Prior research has demonstrated that the natural regeneration of Korean pine ( Pinus koraiensis ) in old-growth forests is quantitatively constrained by the composition of parent trees. To further explore the spatial relationships between regenerated and maternal Korean pine, we examined the spatial patterns of its regeneration across four ontogenetic stages (younger seedlings, older seedlings, smaller saplings, and taller saplings) in five old-growth mixed forest stands representing a gradient of Korean pine basal area proportion (33%-77%). Using spatial point pattern analysis with crown-projected coordinates, we quantified intra- and interspecific spatial associations. Results revealed that Korean pine natural regeneration is forest-type-specific, with the ribbed birch ( Betula costata )-Korean pine forest being the most conducive to regeneration. Distribution patterns indicated a density-dependent ontogenetic shift: regenerated individuals exhibited strong aggregation at the early stage, which shifted to a random-dominated distribution in later stages, a trend amplified in stands with higher proportions of Korean pine. Associations between younger seedlings and parent trees transitioned from fine-scale facilitation to broad-scale repulsion ( p < 0.05), but only where the Korean pine proportion was approximately 50%. Notably, most heterospecific associations were neutral, with facilitation being highly species- and context-specific. We conclude that high conspecific occupancy intensifies intraspecific competition, whereas neutral associations with broadleaved species suggest that niche partitioning governs coexistence. Conservation strategies should therefore focus on regulating parent tree density and maintaining stand diversity to ensure sustainable regeneration. Methodologically, we recommend that future point pattern analyses of large canopy trees, particularly those with severe crown asymmetry, using crown coordinates.

Characterizing full-waveform laser returned intensity and bidirectional reflectance factor of forest stands using discrete point cloud data

Forest conservation and management are increasingly challenged by evolving societal expectations, biodiversity decline, and the impacts of climate change, requiring accurate, spatially detailed data for effective decision-making. Remote sensing and photogrammetry have become critical tools allowing detailed mapping and measurement of forests worldwide. While traditional satellite and airborne remote sensing remains important, ground-based data is becoming increasingly important for monitoring biodiversity and optimising management. Despite advances in deep learning for tree segmentation and species classification, the lack of extensive, high-quality labelled datasets is hampering development. To address this issue, TreeScanPL10K is being introduced - a dataset that surpasses previous resources in scope, comprising 10,417 individual trees, with species identified for approximately 72%. The dataset, which represents most of the forest-forming species in Central Europe, was collected in various Polish forest stands of different ages, composition and development stages. TreeScanPL10K aims to support researchers and forestry professionals by enabling the training and testing of advanced analytical tools, promoting transparency and accelerating progress in precision forestry and ecological studies.

Tree crown damage from disturbance events strongly influences forest demography, yet its effect on stem growth remains poorly quantified, with both positive and negative impacts reported. Hurricanes provide a powerful natural experiment to examine these dynamics, generating a broad range of structural damage across individuals and forest stands. Here we assess how crown damage from Hurricane María (2017) affected poststorm stem growth in a wet subtropical forest in Puerto Rico by combining airborne LiDAR with field measurements for 1,082 trees. Unlike previous studies, paired pre- and posthurricane LiDAR assessment enabled us to quantify crown damage as a continuous, objective variable across the canopy. Using a causal inference framework, we separated individual- from neighborhood-level effects, defined as the damage that occurred within a 5 m radius of each tree. Repeated stem growth censuses allowed direct comparison of individual growth responses before and after the hurricane. Across the community, posthurricane stem growth rates were similar to prehurricane values. Larger and more heavily damaged trees exhibited moderately reduced growth, while neighborhood crown damage and mortality had no detectable effect. However, these damage effects were smaller than the influence of prehurricane growth rates, indicating that prehurricane individual vigor outweighed biomass loss and competitive release in shaping growth responses. These findings highlight the resilience of surviving trees in sustaining carbon uptake after a severe disturbance and challenge the assumption of strong postdamage growth suppression that is embedded in dynamic vegetation models.

Abstract Previous research indicates that the effects of tree species on carbon (C) storage differ with soil age. It has been hypothesized that in young soils, trees with low carbon to nitrogen ratio (C:N) litter promote C accumulation in mineral-associated organic matter (MAOM) and mineral soil layer, while in mature soils, trees with high C:N litter support C storage in the particulate organic matter (POM) and organic soil layer. To test this, we studied adjacent forest stands of alder (low C:N litter) and spruce (high C:N litter) planted on a 50-year-old post-mining spoil heap (young soil) and in the surrounding landscape (&gt; 1,000 years, mature soil). Spruce stored more C in the organic soil layer across both soil ages. In young soil, alder stored more C in the mineral soil layer and MAOM-containing fractions (silt and clay, microaggregates), while no differences between tree species were observed in mature soil. Contrary to our expectations, no significant differences were found for C storage in POM fraction. Our results indicate that low C:N litter of alder promoted high C stocks in MAOM-containing fractions in young soil, but differences between tree species disappeared as the capacity for further C stabilization declined in mature soil. In contrast, high C:N litter of spruce enhanced C accumulation in the organic layer, contributing to greater C storage in mature soil. These findings show the necessity of considering both tree species and soil age when selecting appropriate C storage strategies and highlight the need for context-specific afforestation and reforestation approaches.

The usage of photogrammetric technologies is essential in the concept of precise forestry. Dense unmanned laser scanning (ULS) point clouds are the innovative and precise data source for canopy height model (CHM) generation. It is necessary to choose the CHM generation method and its settings appropriately. This study evaluated different CHM generation methods and aimed to select the optimal parameters for CHM generation based on dense ULS point clouds of a temperate forest in central Europe. The results show that the choice of method and settings influences the quality of parameters describing forest stands, such as tree height or volume, and determining the location of tree tops and 2D tree contours. The most accurate CHMs were generated using the pit-free method. This method provides the lowest differences between the reference values, which were evaluated using the proposed CHM quality index. The cell size of generated rasters had the most significant influence on the quality of CHM, regardless of the method. Among all variants, the optimal variant was selected with a spatial resolution of CHM of 20 cm and a number of height levels of 4 and no interpolation of values for areas without data. For coniferous forest, this variant has a mean tree top location error of 0.1 m, a mean tree top height error of 0.1 m, and a mean tree crown volume error of 8.5 m 3 . For deciduous forest, this variant has a mean tree top location error of 0.3 m, a mean tree top height error of 0.7 m, and a mean tree crown volume error of 40.8 m 3 .

Forest carbon offset programs are emerging as critical tools in mitigating climate change that support sustainable forest management. This study evaluates the carbon sequestration potential and economic viability of 13 distinct forest management scenarios using forest growth simulator (FVS) under both the Climate Action Reserve (CAR) and the American Carbon Registry (ACR) offset protocols. Scenarios included intensive practices such as clear-cutting with artificial regeneration, intermediate treatments like thinning and shelterwood, and passive approaches such as no management and prescribed burning. The no management (M0) scenario yielded the highest cumulative carbon storage but lacked the economic returns necessary for landowners' profit from selling the timber at mills. Conversely, high-grading and repeated clear-cutting scenarios resulted in lower carbon sequestration but higher net present value (NPV) for pine, but less for hardwood and mixed. Notably, the CAR protocol consistently generated greater offsets than ACR due to differences in baseline assumptions and accounting methodologies. This research highlights the trade-offs between carbon sequestration and economic returns. These findings offer actionable insights for landowners, policymakers, and offset program designers aiming to enhance climate benefits through forest management strategies. • Forest carbon offset programs help address climate change while supporting sustainable forest management. • This study evaluated 13 forest management scenarios using FVS under CAR and ACR carbon offset protocols. • M5, M9, and M10 scenarios produced higher NPVs across pine, hardwood, and mixed forest stands. • CAR produced higher carbon offsets than ACR due to differences in baseline assumptions and accounting methods. • Analysis shows a trade-off between maximizing carbon storage and economic returns in forest management planning.

Data descriptionThis dataset compiles detailed representative forest stand structure data from a European hemiboreal forest region; it spans multiple forest types, successional stages, and forest management contexts. It integrates measurements of live trees and dead wood, including fallen trunks, snags (standing dead trees), stumps and fine woody debris (down to 3 mm diameter), together with tree species identity, dimensional attributes, and decay stages. A subset of stands has been surveyed repeatedly, capturing temporal changes in forest structure.Study areaEstonia, hemiboreal forest zone. Field sampling was conducted between 2006 and 2024.Data coverageThe dataset comprises detailed stand-structure measurements from >600 forest stands, mostly represented by 2-ha plots. It includes most common hemiboreal forest types along gradients of dominant tree species and soil moisture. These range from low-productivity, dry Scots pine–dominated forests to black alder–dominated mobile-water swamps, with particularly strong representation of productive Norway spruce–deciduous mixed forests and drained peatland forests. Stand ages range from a few years post clearcutting to old stands with the dominant tree layer >200 years old. Old stands without signs of management are well represented (98 study stands) and constitute a substantial reference set for naturally developing and old-growth forest conditions in the region. The stands encompass a broad range of silvicultural treatments, including post-clearcut and post retention-cut succession, mature forests with sanitary cutting history, stands subject to precommercial and commercial thinning, and shelterwood cutting. In addition, a subset of stands includes repeated measurements of forest structure following ditch closure (rewetting) as part of a peatland forest restoration experiment.MethodsLive trees, standing dead trunks and stumps were recorded along strip plots (area-based sampling), while downed dead wood items were measured along transects (line-intersect method).ApplicationsThe dataset enables modelling above-ground tree carbon, quantitative assessment of habitat conditions for biodiversity, and analyses of their relationships with forest characteristics. It enables analyses of how specific forest management practices (clearcutting, retention forestry, shelterwood harvest, thinning) affect the stand structure, habitat quality, and carbon stocks. Because the dataset includes geopositioned measurements collected starting from the early 2000s onward, it can be combined with time-matched or contemporary remote sensing data, or with newly collected field data from stands of comparable ages, to assess structural changes in similar forest types over time. Given that hemiboreal forest types share structural features with closed-canopy boreal and northern temperate forests dominated by spruce–pine–deciduous mixtures, the dataset is applicable for regional modelling across approximately ten degrees of latitude, spanning from the Fennoscandian middle-boreal zone to the northern limit of the beech region in mid-Lithuania.

The Santa Catalina Mountains are an iconic member of the Madrean Sky Islands, rising above Tucson, Arizona, USA, where the Catalina Highway connects Sonoran desertscrub to stands of conifer forest nearly 2,800 meters in elevation. As one of the ~54 forested mountain areas in this system, the Santa Catalinas host unique biotic communities relative to the surrounding lowlands. However, most of these sky islands lack the surveys of resident small mammals (either historical or recent) needed for studying biodiversity in the context of changing climate and habitat use. From 2021 to 2023, we surveyed 10 localities on the north and south slopes of the Santa Catalina Mountains using holistic sampling methods to document terrestrial small mammal diversity and preserve multiple tissue types. Here we summarize these new collections relative to previous voucher specimens and human observations, identifying gaps for future work to address. Our survey recorded the presence of 15 species, preserved 150 voucher specimens paired with a suite of flash-frozen tissues, and non-lethally sampled another 219 individuals (ear tissue, feces, ectoparasites, and measurements) to provide populational data from sites where vouchering occurred. Despite the road accessibility and long history of sampling in the Santa Catalina Mountains, our surveys extended the known elevational range for 8 species, including the first known specimen of Reithrodontomys fulvescens from the area. Our use of a transect-based survey design, which maximizes species diversity across biotic communities, paired with holistic specimen preservation techniques, provides a model for surveying patterns of population genetic and parasite sharing relationships across other Madrean Sky Islands, bridging a ~40 year lull in specimen preservation while adding new data dimensions that promote integrative studies of small mammal biodiversity. With more complete sampling, other mountains will offer promising replicates for studying eco-evolutionary impacts of the region’s episodic habitat connectivity.

While thinnings immediately reduce aboveground biomass, they promote growth by releasing the remaining trees from competition. The biomass removed in thinnings can be used for energy, thus enabling financial returns prior to final harvest and contributing to the global share of renewable energies. In this study, the effects of thinning on stand structure dynamics and potential residential bioheat utilisation scenarios are assessed for a broadleaved mixed even-aged stand. The results demonstrate that ten years after thinning, aboveground biomass increased, ensuring system sustainability and carbon stocks. Furthermore, an average potential yield of 1.1 Mg·ha−1·a−1 (dry basis) of low-ash forest by-products was obtained, offering a sustainable supply of solid biofuels. However, the energy conversion route chosen has major impacts on the solid bioenergy demand and sustainability. Based on theoretical scenarios, upgrading from traditional fireplaces to more efficient combustion systems may reduce the specific biomass consumption up to eight times for residential heat production. The results obtained in this study highlight the challenge and need to use thinning biomass sustainably in the face of growing bioenergy demands.

Abstract. Eddy covariance (EC) measurements are a backbone of ecological research and have provided valuable insights into the variability of carbon and water fluxes in different ecosystems and under varying environmental conditions. Since these measurements are integrative and weighted over changing areas (footprint), species-specific information cannot be easily derived except for homogenous monocultures. However, EC sites are increasingly established in mixed forest stands which are considered to be more resilient under changing environmental conditions. This leads to the question of how species-specific responses can be determined, and whether the magnitude of fluxes derived from temporally varying flux footprint predictions (FFPs) can provide insight into these responses. At a site in southwestern Germany's Black Forest, primarily composed of mature beech and Douglas fir trees, we investigate the dependence of EC flux measurements on different FFP areas and explore how species-specific contributions to gas exchange can be disentangled using a combined measurement and modeling framework. We applied an ecosystem model that has been calibrated from EC measurements at various sites with beech- and Douglas fir monocultures, and evaluated it with data of soil water content and soil respiration taken at homogeneous parts of the investigated mixed forest site. Then we compared hourly aggregated measurements of net carbon exchange (NEE) and evapotranspiration (ET) with model simulations under four configurations: (i) pure beech, (ii) pure Douglas fir, (iii) a static weighted average of both species, and (iv) a dynamic weighted average based on FFP variations. The results show that weighted combinations of the two species generally provide a better match with hourly EC measurements than single-species simulations, while differences between static and dynamic weighting approaches remain relatively small. However, species-specific flux responses can be significantly different during transitional periods such as autumn and spring when physiological differences between Douglas fir and beeches are most pronounced. We demonstrate that accounting for seasonal differences is particularly important for gap-filling EC measurements in mixed forests and, consequently, for determining annual carbon and water budgets. Furthermore, EC measurements over mixed forests provide valuable information for detailed model evaluation, while species-specific modeling helps disentangle and attribute underlying ecosystem dynamics to individual species.

ABSTRACT Aim Himalaya is unique with diverse vegetation including Alnus nepalensis having potential for human wellbeing. A. nepalensis tree grows in the Himalaya, particularly in inaccessible areas and creates a barrier to soil erosion. A. nepalensis is fast growing and has the ability to enrich soil through nitrogen fixation. Its key role in biomass production and carbon storage makes it important for restoring degraded lands. Therefore, the aim of the study was to understand its potential for carbon credits for income generation and livelihood security to the local communities. Location The present study was conducted in Rudraprayag district, specifically in Chopta, Tungnath Valley, located between 30°28′39″–30°29′51″ N latitude and 79°12′9″–79°13′21″ E longitude in the Garhwal Himalayas, where good forest stands of A. nepalensis were reported between 1000 to 2500 m above sea level elevations. Time Period The study was carried out during 2023–2024 and data were collected. Major Taxa The major tree species associated with A. nepalensis were Rhododendron arboreum, Acer ceasium, Q. leucotricophora, Neolitsea sp., Lyonia ovalifolia, Q. semicarpifolia, Q. floribunda, Ficus palmata , Pyrus pashia , etc. Methods Soil and vegetation data collection and analysis were done using standard established sampling and analysis methods. Results and Main Conclusions Results of study suggest that A. nepalensis had the highest IVI across all altitudes, with an IVI of 300 (lower altitude), 150.9 (middle altitude) and 159.03 (upper altitude). Among the altitudes, A. nepalensis was reported pure in upper altitude and mixed in both middle and lower. Correlation analysis revealed a strong positive relationship between tree volume and biomass and carbon components ( r = 0.956, p &lt; 0.01), highlighting volume as a key predictor of carbon stock. Aboveground and belowground biomass and carbon variables were perfectly correlated ( r = 1.000**, p &lt; 0.01), indicating a tightly integrated biomass‐carbon dynamic. Tree density also significantly correlated with carbon variables ( r = 0.736, p &lt; 0.01). CO 2 sequestration, net carbon stock and O 2 release were strongly interrelated ( r = 1.000), though less correlated with structural parameters. Results revealed that A. nepalensis forest has potential as an effective carbon sinks across elevation zones. Soil physico‐chemical properties under A. nepalensis stands varied significantly with altitude. Moisture and WHC were strongly correlated ( r = 0.898), however, negatively related to pH, indicating more acidic, moisture‐rich soils at higher elevations. Sand decreased ( r = −0.926) and clay increased ( r = 0.882) with altitude, showing texture shifts. SOC and SOM were positively linked to moisture ( r = 0.901) and negatively to pH, suggesting moisture as a key driver of soil carbon. The C: N ratio increased with depth ( r = 0.884), reflecting vertical variation in organic matter quality. A. nepalensis biomass production, C sequestration and soil properties influence with altitudes. These trends underline altitude and moisture as key factors in soil carbon dynamics.

Analyzing the impact of neighbors’ identity and growth rate on individual tree mortality

Discriminating natural and planted forests in subtropical China using Sentinel-2 imagery and inventory data at 10 m resolution

The occurrence of forest pests and diseases is synergistically driven by stand factors (canopy closure, stand density, DBH, etc.) and site factors (elevation, soil type, slope aspect, etc.). To evaluate the effect grade of site factors on the degree of occurrence of specific forest pests and diseases after their interaction with stand factors, and to further determine the infestation severity of specific pests and diseases in stands established on suitable forestlands post-afforestation, a novel forest pest–disease base index model is defined based on the fundamental principles governing the occurrence of forest pests and diseases in specific pure forest stands. The model mandates the selection of pure forest ecosystems and the establishment of standard plots, within which a comprehensive survey of all site factors, stand factors, and target pest and disease incidence is conducted. Through methods such as stepwise regression analysis, key stand factors that influence forest pest and disease occurrence are identified, and a functional relationship between these factors and the forest pest–disease index is established. The optimal model, known as the principal curve, is obtained by relating the key stand factors to the pest–disease index. By proportionally stretching this principal curve, a series of forest pest–disease base index curves, namely the forest pest–disease base index model, is generated. These curves represent different pest–disease base index levels from bottom to top, corresponding to different grades of site effects on forest pest and disease occurrence. Furthermore, a model linking the pest–disease base index and site factors is established to evaluate the potential occurrence of pests and diseases in suitable forestlands. Applied to pure Pinus densiflora stands in Kunyu Mountain, this model quantitatively assesses the grade of site effects on the degree of occurrence of P. densiflora blight and Cephalcia kunyushanica, thereby verifying feasibility and practical applicability. It not only provides theoretical and technical support for pest and disease prediction prior to artificial forest establishment and the determination of infestation severity in post-afforestation stands but also improves ecological regulation methods for forest harmful organisms.

Introduction Railway corridors, as linear landscape structures, are highly exposed to natural hazards. In alpine regions intact protective forests form a key basis for safeguarding the route network by complementing technical protection measures through forest-related ecosystem services. From a long-term perspective, these benefits are only generated by resilient and vital forest stands. To maintain sustainable services and benefits under climate change, an understanding of the biological system and its future developments is essential. Difficulties lie in long reaction times of forest stands to management actions and a broad range of species, that need to be considered. Methods The method used in this study focuses on the extrapolation of potential natural stands based on basic climate parameters by developing a two-dimensional climatic space, describing natural stands for 46 species in all 26 operational units of the Austrian railway corridor. First, we analyzed the current distribution of woody plant species using a climate-envelope modeling approach. Secondly climatic conditions of the Austrian railway network were evaluated and modelled for future climate change scenarios. In the synthesis of steps one and two, potential natural stands were detected, quantified, contextualized and compared to the reference period 1961–2020. Results Several promising species were detected for future climate scenarios and European wide trends were confirmed on the regional scale. Especially Castanea sativa , Ulmus minor , and Sorbus torminalis can help generating vital stands that can deliver the protective functions we are aiming for. Discussion The results mark an initial step toward climate-change-adapted protective forest management by detecting changes in natural site conditions and predicting vulnerable areas along the Austrian railway corridor, offering a management tool for infrastructure operators to guide future species selection and assess risks to protective forest functions.

The online version contains supplementary material available at 10.1007/s10021-026-01047-1.

Abstract. In the forest-steppe ecotone in central Mongolia, forest and permafrost exist close to their climatic limits and are co-located on north-facing slopes. The deciduous forest ecosystems and permafrost on these slopes are linked through interactions in the local energy and water balance. Furthermore, in this region the presence of such permafrost-forest systems provides essential services that supports local livelihoods and ecosystem function. However, forest disturbances that reduce or remove the forest canopies and lead to changes in surface cover could impact ground surface temperatures (GSTs) and potentially lead to permafrost degradation. In this study, we investigate the relationship between different forest states and GSTs at a site in the forest-steppe ecotone. We measured GSTs and surveyed vegetation density and surface cover over two years in an area that features both intact, dead and logged forest and dense stands of young regrowth. Overall, we find GSTs in summer and winter to vary substantially among the forest states, while differences in GST in spring and fall are small. Compared to the intact forest, the annual GST range is increased in the dead and logged forest while it is dampened in stands of young regrowth. Contrary to existing literature, we do not observe a general warming of the ground surface at disturbed sites, but instead find mean annual GSTs at disturbed sites to be 0.5 °C lower than at intact sites. We also find substantial floor vegetation in the dead and logged forest, which has implications for livestock grazing patterns and remote sensing of forest disturbances.

In this study, we investigated the effects of flight and processing parameters on the accuracy of UAV-based photogrammetric digital terrain models (DTM) generated from RGB imagery in ageing deciduous and mixed forest stands. Four 100 × 100 m sample plots were selected, for which the reference terrain surface was established using terrestrial laser scanning. Photogrammetric DTMs derived from various parameter combinations were compared against this reference, analysing the magnitude of deviations and the influence of individual parameters through SHAP (SHapley Additive exPlanations) analysis. Based on the identified effects, we provide recommendations for optimal workflows and parameter settings. The processing chain also incorporates a targeted raster-level smoothing procedure developed by the authors, which effectively removes DTM errors caused by point cloud noise left by filtering algorithms, thereby reducing extreme deviations from the reference surface. The results show that the absolute mean elevation error is primarily influenced by flight parameters and ground point classification scale (parameter of the lasground algorithm). Optimal flight parameters were determined at a flight altitude of 100 m, with 80% front and 90% side overlap. Furthermore, a ground classification scale of 9 m proved optimal in forested environments. The proposed targeted smoothing significantly reduced extreme errors, yielding DTMs with a mean error of approximately 6 cm and maximum deviations of about 40 cm. These accuracies demonstrate that UAV-based photogrammetry, when carefully parameterised, provides a reliable basis for surface model normalization and subsequent forest structural analyses.

The article presents the results of a study on the state of coniferous and deciduous trees growing in the arboretum of the Siberian Forest Experimental Station in Tyumen to provide a possible justification for the use of promising species in order to improve the species composition of forest stands in the Tyumen Region and increase their sustainability. It has been established that according to the average indicators of sanitary and vital state, as well as the average relative height, the majority of the examined introduced coniferous tree species are characterized as healthy and stable, while deciduous tree species are weakened. The proportion of severely weakened specimens among coniferous and deciduous species does not exceed, on average, 20 and 30 %, respectively. Among coniferous tree species, Picea pungens Engelm., Larix sibirica L. and Pinus sibirica Du Tour are distinguished by high vital state indicators and decorative properties. Among deciduous tree species, these are Betula pendula Roth., B. pubescens Ehrh., Populus balsamifera L., Tilia cordata Mill. and Júglans mandshurica Maxim. According to the main inventory indicators, such coniferous species as Larix sibirica Ledeb and Pinus sibirica Du Tour, by the age of 40–60 years old, grow according to Iа–I quality classes and form highly productive stands. These species can be recommended for plantation cultivation. Picea obovata Ledeb, P. pungens Engelm., Thuja occidentalis L., Phellodéndron amurénse Rupr. and Quercus robur L. successfully adapt to the conditions of the temperate continental climate of the forest-steppe zone of the Tyumen Region. This confirms the possibility of their use for landscaping the city of Tyumen. The adaption of individual representatives of woody vegetation of the broad-leaved forest subzone and their introduction into forest stands with the aim of creating forest stands that are complex in structure and composition and, as a result, more stable in the conditions of a changing climate and ecological environment should be among the priority tasks of forestry in the protective forests of the Tyumen Region.