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Understanding how forest ecosystems respond to environmental factors, particularly in the context of global climate change, is essential for devising effective mitigation strategies. This study focuses on quantifying the interaction between forest ecosystems and atmospheric gases. To achieve our objectives, we are using the eddy covariance (EC) flux method to measure air turbulence and gas concentrations above the forest canopy at the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) in southern Estonia. We apply a flux footprint (FFP) model to describe the spatial extent and position of the surface area contributing to the turbulent flux measurements. The FFP analysis provides valuable insights into the long-term changes in SMEAR Estonia, the FFP and its relationship with forest management and land use changes. Our findings reveal that the FFP area varies from year to year due to changes in wind speed and direction, affecting the contribution of different land cover elements to the overall FFP. The average changes in the FFP area at a height of 30 meters were approximately 4.9%, while those at a height of 70 meters were only 1.6%. Moreover, human activities, such as thinning and clear-cutting, influence the growing stock and increment of forest stands.

Pests, past forest management practices and colonization are all factors in wildfires like Jasper’s -- and the solution requires rethinking the way we protect [...]

How do you heal a forest? In the time it takes you to read this story, (https://www.reuters.com/world/americas/deforestation-brazils-amazon-down-by-50-five-year-low-2023-2024-01-12/) more than 5 acres of rainforest just in the Amazon will likely have [...]

Long-lasting drought records can provide valuable insights into the history of hydroclimate change in central China, but meteorological records are too short to capture long-term variability of the humidity. In this study, we established a tree-ring width chronology of Pinus armandii Franch in the Funiu Mountains region of central China. Correlation analyses showed that tree radial growths were mainly limited by hydrothermal combination in May–June. The results of the moving correlation analysis further showed that the response relationship between tree growth and relative humidity in May–June (RH MJ) was the most stable. This relationship has been reconstructed since 1863. The variance of the reconstructed RH MJ was explained by 41.7% (40.6% after adjusting for degrees of freedom). Over the past 158 years, there were 3 wet periods and 4 dry periods. The spectral analysis revealed that the reconstructed RH MJ exhibited quasi-periods of 2-4a and 31.6a, and cross-spectrum analysis showed that the reconstructed RH MJ may be related to ENSO, PDO, solar activity and the East Asian summer monsoon. The spatial correlation analysis revealed that the reconstructed RH MJ accurately depicted the fluctuations in humidity within the Huanghe-Huaihe Plain. Furthermore, the reconstructed RH MJ exhibited a strong negative correlation with the sea surface temperature (SST) of the subtropical North Pacific, while it displayed a highly significant positive correlation with the SST of the eastern equatorial Pacific from the previous May to the current April. This also indicated a possible link between humidity fluctuations in the Huanghe-Huaihe Plain and the Pacific internal variability in climate system. Therefore, this research aims to expand and complement the existing meteorological records, providing important reference significance for forest management, agriculture, and animal husbandry. [ABSTRACT FROM AUTHOR]

As climate change thrives, and the frequency of intense droughts is affecting many forested regions, a mechanistic understanding of the factors conferring drought tolerance in trees is increasingly important. However, studies linking the observed growth reduction to mechanistic traits are still rare. We compared the median growth anomalies of 16 native tree species, gathered across a network of study plots in Bavaria, with the mean species‐specific turgor loss point (πtlp) measured at five locations in Central Europe πtlp explained 37% of the growth anomalies observed in response to the intense droughts between 2018 and 2020 compared to the pre‐drought period between 2006 and 2017 across sites. πtlp constitutes an important leaf drought tolerance trait and influences the growth response of native tree species during extraordinary dry periods. As climate change‐induced droughts intensify, tree species with drought‐tolerant leaves will be less vulnerable to growth reductions. πtlp provides a useful indicator for selecting tree species to adapt forest management systems to climate change. [ABSTRACT FROM AUTHOR]

Forest management influences the occurrence of tree species, the organic matter input to the soil decomposer system, and hence, it can alter soil microbial community and key ecosystem functions it performs. In this study, we compared the potential effect of different forest management, coppice and high forest, on soil microbial functional diversity, enzyme activities and chemical-physical soil properties in two forests, turkey oak and beech, during summer and autumn. We hypothesized that coppicing influences soil microbial functional diversity with an overall decrease. Contrary to our hypothesis, in summer, the functional diversity of soil microbial community was higher in both coppice forests, suggesting a resilience response of the microbial communities in the soil after tree cutting, which occurred 15–20 years ago. In beech forest under coppice management, a higher content of soil organic matter (but also of soil recalcitrant and stable organic carbon) compared to high forest can explain the higher soil microbial functional diversity and metabolic activity. In turkey oak forest, although differences in functional diversity of soil microbial community between management were observed, for the other investigated parameters, the differences were mainly linked to seasonality. The findings highlight that the soil organic matter preservation depends on the type of forest, but the soil microbial community was able to recover after about 15 years from coppice intervention in both forest ecosystems. Thus, the type of management implemented in these forest ecosystems, not negatively affecting soil organic matter pool, preserving microbial community and potentially soil ecological functions, is sustainable in a scenario of climate change. [ABSTRACT FROM AUTHOR]

Forest fires or wildfires frequently occur in Kazakhstan, especially in the months from June to September, damaging the forest resources. Burnt area mapping is important for fire managers to take appropriate mitigation steps and carry out restoration activities after the fire event. In this study, KazEOSat-1 high-resolution satellite datasets are used to map the burnt area in the regions of Kazakhstan. KazEOSat-1 satellite is in a Sun-synchronous orbit, consisting of four bands, namely blue, green, red, and NIR multispectral bands, in 4  m spatial resolution, while panchromatic data are in 1  m spatial resolution. This study examined three spectral indices, namely AVI, BAI, and GEMI, for mapping the burnt area based on the four spectral bands NIR, blue, red, and green of the KazEOSat-1 satellite datasets. The DN values for each band are used to determine TOA reflectance, which is then used as a basis for deriving the aforementioned spectral indices. The results of spectral indices, AVI, BAI, and GEMI are compared based on a discriminative index (M) for quantifying the effectiveness of each index based on burned area derived from KazEOSat-1 datasets. The spectral index BAI shows higher M values than other indices; therefore, the index BAI has the higher capability to extract the burned area as compared with AVI and GEMI. Accuracy was calculated based on the number of forest fire incidents that fell in burned and unburned areas, and the results indicate that BAI shows the highest accuracy, whereas AVI shows the lowest accuracy among them. Therefore, the BAI has the highest ability for extracting the burned area using the KazEOSat-1 satellite datasets. As the revisit time period of KazEOSat is 3  days, this study will be useful to map the burnt area and fire progression in Kazakhstan. [ABSTRACT FROM AUTHOR]

The sustainability of forest species is directly related to the success of stand regeneration. Assuring success is particularly critical in stands where perpetuity relies on natural regeneration, as is often the case with cork oak forests. However, 59% of the stand in Portugal have no natural regeneration, and climate change could further worsen the sustainability of the system. The study summarizes the factors that affect the natural regeneration of cork oak (Quercus suber L.) based on current knowledge and presents a case study on a forest in Northeast Portugal, where the natural regeneration of Quercus suber under the effect of climate change have been monitored and analyzed. The present work focuses on the effect of stand density, i.e., tree cover, on the production of acorns, the establishment and survival of seedlings, and the impact of the summer season on seedling mortality. The monitoring was carried out in February, June, September 2022, and January 2023 in two stands with distinct stand canopy cover, when the region was under extreme drought. Data analysis was performed using the analysis of variance for repeated measures and the Mann–Whitney-Wilcoxon test. The study showed that cork oak regeneration is influenced by stand density, which promoted the establishment success and survival of natural regeneration in a period of reduced precipitation, despite possible competition for water resources. The mean number of seedlings differed significantly between the two stands. However, there were no significant differences in the mean number of seedlings throughout the field measurements. Additionally, the percentage of dead seedlings was low even after the summer season (9.5% of the total seedlings) in the denser stand. These results indicate that high canopy cover can have a protective effect for extreme climatic events and should be considered in forestry management to promote regeneration of the cork oak forests. [ABSTRACT FROM AUTHOR]

Fire suppression has negatively impacted thousands of acres of private and public lands in the United States. As a case study, the New Jersey Pine Barrens (NJPB) are a disturbance driven ecosystem that is experiencing serious ecological implications due to a loss of traditional forest thinning activities such as harvesting for forest products or thinning for wildfire fuel-load reduction measures coupled with a long-standing philosophy of fire suppression and dormant-season prescribed burning. Dense closed-canopy forest conditions, dissimilar to historic open-canopy forests of the NJPB, have reduced abundance and diversity of certain flora and fauna, including regionally imperiled breeding birds. In recent years, active forest stewardship (e.g., thinning, clear-cutting, and burning) has occurred on private and some public lands within the NJPB; however, the impact of such management on breeding birds is unclear due to a paucity of research on this subject within the NJPB. During 2012, 2013, 2016, and 2017, we conducted repeat-visit point counts (n = 1,800) for breeding songbirds across 75 control and 75 treatment sites within the NJPB to assess the influence of forest structure at three strata levels (groundcover, midstory profile, and canopy) on breeding bird communities. Specifically, we constructed a hierarchical community abundance model within a Bayesian framework for Bird Conservation Region (BCR) 30 priority upland birds (n = 12) within three species suites: Forested Upland, Scrub-Shrub (or Young Forest), and Grassland. At the community level, we found a negative relationship between bird abundance and live tree basal area. At the BCR 30 suite level, we found no relationship between Forested Upland suite-level abundance and any of the measured covariates; however, we found a negative relationship between percentage of woody groundcover and Scrub-Shrub suite-level abundance, and negative relationship between horizontal visual obstruction at 2 m above ground level and Grassland suite-level abundance. Furthermore, the two latter species suites exhibited a strong negative relationship with basal area. We recommend active forest stewardship that specifically targets opening the canopy to achieve basal areas between ~0–15 m2/ha via selective thinning, shelter cutting, and small-scale clear cutting. Mechanical treatment and prescribed burning would produce such conditions and have the added benefit of reducing fuel loads across this ~4,500 km2 landscape as well as assisting in carbon defense strategies for the region. [ABSTRACT FROM AUTHOR]

Unprecedented seasonal forest fires pose a significant threat to the carbon stocks of diverse ecosystems, particularly in regions like Uttarakhand, west Himalaya. Understanding the impact of varying fire frequencies on different forest types is crucial for effective conservation and management strategies. This study aims to assess the loss of carbon stock in three distinct forest types—Sal, Pine, and Mixed across an elevation gradient in Uttarakhand, facing unprecedented seasonal forest fires. By investigating pre- and post-fire conditions, analyzing biomass dynamics, and mapping fire frequencies, the research aims to provide insights into the complex interplay of fire regimes and forest resilience. The investigation covers vegetation analysis, biomass assessment, and fire frequency mapping. Biomass and carbon stock calculations were carried out using a non-destructive sampling method. Fire frequency maps were generated using Landsat satellite imagery spanning a decade, integrating MODIS hotspot data for classification. The study reveals distinct patterns in biomass changes across Sal, Pine, and Mixed forests in response to varying fire frequencies. Sal forests exhibit resilience to low-intensity fires, while Pine forests show higher sensitivity. Carbon stock contributions of dominant species varied significantly, with Sal and Chir-Pine forests emerging as crucial contributors. High fire frequencies lead to substantial carbon stock reduction in all forest types. The findings emphasize the sensitivity of aboveground biomass to fire frequency, with significant carbon stock loss observed in higher fire frequency classes. The study underscores the importance of nuanced conservation strategies tailored to distinct forest types and species characteristics. This research provides valuable insights for policymakers, forest managers, and conservationists in formulating targeted conservation and management approaches. [ABSTRACT FROM AUTHOR]

Digital twin approaches have the potential to revolutionise usage, planning and management of cultural ecosystem services i.e. the non-material benefits people obtain from ecosystems, including recreation, tourism, intellectual development, spiritual enrichment, reflection and aesthetic experiences. Here, we outline our blueprint for a prototype digital twin (pDT) for cultural ecosystem services. The pDT consists of two modelling components; a recreation potential model to quantify the cultural ecosystem services of the physical landscape and species distribution models to quantify the biodiversity component. It is envisaged that the digital twin will be used primarily by two user types: 1. those who wanted to enjoy the area and potentially contribute to citizen science programmes and 2. people who want to inform or make evidence-based management decisions (land managers, policy-makers, researchers). [ABSTRACT FROM AUTHOR]

Forests are crucial in supporting biodiversity and providing ecosystem services. Understanding forest biodiversity dynamics under different management strategies and climate change scenarios is essential for effective conservation and management. This paper introduces the Forest Biodiversity Dynamics Prototype Digital Twin (pDT), integrating forest and biodiversity models to predict the effects of management options on forest ecosystems. The primary objective is to identify optimal management strategies that promote biodiversity, focusing on conservation and adaptation to different climate conditions. We start with the case of Finnish forests and bird species and plan to expand to include more European countries and a variety of species as the pDT is further developed. [ABSTRACT FROM AUTHOR]

Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot‐level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad‐scale climatic water and energy availability and fine‐scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high‐elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas. [ABSTRACT FROM AUTHOR]

Natural forests are crucial for climate change mitigation and adaptation, but deforestation and degradation challenges highly reduce their value. This study evaluates the potential of natural forest carbon stock and the influence of management interventions on enhancing forest carbon storage capacity. Based on forest area cover, a study was conducted in nine purposely selected forest patches across various forest ecosystems. Data on diameter, height, and environmental variables from various forest management approaches were collected and analyzed with R Ver. 4.1. The findings revealed a substantial difference (p.029) in carbon stock between environmental variables and management interventions. The findings revealed a strong connection between environmental variables and the overall pool of carbon stock within forest patches (p.029). Carbon stocks were highest in the Moist‐montane forest ecosystem (778.25 ton/ha), moderate slope (1019.5 ton/ha), lower elevation (614.50 ton/ha), southwest‐facing (800.1 ton/ha) and area exclosures (993.2 ton/ha). Accordingly, natural forests, particularly unmanaged parts, are sensitive to anthropogenic stresses, decreasing their ability to efficiently store carbon. As a result, the study highlighted the importance of sustainable forest management, particularly area exclosures and participatory forest management, in increasing forest carbon storage potential. [ABSTRACT FROM AUTHOR]

Inventorying forest ecosystems is an essential part of forest management planning. However, it is quite costly and time-consuming, particularly for larger areas. Recently, significant developments have been made in unmanned aerial vehicle (UAV) technology to improve the cost and time efficiency in forest inventory. Therefore, UAV images have become one of the inventory tools that produces data with high spatial resolution in determining forest resources. This study aims to investigate the contribution of UAV data to forest inventory in a case study area with a total of 30 sample plots located in pure and natural Crimean pine (Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe) stands in the Black Sea backward region of Türkiye. Total tree height (h) and stem volume (v) were recorded at individual tree level (n = 367), and the number of trees (N), mean height (hmean), top height (htop), stand basal area (BA) and stand volume (V) were calculated at sample plot level (n = 30) from both the field and UAV-based data. Pearson's correlation coefficients (r) for h and v were 0.96 and 0.72, respectively, the highest correlation at the sample plot level was observed for the hmean - htop (r = 0.96), while the lowest correlation was found for BA (r = 0.54). The suitability of the observation and prediction values was assessed using a t-test at both individual tree and sample plot levels. According to the t-test results, the observation and prediction values for h, v, hmean, htop, BA and V metrics were found to be compatible (p > 0.05), but not for N (p < 0.05). Overall results indicated that UAV technology has a potential to be used in forest inventory and can contribute to the determination of individual tree and stand metrics. Thereby, it saves cost and time in forest inventory studies and helps monitoring the dynamic structure of the forest ecosystem with an effective approach in forest inventory. [ABSTRACT FROM AUTHOR]

Remote sensing products are typically assessed using a single accuracy estimate for the entire map, despite significant variations in accuracy across different map areas or classes. Estimating per-pixel uncertainty is a major challenge for enhancing the usability and potential of remote sensing products. This paper introduces the dataDriven open access tool, a novel statistical design-based approach that specifically addresses this issue by estimating per-pixel uncertainty through a bootstrap resampling procedure. Leveraging Sentinel-2 remote sensing data as auxiliary information, the capabilities of the Google Earth Engine cloud computing platform, and the R programming language, dataDriven can be applied in any world region and variables of interest. In this study, the dataDriven tool was tested in the Rincine forest estate study area—eastern Tuscany, Italy—focusing on volume density as the variable of interest. The average volume density was 0.042, corresponding to 420 m3 per hectare. The estimated pixel errors ranged between 93 m3 and 979 m3 per hectare and were 285 m3 per hectare on average. The ability to produce error estimates for each pixel in the map is a novel aspect in the context of the current advances in remote sensing and forest monitoring and assessment. It constitutes a significant support in forest management applications and also a powerful communication tool since it informs users about areas where map estimates are unreliable, at the same time highlighting the areas where the information provided via the map is more trustworthy. In light of this, the dataDriven tool aims to support researchers and practitioners in the spatially exhaustive use of remote sensing-derived products and map validation. [ABSTRACT FROM AUTHOR]

The timing, location, intensity, and drivers of forest disturbance and recovery are crucial for developing effective management strategies and policies for forest conservation and ecosystem resilience. Although many algorithms and improvement methods have been developed, it is still difficult to guarantee the detection accuracy for forest disturbance and recovery patterns in southern China due to the complex climate and topography, faster forest recovery after disturbance, and the low availability of noise-free Landsat images. Here, we improved the LandTrendr parameters for different provinces to detect forest disturbances and recovery trajectories based on the LandTrendr change detection algorithm and time-series Landsat images on the GEE platform, and then applied the secondary random forest classifier to classify the forest disturbance and recovery patterns in southern China during 1990–2020. The accuracy evaluation indicated that our approach and improved parameters of the LandTrendr algorithm can increase the detection accuracy for both the spatiotemporal patterns and multiple events of forest disturbance and recovery, with an overall accuracy greater than 86% and a Kappa coefficient greater than 0.91 for different provinces. The total forest loss area was 1.54 × 105 km2 during 1990–2020 (4931 km2/year); however, most of these disturbed forests were recovered and only 6.39 × 104 km2 was a net loss area (converted to other land cover types). The area with two or more times of disturbance events accounted for 11.50% of the total forest loss area. The total forest gain area (including gain after loss and the afforestation area) was 5.44 × 105 km2, among which, the forest gain area after loss was 8.94 × 104 km2, and the net gain area from afforestation was 4.55 × 105 km2. The timing of the implementation of forestry policies significantly affected the interannual variations in forest disturbance and recovery, with large variations among different provinces. The detected forest loss and gain area was further compared against with inventory and other geospatial products, and proved the effectiveness of our method. Our study suggests that parameter optimization in the LandTrendr algorithm could greatly increase the accuracy for detecting the multiple and lower rate disturbance/recovery events in the fast-regrowing forested areas. Our findings also offer a long-term, moderate spatial resolution, and precise forest dynamic data for achieving sustainable forest management and the carbon neutrality goal in southern China. [ABSTRACT FROM AUTHOR]

This study aims to establish a deep learning-based classification framework to efficiently and rapidly distinguish between coniferous and broadleaf forests across the Loess Plateau. By integrating the deep residual neural network (ResNet) architecture with transfer learning techniques and multispectral data from unmanned aerial vehicles (UAVs) and Landsat remote sensing data, the effectiveness of the framework was validated through well-designed experiments. The study began by selecting optimal spectral band combinations, using the random forest algorithm. Pre-trained models were then constructed, and model performance was optimized with different training strategies, considering factors such as image size, sample quantity, and model depth. The results indicated substantial improvements in the model's classification accuracy and efficiency for reasonable image dimensions and sample sizes, especially for an image size of 3 × 3 pixels and 2000 samples. In addition, the application of transfer learning and model fine-tuning strategies greatly enhanced the adaptability and universality of the model in different classification scenarios. The fine-tuned model achieved remarkable performance improvements in forest-type classification tasks, increasing classification accuracy from 85% to 93% in Zhengning, from 89% to 96% in Yongshou, and from 86% to 94% in Baishui, as well as exceeding 90% in all counties. These results not only confirm the effectiveness of the proposed framework, but also emphasize the roles of image size, sample quantity, and model depth in improving the generalization ability and classification accuracy of the model. In conclusion, this research has developed a technological framework for effective forest landscape recognition, using a combination of multispectral data from UAVs and Landsat satellites. This combination proved to be more effective in identifying forest types than was using Landsat data alone, demonstrating the enhanced capability and accuracy gained by integrating UAV technology. This research provides valuable scientific guidance and tools for policymakers and practitioners in forest management and sustainable development. [ABSTRACT FROM AUTHOR]

Featured Application: Penetration resistance is a descriptor of soil compaction. In this study, we have exercised control over the weight of the payload of three timber extraction options, therefore the results may be used to estimate the contribution to soil compaction of each pass, as well as for comparison and for planning of operations, given the trends and the magnitude of penetration resistance between the passes. Local effects of ground-based timber harvesting, such as soil compaction, are often important for forest management and resilience of forests. One way to evaluate the compaction of the forest soils is by the penetration resistance. Most often, however, the control over the weight of the means used to extract the wood is difficult to maintain, influencing therefore the outcomes of the comparison studies. In this study, a controlled experiment was set up to see how the penetration resistance is affected by the number of passes of three wood extraction methods. A first objective of the study was to characterize the undisturbed soils by the mean values of penetration resistance along the profile. The second objective of the study was to compare the changes in penetration resistance induced by the number of passes along the soil profile. The extraction means were selected based on their typical use in flat-land operations, namely horse logging, skidding and forwarding, and the weight of their loads was determined before the experiment; then, each one was tested in a different area by operating in a closed loop on flat land, with 15 passes over the respective testing area. Penetration resistance was sampled up to 80 cm in depth in 10 control points, as well as in 10 sampling points over the wheels' footprints. Ten samples were taken on the latter after the first, second, third, fourth, fifth, tenth and fifteenth passes, and comparisons were set up based on natural changing points in penetration resistance found in the control areas. The comparisons found significant differences by an increase in penetration resistance for all three extraction means, and there was a difference by an order of magnitude and depth; horse logging affected it the least and forwarding the most in magnitude, while skidding seemed to produce more significant changes in depth. However, the magnitude and depth of these changes may have depended on the characteristics of the soils from the test areas, and it cannot be concluded that the found levels of penetration resistance will affect the trees located nearby the experimental trails. The problem of soil compaction should be further examined by dedicated studies, given the variability in soil characteristics and diversity in means used to extract timber. [ABSTRACT FROM AUTHOR]

Climate change mitigation technologies have been a focus in reducing atmospheric carbon levels for the past few years. One such mitigation technology is pyrolysis, where biomass feedstocks are combusted at elevated temperatures for varying durations to produce three main products: biochar, bio-oil, and biogas. While bio-oil and biogas are typically used to produce energy via further combustion, biochar can be used in several different applications. Furthermore, using forest harvest residues as a feedstock for biochar production helps use excess biomass from the forestry industry that was previously assumed unmarketable. In our study, we combined forest carbon analysis modelling with cradle-to-gate life cycle emissions to determine the greenhouse gas emissions of biochar produced from forest harvest residues. We examined three collection scenarios, spanning two harvesting methods in one forest management unit in northern Ontario, Canada. From our analysis, we observed immediate reductions (− 0.85 tCO2eq·tbiochar−1 in year 1) in CO2-equivalent emissions (CO2eq) when producing biochar from forest harvest residues that would have undergone controlled burning, without considering the end use of the biochar. For the forest harvest residues that would remain in-forest to decay over time, producing biochar would increase overall emissions by about 6 tCO2eq·tbiochar−1. Throughout the 100-year timeframe examined–in ascending order of cumulative emissions–scenario ranking was: full tree harvesting with slash pile burn < full tree harvesting with slash pile decay < cut-to-length/tree-length harvesting. Highlights: Cradle-to-gate life cycle analysis for biochar production was evaluated. Forest harvest collection methods influence overall life cycle emissions for biochar. Harvest residues that typically undergo controlled burning are an ideal feedstock. [ABSTRACT FROM AUTHOR]

To date, only a limited number of studies have utilized remote sensing imagery to estimate aboveground biomass (AGB) in the Miombo ecoregion using wall-to-wall medium resolution optical satellite imagery (Sentinel-2 and Landsat), localized airborne light detection and ranging (lidar), or localized unmanned aerial systems (UAS) images. On the one hand, the optical satellite imagery is suitable for wall-to-wall coverage, but the AGB estimates based on such imagery lack precision for local or stand-level sustainable forest management and international reporting mechanisms. On the other hand, the AGB estimates based on airborne lidar and UAS imagery have the precision required for sustainable forest management at a local level and international reporting requirements but lack capacity for wall-to-wall coverage. Therefore, the main aim of this study was to investigate the use of UAS-lidar as a sampling tool for satellite-based AGB estimation in the Miombo woodlands of Zambia. In order to bridge the spatial data gap, this study employed a two-phase sampling approach, utilizing Sentinel-2 imagery, partial-coverage UAS-lidar data, and field plot data to estimate AGB in the 8094-hectare Miengwe Forest, Miombo Woodlands, Zambia, where UAS-lidar estimated AGB was used as reference data for estimating AGB using Sentinel-2 image metrics. The findings showed that utilizing UAS-lidar as reference data for predicting AGB using Sentinel-2 image metrics yielded superior results (Adj-R2 = 0.70, RMSE = 27.97) than using direct field estimated AGB and Sentinel-2 image metrics (R2 = 0.55, RMSE = 38.10). The quality of AGB estimates obtained from this approach, coupled with the ongoing advancement and cost-cutting of UAS-lidar technology as well as the continuous availability of wall-to-wall optical imagery such as Sentinel-2, provides much-needed direction for future forest structural attribute estimation for efficient management of the Miombo woodlands. [ABSTRACT FROM AUTHOR]

Wood is the water conducting tissue of tree stems. Like most angiosperm trees, poplar wood contains water-conducting vessel elements whose functional properties affect water transport and growth rates, as well as susceptibility to embolism and hydraulic failure during water stress and drought. Here we used a unique hybrid poplar pedigree carrying genomically characterized chromosomal insertions and deletions to undertake a systems genomics analysis of vessel traits. We assayed gene expression in wood forming tissues from clonal replicates of genotypes covering dosage quantitative trait loci with insertions and deletions, genotypes with extreme vessel trait phenotypes, and control genotypes. A gene co-expression analysis was used to assign genes to modules, which were then used in integrative analyses to identify modules associated with traits, to identify putative molecular and cellular processes associatedwith eachmodule, and finally to identify candidate genes using multiple criteria including dosage responsiveness. These analyses identified known processes associated with vessel traits including stress response, abscisic acid and cell wall biosynthesis, and in addition identified previously unexplored processes including cell cycle and protein ubiquitination. We discuss our findings relative to component processes contributing to vessel trait variation including signaling, cell cycle, cell expansion, and cell differentiation. [ABSTRACT FROM AUTHOR]

Background: Tree seedling regeneration in forests is often hindered by the competitive influence of dense understory bamboo competition. While localized studies have investigated the ecological effects of understory bamboo removal on tree seedlings, a comprehensive analysis at a global scale is lacking. In this meta-analysis, we synthesized 497 observations from 32 experimental studies to assess the overall effects of understory bamboo removal on tree seedling regeneration. Results: The results showed that understory bamboo removal enhanced tree seedling survival, emergence, and height growth. However, the response of tree seedlings to bamboo removal varied depending on regeneration characteristics, forest types, and bamboo removal methods. Specifically, understory bamboo removal increased the survival rate of deciduous seedlings but had no significant effect on evergreen seedlings. For regeneration stages, bamboo removal had a significant positive effect on the survival rate of saplings but not on seedlings. Regarding differences across forest types, bamboo removal significantly increased the emergence density of seedlings in deciduous broadleaf forests but had a significant negative influence in evergreen and mixed evergreen-deciduous forests. Additionally, natural removal of bamboo showed a greater positive effect on seedlings than bamboo removal by artificial or animal gnawing methods. Furthermore, we found that the duration of bamboo removal, mean annual temperature, precipitation of seasonality, and soil pH strongly influenced the response ratios of tree seedling regeneration. Conclusions: Our meta-analysis demonstrates the significant effects of understory bamboo removal on multiple facets of tree seedling dynamics across different regeneration characteristics, forest types, and bamboo removal methods. In addition, our study emphasizes that the duration of bamboo removal, climate, and soil pH have a critical effect on tree seedling regeneration. Our findings elucidate the effects of understory bamboo removal on seedling regeneration, offering robust scientific insights for sustainable forest management. [ABSTRACT FROM AUTHOR]

Biodiversity and biomass of aboveground arthropods in central European forests continuously declined during the last decade. However, whether belowground microarthropod communities follow similar patterns has not been investigated. In this study, we compared the abundance, diversity, community composition, stability and asynchrony of oribatid mites (Acari: Oribatida) sampled in four forest types of increasing management intensity (unmanaged beech, old managed beech, young managed beech, and coniferous) at three‐year intervals from 2008 to 2020. Forest sites were replicated in three regions in southern, central and northern Germany, i.e. the Swabian Alb, Hainich‐Dün and the Schorfheide Chorin, which differ in soil characteristics and climate. We found 25 152 individuals and 121 species of oribatid mites and detected no linear decline in abundance and diversity over the last decade, suggesting that microarthropods in forest soils are buffered against land‐use effects. However, we observed that years with low winter precipitation in regions with soils that are prone to drought, resulted in significant decreases in oribatid mite densities. Community compositions remained similar across sampling years, but differed between regions and forest types, predominantly due to differences in the proportion of asexual individuals. The stability of oribatid mite communities did not decrease in managed forests and was highest in deep soils with high water‐holding capacity, which may reduce temporal variation, suggesting that soil properties are more important for the stability of oribatid mite communities than forest management. However, stability patterns were not explained by asynchrony in species fluctuations, as all communities either showed a high degree of synchrony or were not different from random. Our study highlights that the temporal dynamics of belowground communities may differ from those aboveground, and that regional differences in precipitation and soil properties are more important than forest types. [ABSTRACT FROM AUTHOR]

Saproxylic communities residing in tree hollows form complex food webs that vary over time. However, this study aims to explore the seasonal variation patterns of these communities in Mediterranean ecosystems using ecological network analysis. The focus is on saproxylic Syrphidae (Diptera) and Coleoptera communities in three Mediterranean forests in Cabañeros National Park (Spain), revealing dynamics influenced by forest type and seasonality. During summer, nestedness is observed only in F. angustifolia, while modularity is observed in Q. rotundifolia during spring and autumn. Modularity implies specialized interactions that affect species functions and responses, which may restrict adaptability and resilience to environmental perturbations during these time periods. The seasonal changes in interaction attributes reveal greater connectivity in Q. rotundifolia and Q. pyrenaica in autumn. It is concluded that studying the temporal patterns of saproxylic community assemblages is increasingly important in the context of current climate change in the Mediterranean, which could significantly influence the spatio-temporal distribution of interactions between them. These results highlight the complex dynamics of saproxylic insect ecological networks, which are crucial for the conservation and ecosystem management of Mediterranean forests. [ABSTRACT FROM AUTHOR]

Texture, soil organic matter (SOM), and soil depth (SoD) are crucial properties in forest management because they can supply spatial information on forest site productivity and guide fertilizer applications. However, soil properties possess an inherent uncertainty that must be mapped to enhance decision making in management applications. Most digital soil mapping predictions primarily concentrate on the mean of the distribution, often neglecting the estimation of local uncertainty in soil properties. Additionally, there is a noticeable scarcity of practical soil examples to demonstrate the prediction uncertainty for the benefit of forest managers. In this study, following a digital soil mapping (DSM) approach, a Quantile Regression Forest (QRF) model was developed to generate high-resolution maps and their uncertainty regarding the texture, SoD, and SOM, which were expressed as standard deviation (Sd) values. The results showed that the SOM (R2 = 0.61, RMSE = 2.03% and with an average Sd = 50%), SoD (R2 = 0.74 and RMSE = 19.4 cm), clay (R2 = 0.63, RMSE = 10.5% and average Sd = 29%), silt (R2 = 0.59, RMSE = 6.26% and average Sd = 33%), and sand content (R2 = 0.55, RMSE = 9.49% and average Sd = 35%) were accurately estimated for forest plantations in central south Chile. A practical demonstration of precision fertilizer application, utilizing the predictive distribution of SOM, effectively showcased how uncertainty in soil attributes can be leveraged to benefit forest managers. This approach holds potential for optimizing resource allocation and maximizing economic benefits. [ABSTRACT FROM AUTHOR]

Accurately estimating forest aboveground biomass (AGB) is imperative for comprehending carbon cycling, calculating carbon budgets, and formulating sustainable forest management plans. Currently, random forest (RF) and other machine learning models are widely used to estimate forest AGB, as they can effectively handle nonlinear relationships. However, by constructing a global model using all the samples collected from a study area, these models fail to account for the spatial heterogeneity in the AGB and cannot correct the prediction biases, thereby constraining the estimation accuracy. To overcome these limitations, we proposed a novel approach termed geographical random forest and empirical Bayesian kriging (GRFEBK). This hybrid model combines the localized modeling capability of geographical random forest (GRF) with the bias correction strength of empirical Bayesian kriging (EBK). GRF adapts RF to account for the spatial heterogeneity of the AGB, while EBK utilizes the spatial autocorrelation of residuals to correct the prediction deviations. This study was conducted in Hainan Island, utilizing spectral bands, vegetation indices, tasseled cap components derived from Landsat-8 imagery, backscattering coefficients from ALOS-2 synthetic aperture radar, topographic features, and the forest canopy height as the explanatory variables. A total of 195 forest aboveground biomass (AGB) samples were collected for modeling and assessing the predictive accuracy. The results demonstrate that, among the tested models, including GRFEBK, RF, support vector machine (SVM), k-nearest neighbor (KNN), geographically weighted regression (GWR), GRF, and EBK, GRFEBK attains the highest R 2 (0.78) and the lowest RMSE (36.04 Mg/ha) and RRMSE (22.87%), significantly outperforming the conventional models and using GRF or EBK alone. These results demonstrate that by accounting for local non-stationarity in AGB and correcting prediction biases, GRFEBK achieves significantly higher accuracy than conventional RF and other models. While the results are promising, the computational cost of GRFEBK and its performance under varying geographical conditions warrant further investigation at larger scales to assess its broader applicability. Nevertheless, GRFEBK provides an innovative and more reliable approach for accurate forest AGB estimation with great potential to support global forest resource monitoring. [ABSTRACT FROM AUTHOR]

Dead trees are vital structural elements in forests playing key roles in the carbon and nutrient cycle. Stem traits and fungal community composition are both important drivers of stem decay, and thereby affect ecosystem functioning, but their relative importance for stem decomposition over time remains unclear.To address this issue, we used a common garden decomposition experiment in a Dutch larch forest hosting fresh logs from 13 common temperate tree species. In total, 25 fresh wood and bark traits were measured as indicators of wood accessibility for decomposers, nutritional quality and chemical or physical defence mechanisms. After 1 and 4 years of decay, we assessed the richness and composition of wood‐inhabiting fungi using amplicon sequencing and determined the proportional wood density loss.Average proportional wood density loss for the first year was 18.5%, with further decomposition occurring at a rate of 4.3% year−1 for the subsequent 3 years across tree species. Proportional wood density loss varied widely across tree species in the first year (8.7–24.8% year−1) and subsequent years (0–11.3% year−1). The variation was directly driven by initial wood traits during the first decay year, then later directly driven by bark traits and fungal community composition. Moreover, bark traits affected the composition of wood‐inhabiting fungi and thereby indirectly affected decomposition rates. Specifically, traits promoting resource acquisition of the living tree, such as wide conduits that increase accessibility and high nutrient concentration, increased initial wood decomposition rates. Fungal community composition, but not fungal richness explained differences in wood decomposition after 4 years of exposure in the field, where fungal communities dominated by brown‐rot and white‐rot Basidiomycetes were linked to higher wood decomposition rate.Synthesis: Understanding what drives deadwood decomposition through time is important to understand the dynamics of carbon stocks. Here, using a tailor‐made experimental design in a temperate forest setting, we have shown that stem trait variation is key to understanding the roles of these drivers; initially, wood traits explained decomposition rates while subsequently, bark traits and fungal decomposer composition drove decomposition rates. These findings inform forest management with a view to selecting tree species to promote carbon storage. [ABSTRACT FROM AUTHOR]

This paper summarizes a two-year (2021 and 2022) survey which sought to determine the breeding population of White-backed Woodpecker (Dendrocopos leucotos) in Hungary. The survey was initiated by the Hungarian Woodpecker Group of MME/BirdLife Hungary and was the first to be conducted nationwide on this species. All hill ranges where the species was historically known to occur were visited. A total of 31 observers were involved, and 102 UTM squares in which White-backed Woodpeckers were known to breed, or potentially breed, were visited. The results suggest that the Hungarian breeding population of this endangered species ranges between 480 and 800 pairs. [ABSTRACT FROM AUTHOR]

Accurate information on forest tree species composition is vital for various scientific applications, as well as for forest inventory and management purposes. Country-wide, detailed species maps are a valuable resource for environmental management, conservation, research, and planning. Here, we performed the classification of 16 dominant tree species and genera in Poland using time series of Sentinel-2 imagery. To generate comprehensive spectral–temporal information, we created Sentinel-2 seasonal aggregations known as spectral–temporal metrics (STMs) within the Google Earth Engine (GEE). STMs were computed for short periods of 15–30 d during spring, summer, and autumn, covering multi-annual observations from 2018 to 2021. The Polish Forest Data Bank served as reference data, and, to obtain robust samples with pure stands only, the data were validated through automated and visual inspection based on very-high-resolution orthoimagery, resulting in 4500 polygons serving as training and test data. The forest mask was derived from available land cover datasets in GEE, namely the ESA WorldCover and Dynamic World dataset. Additionally, we incorporated various topographic and climatic variables from GEE to enhance classification accuracy. The random forest algorithm was employed for the classification process, and an area-adjusted accuracy assessment was conducted through cross-validation and test datasets. The results demonstrate that the country-wide forest stand species mapping achieved an accuracy exceeding 80 %; however, this varies greatly depending on species, region, and observation frequency. We provide freely accessible resources, including the forest tree species map and training and test data: 10.5281/zenodo.10180469 (Grabska-Szwagrzyk, 2023a). [ABSTRACT FROM AUTHOR]

Summary: The understanding of tree growth processes is crucial for promoting sustainable forest management strategies. This is a challenging task in highly biodiverse ecosystems where many tree species are observed on very few individuals and the small sample sizes hinder a good fit of species‐specific models. We propose the use of finite mixture of random coefficient regression models with multilevel nested random effects to infer guild specific fixed and random effects while evaluating the relative importance of the nested sources of variability on goodness‐of‐fit. This approach extends finite mixture of linear mixed model used for longitudinal or single group structured data contexts. A dedicated expectation–maximisation algorithm is introduced for parameter estimation. Simulations are performed for the evaluation of the misspecification of nested‐grouping structures. This work has been motivated by data collected biennially in Central African rainforests from 1986 to 2010. We show the accuracy of the proposed approach in successfully reproducing individual growth processes and classifying tree species into well‐differentiated clusters with clear ecological interpretations. Moreover, results confirm that interindividual variability appears as the most important factor to explain tropical tree species growth process variability from Central Africa forests. [ABSTRACT FROM AUTHOR]

The origin and development of agriculture and its relationship with climate change are hotly debated topics among environmental archaeologists. In this study, we analyzed wood charcoal materials from the Neolithic Xinglong site in northern China in order to understand the woody vegetation around the site and how early millet farmers shaped local woodlands. Our results suggest that the area around the Xinglong sites during 8700–7000 yr BP was primarily woodlands, including Prunus sibirica shrubs, Ulmus and Acer forests, and Populus stands near waterways. From 8000 to 7000 yr BP, the warm and humid climate probably contributed to the expansion of Acer, Rhamnus, and Juniperus, and may have facilitated the development of early millet agriculture. Among these ancient wood fragments that we studied, the high percent of Prunus charcoal appears to indicate an abundance of fruit trees, which might have constituted the main component of local vegetation. Meanwhile, the wood taxa illustrate the existence of a variety of ecological habitats, and it is logical to assume that people made full use of the locally available wood resources. Notably, Populus and Ulmus were the dominant sources of fuel. The results of tree-ring curvature analyses indicate that people mainly collected trunks or large branches of Ulmus, Populus, Acer, and Juniperus timbers. We interpret the increasing use of Prunus twigs and the declining percentage of Prunus charcoal in the period between 8000–7000 yr BP as indicating that people started to protect and manage wild fruit trees. They may have started pruning to acquire more food resources as part of the cultural responses and adaptation strategies employed by these early millet cultivators. [ABSTRACT FROM AUTHOR]

Insect defoliation is a widespread cause of forest disturbance in Canada, and it has the potential to alter terrestrial carbon contributions to stream consumers and thus affect stream ecosystems. Although defoliation by spruce budworms (Choristoneura fumiferana) is considered a natural disturbance with importance to forest succession, the magnitude and duration of outbreaks are increasing, and there is a growing need to understand their downstream consequences. To examine this, algal productivity and autochthonous (in-stream) energy supporting macroinvertebrate and fish consumers (using δ13C, δ15N) were examined in 12 streams in the Gaspé Peninsula, Québec, Canada, that ranged in watershed defoliation from spruce budworm. Hierarchical partitioning models were used to assess the contributions of watershed and stream variables to these endpoints. Total seasonal algal production ranged fourfold among sites, and cumulative defoliation was the strongest predictor. Consumers from streams with greater defoliation (cumulative or annual) had lower reliance on autochthonous carbon, despite increased algal production, and this effect was greater for brook trout than macroinvertebrates. These findings demonstrate for the first time that insect outbreaks—which alter forest structure and function—also similarly affect downstream aquatic ecosystems by causing changes in the production and contributions of carbon sources. This suggests that insect control strategies and forest management decisions should also consider implications for downstream aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Summary: Understanding how selective logging affects biodiversity is crucial to planning cost-effective conservation strategies in tropical forests, yet there is limited understanding of its impacts on fauna functional diversity in the tropical Americas. We assessed how selective logging intensification and time since logging influence multiple metrics of fauna functional integrity in the Brazilian Amazon by collecting bird and dung beetle data within 48 logging management units that had experienced varying exploitation intensities between 1.5–2.0 and 5.0–6.0 years before the faunal surveys. We investigated assemblage responses and used functional attributes to assess changes in functional diversity, specialization, originality and species rarity. Using point counts and pitfall traps, we collected 5081 records of 182 bird species and 7892 dung beetles from 45 species. Logging intensification led to significant declines in most dung beetle responses and bird body mass, whereas time since logging was a key driver of dung beetle and bird functional and taxonomic diversity. Our study presents novel empirical evidence of how logging intensification effects vary across taxa, ecological metrics and time since logging, which is key to informing forest conservation and further investigating environmental degradation impacts on tropical biodiversity. [ABSTRACT FROM AUTHOR]

We investigated whether there are significant differences in the climatic response of resin-tapped and untapped maritime pine (Pinus pinaster Ait.) trees in four forest stands in the central mountains of Spain, where the species is of natural origin. The stands are located in different provenance regions, with the westernmost site located on the northern slopes of Sierra de Gredos and the easternmost in the transition to the middle Duero basin, with altitudes ranging from 900 to 1350 m a.s.l. Dominant trees were sampled and standard dendrochronological methods were used to compare tree growth of both types of trees at each site. Climate-tree growth relationships were assessed using bootstrap correlations and response functions between tree-ring growth indices and climate variables, for both partials and full local chronologies of each stand, selecting climatic data from the most complete and closest meteorological stations. Our results showed that the trees selected for resin extraction were older, on average, and when site characteristics were favorable enough for maritime pine growth and resin extraction, all trees were resintapped. Contrastingly, when site characteristics were unfavorable for resin extraction, only the largest and the best-developed trees were tapped. No major differences were found between the climatic responses of resin-tapped and untapped trees, and it was therefore possible to use all the available tree-ring width series per site, both resin-tapped and untapped trees, to identify the main climatic drivers of maritime pine growth in central Spain. In addition, we have expanded the chronologies network of Pinus pinaster in Spain in number and length. This work may provide valuable information to improve forest management strategies for sustainable resin production. [ABSTRACT FROM AUTHOR]

Canopy gaps are a prevalent disturbance form in forest ecosystems that promote forest regeneration and succession by modifying the heterogeneity of the microenvironment. However, a significant knowledge gap exists in comprehending the global-scale impact of canopy gaps on soil nutrient properties, which is related to forest management and conservation tactics. In this study, 518 paired observations derived from 31 peer-reviewed articles were meta-analyzed to evaluate the overall response of soil nutrient properties to canopy gaps. The results showed that canopy gaps increased NO3−–N (+ 22.20%) and MBP (+ 194.17%). The canopy gap decreased the content of TN, MBC, and C:P ratio by 9.27%, 19.58%, and 19.25%, respectively. The size of canopy gaps significantly reduced SOC (−14.37%), MBC (−27.45%), TN (−11.98%), NH4+–N (−65.26%), C:N (−15.77%, −16.02%) and C:P ratio (−28.92%), but significantly increases NO3−–N (+ 37.25%). Hence, it is advisable to establish a critical gap size that caters to the specific soil fertility requirements of various regions for the optimal release of soil nutrients. These findings hold substantial significance for optimizing canopy gap management, comprehensively understanding the impact of canopy gaps on soil nutrient properties, and facilitating decision-making to assess soil fertility following canopy gap disturbances. [ABSTRACT FROM AUTHOR]

Riparian buffer zones (RBZs) are an important instrument for environmental policies for water and biodiversity protection in managed forests. We investigate the variation of the cost of implementing RBZs within different property size classes across the size range of non-industrial forest owner properties in Southern Sweden. Using the Heureka PlanWise decision support system, we quantified the cost of setting aside RBZs or applying alternative management in them, as the relative loss of harvest volume and of net present value per property. We did this for multiple simulated as well as real-world property distributions. The variation of cost distribution among small properties was 4.2–6.9 times higher than among large properties. The interproperty cost inequality decreased non-linearly with increasing property size and levelled off from around 200 ha. We conclude that RBZs, due to the irregular distribution of streams, cause highly unequal financial consequences for owners, with some small property owners bearing a disproportionally high cost. This adds to previous studies showing how environmental considerations differentially affect property owners. We recommend decision makers to stimulate the uptake of RBZs by alleviating these inequalities between forest owners by including appropriate cost sharing or compensation mechanisms in their design. [ABSTRACT FROM AUTHOR]

Induced by climate change associated disturbances and further promoted by changes in forest management, the proportion of European beech, a highly competitive climax species, is increasing in Central Europe. However, its climatic stability is questioned by the recent loss of vitality. In this regard, the evaluation of seed sources used for reforestation receives great attention. Here, we present a multi-trait evaluation of height, basal area and stem quality assessed over 25 years for 85 provenances grown at three sites in northern, western and eastern Germany. Considerable provenance differentiation exists, explaining 21% (proportion of trees with acceptable stem form) to 45% (basal area) of the variance on single sites and 20 to 39% across sites, while provenance by environment interactions are absent. On the landscape level, this results in distinct patterns with spatially adjacent provenances showing a similar trait expression. These patterns are highly similar for height and basal area but divergent for stem form. They could be directly linked to geographic variables with multivariate regression tree analysis that captured 58% of the phenotypic variation, delineating eleven 'ecotypes' shaped by local adaptation. A selection based on two multi-trait indices gives highly concordant results. Particularly, the intermediate elevations of the central highlands in Western Germany host highly suitable provenances. Lower elevation provenances from continental climates in the south-east profit from the transfer to favorable growing conditions. Since the majority of provenances was already exposed to elevated temperatures compared to their origin during the observation period, this study gives a first indication for the potential benefits of assisted migration facing climate change. [ABSTRACT FROM AUTHOR]

Improving water-holding functions is an important purpose of sustainable forest management. However, few studies have examined whether there are differences in water-holding capacities between the forests dominated by trees associated with different mycorrhizal types and what are the main factors leading to the differences. Here, we investigated seven parameters of water-holding capacities of soils, litter, and canopy interception in 210 forest plots (10 m × 10 m). The plots were equally divided into three forest types associated with mycorrhizal types, including AM plots (arbuscular mycorrhizal trees > 75% in dominance), ECM plots (ectomycorrhizal trees > 75%), and AM + ECM plots (between 25 and 75%). We calculated tree diversity (richness, Shannon–wiener index, Simpson index, evenness), community structure (diameter at breast height, height, under branch height, density, neighborhood comparison-U, uniform angle index-W, and mingling index-M), and soil physics (soil bulk density and field water content). The results showed that: (1) ECM-dominated communities increased 1.6–2.0-fold in the litter water-holding capacities than those of AM and AM + ECM. The canopy interception of the ECM community was the highest (0.97 mm), significantly higher than that of the AM + ECM community (0.58 mm). (2) The ECM community had lower field soil water-holding capacity (p < 0.05) but 42–78% higher soil non-capillary water capacity than that of AM and AM + ECM (p < 0.05). (3) ECM forests were characterized by low tree species evenness, big-sized trees, and low bulk density, favoring increasing ecosystem water-holding capacities. Moreover, increasing ECM tree dominance enhanced the contribution of community structure to water-holding variations. (4) ECM trees increased ecosystem water-holding functions by direct effects (mainly on the litter) and indirect effects from soil physics (mainly on the soils) or tree size (mainly on the canopy) regulations. This study highlighted that ECM trees enhanced water-holding capacity, providing important information for planting and managing temperate water conservation forests. [ABSTRACT FROM AUTHOR]

Extensive mortality of susceptible spruce can be caused by spruce beetles at epidemic population levels, as in the ongoing outbreak in Southcentral Alaska. Although information on outbreak extent and severity underpins forest management and research, the data products available in Alaska have substantial gaps. Widely available high-resolution satellite imagery are a promising data source for detecting beetle kill because it is possible, though challenging, to identify individual trees. However, the applicability of automated deep-learning approaches for regional-scale mapping has not been evaluated. Here, we assess a deep convolutional network for mapping dead spruce in high-resolution (∼ 2 m) satellite imagery of Southcentral Alaska. The network identified dead spruce pixels across stand characteristics, achieving an average accuracy of 95%. To upscale to the stand scale, we mitigated overestimation of dead tree pixels at elevated severity by calibration. Stand-scale areal severity, the fraction of dead spruce pixels within a stand, was mapped with an RMSE of 0.02 at 90 m scale. The estimated severity exceeded 0.05 in fewer than 4% of the landscape, and approximately 90% of dead trees pixels were found in low-severity stands. Severity was weakly associated with stand-scale Landsat reflectance changes, a clear relation between SWIR reflectance change and severity only emerging above 0.1 severity. In conclusion, high-resolution satellite imagery are suited to automated mapping of beetle-associated kill at tree and stand scale across the severity spectrum. Such data products support forest and fire management and further understanding of the dynamics and consequences of beetle outbreaks. [Display omitted] • Automatic mapping of dead spruce trees in 2 m resolution satellite imagery. • Accurate stand-scale severity maps by calibrated upscaling. • Predominantly low to moderate severity, with most dead trees in low-severity stands. • Moderate-resolution images showed limited sensitivity to low-severity mortality. [ABSTRACT FROM AUTHOR]

Visual geo-localization enables the UAV to know its position in GNSS-denied application scenarios, such as disaster emergency response, forest inventory management and indoor facility monitoring. However, there are still some challenges in using oblique-view imagery, especially for UAV images with large oblique viewing angles, to perform visual geo-localization. On the one hand, using geotags of references as image-level geo-localization results is insufficient for oblique-view imagery, because the UAV is often situated at a distance and not directly over the observation area. On the other hand, the obvious differences in viewpoint, viewing angle, and scale between UAV oblique-view images and geo-tagged orthographic reference images severely limit the accuracy of all three steps in pixel-level geo-localization, including image-based retrieval, matching and space resection. In this study, we proposed a coarse-to-fine visual geo-localization method to address these challenges for UAV position determination using oblique-view imagery, assisted by orthographic references. Firstly, we proposed a novel image-level geo-localization method by employing Segments Direction Statistics (SDS) feature patterns and bilateral retrieval strategy. Secondly, we matched UAV oblique-view images with geo-tagged orthographic reference images using feature points and descriptors extracted by the improved SuperPoint network, incorporating the Discrete Gaussian Pyramid Module (DGPM) and the Two-stage Matching Results Refinement Module (TMRRM). Thirdly, based on the matched points with 2D pixel coordinates and 3D ground coordinates, we adopted the triangular pyramid constrained resection method with angle similarity constraints to accurately determine the pixel-level position of UAV. We conducted experiments using a publicly available multi-view images dataset (University-1652), as well as two self-collected datasets of oblique-view images captured by UAVs. Experiments indicate that the localization error of the proposed method is less than 0.1 m for applications with the flight height about 200 m. Meanwhile, the error is about 10 m for UAVs with extremely high flight height (more than 4 km) and large oblique viewing angle (more than 60°). And the average time cost of the proposed method is about 400 ms. Therefore, experimental results demonstrated the effectiveness and efficiency of the proposed method in automatically obtaining reliable UAV positions using oblique-view imagery, as well as its robustness for various UAV oblique-view image-based applications. [ABSTRACT FROM AUTHOR]

Growth and yield systems are essential tools for enhancing forest management decision-making. This study systematically evaluated three stand-level models and two data types for predicting stand survival and basal area of Chinese fir (Cunning lanceolate (Lamb.) Hook.) plantations in southern China. The first model links survival and diameter through the self-thinning concept. The second model incorporates stand diameter, the previous year's diameter, and stand survival, while the third model treats stand survival and diameter as mutually independent functions of only stand age. Model 2 was the best performer for short-term prediction (2–4 years), whereas Model 3 excelled in longer projection periods (6–10 years). Despite the independent predictions of stand survival and diameter in Model 3, it closely tracked observed self-thinning trajectories in long-term predictions. Tree-level model growth derived from Models 2 and 3 performed optimally for short-term and long-term tree-level predictions, respectively. While limited to four experimental sites, this research contributes theoretical groundwork to growth and yield modeling for Chinese fir plantations. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of soil organic carbon (SOC) sequestration in forests is vital to ecosystem carbon budgeting and helps gain insight in the functioning and sustainable management of world forests. An explicit knowledge of the mechanisms driving global SOC sequestration in forests is still lacking because of the complex interplays between climate, soil, and forest type in influencing SOC pool size and stability. Based on a synthesis of 1179 observations from 292 studies across global forests, we quantified the relative importance of climate, soil property, and forest type on total SOC content and the specific contents of physical (particulate vs. mineral‐associated SOC) and chemical (labile vs. recalcitrant SOC) pools in upper 10 cm mineral soils, as well as SOC stock in the O horizons. The variability in the total SOC content of the mineral soils was better explained by climate (47%–60%) and soil factors (26%–50%) than by NPP (10%–20%). The total SOC content and contents of particulate (POC) and recalcitrant SOC (ROC) of the mineral soils all decreased with increasing mean annual temperature because SOC decomposition overrides the C replenishment under warmer climate. The content of mineral‐associated organic carbon (MAOC) was influenced by temperature, which directly affected microbial activity. Additionally, the presence of clay and iron oxides physically protected SOC by forming MAOC. The SOC stock in the O horizons was larger in the temperate zone and Mediterranean regions than in the boreal and sub/tropical zones. Mixed forests had 64% larger SOC pools than either broadleaf or coniferous forests, because of (i) higher productivity and (ii) litter input from different tree species resulting in diversification of molecular composition of SOC and microbial community. While climate, soil, and forest type jointly determine the formation and stability of SOC, climate predominantly controls the global patterns of SOC pools in forest ecosystems. [ABSTRACT FROM AUTHOR]

In 2019, the Maya Leaders Alliance unveiled "The Future We Dream," a vision document sharing a common interest among the Mopan and Q'eqchi' Maya people of Belize for a future in which they are committed to sustaining a reciprocal relationship with and stewardship of the land. In this context, this paper shares results from three communities bordering a forest reserve who were asked to identify important practices, which they considered "traditional" and "environmentally sustainable," as part of a collaborative NGO project to promote indigenous forest management. Through analysis of data collected alongside Indigenous Community Promoters (ICPs), it explores how these terms were defined and deployed to discuss healthy forests and healthy communities. The paper discusses how collaborative and community- led data collection addresses both the need to decolonize sustainability discourse and produce better data for better project outcomes (Maya, traditional ecological knowledge, forest management, environmental sustainability, indigenous land rights). [ABSTRACT FROM AUTHOR]

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Background: Globally increasing atmospheric nitrogen (N) deposition has altered soil phosphorus (P) transformations and availability, and thereby influenced structure and function of terrestrial ecosystems. Edaphic characteristics and chemical form of deposited N could be important factors determining impacts of N deposition on soil P transformations, yet the underlying mechanisms remain largely unknown. Objectives of this study were to examine how mineral-N and amino N differently affect P fractions, and identify key soil properties determining N addition impacts on soil P transformations. Considering that amino N is an important component of deposited N and forest soils vary greatly in different regions, the results of present study can guide the management of forests across different soils under ongoing N deposition scenarios. Methods: We conducted a 60-day laboratory experiment to investigate the effects of N addition (NH4NO3 and glycine) on soil P fractions and related biochemical properties in four representative forest soils (brown, yellow brown, aeolian sandy, and red soils) in China. Glycine and NH4NO3 were separately added at three rates (5, 10 and 20 g N m–2 yr–1). Results: Firstly, the percent changes in organic P fractions with N addition were significantly greater than changes in inorganic P fractions across all soils. Secondly, the percent changes in P fractions with glycine and NH4NO3 additions were significantly correlated across all soils and treatments. However, glycine addition had significantly greater impacts on organic P fractions than NH4NO3 addition in the aeolian sandy and red soils with low organic carbon content. Thirdly, P fractions responded differently to N addition among the four soils. N-induced changes in microbial biomass and phosphatase activities, pH, exchangeable Ca2+ and Mg2+ contributed differently to the changes in P fractions with N addition in the four soils. Conclusions: The different responses of P fractions to N addition in the four soils were mainly generated by the differences in extent of microbial N limitation, acid buffering capacity, and cation exchange capacity among the soils. The different impacts of mineral and amino N on soil P fractions can be ascribed to their divergent effects on soil pH, microbial biomass and activities. [ABSTRACT FROM AUTHOR]

India's high mountain, van panchayat forests are a long-standing example of community-led forest governance. These provide vital support for mountain communities' wellbeing, yet little is known about how environmental and social change is currently perceived or addressed, despite many claims that characterize van panchayats to be in crisis due to policy interventions by state forest actors and erosion of local management institutions. This research investigates how changes in forest dependence, governance, and health drive forest management decisions. Using open-ended interviews with 41 forest stewards and knowledge holders in a high mountain valley in Uttarakhand, our analysis describes managers' perceptions of environmental and social changes and their implications for management choices. We found that van panchayats are currently navigating stewardship pathways in response to: (a) population shifts and changes to historically forest-dependent livelihoods; (b) a shift in governance regimes across van panchayats, affected by both regulatory changes and local institutional capacity; (c) the effects of global environmental change as it intersects with local influences on mountain ecosystems. Forest stewards' perceptions of the drivers, trends, significance, and appropriate management responses to these changes varied widely. An overall decline in rightsholders' dependence on forest resources was commonly reported, as was improved forest health in van panchayats in relation to other forest types. However, van panchayat managers disagreed on whether declining dependence positively or negatively affects forest health, whether the state is absent or actively wresting control from communities, and if successful forest restoration efforts will continue. A lack of shared understanding of these issues complicates forest stewards' efforts to cooperate towards mutually desired ends, exacerbated by a co-management policy which isolates forest councils' efforts from neighbouring forests. Accordingly, we encourage policy changes to enhance collaborative decision-making and to address implications of diverse perceptions, priorities and practices of care in mountain forests. [ABSTRACT FROM AUTHOR]

Sri Lanka, as a developing tropical country, faces serious environmental challenges. Forests, as important ecosystems of Sri Lanka, are under pressure from intensive human activities and climate change. Invasive species represent a great hazard to autochthonous plant species and ecosystems, which are, at the same time, hosts to extraordinarily high biodiversity, of which a high percentage is endemic. In this paper, we reviewed the most challenging environmental problems of Sri Lanka and suggested the improvement of a number of them through silvicultural measures and cooperation with international experts, namely Czech foresters. We also reviewed the main forest biomes and addressed the specific problems and management of different forest types. [ABSTRACT FROM AUTHOR]