure remains unclear. A fixed plot of 200 m × 110 m was established in the Nanpan River Basin, Southwest China, within an old-growth oak forest (> 300 years old), and the influence of site substrates (i.e., rock and soil), topographic factors, sample area, and orientation on diameter distribution was analyzed. Trees on both rock and soil exhibited a reverse-J shape, quantifiable through the Weibull function. The substrates had a similar density, approximately 2100 plants/ha. However, the average and range of diameter of trees on rock were smaller than those on soil, suggesting that rock constrains tree growth. The diameter distribution of trees across microtopography also displayed a reverse-J shape. Yet, higher elevations and sunny slopes showed a greater curvature of diameter classes compared to lower elevations and shady slopes, indicating habitat preferences in karst trees. Sample area and orientation had minimal effects on diameter class curve that reached stability when the plot size was 6000 m². These results suggest that the reverse J-shaped diameter distribution prevails at small scales in karst old-growth forests, encompassing multiple curvatures and spanning forest ecosystems.

Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), one of the most commercially important tree species in western North America and one of the most valuable timber trees worldwide, was introduced to Europe in 1827. It became a major species for afforestation in Western Europe after WWII, currently grows in 35 countries on over 0.83 million ha and is one of the most widespread non-native tree species across the continent. A lower sensitivity to drought makes Douglas-fir a potential alternative to the more drought-sensitive Norway spruce so its importance in Europe is expected to increase in the future. It is one of the fastest growing conifer species cultivated in Europe, with the largest reported dimensions of 2.3 m in diameter and 67.5 m in height. Pure stands have high productivity (up to 20 m³ ha⁻¹a⁻¹) and production (over 1000 m³ ha⁻¹). The species is generally regenerated by planting (initial stocking density from less than 1000 seedlings ha⁻¹ to more than 4000 ha⁻¹), using seedlings of European provenance derived from seed orchards or certified seed stands. As the range of end-uses of its wood is very wide, the rotation period of Douglas-fir is highly variable and ranges between 40 and 120 years. When the production of large-sized, knot-free timber is targeted, thinnings are always coupled with pruning up to 6 m. There is an increasing interest in growing Douglas-fir in mixtures and managing stands through close-to-nature silviculture, but the species’ intermediate shade tolerance means that it is best managed through group selection or shelterwood systems.

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.

Due to the lack of a uniform and accurate definition of ‘drought’, several indicators have been introduced based on different variables and methods, and the efficiency of each of these is determined according to their relationship with drought. The relationship between two drought indices, SPI (standardized precipitation index) and SPEI (standardized precipitation-evapotranspiration index) in different seasons was investigated using annual rings of 15 tree samples to determine the effect of drought on the growth of oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests of northern Iran. The different evapotranspiration calculation methods were evaluated on SPEI efficiency based on Hargreaves-Samani, Thornthwaite, and Penman–Monteith methods using the step-by-step M5 decision tree regression method. The results show that SPEI based on the Penman–Monteith in a three-month time scale (spring) had similar temporal changes and a better relationship with annual tree rings (R ² = 0.81) at a 0.05 significant level. Abrupt change and a decreasing trend in the time series of annual tree rings are similar to the variation in the SPEI based on the Penman–Monteith method. Factors affecting evapotranspiration, temperature, wind speed, and sunshine hours (used in the Penman–Monteith method), increased but precipitation decreased. Using non-linear modeling methods, SPEI based on Penman–Monteith best illustrated climate changes affecting tree growth.

COVID-19 posed challenges for global tourism management. Changes in visitor temporal and spatial patterns and their associated determinants pre- and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed. Data was collected through social media programming and analyzed using spatiotemporal analysis and a geographically weighted regression (GWR) model. Results highlight that COVID-19 significantly changed park visitation patterns. Visitors tended to explore more remote areas peri-pandemic. The GWR model also indicated distance to nearby trails was a significant influence on visitor density. Our results indicate that the pandemic influenced tourism temporal and spatial imbalance. This research presents a novel approach using combined social media big data which can be extended to the field of tourism management, and has important implications to manage visitor patterns and to allocate resources efficiently to satisfy multiple objectives of park management.

Acorn production in oaks (Quercus spp.) shows considerable inter-annual variation, known as masting. The effects of pollen sourced from trees within or outside the stand on acorn production were investigated in pedunculate oak (Quercus robur L.) in an ancient mixed woodland during two moderate masting years. Comparisons were made between natural pollination, hand pollinations with out-of-stand pollen, in-stand pollen or a 1:1 combination of the two pollen sources, and for bagged flowers left unpollinated. After all treatments, > 85% of the flowers or developing acorns were aborted between May and August of both years. When flowers were protected with pollen bags and no pollen added, no acorns were produced. In contrast, hand pollination with out-of-stand pollen produced the most acorns both years and significantly more than within-stand pollen or natural pollination in 2022. Hand pollination with out-of-stand or within-stand pollen provided significantly more acorns than natural pollination in 2023. In 2022, hand pollination with a 1:1 mixture of out-of-stand and within-stand pollen yielded an intermediate number of mature acorns between those for the out-of-stand and within-stand pollination treatments. The study provides clear evidence of maternal choice during acorn development in pedunculate oak and of the benefits of pollen supplementation. It also confirms that pedunculate oak is a fruit-maturation masting species; abortion of pollinated flowers and immature acorns determines a mast year (rather than the number of flowers produced) at this site.

Fraxinus mandshurica Rupr. is one of the main afforestation species in northeast China, and there is great demand for improved F. mandshurica varieties. The results of an investigation into and analysis of the growth traits of F. mandshurica provenances and families showed that there were significant differences in different periods. However, variations in growth traits decreased year by year. There was a significant negative correlation between tree heights of the provenances and sunshine hours in their areas of origin. The provenances of Xinglong, Hailin and Wuchang were selected based on the volume of 18-year-old trees. The average genetic gain from the selection of fast-growing provenances was 19.4%. Ten superior fast-growing families were selected. The average volume of the selected families was 22.6%, higher than that of all families. The correlation coefficient between heights at 6-year-old and at 18a was 0.838 for provenances, and between heights at 4-year-old and at 18-year-old was 0.303 for families. These results indicate that early selection for height in provenances or families could be performed at 6 years or 4 years, respectively. Early selection for DBH and volume in families could start at 8 years.

Non-photosynthetic components within a forest ecosystem account for a large proportion of the canopy but are not involved in photosynthesis. Therefore, the accuracy of gross primary production (GPP) estimates is expected to improve by removing these components. However, their influence in GPP estimations has not been quantitatively evaluated for deciduous forests. Several vegetation indices have been used recently to estimate the fraction of photosynthetically active radiation absorbed by photosynthetic components (

) for partitioning

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(photosynthetically active radiation absorbed by photosynthetic components). In this study, the enhanced vegetation index (EVI) estimated

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and to separate the photosynthetically active radiation absorbed by photosynthetic components (

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) from total APAR observations (

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) at two deciduous forest sites. The eddy covariance-light use efficiency (EC-LUE) algorithm was employed to evaluate the influence of non-photosynthetic components and to test the performance of

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in GPP estimation. The results show that the influence of non-photosynthetic components have a seasonal pattern at deciduous forest sites, large differences are observed with normalized root mean square error (RMSE^*) values of

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-based GPP and

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-based GPP between tower-based GPP during the early and end stages, while slight differences occurred during peak growth seasons. In addition, daily GPP estimation was significantly improved using the

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-based method, giving a higher coefficient of determination and lower normalized root mean square error against the GPP estimated by the

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-based method. The results demonstrate the significance of partitioning

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from

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for accurate GPP estimation in deciduous forests.

In recent years, the situation of the Hyphantria cunea (Drury) (Lepidoptera: Erebidae), infestation in China has been serious and has a tendency to continue to spread. A comprehensive analysis was carried out to examine the spatial distribution trends and influencing factors of H. cunea. This analysis involved integrating administrative division and boundary data, distribution data of H. cunea, and environmental variables for 2021. GeoDetector and gravity analysis techniques were employed for data processing and interpretation. The results show that H. cunea exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern China. During these years, the focal point of the infestation was in Shandong Province with a spread towards the northeast. Conditions such as high vegetation density in eastern China provided favorable situations for growth and development of H. cunea. In China, the spatial distribution of the moth is primarily influenced by two critical factors: precipitation during the driest month and elevation. These play a pivotal role in determining the spread of the species. Based on these results, suggestions are provided for a multifaceted approach to prevention and control of H. cunea infestation.

Bushfires are devastating to forest managers, owners, residents, and the natural environment. Recent technological advances indicate a potential for faster response times in terms of detecting and suppressing fires. However, to date, all these technologies have been applied in isolation. This paper introduces the latest fire detection and suppression technologies from ground to space. An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppression. The framework harnesses the advantages of satellite-based, drone, sensor, and human reporting technologies as well as image processing and artificial intelligence machine learning. The study concludes that, if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements, a fire detection and resource suppression system can achieve the ultimate aim: to reduce the risk of fire hazards and the damage they may cause.

Although numerous studies have proposed explanations for the specific and relative effects of stand structure, plant diversity, and environmental conditions on carbon (C) storage in forest ecosystems, understanding how these factors collectively affect C storage in different community layers (trees, shrubs, and herbs) and forest types (mixed, broad-leaved (E), broad-leaved (M), and coniferous forest) continues to pose challenges. To address this, we used structural equation models to quantify the influence of biotic factors (mean DBH, mean height, maximum height, stem density, and basal area) and abiotic factors (elevation and canopy openness), as well as metrics of species diversity (Shannon–Wiener index, Simpson index, and Pielou’s evenness) in various forest types. Our analysis revealed the critical roles of forest types and elevation in explaining a substantial portion of variability in C storage in the overstory layer, with a moderate influence of stand factors (mean DBH and basal area) and a slightly negative impact of tree species diversity (Shannon–Wiener index). Notably, forest height emerged as the primary predictor of C storage in the herb layer. Regression relationships further highlighted the significant contribution of tree species diversity to mean height, understory C storage, and branch biomass within the forest ecosystem. Our insights into tree species diversity, derived from structural equation modeling of C storage in the overstory, suggest that the effects of tree species diversity may be influenced by stem biomass in statistical reasoning within temperate forests. Further research should also integrate tree species diversity with tree components biomass, forest mean height, understory C, and canopy openness to understand complex relationships and maintain healthy and sustainable ecosystems in the face of global climate challenges.

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.

Heat shock transcription factors (Hsfs) have important roles during plant growth and development and responses to abiotic stresses. The identification and function of Hsf genes have been thoroughly studied in various herbaceous plant species, but not woody species, especially Phoebe bournei, an endangered, unique species in China. In this study, 17 members of the Hsf gene family were identified from P. bournei using bioinformatic methods. Phylogenetic analysis indicated that PbHsf genes were grouped into three subfamilies: A, B, and C. Conserved motifs, three-dimensional structure, and physicochemical properties of the PbHsf proteins were also analyzed. The structure of the PbHsf genes varied in the number of exons and introns. Prediction of cis-acting elements in the promoter region indicated that PbHsf genes are likely involved in responses to plant hormones and stresses. A collinearity analysis demonstrated that expansions of the PbHsf gene family mainly take place via segmental duplication. The expression levels of PbHsf genes varied across different plant tissues. On the basis of the expression profiles of five representative PbHsf genes during heat, cold, salt, and drought stress, PbHsf proteins seem to have multiple functions depending on the type of abiotic stress. This systematic, genome-wide investigation of PbHsf genes in P. bournei and their expression patterns provides valuable insights and information for further functional dissection of Hsf proteins in this endangered, unique species.

Atmospheric nitrogen (N) deposition is predicted to increase, especially in the subtropics. However, the responses of soil microorganisms to long-term N addition at the molecular level in N-rich subtropical forests have not been clarified. A long-term nutrient addition experiment was conducted in a subtropical evergreen old-growth forest in China. The four treatments were: control, low N (50 kg N ha⁻¹ a⁻¹), high N (100 kg N ha⁻¹ a⁻¹), and combined N and phosphorus (P) (100 kg N ha⁻¹ a⁻¹ + 50 kg P ha⁻¹ a⁻¹). Metagenomic sequencing characterized diversity and composition of soil microbial communities and used to construct bacterial/fungal co-occurrence networks. Nutrient-treated soils were more acidic and had higher levels of dissolved organic carbon than controls. There were no significant differences in microbial diversity and community composition across treatments. The addition of nutrients increased the abundance of copiotrophic bacteria and potentially beneficial microorganisms (e.g., Gemmatimonadetes, Chaetomium, and Aureobasidium). Low N addition increased microbiome network connectivity. Three rare fungi were identified as module hubs under nutrient addition, indicating that low abundance fungi were more sensitive to increased nutrients. The results indicate that the overall composition of microbial communities was stable but not static to long-term N addition. Our findings provide new insights that can aid predictions of the response of soil microbial communities to long-term N addition.

Increasing human activity is altering the structure of forests, which affects the composition of communities, including birds. However, little is known about the key forest structure variables that determine the richness of bird communities in European temperate oak forests. We, therefore, aimed to identify key variables in these habitats that could contribute to the design of management strategies for forest conservation by surveying 11 oak-dominated forest sites throughout the mid-mountain range of Hungary at 86 survey points to reveal the role of different compositional and structural variables for forest stands that influence the breeding bird assemblages in the forests at the functional group and individual species levels. Based on decision tree modelling, our results showed that the density of trees larger than 30 cm DBH was an overall important variable, indicating that large-diameter trees were essential to provide diverse bird communities. The total abundance of birds, the foliage-gleaners, primary and secondary cavity nesters, residents, and five specific bird species were related to the density of high trunk diameter trees. The abundance of shrub nesters was negatively influenced by a high density of trees over 10 cm DBH. The density of the shrub layer positively affected total bird abundance and the abundance of foliage gleaners, secondary cavity nesters and residents. Analysis of the co-dominant tree species showed that the presence of linden, beech, and hornbeam was important in influencing the abundance of various bird species, e.g., Eurasian Treecreeper (Certhia familiaris), Marsh Tit (Poecile palustris) and Wood Warbler (Phylloscopus sibilatrix). Our results indicated that large trees, high tree diversity, and dense shrub layer were essential for forest bird communities and are critical targets for protection to maintain diverse and abundant bird communities in oak-dominated forest habitats.

Urbanization has resulted in a significant degradation of soil quality, subjecting plants to persistent abiotic stressors such as heavy metal pollution, salinization, and drought. UDP-glycosyltransferases (UGTs) participate in protein glycosylation, secondary metabolite synthesis, and detoxification of exogenous toxic substances. Iris sanguinea Donn ex Hornem exhibits a high degree of resistance to various abiotic stressors. To enhance the plant’s response to adversity, a novel glycosyltransferase belonging to the UGT78 family, encoding flavonoid 3-O-glucosyltransferase (UF3GT), was cloned from the monocot species I. sanguinea. Compared with the control group, overexpression of IsUGT78 enhanced sensitivity to cadmium stress, while showing no significant impact under NaCl and d-sorbitol treatments. Under cadmium treatment, arabidopsis exogenously transformed with the IsUGT78 gene possessed lower germination, fresh weight, root length, and chlorophyll content and increased malondialdehyde content than the wild type arabidopsis. In addition, metabolomics in leaves led to the identification of 299 flavonoid metabolites, eight and 127 which were significantly up- and down-regulated, respectively, in the transgenic plants. Of note, all eight upregulated flavonoid compounds were glycosylated. Given that arabidopsis, which exogenously expresses the IsUGT78 gene, has reduced resistance to cadmium, IsUGT78 may lead to a reduced ability to cope with cadmium stress.

Investing in projects that support environmental benefits, such as tree harvesting, has the potential to reduce air pollution levels in the atmosphere in the future. However, this kind of investment may increase the current level of emissions. Therefore, it is necessary to estimate how much the policy affects the current level of CO₂ emissions. This makes sure the policy doesn’t increase the level of CO₂ emissions. This study aims to analyze the effect of the One Billion Trees program on CO₂ emissions in New Zealand by employing the 2020 input–output table analysis. This investigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand. The results of this study for the first year of plantation suggest that the policy increases the level of CO₂ emissions in all regions, especially in the Waikato region. The direct and indirect impact of the policy leads to 64 kt of CO₂ emissions on the demand side and 270 kt of CO₂ emissions on the supply side. These lead to 0.19 and 0.74% of total CO₂ emissions being attributed to investment shocks. Continuing the policy is recommended, as it has a low effect on CO₂ emissions. However, it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.

Urbanization provides both challenges and opportunities for biodiversity conservation, but patterns of urban plant diversity across land uses, especially in Asian countries, remains unclear. To determine these patterns of diversity, woody plants in 174 sample quadrats across various land use types in Kyoto City were investigated. Richness, abundance, and evenness were evaluated at city, land use, and quadrat scales, and biodiversity of different land use types was compared. At the city level, 223 species in 77 families were recorded. At the land use level, residential areas had the highest total biological richness, with moderate to low evenness, while commercial areas exhibited low richness. At the quadrat level, the low-rise residential area had higher species richness than the other land uses. Species abundance and evenness in quadrats were significantly different across land use types for the canopy layer but not for the understory. The results provide insights into urban biodiversity design and management by identifying prior land uses for biodiversity improvement and by highlighting the contribution of residential private yards. Urban heterogeneity, scale, and multidimensionality should be considered when measuring urban biodiversity.

To evaluate the relationships among clones and open pollinated families from the same plus trees and to select elite breeding materials, growth, and wood characteristics of 33-year-old Pinus koraiensis clones and families were measured and analyzed. The results show that growth and wood characters varied significantly. The variation due to clonal effects was higher than that of family effects. The ratio of genetic to phenotypic coefficient of variation of clones in growth and wood traits was above 90%, and the repeatability of these characteristics was more than 0.8, whereas the ratio of genetic to phenotypic coefficient of variation of families was above 90%. The broad-sense heritability of all characteristics exceeded 0.4, and the narrow-sense family heritability of growth traits was less than 0.3. Growth characteristics were positively correlated with each other, but most wood properties were weakly correlated in both clones and families. Fiber length and width were positively correlated between clones and families. Using the membership function method, eleven clones and four families were selected as superior material for improved diameter growth and wood production, and two families from clonal and open-pollinated trees showed consistently better performance. Generally, selection of the best clones is an effective alternative to deployment of families as the repeatability estimates from clonal trees were higher than narrow-sense heritability estimates from open pollinated families. The results provide valuable insight for improving P. koraiensis breeding programs and subsequent genetic improvement.

Effective development and utilization of wood resources is critical. Wood modification research has become an integral dimension of wood science research, however, the similarities between modified wood and original wood render it challenging for accurate identification and classification using conventional image classification techniques. So, the development of efficient and accurate wood classification techniques is inevitable. This paper presents a one-dimensional, convolutional neural network (i.e., BACNN) that combines near-infrared spectroscopy and deep learning techniques to classify poplar, tung, and balsa woods, and PVA, nano-silica-sol and PVA-nano silica sol modified woods of poplar. The results show that BACNN achieves an accuracy of 99.3% on the test set, higher than the 52.9% of the BP neural network and 98.7% of Support Vector Machine compared with traditional machine learning methods and deep learning based methods; it is also higher than the 97.6% of LeNet, 98.7% of AlexNet and 99.1% of VGGNet-11. Therefore, the classification method proposed offers potential applications in wood classification, especially with homogeneous modified wood, and it also provides a basis for subsequent wood properties studies.

Vegetation productivity on the southern edge of the Inner Mongolian Plateau, which plays a vital role in the ecological environment and in the arable and pastoral production in this region, can be characterized by the NDVI (normalized difference vegetation index). However, the observed NDVI data span only the last ~ 40 years. The growth of Pinus tabulaeformis Carr. is strongly correlated with the NDVI, making it a valuable proxy for extending the length of observed NDVI datasets. In this study, we reconstructed an NDVI series for 1776–2021 for the Daqing Mountains, based on a tree-ring width chronology. The reconstructed data accounted for 55% of the variance in the observed data, and its statistical characteristics and validation indicate that the reconstruction is dependable. Spatial correlation analysis demonstrated the consistency of climate signals in central Inner Mongolia in both the arable and pastoral zones. The results of superposed epoch analysis revealed a good temporal consistency between drought and flood events and the reconstructed NDVI sequence in this region.

Anthropogenic disturbances are widespread in tropical forests and influence the species composition in the overstory. However, the impacts of historical disturbance on tropical forest overstory recovery are unclear due to a lack of disturbance data, and previous studies have focused on understory species. In this study, the purpose was to determine the influence of historical disturbance on the diversity, composition and regeneration of overstory species in present forests. In the 20-ha Xishuangbanna tropical seasonal rainforest dynamics plot in southwestern China, the historical disturbance boundaries were delineated based on panchromatic photographs from 1965. Factors that drove species clustering in the overstory layer (DBH ≥ 40 cm) were analyzed and the abundance, richness and composition of these species were compared among different tree groups based on multiple regression tree analysis. The coefficient of variation of the brightness value in historical panchromatic photographs from 1965 was the primary driver of species clustering in the overstory layer. The abundance and richness of overstory species throughout the regeneration process were similar, but species composition was always different. Although the proportion of large-seeded and vigorous-sprouting species showed no significant difference between disturbed and undisturbed forests in the treelet layer (DBH < 20 cm), the difference became significant when DBH increased. The findings highlight that historical disturbances have strong legacy effects on functional group composition in the overstory and the recovery of overstory species was multidimensional. Functional group composition can better indicate the dynamics of overstory species replacement during secondary succession.

Evaluating long-term changes in precipitation resources is important for accurate hydrological evaluation and forecasting, water security and rational allocation of water resources. For this purpose in the Xinjiang Habahe area, tree-ring specimens were collected from Picea obovata, Larix sibirica, and Betula platyphylla to establish a tree-ring width chronology, which was used to analyse a correlation with the average temperature and precipitation per month for 1958–2016. Based on correlation coefficients for monthly temperature and precipitation with the chronology of tree-ring widths, radial tree growth was mainly restricted by precipitation, and tree-ring width chronology was significantly correlated with overall precipitation from the previous July to the next June (r = 0.641, P < 0.01). The above results were used to establish a transformation equation, and the overall precipitation from the previous July to the following June from 1800 to 2016 in Habahe was reconstructed after adjusted degrees of freedom, and obtain an explanatory rate of the variation up to 41.1% (40.0%). In addition to the reliability of the reconstructed values, the stability of the conversion function was determined via the “leave-one-out” method, which is commonly used in research on tree rings, and by cross-checking the conversion function with the reduced error value (RE), product mean test (t), with a sign test (ST). During the last 217 years, there were nine dry periods: 1803–1829, 1861–1865, 1872–1885, 1892–1905, 1916–1923, 1943–1954, 1961–1966, 1973–1981, and 2005–2011; and 12 wet periods: 1830–1834, 1836–1860, 1866–1871, 1886–1891, 1906–1915, 1925–1930, 1934–1942, 1955–1960, 1967–1972, 1982–1996, 2000–2004, and 2012–2016. Comparisons of the reconstructions for neighboring regions and a spatial correlation analysis showed that the reconstructed sequence of the present precipitation data better represented the changes in precipitation in Habahe. Additionally, a power spectrum analysis revealed that precipitation over the past 217 years in Habahe Province exhibited 2–5 years of quasiperiodic variation. A power spectrum analysis and wavelet analysis indicated that El Niño-Southern Oscillation influenced the precipitation cycles. This reconstruction provides more information on high-frequency precipitation, which is an important supplement to the existing tree-ring reconstruction of precipitation in the study area. The reconstruction of regional high-resolution precipitation changes over the last several hundred years provides unique, important data for understanding regional differences in climate at the decadal-centennial scale.

In the context of ongoing climate change, relationships between tree growth and climate present uncertainties, which limits the predictions of future forest dynamics. Northwest China is a region undergoing notable warming and increased precipitation; how forests in this region will respond to climate change has not been fully understood. We used dendrochronological methods to examine the relationship between climate and the radial growth of four tree species in a riparian forest habitat in Altai region: European aspen (Populus tremula), bitter poplar (Populus laurifolia), Swedish birch (Betula pendula), and Siberian spruce (Picea obovata). The results reveal that European aspen was insensitive to climate changes. In contrast, bitter poplar showed a positive response to elevated temperatures and negative to increased moisture during the growing season. Swedish birch and Siberian spruce were adversely affected by higher temperatures but benefited from increased precipitation. A moving correlation analysis suggested that, against a backdrop of continuous warming, growth patterns of these species will diverge: European aspen will require close monitoring, bitter poplar may likely to show accelerated growth, and the growth of Swedish birch and Siberian spruce may be inhibited, leading to a decline. These findings offer insight into the future dynamics of riparian forests under changing climate.

This study assessed the effect of patch scarification and mounding on the physical properties of the root layer and the success of tree planting in various types of forests. This study was conducted on 12 forest sites in taiga forests of the European part of Russia. A total of 54 plots were set up to assess seedling survival; root collar diameter, height, and heigh increment were measured for 240 seedlings to assess growth. In the rooting layer, 240 soil samples were taken to determine physical properties. The study showed that soil treatment methods had no effect on bulk density and total porosity in Cladina sites. However, reduced soil moisture was noted, particularly in mounds, resulting in increased aeration. In Myrtillus sites, there were increased bulk density, reduced soil moisture, and total porosity in the mounds. Mounding treatment in Polytrichum sites resulted in reduced soil moisture and increased aeration porosity. In the Myrtillus and Polytrichum sites, patch scarification had no effects on physical properties. In Polytrichum sites, survival rates, heights, and heigh increments of bareroot Norway spruce seedlings in mounds were higher than in patches; however, the same did not apply to diameter. In Cladina and Myrtillus sites, there was no difference in growth for bareroot and containerised seedlings with different soil treatments. Growing conditions and soil types should be considered when applying different soil treatment methods to ensure high survival rates and successful seedling growth.

Thinning is an effective management step for sustainable forest development, yet less attention is paid to the restoration of soil microbiota after thinning. In this study, both abundant and rare soil microbial communities (i.e., bacterial, fungal), were evaluated under various thinning treatments in a mixed stand of Cunninghamia lanceolata and Sassafras tzumu using MiSeq sequencing. Thinning did not significantly change either abundant or rare bacterial and fungal community composition, but affected their alpha diversity. The Shannon– Wiener indexes of rare fungal taxa under medium thinning were significantly lower than in the light thinning (P < 0.05 level). Xanthobacteraceae dominated the abundant bacterial taxa, and Saitozyma and Mortierlla the abundant fungal taxa. The most common rare bacterial taxa varied; there was no prevalent rare fungal taxa under different thinnings. In addition, soil available nitrogen, total phosphorus, and pH had significant effects on rare bacterial taxa. Nutrients, especially available phosphorus, but not nitrogen, affected abundant and rare soil fungi. The results indicate that soil properties rather than plant factors affect abundant and rare microbial communities in soils of mixed stands. Thinning, through mediating soil properties, influences both abundant and rare bacterial and fungal communities in the mixed C. lanceolata and S. tzumu stand.

The combined use of LiDAR (Light Detection And Ranging) scanning and field inventories can provide spatially continuous wall-to-wall information on forest characteristics. This information can be used in many ways in forest mapping, scenario analyses, and forest management planning. This study aimed to find the optimal way to obtain continuous forest data for Catalonia when using kNN imputation (kNN stands for “k nearest neighbors”). In this method, data are imputed to a certain location from k field-measured sample plots, which are the most similar to the location in terms of LiDAR metrics and topographic variables. Weighted multidimensional Euclidean distance was used as the similarity measure. The study tested two different methods to optimize the distance measure. The first method optimized, in the first step, the set of LiDAR and topographic variables used in the measure, as well as the transformations of these variables. The weights of the selected variables were optimized in the second step. The other method optimized the variable set as well as their transformations and weights in one single step. The two-step method that first finds the variables and their transformations and subsequently optimizes their weights resulted in the best imputation results. In the study area, the use of three to five nearest neighbors was recommended. Altitude and latitude turned out to be the most important variables when assessing the similarity of two locations of Catalan forests in the context of kNN data imputation. The optimal distance measure always included both LiDAR metrics and topographic variables. The study showed that the optimal similarity measure may be different for different regions. Therefore, it was suggested that kNN data imputation should always be started with the optimization of the measure that is used to select the k nearest neighbors.

Under global warming, drought will reduce productivity of Pinus halepensis s.l. (subspecies halepensis and brutia) and cause a retreat from its rear edge distribution (latitudinal/elevational) in the Mediterranean. To test whether topography can influence this scenario, we studied for approximately 40 years the growth of six natural pine stands in water-limited habitats on the islands of Zakinthos and Samos (eastern Mediterranean Greece), and determined the critical moisture sources that drove pine growth. Dominant pines were selected with no permanent water sources under contrasting moisture conditions created by topography (“wet”-gulley/valley vs. “dry”-upslope habitats). The responses of P. halepensis s.l. to drought under a moderate and a worst case scenario were tested, projected under global warming (approx. − 25% and 40% in annual precipitation compared to 1961–1990 average). Our results show that “wet” habitat pines had higher productivity under normal to wet climate. However, the more precipitation declined, “wet” habitat tree growth was reduced at a significantly faster rate, but also showed a faster recovery, once rainfall returned. Thus, Pinus halepensis s.l. populations in gullies/valleys, may be more drought resilient and less likely to retreat towards higher elevation/latitudes under global warming, compared to pines on dry upslope sites. Under moderate drought, both ecosystems relied on deeper moisture pools supplied by rainfall of the previous 3–6 years (including the year of growth). However, valley/gully habitat pines on significantly deeper soils (and probably on deeper heavily weathered bedrock), appeared to utilize surface moisture from winter/spring rainfall more efficiently for survival and recovery. Thus, deep soils may provide the key “buffer” for pine survival in such ecosystems that could act as potential refugia for P. halepensis s.l. under climate change.

Effective landscape-scale fuel management strategies are essential for reducing wildfire risk in Mediterranean fire-prone areas. In this study, the minimum travel time (MTT) fire-spread algorithm as implemented in FlamMap was applied to assess the potential of alternative fuel treatments for lowering wildfire losses in a 5,740-ha study area in eastern Sardinia, Italy. Twenty-seven wildfires at 10-m resolution were simulated considering three wind speeds (15, 18, and 21 km h⁻¹) to compare fuel treatments: no treatment (NT), irrigated agroforestry areas with shrub clearing (T1), prescribed fire in eucalyptus stands (T2), and irrigated grasslands (T3). The simulations replicated a recent large wildfire that occurred in the study area (Orrì wildfire, 2019) and considered the weather and fuel moisture conditions associated with this event. The average wildfire exposure outputs (burned area, probability of burning, conditional flame length, potential crown fire occurrence, and surfaces withflame lengths above 2.5 m) decreased after fuel treatments, compared to no treatment. T1 was the most effective strategy in mitigating wildfire hazards and provided the most significant performance for several wildfire exposure indicators. Treating only 0.5% of the study area (~ 30 ha) resulted in a decrease in all wildfire exposure metrics to ~ 10% within the study area. In addition, the total surface characterized by high flame length (average > 2.5 m) was the lowest in the T1 treatment. This study can help land and fire managers optimize fuel treatment opportunities and wildfire risk mitigation strategies in Mediterranean areas.

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.