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Instance segmentation is crucial for analysing individual tree crowns in aerial imagery, which plays an important role in forest management, risk modelling, biodiversity modelling, forest health and human wellbeing studies. Traditional instance segmentation methods struggle in diverse rural landscapes where canopy images feature primarily small and medium tree objects, varying from isolated trees to dense forest stands. This paper introduces YOLOv8E, a new and efficient YOLOv8 method, optimised for precise instance segmentation and species classification of tree crowns. This method includes new schemes for selecting candidate positive samples for each instance and a refined network design tailored for small and medium-sized tree crowns. Adjustments in hyperparameters, particularly within the Task-Aligned Assigner, are also discussed to better suit canopy segmentation tasks. Comprehensive experiments conducted on the datasets for Wellington City, Aotearoa New Zealand, demonstrate that YOLOv8E outperforms a number of recent methods, achieving 36.1 and 32.2 in terms of the Box AP and Mask AP metrics respectively. [ABSTRACT FROM AUTHOR]

Ecological restoration is widely recognized as an essential technique for addressing soil degradation, biomass decline, and biodiversity loss. Improving and maintaining soil quality is critical to ensuring environmental sustainability and successful forest recovery. This systematic review aimed to assess the impact of ecological forest restoration efforts on soil quality in humid regions, as well as to compare the effectiveness of various ecological restoration strategies on soil quality indicators. Subsequently, a systematic search on various databases (e.g., Scopus and Google Scholar) yielded 696 records, of which 28 primary studies met the inclusion criteria. The results emphasized that chemical and physical soil properties are the key indicators for assessing ecosystem performance during forest restoration. The most commonly measured parameters were soil carbon, nitrogen, phosphorus, pH, bulk density, and soil porosity. It was shown that the restoration process required a longer duration to reach a comparable level of recovery as seen in mature forests, particularly in terms of fully restoring soil quality. Additionally, it has been noted that prior land use influences the length of time needed for soil quality recovery. In planted sites, soil quality may keep improving as the site ages, though it tends to stabilize after a certain period. [ABSTRACT FROM AUTHOR]

Leaf chlorophyll content is a major indicator of plant health and productivity. Optical remote sensing estimation of chlorophyll limits its retrievals to two-dimensional (2D) estimates, not allowing examination of its distribution within the canopy, although it exhibits large variation across the vertical profile. Multispectral and hyperspectral Terrestrial Laser Scanning (TLS) instruments can produce three-dimensional (3D) chlorophyll estimates but are not widely available. Thus, in this study, 14 chlorophyll vegetation indices were developed using six wavelengths employed in commercial TLS instruments (532 nm, 670 nm, 808 nm, 785 nm, 1064 nm, and 1550 nm). For this, 200 simulations were carried out using the novel bidirectional mode in the Discrete Anisotropic Radiative Transfer (DART) model and a realistic forest stand. The results showed that the Green Normalized Difference Vegetation Index (GNDVI) of the 532 nm and either the 808 nm or the 785 nm wavelengths were highly correlated to the chlorophyll content (R2 = 0.74). The Chlorophyll Index (CI) and Green Simple Ratio (GSR) of the same wavelengths also displayed good correlation (R2 = 0.73). This study was a step towards canopy 3D chlorophyll retrieval using commercial TLS instruments, but methods to couple the data from the different instruments still need to be developed. [ABSTRACT FROM AUTHOR]

Variable retention harvesting (VRH) was designed for timber purposes and biodiversity conservation in natural forests. This system was globally tested, but few studies are related to soil microbial components. The objective was to evaluate different retention types (aggregated and dispersed retention) considering different years-after-harvesting (6, 9, 16 YAH) on soil microbial community attributes compared with unmanaged primary forests (PF) in Nothofagus pumilio forests of Tierra del Fuego (Argentina). This study also evaluated the influence of climate, soil, and understory vegetation. Results showed that aggregated retention increased microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and soil basal respiration (SBR) compared to dispersed retention, but with similar values than PF. However, harvested areas decreased MBC/MBN values compared with PF. The results showed an overall decrease in microbial biomass and activity in 9 YAH stands, with a positive recovery at 16 YAH. Soil pH, mean annual temperature, and understory vegetation cover showed a positive relationship with MBC, MBN, and SBR. The recovery after 16 YAH reached to different microbial communities. Therefore, the maintenance of retention components in managed stands for longer periods is needed. The results highlight some advantages of VRH as a tool for conservation of forest-dwelling soil microorganisms, including microbial biomass and activity. [ABSTRACT FROM AUTHOR]

Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements (R2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m2 (Niwot) and 52.8 W/m2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements. Plain Language Summary: Understanding how forests use water, especially during droughts, is crucial for a changing climate. We developed a method using thermal cameras to estimate individual tree water loss (transpiration), something traditional methods lack. These cameras capture temperature data from the tree crown, which is then used to estimate transpiration rates. Tests in two forests showed this method aligns well with existing water use measurements. The study also revealed fascinating differences in how species handle drought. For instance, lodgepole pine outperformed Engelmann spruce in one forest, while red oak proved more resistant than red maple in the other. This shows that the thermal cameras can help assess how different trees resist drought conditions. This thermal camera technique has the potential to become a valuable tool for monitoring forest health as our climate evolves. Key Points: Canopy‐level evapotranspiration derived from thermal cameras agreed well with eddy covariance measurementsCrown temperature measurements facilitated the estimation of individual‐tree transpiration of co‐occurring species using the same approachThe results show interspecific differences in water use and response to drought that align with species traits [ABSTRACT FROM AUTHOR]

The accurate prediction of the state of health (SOH) for lithium-ion batteries is a key factor for improving the performance of battery management systems (BMS). However, traditional point prediction methods are difficult to effectively eliminate errors due to the uncertainty of variables and application environments. This paper presents a model for predicting the interval of lithium-ion batteries based on health indicators (HIs) during charging, which addresses the limitations of current point prediction in practical applications. First, twelve HIs are extracted from the current and voltage variables of the charging process. Secondly, feature selection is performed by random forest (RF) training, and the selected HIs are dimensioned using partial least squares (PLS). Finally, a long short-term memory network (LSTM) combined with quantile regression (QR) is used to derive the quantile values of the prediction points and each quantile is employed as input information for Gaussian kernel density estimation (KDE) to obtain the SOH probability density distribution. The experimental results based on the NASA PCOE Li-ion battery dataset and CALCE Li-ion battery dataset show that the SOH interval coverage is more than 90% and the average width of the interval is less than 0.294. [ABSTRACT FROM AUTHOR]

Scots pine (Pinus sylvestris L.), a keystone species in Eurasian forests, supports diverse fungal communities and thus contributes to forest health and ecosystem functions. The southern marginal populations of P. sylvestris in Türkiye, situated in more arid and warm conditions, offer a unique environment to explore fungal biodiversity. In this study, the authors investigated the fungal assemblages in living (green) and dead (senescent, fallen, and litter) Scots pine needles in Türkiye. Using a culture-based approach coupled with DNA sequencing, distinct fungal communities were identified across different needle types. Frequent isolates included well-known P. sylvestris associates, including Lophodermium pinastri, Sydowia polyspora, and Cyclaneusma minus. Novel findings, such as unidentified Eurotiomycete and Basidiomycete taxa, suggest potentially new species and hidden fungal diversity in this biogeographically important region. Additionally, this study reports the first records of Desmazierella acicola and Phacidium lacerum in Türkiye, further underscoring the region's underexplored fungal biodiversity. Moreover, the biodiversity and community structure analysis revealed the intricate and complex nature of fungal colonization and succession, with significant variations between green, senescent, freshly fallen, and litter needles sampled concurrently. These findings provide new insights into the fungal communities of marginal, understudied Scots pine populations. [ABSTRACT FROM AUTHOR]

In the current context of climate change, this paper provides a brief overview of climate-vegetation interactions in the Mediterranean basin, where global warming and aridification trends are predicted to intensify. Rising temperatures coupled with extreme drought events have notable impacts on forest ecosystems, triggering dieback and mortality phenomena worldwide. The health status of forest vegetation may be assessed by either ground surveys or remote sensing. Several investigations of declining oak forests in the Apennine region have shown that the drought vulnerability of Mediterranean oaks is dependent on differences in access to deep soil water pools, which can be related to differences in rooting depth, tree size and growth rate. Forest dieback is widely reported in Italy, but the extent and overall distribution of this phenomenon have not yet been well defined. Thus, understanding the future dynamics of forest stands has several key objectives: inventorying declining forest stands to gain insight into the phenomenon and create a nationallevel database; locating these stands to allow monitoring of their evolution over time; and monitoring to allow planning of mitigation measures, as well as recovery and adaptation strategies. This background led to the implementation of SilvaCuore, the first web application designed in Italy to report forest health status. Silvacuore is a web application developed with the aim of improving the link between citizens and the scientific community by contributing to the development of a valuable scientific database. The direct involvement of citizens in forest preservation offers an interesting perspective because the innovative use of technology can tap into citizens' growing enthusiasm for environmental topics. Thus, SilvaCuore may be viewed from a dual perspective as a resource for the scientific community and as a unique opportunity for citizens to take an active role in research activities (Citizen Science project). [ABSTRACT FROM AUTHOR]

Predicting forest health at a regional level is challenging as forests are simultaneously attacked by multiple pathogens. Usually, the impacts of each pathogen are studied separately, however, interactions between them can affect disease dynamics. Pathogens can interact directly by competing for the same niche, but also facilitate or suppress each other via indirect effects through the host. We studied 66 native Mediterranean Pinus nigra stands located in the Pyrenees which were affected by two pathogens with different structural specificity: Dothistroma pini causing Dothistroma needle blight and Diplodia sapinea causing Diplodia shoot blight. We explored the ecology of both pathogens and whether the diseases they caused had an impact on trees and recruits. No signs of competition were found on adult trees. Diplodia shoot blight was restricted to the warmest and driest areas, while no climatic restrictions were identified for Dothistroma needle blight. Both diseases caused additive effects on crown defoliation and defoliated trees showed stagnated growth. In the regeneration layer, signs of disease suppression were found. In the warmest and driest areas, seedling mortality was mainly associated with Diplodia shoot blight, even though both pathogens were detected. Clear signs of D. pini spillover from canopy trees to recruits were found. However, seedling mortality caused by Dothistroma needle blight was only restricted to the coldest and wettest sites where D. sapinea could not survive. Large crowns in adult trees probably allow both pathogens to co‐exist and cause additive impacts. The smaller size of recruits and a higher susceptibility to environmental stress compared to adult trees probably facilitates the effects of Diplodia shoot blight which masked those caused by Dothistroma needle blight. By considering climatic constraints, host ontogeny and structural specificity, we could dissect the disease impacts of two different pathogens and successfully explain forest health at a regional scale. [ABSTRACT FROM AUTHOR]

[Objective] Forest health assessment is the basis for forest management. The aims of this study are to conduct forest health assessment, and to provide a certain theoretical basis for achieving sustainable forest management goals. [Methods] This study focused on the widely distributed plantations of Platycladus orientalis, Quercus variabilis, and Robinia pseudoacacia in the southern foothills of the Taihang Mountains. Principal component analysis, cluster analysis, and discriminant analysis were used. Stand productivity, site conditions, community organizational structure, stability and sustainability were selected to evaluate the forest health status, which composed of 21 secondary indicators. [Results Tree height, diameter at breast height, total soil K content and forest fire risk index were the main factors affecting forest health in the study area. Their principal component factor loadings were all greater than 0.6. Among the 17 surveyed plots, 8 plots had a forest health level of healthy' or 'sub healthy' (accounting for 47.0% of the total), while the corresponding forest health levels of Platycladus orientalis, Quercus variabilis, and Robinia pseudoacacia plantations were 60.0%, 33.4%, and 50.0%, respectively. The forest health levels of 9 plots were 'medium healthy' or 'unhealthy' (accounting for 53.0% of the total), and the corresponding forest health levels of Platycladus orientalis, Quercus variabilis, and Robinia pseudoacacia plantations were 40.0%, 66.7%, and 50.0%, respectively. Conclusion Overall, the health status of Platycladus orientalis and Robinia pseudoacacia plantations in the research area is good, while the health status of Quercus variabilis plantations is poor. [ABSTRACT FROM AUTHOR]

Abstract Vertical stratification of forest plays important roles in the local material balance and in maintaining forest health by distributing and redistributing precipitation materials through adsorption, fixation, and release. Differences in runoff nutrient concentrations among vertical layers are closely related to vertical stratification (factors such as the trunk, canopy, forest litter, and soil physical and chemical properties). Long-term forest observations revealed significant spatial differences in Pinus massoniana (Pinus massoniana Lamb.) forests in the Three Gorges Reservoir area. Pinus massoniana forests on downslopes were characterized by a dense canopy, green needles, and rich forest vegetation, while those on upslopes were characterized by low vegetation cover, dead trees, and decreases in the tree height, diameter at breast height, and volume per plant with increasing slope. By analyzing the soil at different sites, we found that the pH of the forest land soil differed significantly among different slope positions. Soil on upper slopes was significantly more acidic than soil on lower slopes, indicating that acidic substances were intercepted by filtration through the broad litter layer and the soil surface layer. This filtration process resulted in a normal rhizosphere environment suitable for the absorption of nutrients by vegetation on the lower slopes. In this way, downhill sites provided a good microenvironment for the growth of Pinus massoniana and other vegetation. Our results show that direct contact between needles and acid rain was not the main cause of root death. Instead, the redistribution of rainfall substances by forest spatial stratification caused changes in the soil microenvironment, which inhibited the absorption of nutrients by the roots of Pinus massoniana and the growth of understory plants in Pinus massoniana forests on upper slopes. These findings emphasize that increasing land cover with forests with vertical structural stratification plays an important role in woodland material redistribution and forest conservation.

Background: The ancient kauri (Agathis australis) dominated forests of Aotearoa New Zealand are under threat from a multitude of ecological disturbances such as forest fragmentation, biodiversity loss, climate change, and the spread of the virulent soil pathogen Phytophthora agathidicida. Taking a wider ecosystem-level approach, our research aimed to explore the impacts of forest disturbance and disease outbreaks on the biosynthetic potential and taxonomic diversity of the kauri soil microbiome. We explored the diversity of secondary metabolite biosynthetic gene clusters (BGCs) in soils from a range of kauri forests that varied according to historical disturbance and dieback expression. To characterise the diversity of microbial BGCs, we targeted the non-ribosomal peptide synthetase (NRPS) and polyketide synthetase (PKS) gene regions for sequencing using long-read PacBio® HiFi sequencing. Furthermore, the soil bacterial and fungal communities of each forest were characterized using 16 S rRNA and ITS gene region sequencing. Results: We identified a diverse array of naturally occurring microbial BGCs in the kauri forest soils, which may offer promising targets for the exploration of secondary metabolites with anti-microbial activity against P. agathidicida. We detected differences in the number and diversity of microbial BGCs according to forest disturbance history. Notably, soils associated with the most undisturbed kauri forest had a higher number and diversity of microbial NRPS-type BGCs, which may serve as a potential indicator of natural levels of microbiome resistance to pathogen invasion. Conclusions: By linking patterns in microbial biosynthetic diversity to forest disturbance history, this research highlights the need for us to consider the influence of ecological disturbances in potentially predisposing forests to disease by impacting the wider health of forest soil ecosystems. Furthermore, by identifying the range of microbial BGCs present at a naturally high abundance in kauri soils, this research contributes to the future discovery of natural microbial compounds that may potentially enhance the disease resilience of kauri forests. The methodological approaches used in this study highlight the value of moving beyond a taxonomic lens when examining the response of microbial communities to ecosystem disturbance and the need to develop more functional measures of microbial community resilience to invasive plant pathogens. [ABSTRACT FROM AUTHOR]

The Ore Mountains were historically one of the most polluted areas in Europe, where high sulphur dioxide concentrations and a high level of atmospheric deposition led to a vast decline in Norway spruce stands in the mountain ridge plateau. In this article, we evaluate the trends in the atmospheric deposition load, soil chemistry, tree nutrition, crown defoliation and height increment in a network of twenty research plots monitored for last thirty years in this region. The decrease in sulphur and nitrogen deposition was most pronounced at the end of 1990s. Extreme values of sulphur deposition (100–200 kg.ha−1.year−1) were recorded in throughfall under mature Norway spruce stands in the late 1970s, and after felling of the damaged stand, the deposition levels were comparable to open plot bulk deposition. Nitrogen deposition decreased more slowly compared with sulphur, and a decrease in base cation deposition was observed concurrently. The current deposition load is low and fully comparable to other mountain areas in central Europe. Accordingly, the health of young spruce stands, as assessed by defoliation and height increment, has improved and now corresponds to the Czech national average. On the other hand, no significant changes were observed in the soil chemistry, even though some of the plots were limed. Acidic or strongly acidic soil prevails, often with a deficiency of exchangeable calcium and magnesium in the mineral topsoil, as well as decreases in available phosphorus. This is reflected in the foliage chemistry, where we see an imbalance between a relatively high content of nitrogen and decreasing contents of phosphorus, potassium and calcium. Despite the observed positive trends in air quality and forest health, the nutritional imbalance on acidified soils poses a risk for the future of forest stands in the region. [ABSTRACT FROM AUTHOR]

Old trees are irreplaceable conservation resources with numerous ecological and socio-cultural values. While many forests have experienced significant declines under recent climate warming, the risk of growth declines in old trees remains unknown. Here, we tackle this problem by dendrochronological studies of 30 old trees in a Platycladus orientalis forest at the northern boundary of the Taihang Mountain of China. We examined annual growth trajectories of trees at individual level and discovered four severe growth decline events over the last 150 years, including the periods of 1894–1899, 1913–1919, 1964–1967 and 2004–2018. The most recent growth decline event lasted for 15-year and involced 50% to 75% of the old trees. This decline was unprecedented in both its extent and duration. Furthermore, the growth–climate relationship of these old trees has changed since 1990. Before 1990, tree growth was significantly correlated with minimum winter; after 1990, tree growth became significantly correlated with the self-calibrating Palmer Drought Index. These results suggest that warming-induced droughts after 1990 could be the primary driver of the recent growth decline. If climate warming continues and drought stresses intensify, the old trees may face an increased risk of growth decline and even mortality. [ABSTRACT FROM AUTHOR]

Castanea sativa is a high-value tree species whose stands have faced significant threats over the past century. The occurrence of one such threat, Chestnut Red Stain—a heartwood discoloration caused by the fungus Fistulina hepatica—has recently increased. This disease devalues the timber by up to 70% due to the rejection of stained wood by the industry. This study aimed to evaluate the effects of three management strategies on the occurrence of F. hepatica in chestnut coppice stands. Additionally, the co-occurrence of F. hepatica and Cryphonectria parasitica, both highly prevalent in the study area, was assessed. In 2013, three different silvicultural treatments were applied to five plots. Seven years later, the stand characteristics were measured, and the incidence of F. hepatica was evaluated using molecular tools. Data modeling revealed that the quadratic mean diameter before the interventions was related to the incidence of F. hepatica. Our results suggest that the thinning at earlier stand stages may be more critical than the type or intensity of the thinning in reducing the incidence of the fungus in the mid-term. This finding provides forest managers with new guidance to improve silvicultural treatments and prevent F. hepatica damage. [ABSTRACT FROM AUTHOR]

Xinjiang is an important forest and fruit production area in China, and Cytospora canker, caused by the genus Cytospora Ehrenb., has caused serious losses to forestry production in Xinjiang. In this study, we constructed ensemble models based on Biomod2 to assess the potential geographical distribution of Cytospora chrysosperma, C. nivea, and C. mali in Xinjiang, China and their changes under different climate change scenarios, using species occurrence data and four types of environmental variables: bioclimatic, topographic, NDVI, and soil. The model performance assessment metrics (AUC and TSS) indicated that the ensemble models are highly reliable. The results showed that NDVI had the most important effect on the distribution of all three species, but there were differences in the response patterns, and bioclimatic factors such as temperature and precipitation also significantly affected the distribution of the three species. C. chrysosperma showed the broadest ecological adaptation and the greatest potential for expansion. C. nivea and C. mali also showed expansion trends, but to a lesser extent. The overlapping geographical distribution areas of the three species increased over time and with an intensification of the climate scenarios, especially under the high-emission SSP585 scenario. The centroids of the geographical distribution for all three species generally shifted towards higher latitude regions in the northeast, reflecting their response to climate warming. C. chrysosperma may become a more prevalent forest health threat in the future, and an increase in the overlapping geographical distribution areas of the three species may lead to an increased risk of multiple infections. These findings provide an important basis for understanding and predicting the distribution and spread of the genus Cytospora in Xinjiang and are important for the development of effective forest disease prevention and control strategies. [ABSTRACT FROM AUTHOR]

Illness is a significant global societal issue in the 21st century. Forest, as an important part of terrestrial ecosystem, holds substantial health and well-being benefits. People can gain health benefits from interacting with forests, even for short periods. Unfortunately, there is a lack of systematic concern regarding the beneficial elements that forest provides to humans. In this study, a systematic review and meta-analysis were conducted following established guidelines, comprehensively evaluating the beneficial elements of the forest environment. The results indicated that the beneficial forest elements relevant to human health include beneficial substances (clean air, high-quality freshwater, CO2/O2 balance, negative air ions, and phytoncides) and beneficial factors (moderate thermal environment and biodiversity). These beneficial forest elements are products of plant's physiological processes. While their production pathways are relatively well understood, the mechanisms by which these elements impact health are unclear. This review provided the foundational data and theoretical insights for future research on the health benefits of forest elements. [ABSTRACT FROM AUTHOR]

During the summer of 2022, heat waves exacerbated drought conditions across Europe, significantly deteriorating Slovakia's forest health (FH). The main symptoms were defoliation and discolouration (mainly browning). According to the literature, completely brown leaves/needles are considered defoliation, and premature yellowing halts assimilation and reduces production. Thus, evaluating FH based solely on defoliation may underestimate the impact severity. To address this issue, we proposed a formula that integrates both defoliation and discolouration metrics. Then, by linking terrestrial and satellite data (a mosaic from Sentinel-2 and Landsat 9), regression models were developed using two-phase sampling to estimate defoliation, discolouration, and their combination. In the first phase, the Gram–Schmidt transformation of four satellite mosaic bands was used to derive two orthogonal components: one optimized for FH estimation (NSC2) and one for eliminating the influence of species composition on FH classification (NSC1). In the second phase, ground data were collected for the construction of a regression and to improve the first-phase results. The NSC2 component showed a strong correlation with defoliation, discolouration, and their combination. The standard error of the estimate was ±9.7% and the R2 was 0.83 for the combined symptoms, which enabled a detailed assessment of the intensity of forest damage. Our method is independent of tree species and has potential in FH assessments of temperate forests in Europe. [ABSTRACT FROM AUTHOR]

This study examines the critical interaction between seasonal precipitation variability and forest maturity in determining ion deposition patterns in rehabilitated forest ecosystems. This research was conducted in rehabilitated forest sites in Bintulu, Sarawak, Malaysia that had ecologically similar plant distribution, species, and age in each planting area. This facilitated the standardization of rainfall deposition in the different study plots which streamlined the study of these specific facets of ecosystem dynamics. The goal is to understand how seasonal changes and the age of the forest influence the chemical composition of the flux that relates to the movement and deposition of nutrients through the forest ecosystem. This flux is a key factor in the health of the forest ecosystem and nutrient cycling. Using ion exchange resin (IER) samplers, we accurately measured and compared the deposition of different ions (Ca2+, Na+, Fe2+, Cu2+, NO3−, NH4+ and SO42−) across different seasons and forest ages. The deposition of Ca2+ and NH₄+ was significantly lower in the low‐precipitation season than in the high‐precipitation season in all forest stands, regardless of the year they were established (1996, 1999, 2002, 2005, and 2009). In contrast, ions such as Na+, Fe2+, Cu2+, NO3− and SO42− showed no clear seasonal fluctuations. In addition, the study shows that through‐fall in forest stands from 2002, 2005 and 2009 had higher concentrations of Ca2+ in both seasons than in 1996 and 1999. Interestingly, forest stands from 2009 and 2002 had elevated levels of Na+ and SO₄2− in seasons with low precipitation, while stands from 1996 had higher levels in seasons with high precipitation. Our results emphasize the crucial role of precipitation amount and canopy age in determining ion deposition in forest ecosystems. By demonstrating the significant influence of precipitation seasonality and forest maturity on the chemical composition of throughfall, this study contributes to a deeper understanding of nutrient dynamics in developing forest landscapes and provides valuable insights for ecological restoration measures. [ABSTRACT FROM AUTHOR]

Background: Tree ontogeny is the genetic trajectories of regenerative processes in trees, repeating in time and space, including both development and reproduction. Understanding the principles of tree ontogeny is a key priority in emulating natural ecological patterns and processes that fall within the calls for closer-to-nature forest management. By recognizing and respecting the growth and development of individual trees and forest stands, forest managers can implement strategies that align with the inherent dynamics of forest ecosystem. Therefore, this study aims to determine the ontogenetic characteristics of tree regeneration and growth in northern European hemiboreal forests. Methodology: We applied a three-step process to review i) the ontogenetic characteristics of forest trees, ii) ontogenetic strategies of trees for stand-forming species, and iii) summarise the review findings of points i and ii to propose a conceptual framework for transitioning towards closer-to-nature management of hemiboreal forest trees. To achieve this, we applied the super-organism approach to forest development as a holistic progression towards the establishment of natural stand forming ecosystems. Results: The review showed multiple aspects; first, there are unique growth and development characteristics of individual trees at the pre-generative and generative stages of ontogenesis under full and minimal light conditions. Second, there are four main modes of tree establishment, growth and development related to the light requirements of trees; they were described as ontogenetic strategies of stand-forming tree species: gap colonisers, gap successors, gap fillers and gap competitors. Third, the summary of our analysis of the ontogenetic characteristics of tree regeneration and growth in northern European hemiboreal forests shows that stand-forming species occupy multiple niche positions relative to forest dynamics modes. Conclusions: This study demonstrates the importance of understanding tree ontogeny under the pretext of closer-to-nature forest management, and its potential towards formulating sustainable forest management that emulates the natural dynamics of forest structure. We suggest that scientists and foresters can adapt closer-to-nature management strategies, such as assisted natural regeneration of trees, to improve the vitality of tree communities and overall forest health. The presented approach prioritizes ecological integrity and forest resilience, promoting assisted natural regeneration, and fostering adaptability and connectivity among plant populations in hemiboreal tree communities. [ABSTRACT FROM AUTHOR]

Net primary productivity (NPP) is a key indicator of the health of forest ecosystems that offers important information about the net carbon sequestration capacity of these systems. Precise assessment of NPP is crucial for measuring carbon fixation and assessing the general well-being of forest ecosystems. Due to the distinct ecological characteristics of various forest types, accurately understanding and delineating the distribution of these types is crucial for studying NPP. Therefore, an accurate forest-type classification is necessary prior to NPP calculation to ensure the accuracy and reliability of the research findings. This study introduced deep learning technology and constructed an HRNet-CASA framework that integrates the HRNet deep learning model and the CASA model to achieve accurate estimation of forest NPP in Huangshan District, Huangshan City, Anhui Province. Firstly, based on VHR remote sensing images, we utilized the HRNet to classify the study area into six forest types and obtained the forest type distribution map of the study area. Then, combined with climate data and forest type distribution data, the CASA model was used to estimate the NPP of forest types in the study area, and the comparison with the field data proved that the HRNet-CASA framework simulated the NPP of the study area well. The experimental findings show that the HRNet-CASA framework offers a novel approach to precise forest NPP estimation. Introducing deep learning technology not only enables precise classification of forest types but also allows for accurate estimation of NPP for different types of forests. This provides a more effective tool for forest ecological research and environmental protection. [ABSTRACT FROM AUTHOR]

Weather is a significant factor influencing forest health, productivity, and the carbon cycle. However, our understanding of these effects is limited for many regions and ecosystems. Assessing the impact of weather variability on harvester productivity from plantation forests may assist in forest planning through the use of data modeling. We investigated whether weather data combined with timber harvesting attributes could be used to create a high-performance model that could accurately predict harvester productivity in Eucalyptus plantations using machine learning. Furthermore, we aimed to provide an online application to assist forest managers in applying the model. For the modeling, we considered 15 weather and timber harvesting attributes. We considered productivity as the target attribute. We subjected the database to 24 common algorithms in default mode and compared them according to error metrics and accuracy. From the timber harvesting features combined with weather features, the Catboost model can predict the productivity of harvesters in a tuned mode, with a coefficient of determination of 0.70. The use of weather data combined with timber harvesting attributes in the model is an accurate approach for predicting harvester productivity in Eucalyptus plantations, allowing for the creation of an online, free application to assist forest managers. [ABSTRACT FROM AUTHOR]

As the most important way to mitigate climate change, forest carbon storage has been the subject of extensive research. A comprehensive study was carried out to investigate the influence of elevation gradients and diameter classes on the forest growth, composition, diversity, and carbon pools of the Bagh Drush Khel Forest area. Research revealed that elevation gradients significantly influenced the composition, diversity, and carbon pools in forests. At lower elevations, Eucalyptus camaldulensis was the dominant species, with Olea ferruginea as a co-dominant species, whereas at higher elevations, Pinus roxburghii was the dominant species with Quercus incana as a co-dominant species. Regeneration was higher at higher elevations with the maximum number of saplings and seedlings of P. roxburghii. Species diversity association with elevation was negative (R2 = −0.44; p < 0.05—Shannon Index). Soil organic carbon (SOC association with elevation was non-significant while positive with DBH classes (R2 = 0.37; p < 0.05). Overall, carbon pool association with elevation and diameter at breast height (DBH) were negative (R2 = −0.73; p < 0.05) and (R2 = −0.45; p < 0.05). Litter biomass correlated positively with elevation (R2 = 0.25; p < 0.05) and DBH (R2 = 0.11; p < 0.05), while deadwood biomass correlated negatively with elevation gradients (R2 = −0.25; p < 0.05), and no effect was observed for DBH classes. The highest carbon stock (845.89 t C/ha) was calculated at low elevations, which decreased to (516.27 t C/ha) at high elevations. The overall carbon stock calculated was (2016.41 t C/ha) respectively. A total of six tree species were found at the study site. Future research is essential for forest health monitoring and understanding fine-scale impacts. This study offers a methodological framework for similar investigations in unexplored yet potentially significant forest regions worldwide. [ABSTRACT FROM AUTHOR]

Estimating tree height at the national to regional scale is crucial for assessing forest health and forest carbon storage and understanding forest ecosystem processes. It also aids in formulating forest management and restoration policies to mitigate global climate change. Extensive ground-survey data offer a valuable resource for estimating tree height. In tree height estimation modeling, a few comparative studies have examined the effectiveness of global-based versus local-based models, and the spatial heterogeneity of independent variable parameters remains insufficiently explored. This study utilized ~200,000 ground-survey data points covering the entire provincial region to compare the performance of the global-based Ordinary Least Squares (OLS) and Random Forest (RF) model, as well as local-based Geographically Weighted Regression (GWR) model, for predicting the average tree height of Chinese fir forests in Zhejiang Province China. The results showed that the GWR model outperformed both OLS and RF in terms of predictive accuracy, achieving an R-squared (R2) and adjusted R2 of 0.81 and MAE and RMSE of 0.93 and 1.28, respectively. The performance indicated that the local-based GWR held advantages over global-based models, especially in revealing the spatial non-stationarity of forests. Visualization of parameter estimates across independent variables revealed spatial non-stationarity in their impact effects. In mountainous areas with dense forest coverage, the parameter estimates for average age were notably higher, whereas in forests proximate to urban areas, the parameters were comparatively lower. This study demonstrates the effectiveness of large ground-survey data and GWR in tree height estimation modeling at a provincial scale. [ABSTRACT FROM AUTHOR]

Forest health is an attractive concept in forestry research, which environmental, social, and political interests have shaped. Assessing forest health is crucial, but finding a single definition of the concept is complex. It is determined by the aim of the forest study, different areas of knowledge, scales of work, technology, methodologies, the historical moment, or the source of funding, among others. With almost a century of scientific evidence, the aim is to identify and contextualise temporal changes in the relevance of this key concept. Trends are analysed through the construction of three main descriptors (state variables, drivers, and methods) and the main conceptual subdomains (themes). This review reveals the significant geographical bias driven by diverse needs and interests. Methodologies have evolved from traditional inventories to the use of advanced tools such as remote sensing or ecophysiology, improving forest characterisation at both global and individual scales. Research has evolved from unicausality towards holistic and multidisciplinary approaches, influencing research to date and future scenarios. We identified key knowledge gaps in the scientific literature, particularly the concepts of ecosystem services, Essential Biodiversity Variables (EBVs) and the concept of "one health". These findings highlight the need for a research assessment, future directions, and scenarios for forest health research. [ABSTRACT FROM AUTHOR]

The EFSA Panel on Plant Health performed a pest categorisation of Monema flavescens (Lepidoptera, Limacodidae), following the commodity risk assessment of Acer palmatum plants grafted on A. davidii from China, in which M. flavescens was identified as a pest of possible concern to the European Union. This species can be identified by morphological taxonomic keys and by barcoding. The adults of the overwintering generation emerge from late June to late August. The eggs are laid in groups on the underside of the host‐plant leaves, on which the larvae feed throughout their six to eight larval instars. Pupation occurs in ovoid cocoons at the junction between twigs and branches, or on the trunk. Overwintering occurs as fully grown larvae or prepupae in their cocoon. There are one or two generations per year. M. flavescens is polyphagous and feeds on broadleaves; it has been reported on 51 plant species belonging to 24 families. It mainly occurs in Asia (Bhutan, China, the Democratic People's Republic of Korea, Japan, Nepal, the Republic of Korea), Russia (Eastern Siberia) and Taiwan. It is also present in the USA (Massachusetts). The pest's flight capacities are unknown. The main pathway for entry and spread is plants for planting with cocoons attached. This is partially closed by prohibition of some hosts. In several EU member states climatic conditions are conducive for establishment and many host plants are widespread. Introduction of M. flavescens may result in defoliations influencing tree health and forest diversity. The caterpillars also have urticating spines affecting human health. Phytosanitary measures are available to reduce the likelihood of entry, establishment and spread, and there is a definite potential for classical biological control. Recognising that natural enemies prevent M. flavescens being regarded as a pest in Asia, there is uncertainty regarding the magnitude of potential impact in EU depending on the influence of natural enemies. All criteria assessed by EFSA for consideration as a potential quarantine pest are met. [ABSTRACT FROM AUTHOR]

Unsustainable snaring is causing biodiversity declines across tropical protected areas, resulting in species extinctions and jeopardizing the health of forest ecosystems. Here, we used 11 years of ranger‐collected data to assess the impact of intensive snare removal on snaring levels in two protected areas in Viet Nam. Snare removal resulted in significant declines in snare occupancy (36.9, 95% Bayesian credible interval [4.6, 59.0] reduction in percent area occupied), but snaring levels nonetheless remained high (31.4, [23.6, 40.8] percent area occupied), and came with a substantial financial cost. Our results indicate that snare removal remains an important component of efforts to protect tropical protected areas but by itself is likely insufficient to address this threat. To stop snaring in protected areas, a multifaceted approach will be necessary that combines short‐term reactive snare removal with long‐term proactive programs that address the underlying drivers behind snaring. [ABSTRACT FROM AUTHOR]

Protected areas in South Asia face significant challenges due to human disturbance and deforestation. The ongoing debate surrounds the recent surge in illegal encroachment of forest buffer zones in the Musali divisional secretariat division (DSD), which has led to a significant loss of forest cover over the past three decades. In this context, detecting changes in forest cover, assessing forest health, and evaluating environmental quality are crucial for sustainable forest management. As such, our efforts focused on assessing forest cover dynamics, forest health, and environmental conditions in the DSD from 1988 to 2022. We employed standardized image processing techniques, utilizing Landsat-5 (TM) and Landsat-8 (OLI) images. However, the forest area in the DSD has shown minimal changes, and environmental conditions and forest health have illustrated considerable spatial-temporal variations over the 34 years. The results indicated that 8.5 km2 (1.9%) of forest cover in the DSD has been converted to other land use classes. Overall, the Normalized Difference Vegetation Index (NDVI) has declined over time, while Land Surface Temperature (LST) exhibits an increasing trend. The regression results demonstrated a robust inverse relationship between LST and NDVI. The declining vegetation conditions and the increasing LST contribute to an increase in environmental criticality. The derived maps and indices will be beneficial for forest authorities in identifying highly sensitive locations. Additionally, they could enable land use planners to develop sustainable land management strategies. [ABSTRACT FROM AUTHOR]

As a component of the biogeochemical cycle, litterfall contributes carbon and nutrients to forest ecosystems by transferring organic material to mineral soil. Litterfall therefore serves as an important indicator for soil fertility and ecosystem health. This study aimed to determine the impact of different levels of thinning (light, moderate, and heavy) on litterfall quantity (needles, branches, bark, cones, and miscellaneous parts) and on the amount of carbon and nutrients entering the ecosystem in black pine afforestation areas. Three levels of low thinning, namely light, moderate, and heavy thinning (15%, 25%, and 35% of breast height area, respectively), were applied as treatments. Additionally, a control plot was included in the experiment. Litterfall samples were collected four times per year (once per season) from 12 treatment plots for three years. In the laboratory, dry weight measurements and analyses of carbon and macro–micro nutrient elements (N, P, K, Ca, Mg, S, Na, Fe, Cu, Zn, and Mn) were performed on litterfall samples taken from the field. Differences between treatments in terms of litterfall and the amount of carbon and nutrient elements entering the ecosystem were evaluated through variance analysis and the Duncan test. According to the findings, the quantity of litterfall input into the forest floor was highest in the control treatment, at 6,543 kg ha−1 year−1 and lowest in the heavy treatment, at 4,378 kg ha−1 year−1, showing a significant variation in litterfall quantity. The input of C to the soil ranged between 2,233 kg ha−1 year−1 and 3,347 kg ha−1 year−1 depending on thinning treatment. Although thinning treatment reduced C input to the soil, there was no significant difference among treatments. This also applied to nutrient elements such as N, P, K, Mg, and S. Needles constituted the majority of litterfall components (60%) and had the highest C density among all components, at 51.2%. The weighted carbon ratio for litterfall was calculated at 50.8%. Considering carbon-focused planning, performing moderate thinning interventions in the study area or similar pine-afforested areas may be a suitable option for maintaining the sustainability and health of the forest. [ABSTRACT FROM AUTHOR]

The Leaf Area Index (LAI) plays a crucial role in assessing the health of forest ecosystems. This study utilized ICESat-2/ATLAS as the primary information source, integrating 51 measured sample datasets, and employed the Sequential Gaussian Conditional Simulation (SGCS) method to derive surface grid information for the study area. The backscattering coefficient and texture feature factor from Sentinel-1, as well as the spectral band and vegetation index factors from Sentinel-2, were integrated. The random forest (RF), gradient-boosted regression tree (GBRT) model, and K-nearest neighbor (KNN) method were employed to construct the LAI estimation model. The optimal model, RF, was selected to conduct accuracy analysis of various remote sensing data combinations. The spatial distribution map of Dendrocalamus giganteus in Xinping County was then generated using the optimal combination model. The findings reveal the following: (1) Four key parameters—optimal fitted segmented terrain height, interpolated terrain surface height, absolute mean canopy height, and solar elevation angle—are significantly correlated. (2) The RF model constructed using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 data achieved optimal accuracy, with a coefficient of determination (R2) of 0.904, root mean square error (RMSE) of 0.384, mean absolute error (MAE) of 0.319, overall estimation accuracy (P1) of 88.96%, and relative root mean square error (RRMSE) of 11.04%. (3) The accuracy of LAI estimation using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 remote sensing data showed slight improvement compared to using either ICESat-2/ATLAS data combined with Sentinel-1 or Sentinel-2 data alone, with a significant enhancement in LAI estimation accuracy compared to using ICESat-2/ATLAS data alone. (4) LAI values in the study area ranged mainly from 2.29 to 2.51, averaging 2.4. Research indicates that employing ICESat-2/ATLAS spaceborne LiDAR data for regional-scale LAI estimation presents clear advantages. Incorporating SAR data and optical imagery and utilizing diverse data types for complementary information significantly enhances the accuracy of LAI estimation, demonstrating the feasibility of LAI inversion with multi-source remote sensing data. This approach offers an innovative framework for utilizing multi-source remote sensing data for regional-scale LAI inversion, demonstrates a methodology for integrating various remote sensing data, and serves as a reference for low-cost high-precision regional-scale LAI estimation. [ABSTRACT FROM AUTHOR]

Bursaphelenchus xylophilus is a pest that interferes with the health of forests and hinders the development of the forestry industry, and its spread is influenced by changes in abiotic factors and human activities. The potential distribution areas of B. xylophilus in China under four shared-economic pathways were predicted using the optimized MaxEnt model (version 3.4.3), combining data from a variety of environmental variables: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, whether the niche of B. xylophilus has changed over time is analyzed. The results showed that human activities, precipitation in the driest month, annual precipitation, and elevation had significant effects on the distribution of B. xylophilus. In the current conditions, human activities greatly reduced the survival area of B. xylophilus, and its suitable distribution area was mainly concentrated in the southwestern and central regions of China. Under the influence of climate change in the future, the habitat of B. xylophilus will gradually spread to the northeast. In addition, the ecological niche overlap analysis showed that B. xylophilus in future climate was greater than 0.74. This study provides important information for understanding the ecological adaptation and potential risk of B. xylophilus, which can help guide the decision making of pest control and forest protection. [ABSTRACT FROM AUTHOR]

Pecan forests (Carya illinoinensis) are significant contributors to both food and oil production, and thrive in diverse soil environments, including coastal regions. However, the interplay between soil microbes and pecan forest health in coastal environments remains understudied. Therefore, we investigated soil bacterial and fungal diversity in coastal (Dafeng, DF) and inland (Guomei, GM) pecan plantations using high-throughput sequencing. The results revealed a higher microbial diversity in the DF plantation than in the GM plantation, significantly influenced by pH and edaphic factors. The dominant bacterial phyla were Proteobacteria, Acidobacteriota and Bacteroidota in the DF plantation, and Acidobacteriota, Proteobacteria, and Verrucomicrobiota in the GM plantation. Bacillus, Nitrospira and UTCFX1 were significantly more abundant bacterial genera in DF soil, whereas Candidatus Udaeobacter, HSB_OF53-F07 and ADurbBin063-1 were more prevalent in GM soil. Basidiomycota dominated fungal sequences in the GM plantation, with a higher relative abundance of Ascomycota in the DF plantation. Significant differences in fungal genus composition were observed between plantations, with Scleroderma, Hebeloma, and Naucoria being more abundant in DF soil, and Clavulina, Russula, and Inocybe in GM soil. A functional analysis revealed greater carbohydrate metabolism potential in GM plantation bacteria and a higher ectomycorrhizal fungi abundance in DF soil. Significantly positive correlations were detected between certain bacterial and fungal genera and pH and total soluble salt content, suggesting their role in pecan adaptation to coastal environments and saline–alkali stress mitigation. These findings enhance our understanding of soil microbiomes in coastal pecan plantations, and are anticipated to foster ecologically sustainable agroforestry practices and contribute to coastal marshland ecosystem management. [ABSTRACT FROM AUTHOR]

This paper addresses the question of how catchment-scale water and energy balances have responded to climatic and land surface changes over the last 70 years in the federal state of Saxony in eastern Germany. Therefore, observational data of hydrological and meteorological monitoring sites from 1951 to 2020 across 71 catchments are examined in a relative water- and energy-partitioning framework to put the recent drought-induced changes into a historical perspective. A comprehensive visualization method is used to analyze the observed time series. The study focuses on changes on a decadal timescale and finds the largest decline in observed runoff in the last decade (2011–2020). The observed decline can be explained by the significant increase in aridity, caused by the reduction in annual mean rainfall and a simultaneous increase in potential evaporation. In a few mainly forested headwater catchments, the observed decline in runoff was even stronger than predicted by climate conditions alone. These catchments are still recovering from past widespread forest damages sustained in the 1970s to 1980s, resulting in a continuous increase in actual evapotranspiration due to forest regrowth. On the contrary, runoff stayed almost constant in other catchments despite an increase in aridity. These results highlight that water budgets in Saxony are in an unstable, non-stationary regime due to significant climatic changes and the regional impacts of land surface changes such as forest health. The recent decreases in the mean annual runoff are substantial and must be taken into account by the authorities for freshwater management. [ABSTRACT FROM AUTHOR]

Abstract Background Bolete cultivation is economically and ecologically valuable. Ectomycorrhizae are advantageous for plant development and productivity. This study investigated how boletes affect the formation of Pinus thunbergii and Quercus acutissima ectomycorrhizae using greenhouse-based mycorrhizal experiments, inoculating P. thunbergii and Q. acutissima with four species of boletes (Suillus bovinus, Suillus luteus, Suillus grevillei, and Retiboletus sinensis). Results Three months after inoculation, morphological and molecular analyses identified S. bovinus, S. luteus, S. grevillei and R. sinensis ectomycorrhizae formation on the roots of both tree species. The mycorrhizal infection rate ranged from 40 to 55%. The host plant species determined the mycorrhiza morphology, which was independent of the bolete species. Differences in plant growth, photosynthesis, and endogenous hormone secretion primarily correlated with the host plant species. Infection with all four bolete species significantly promoted the host plants’ growth and photosynthesis rates; indole-3-acetic acid, zeatin, and gibberellic acid secretion increased, and the abscisic acid level significantly decreased. Indole-3-acetic acid was also detected in the fermentation broths of all bolete species. Conclusions Inoculation with bolete and subsequent mycorrhizae formation significantly altered the morphology and hormone content in the host seedlings, indicating growth promotion. These findings have practical implications for culturing pine and oak tree species.

Pine wood nematode disease, commonly referred to as pine wilt, poses a grave threat to forest health, leading to profound ecological and economic impacts. Originating from the pine wood nematode, this disease not only causes the demise of pine trees but also casts a long shadow over the entire forest ecosystem. The accurate identification of infected trees stands as a pivotal initial step in developing effective prevention and control measures for pine wilt. Nevertheless, existing identification methods face challenges in precisely determining the disease status of individual pine trees, impeding early detection and efficient intervention. In this study, we leverage the capabilities of unmanned aerial vehicle (UAV) remote sensing technology and integrate the VGG classical small convolutional kernel network with U-Net to detect diseased pine trees. This cutting-edge approach captures the spatial and characteristic intricacies of infected trees, converting them into high-dimensional features through multiple convolutions within the VGG network. This method significantly reduces the parameter count while enhancing the sensing range. The results obtained from our validation set are remarkably promising, achieving a Mean Intersection over Union (MIoU) of 81.62%, a Mean Pixel Accuracy (MPA) of 85.13%, an Accuracy of 99.13%, and an F1 Score of 88.50%. These figures surpass those obtained using other methods such as ResNet50 and DeepLab v3+. The methodology presented in this research facilitates rapid and accurate monitoring of pine trees infected with nematodes, offering invaluable technical assistance in the prevention and management of pine wilt disease. [ABSTRACT FROM AUTHOR]

Soil fungi play a critical role in the biogeochemical cycles of forest ecosystems. Larix gmelinii is a strong and important timber tree species, which forms close associations with a wide range of soil fungi. However, the temporal-spatial disparity effects on the assembly of soil fungal communities in L. gmelinii forests are poorly understood. To address these questions, a total of 120 samples, including 60 bulk soil and 60 root samples, were collected from Aershan and Genhe in July (summer) and October (autumn)2021. We obtained 7,788 operational taxonomic units (OTUs) after merging, filtering, and rarefying using high-throughput sequencing. The dominant phyla are Basidiomycota, Ascomycota, Mortierellomycota, and Mucoromycota. There were 13 dominant families, among which the families with average relative abundance more than 5% included Thelephoraceae, Mortierellaceae, Archaeorhizomycoaceae, and Inocybaceae. In the functional guilds, symbiotrophic fungi had a relative advantage in the identified functions, and the relative abundances of pathotrophic and saprotrophic fungi varied significantly between sites. There were 12 families differentially expressed across compartments, 10 families differentially expressed between seasons, and 69 families were differentially expressed between sites. The variation in alpha diversity in the bulk soil was greater than that in the rhizosphere soil. Among the three parts (compartment, season, and site), the site had a crucial effect on the beta diversity of the fungal community. Deterministic processes dominated fungal community assembly in Genhe, whereas stochastic processes dominated in Aershan. Soil physicochemical properties and climatic factors significantly affected fungal community structure, among which soil total nitrogen and pH had the greatest effect. This study highlights that spatial variations play a vital role in the structure and assembly of soil fungal communities in L. gmelinii forests, which is of great significance for us in maintaining the health of the forests. [ABSTRACT FROM AUTHOR]

Monitoring drought stress is crucial for estimating productivity and assessing the health status of forest ecosystems under global climate change. Solar-induced chlorophyll fluorescence (SIF) is mechanistically coupled to photosynthesis and has advantages over greenness-based vegetation indices in detecting drought. In recent years, SIF has commonly been used in monitoring drought stress in crop ecosystems. However, the response of tower-based SIF to drought stress in forest ecosystems remains unclear. In this study, we investigated the potential of tower-based SIF to monitor drought, which was quantified using the plant water stress index (PWSI) in a Chinese cork oak plantation. The results show the negative effect of drought on SIF, and afternoon depression of SIF emission under drought stress was observed. Canopy SIF (F) exhibited a nonlinear relationship with PWSI, while the quantum yield of SIF (ΦF) exhibited a significant linear relationship with PWSI at 687 nm and 760 nm (ΦF687: R2 = 0.90; ΦF760: R2 = 0.85). Incident radiation (PAR) and canopy structure affected the response of SIF to drought stress, with PAR as the main factor causing the nonlinear relationship between F and PWSI. Afternoon depression was described as the afternoon/morning ratio (AMR). AMRF and AMRΦF exhibited a negative linear response to PWSI. AMRF was less affected than F by PAR and canopy structures, and AMRΦF was more physiologically representative than ΦF. Moreover, AMRΦF was sensitive to VPD and REW, and it might be a good indicator of drought. Red SIF was more sensitive to drought than far-red SIF, as the R2 of PWSI with AMRΦF687 (R2 = 0.89) was higher than that with AMRΦF687 (R2 = 0.84). These results highlight the potential of tower-based SIF, especially red SIF, for drought monitoring in a plantation, and consideration of the physiological diurnal variation in SIF under drought stress is crucial for improving the accuracy of drought stress monitoring. [ABSTRACT FROM AUTHOR]

Pine wood nematode (PWN) disease is a severe contagious disease in forests which endangers the health of forests, as it can rapidly kill trees. The detection of regions impacted by this disease plays a crucial role in forest management, remediation efforts and ensuring the overall ecological security of forests. With the advancements in remote sensing technology, remote sensing images offer distinct advantages such as extensive coverage, timely data acquisition and high spatial resolution, making them highly suitable for accurately and efficiently identifying PWN disease areas. This article introduces a deep learning approach for the identification of PWN disease areas using multi-temporal and multi-source remote sensing images. Specifically, a specialized model called the bitemporal image transformer (BIT) model is developed and trained using multi-temporal Beijing-2 and Beijing-3 images acquired at different stages of PWN disease. BIT is a twin network for semantic segmentation with transformer structure and its backbone utilizes the Resnet structure. The input bitemporal image can be represented by several semantic tokens and encoded using a transformer encoder. The contextual information learned from the tokens is subsequently applied back to the pixel space. Finally, transformer decoder is utilized to refine the original features. To evaluate the model's generalization ability, the best-trained model for different regions affected by pine nematode disease is identified using a transfer learning mechanism. The experimental results demonstrate a significant enhancement in classification accuracy using the proposed method, with a noteworthy 15.23% improvement in F1-score, 9.34% in accuracy, 11.7% in precision, 12.88% in recall, compared to traditional methods. Moreover, the model exhibits impressive generalization ability across various forest regions. In summary, this research introduces a promising approach that utilizes remote sensing images and deep learning techniques as a powerful tool for precisely identifying and managing areas affected by PWN disease. [ABSTRACT FROM AUTHOR]

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

The effects of the changing frequency and severity of drought events in Central Europe may become a growing concern for its forests. In this study, we looked into how Hungary's forests have been affected by the 2022 compound heatwave and drought, following an arid period from 2018 to 2021. We used our active intensive monitoring plots of the Forest Protection Measuring and Monitoring System (Level II in the ICP Forests) across the country between 2017 and 2022. We analyzed satellite images to support a survey of the large-scale drought utilizing moderate and high-resolution data. The health state of the forest calculated and mapped on the NDVI, ZNDVI, and NDWI indices showed damage and regeneration throughout the period studied. Overall, the forest stands observed tolerated the negative impacts of the drought (126–204 mm water deficit in 2022) based on our biomass data (the summer leaf loss was 14% in each monitoring plot). However, the classified Z-NDVI values of the Sentinel-2 satellite imagery for the period 2017–2022 showed a severe drought in 2022, which was followed by some improvement in 2023. [ABSTRACT FROM AUTHOR]

Dynamic ecosystems, such as the Amazon forest, are expected to show critical slowing down behavior, or slower recovery from recurrent small perturbations, as they approach an ecological threshold to a different ecosystem state. Drought occurrences are becoming more prevalent across the Amazon, with known negative effects on forest health and functioning, but their actual role in the critical slowing down patterns still remains elusive. In this study, we evaluate the effect of trends in extreme drought occurrences on temporal autocorrelation (TAC) patterns of satellite-derived indices of vegetation activity, an indicator of slowing down, between 2001 and 2019. Differentiating between extreme drought frequency, intensity, and duration, we investigate their respective effects on the slowing down response. Our results indicate that the intensity of extreme droughts is a more important driver of slowing down than their duration, although their impacts vary across the different Amazon regions. In addition, areas with more variable precipitation are already less ecologically stable and need fewer droughts to induce slowing down. We present findings indicating that most of the Amazon region does not show an increasing trend in TAC. However, the predicted increase in extreme drought intensity and frequency could potentially transition significant portions of this ecosystem into a state with altered functionality. [ABSTRACT FROM AUTHOR]

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Background: The forest fires that ravaged parts of Indonesia in 2015 were the most severely polluting of this century but little is known about their effects on health care utilization of the affected population. We estimate their short-term impact on visit rates to primary and hospital care with particular focus on visits for specific smoke-related conditions (respiratory disease, acute respiratory tract infection (ARTI) and common cold). Method: We estimate the short-term impact of the 2015 forest fire on visit rates to primary and hospital care by combining satellite data on Aerosol Optical Depth (AOD) with administrative records from Indonesian National Health Insurance Agency (BPJS Kesehatan) from January 2015–April 2016. The 16 months of panel data cover 203 districts in the islands of Sumatra and Kalimantan before, during and after the forest fires. We use the (more efficient) ANCOVA version adaptation of a fixed effects model to compare the trends in healthcare use of affected districts (with AOD value above 0.75) with control districts (AOD value below 0.75). Considering the higher vulnerability of children's lungs, we do this separately for children under 5 and the rest of the population adults (> 5), and for both urban and rural areas, and for both the period during and after the forest fires. Results: We find little effects for adults. For young children we estimate positive effects for care related to respiratory problems in primary health care facilities in urban areas. Hospital care visits in general, on the other hand, are negatively affected in rural areas. We argue that these patterns arise because accessibility of care during fires is more restricted for rural than for urban areas. Conclusion: The severity of the fires and the absence of positive impact on health care utilization for adults and children in rural areas indicate large missed opportunities for receiving necessary care. This is particularly worrisome for children, whose lungs are most vulnerable to the effects. Our findings underscore the need to ensure ongoing access to medical services during forest fires and emphasize the necessity of catching up with essential care for children after the fires, particularly in rural areas. [ABSTRACT FROM AUTHOR]

To adapt forest ecosystems and forest management to climate change, it is essential to know which forest regions and which tree species are resilient to climate variability and which ones are possibly affected most by past and anticipated future changes. In this contribution, for the main forest regions of Türkiye and six tree species, recent climate variability and trends were quantified and statistically correlated to record tree defoliation and vitality. Climate variables considered are maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean), and total precipitation (Prcp), which are compared to forest health responses recorded as part of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) on 277 plots across forests along the Black Sea and Mediterranean regions. In addition, long-term data on satellite measurements of the normalized difference vegetation index (NDVI) were extracted for the same 277 plots for the period 2008–2020. Firstly, 30 years (1991–2020) of reanalysis of climate variables from ECMWF were extracted for all plots; secondly, individual correlations and cross-correlations of climate variables and tree health and vitality were computed for the period 2008–2020 (significance level of 95%) for the four most dominant species from the Black Sea forests (F. orientalis, Q. cerris, P. sylvestris, P. orientalis) and two species from Mediterranean forests (P. brutia and C. libani). Temperature showed a stronger effect on most species than precipitation. Finally, time-lagged correlations were analyzed for seven-time lags (significance level of 95%) to evaluate legacy effect. The analysis revealed that different tree species from the two regions show different responses to climate variables. Species in the Mediterranean region are more resistant to droughts and climatic variations. Legacy effects of defoliation and NDVI have lasted for at least 2 years. [ABSTRACT FROM AUTHOR]

Forest loss and overhunting are eroding African tropical biodiversity and threatening local human food security, livelihoods, and health. Emblematic of this ecological crisis is Africa's most endangered group of monkeys, the red colobus (genus Piliocolobus). All 17 species, found in forests from Senegal in the west to the Zanzibar archipelago in the east, are threatened with extinction. Red colobus are among the most vulnerable mammals to gun hunting, typically disappearing from heavily hunted forests before most other large‐bodied animals. Despite their conservation status, they are rarely a focus of conservation attention and continue to be understudied. However, red colobus can act as critical barometers of forest health and serve as flagships for catalyzing broader African tropical forest conservation efforts. We offer a plan for conservation of red colobus and their habitats and discuss conservation and policy implications. [ABSTRACT FROM AUTHOR]

Laurel wilt, a fungal disease (Harringtonia lauricola T.C. Harr., Fraedrich and Aghayeva) spread by the Asian redbay ambrosia beetle [Xyleborus glabratus Eichhoff (Coleoptera: Curculionidae: Scolytinae)], presents an imminent threat to North American members of the Lauraceae family, having caused extensive mortality in several species, especially redbay (Persea borbonia L. Spreng). Varying levels of disease resistance have been recorded in redbay under controlled conditions. To investigate if previously monitored putatively resistant field redbays have influenced the regeneration and survival of conspecifics within the surrounding 0.08 ha, a survey was conducted in 2018-19 and compared to similar data collected years prior (2008-09, 2013) along the coasts of Florida, Georgia, and South Carolina, United States. Plots were originally established at six disease-infested study sites around large redbay (>7.5-cm diameter at breast height (1.37 m) (DBH)) that had survived the initial laurel wilt disease epidemic that began in approximately 2007. In 2018-19, a subset of 61 plots within 16 m of the original "survivor" redbay were recorded and compared to previous surveys. Among the original redbay selected for resistance, 22 of 61 (36%) survivors across all sites were alive in 2018 with survival rates varying from 0 to 70% between survey periods (average mortality 3.6%/year). Trees that died in years since 2008-09 had their plots reclassified as susceptible or "suscepts". Changes in mean quadratic diameter at 1.37 m of redbay plots near survivors were significantly greater than those near suscepts, and in 2018-19, the average diameter of redbay near survivors was 7.62 cm vs. 4.90 cm for suscepts. The diameter distribution of dead and live redbay in the whole population showed a decrease in live individuals surviving past 8 cm DBH in 2018–2019, but 20 of 22 survivor candidate trees were larger than 8 cm DBH. Regeneration was occurring both clonally and sexually and tended to be greater near suscepts, but midstory resprouts per hectare and understory seedlings interacted significantly with the site and the latter differed between sites. These findings indicate that redbay is regenerating in these ecosystems, and disease resistance may allow for increased average tree size for some individuals, but an upper size threshold of around 8 cm DBH may still exist for much of the population. In addition, the importance of site variables in regeneration was apparent, making either local genetic or environmental effects an important topic for future research. Continuing to monitor these survivors while locating new candidates for disease screenings and breeding, preventing the introductions of new strains of H. lauricola, shedding light on the nature of resistance and its heritability, and initiating outplanting trials with resistant germplasm are instrumental steps in bringing redbay back to prominence in its historical range. [ABSTRACT FROM AUTHOR]

In recent years, several drought events hit Poland, affecting its forests. In Opole, Poland, tons of Pinus sylvestris L. deadwood is removed every year due to drought. Understanding the physiological mechanisms underlying tree vulnerability to drought, and tree responses, is important to develop forest management strategies to face the ongoing climate change. This research provides comprehensive local-scale analyses of the sensitivity of healthy and declining trees to drought. We used dendrochronology and stable isotope analysis to compare five healthy and five declining trees. The analysis focused particularly on comparisons of basal area increment (BAI), δ13C, and intrinsic water-use efficiency (iWUE), as well as tree resistance, resilience, and recovery in response to drought events and sensitivity to selected meteorological parameters. We observed a significant reduction in BAI values in declining trees after 2000. Fifteen years later, the reduction was also visible in the iWUE values of these trees. Despite similar δ13C chronology patterns, declining trees showed higher δ13C correlations with meteorological parameters. We have shown that dendrochronology enables early detection of poor forest health conditions. Differences in iWUE chronologies occurring in recent years suggest that trees of both groups have chosen different adaptive strategies to cope with drought stress. [ABSTRACT FROM AUTHOR]

Studies of Phytophthora impact in forests generally focus on individual species without recognition that Phytophthora occur in multispecies communities. This study investigated community structure of Phytophthora species in the rhizosphere of Agathis australis (kauri) in Te Wao Nui o Tiriwa/Waitākere Ranges, New Zealand, in the context of kauri dieback disease expression. Soil sampling and tree monitoring were conducted on 767 randomly selected mature kauri trees. Phytophthora species were detected using both soil baiting and DNA metabarcoding of environmental DNA (eDNA). Four species were detected with soil baiting (P. agathidicida, P. cinnamomi, P. multivora, and P. pseudocryptogea/P. cryptogea) and an additional three species with metabarcoding (P. kernoviae, P. cactorum/P. aleatoria and an unknown clade 7 species). Phytophthora cinnamomi was the most abundant species and was distributed throughout the forest. Both P. multivora and P. agathidicida were limited to forest edges, suggesting more recent introductions. P. agathidicida presence was strongly correlated with declining canopy health, confirming its role as the main driver of kauri dieback. The limited distribution of P. agathidicida and infrequent detections (11.0% samples) suggests that that this species is spreading as an introduced invasive pathogen and provide hope that with strategic management (including track upgrades and closures, restricting access to uninfected areas, and continual monitoring) uninfected areas of the forest can be protected. The frequent detections of P. cinnamomi and P. multivora from symptomatic trees in the absence of P. agathidicida suggest more research is needed to understand their roles in kauri forest health. [ABSTRACT FROM AUTHOR]

Spongy moth (Lymantria dispar dispar) has caused considerable damage to oak trees across eastern deciduous forests. Forest management, post-outbreak, is resource intensive and typically focused on ecosystem restoration or resource loss mitigation. Some local forest managers and government partners are exploring developing technologies such as Unpiloted Aerial Systems (UASs, UAVs, or drones) to enhance their ability to gather reliable fine-scale information. However, with limited resources and the complexity of investing in hardware, software, and technical expertise, the decision to adopt UAS technologies has raised questions on their effectiveness. The objective of this study was to evaluate the abilities of two UAS surveying approaches for classifying the health of individual oak trees following a spongy moth outbreak. Combinations of two UAS multispectral sensors and two Structure from Motion (SfM)-based software are compared. The results indicate that the overall classification accuracy differed by as much as 3.8% between the hardware and software configurations. Additionally, the class-specific accuracy for 'Declining Oaks' differed by 5–10% (producer's and user's accuracies). The processing experience between open-source and commercial SfM software was also documented and demonstrated a 25-to-75-fold increase in processing duration. These results point out major considerations of time and software accessibility when selecting between hardware and software options for fine-scale forest mapping. Based on these findings, future stakeholders can decide between cost, practicality, technical complexity, and effectiveness. [ABSTRACT FROM AUTHOR]

The Norway spruce is one of the most important tree species in Europe. This tree species has been put under considerable pressure due to the ongoing impacts of climate change. Meanwhile, frequent droughts and pest outbreaks are reported as the main reason for its dieback, resulting in severe forest cover loss. Such was the case with Norway spruce forests within the Kopaonik National Park (NP) in Serbia. This study aims to quantify, spatially and temporally, forest cover loss and to evaluate the sensitivity of various vegetation indices (VIs) in detecting drought-induced response and predicting the dieback of Norway spruce due to long-lasting drought effects in the Kopaonik NP. For this purpose, we downloaded and processed a large number of Landsat 7 (ETM+), Landsat 8 (OLI), and Sentinel 2 (MSI) satellite imagery acquired from 2009 to 2022. Our results revealed that forest cover loss was mainly driven by severe drought in 2011 and 2012, which was later significantly influenced by bark beetle outbreaks. Furthermore, various VIs proved to be very useful in monitoring and predicting forest health status. In summary, the drought-induced response detected using various VIs provides valuable insights into the dynamics of forest cover change, with implications for monitoring and conservation efforts of Norway spruce forests in the Kopaonik NP. [ABSTRACT FROM AUTHOR]