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5768 Articles

Published in last 50 years

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  • Forest Inventory And Analysis
  • Forest Inventory And Analysis
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Shaping the future of forestry in Germany: Stakeholder perspectives on optimizing forest management through Augmented Reality.

Shaping the future of forestry in Germany: Stakeholder perspectives on optimizing forest management through Augmented Reality.

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  • Journal IconJournal of environmental management
  • Publication Date IconJun 1, 2025
  • Author Icon Felipe De Miguel-Díez + 1
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Modeling the growth and yield of natural hardwood stands in the southern United States using the Forest Inventory and Analysis data

Modeling the growth and yield of natural hardwood stands in the southern United States using the Forest Inventory and Analysis data

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  • Journal IconForest Ecology and Management
  • Publication Date IconJun 1, 2025
  • Author Icon Friday N Ogana + 2
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Optimal plot size and shape for sampling growing stocks and tree species diversity in tropical forests: Results from a forest inventory in Hazarikhil Wildlife Sanctuary of Bangladesh

Optimal plot size and shape for sampling growing stocks and tree species diversity in tropical forests: Results from a forest inventory in Hazarikhil Wildlife Sanctuary of Bangladesh

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  • Journal IconForest Ecology and Management
  • Publication Date IconJun 1, 2025
  • Author Icon Meherin Binta Musa + 8
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Evaluating LiDAR technology for accurate measurement of tree metrics and carbon sequestration.

Evaluating LiDAR technology for accurate measurement of tree metrics and carbon sequestration.

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  • Journal IconMethodsX
  • Publication Date IconJun 1, 2025
  • Author Icon Suradet Tantrairatn + 4
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Combining national forest inventories reveals distinct role of climate on tree recruitment in European forests

Combining national forest inventories reveals distinct role of climate on tree recruitment in European forests

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  • Journal IconEcological Modelling
  • Publication Date IconJun 1, 2025
  • Author Icon Louis A König + 19
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Carbon and Water Fluxes in a Temperate Scots Pine Chronosequence Study in Poland: An EC Measurement Story from an ICOS-Aspiring Country

Long-term measurements of greenhouse gases, and consequently the carbon, water, and nitrogen cycles, have been the focus of numerous studies for decades. Currently, the most accurate and widely used method for real-time, spatially-averaged estimates of these fluxes is the eddy covariance technique (EC). Over time, individual sites across Europe have been integrated into the Integrated Carbon Observation System (ICOS), creating a network with standardized measurement and data processing protocols, thereby producing high-quality, directly comparable results. Since forests play a major role in the land CO2 sink both globally and in Europe, there is naturally a substantial number of forest EC sites within ICOS. However, there are still well-equipped research sites that, for various reasons, are not yet included in this network. A notable example is Poland, the ninth largest country in Europe by area (and seventh by population), which also marks the eastern border of the European Union. In this presentation, we aim to highlight the most interesting results from a network of Scots pine forest sites in Poland, which have been measuring EC CO2 and H2O fluxes for periods ranging from a few to over 10 years. The primary goal is not only to share the results of our analysis but also to explore new collaboration opportunities with the eLTER network to fully utilize the potential of our sites beyond greenhouse gas fluxes. To provide context for why Scots pine (Pinus sylvestris) was chosen for the Polish network, it is the most widespread pine species globally and the second most distributed conifer after the common juniper (Juniperus communis). Its natural Euro-Asian range spans vast areas, and in Poland, Scots pine dominates 58.6% of the total forest area. Additionally, the mean age of Scots pine trees in Poland is 62 years, meaning that most of them are mature stands. After several years of continuous EC and basic meteorological measurements, complemented by carbon stock inventories in soil and biomass, we addressed the following research questions: What is the nature of the relationship between the age of temperate, managed Scots pine stands, and their sequestration abilities (chronosequence approach)? At what age do these stands reach their maximum sequestration potential? Does the classic forest inventory-based carbon accumulation in woody biomass align with the EC-derived Net Ecosystem Exchange estimates at both annual (based on dendrometers) and multiannual (forest inventory) scales? What is the nature of the relationship between the age of temperate, managed Scots pine stands, and their sequestration abilities (chronosequence approach)? At what age do these stands reach their maximum sequestration potential? Does the classic forest inventory-based carbon accumulation in woody biomass align with the EC-derived Net Ecosystem Exchange estimates at both annual (based on dendrometers) and multiannual (forest inventory) scales? Additional questions related specifically to the impact of different forest management practices on the carbon budget of temperate Scots pine forests were also explored and will be discussed here. In conclusion, although the presented Scots pine EC sites are not yet part of ICOS, the results may be of significant interest to other forest site Principal Investigators (PIs) in this network. This comprehensive, long-term dataset on carbon and water flux exchange between the atmosphere and one of Europe’s most common forest tree species holds relevance not only for climate-related impacts but also for socio-economic factors, as Scots pine is a crucial wood source species.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Klaudia Ziemblinska + 4
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Development of ecosystem processes, functions and biodiversity in new forests on post-agricultural land

Afforestation of post-agricultural land offers a promising nature-based solution to address climate change and biodiversity loss. However, understanding the long-term effects of land-use legacies on ecosystem processes and functions in these new forests requires a comprehensive integration of field-based measurements and advanced technologies. This study combines forest inventory data, biodiversity surveys, and soil sampling with remote sensing (LiDAR) and environmental DNA (eDNA) to assess forest structure (FS), biodiversity, and carbon dynamics in forests established on former agricultural land. We conducted a chronosequence study in beech (Fagus sylvatica), oak (Quercus robur), and spruce (Picea abies) stands planted over the past 50 years in the same afforestation area in Denmark. Ground truth data were collected within a circular plot of 15 m radius and included forest inventory, understory vegetation and soil fungal community composition from 2022, while forest floor carbon and mineral soil organic carbon (SOC) stock was from the years 1998, 2011 and 2022. FS was analysed using high-resolution national LiDAR data under leaf-off conditions from 2019, while the PacBio sequencing technology for eDNA analyses was employed to explore belowground fungal diversity and community composition. Preliminary findings suggest that FS and biodiversity are shaped by a combination of tree species types and stand age. Spruce showed rapid vertical development with dense canopy cover, while oak forests supported higher structural heterogeneity and tree species richness due to their multi-layered canopy architecture and light conditions, supporting colonization of other woody species. Beech forests exhibited significant vertical heterogeneity at later stages but tended to develop a more homogeneous structure over time. The development in understory plant and belowground fungal communities reflected land-use legacies, showing a gradual yet slow, recovery over time. In general, open habitat understory species disappeared with canopy closure and forest specialist species slowly increased over time, while generalist species remained abundant in all surveys. Dispersal limitations emerged as a primary constraint shaping the vegetation. Fungal communities transitioned more rapidly, becoming dominated by ectomycorrhizal and basidiomycete species. Forest floor carbon sequestration followed a non-linear temporal trend, stabilizing after about 30 years, suggesting higher SOC stocks under spruce compared to oak. The mineral soil C stocks increased with forest age across the three soil inventories and sequestrated 0.29 ± 0.05 Mg C ha-1 per year, where spruce exhibited the highest rates of soil carbon accumulation and biomass over time. This study emphasizes the value of combining traditional ecological measurements with emerging technologies to better understand the complex interactions driving forest development on post-agricultural landscapes. The findings highlight the potential of afforestation to support biodiversity recovery, carbon sequestration, and ecosystem functioning, while emphasizing the long-term influence of agricultural legacies on forest ecosystems.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Yamina Rosas + 7
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Combining long-term ICP Forests monitoring data with the Yasso carbon cycling model at the European scale

Forests form a major organic carbon reservoir, both above- and belowground. In the course of global change, predicting possible changes in these carbon reservoirs is essential. To this end, the Horizon Europe PathFinder project aims to develop an innovative forest monitoring system allowing consistent EU greenhouse gas reporting of LULUCF (Land Use, Land Use Change & Forestry) in combination with advanced policy pathway assessments. Greenhouse gas reporting of soil organic carbon (SOC) stock changes in forests commonly relies on simulations by soil carbon cycling models, such as Yasso (Y20), which uses only climate data and soil carbon inputs that can be derived by country-specific approaches from National Forest Inventories. However, the agreement between measured versus simulated carbon stocks and changes at the European scale has not yet been established. Within the framework of this project, this study aims to derive European-wide harmonised soil carbon inputs and stock estimates since the 1990s and further develop the current estimation methodology. After exploration of the available data sets, the ICP Forests Level II forest condition monitoring database was found the most suitable to set the initial modelling conditions. It is the only harmonised data set at the European scale that comprises above- and belowground compartments and contains repeated assessments on a subset of about 200 plots across Europe. The pre-processing of the observed data on soil carbon stock, growth and litterfall from the central ICP Forests database was very labour-intensive. As part of the ICP Forests monitoring programme, carbon concentrations and bulk densities are measured down to a depth of 80 cm. Using mass-preserving splines, soil carbon stocks were estimated down to a depth of 100 m to make them comparable with Y20. Regression models were developed to estimate litterfall inputs based on forest inventory data. We simulated SOC stocks by Y20 in ICP Forests Level II plots with available stand inventory data and soil characterization. Soil carbon inputs were obtained using two approaches: an inventory approach, with litterfall estimated by the above-mentioned regression models, and root and coarse-woody inputs by allometric functions, and a satellite approach, with net primary production (NPP) from MODIS at 500 m resolution. The Y20-simulated SOC stocks were compared with the SOC stocks to 100 cm depth based on the soil inventory data. an inventory approach, with litterfall estimated by the above-mentioned regression models, and root and coarse-woody inputs by allometric functions, and a satellite approach, with net primary production (NPP) from MODIS at 500 m resolution. The Y20-simulated SOC stocks were compared with the SOC stocks to 100 cm depth based on the soil inventory data. On average, the satellite approach estimated higher soil carbon inputs than the inventory approach (+20%). The SOC stocks simulated by Y20 were overall in line with observed SOC stocks. The simulations for broadleaf-dominated stands agreed well with SOC measurements, with average deviations below 1 kg C m-2 using the satellite approach. In coniferous stands, Y20-simulated SOC stocks were lower than observed by 3-5 kg C m-2. This is likely due to the intrinsic soil properties driving SOC storage and stabilization in highly acidic, coniferous forests (i.e. Podzols and Umbrisols), which are not accounted for in Y20.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Nathalie Cools + 8
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How ‘long term’ is long term enough? Bridging neo- and paleo-ecological timescales

A challenge in assessing the impacts of ongoing human-driven environmental and climate changes is the limited long-term data from monitoring programs and field studies, which rarely span more than a few decades (Nevalainen et al. 2020, Dodds et al. 2012). In line with common usage of ‘long term’ in ecology, Dodds et al. (2012) fined a “long-term ecological data set as data that are measured systematically through time using standardized methods that allow for the elucidation of ecological system responses (e.g., linear, lag, threshold, regime shift) to drivers, disturbances (e.g., presses or pulses), recovery from disturbances, and relevant interactions for a given hypothesis.” However, while experimental, field, and monitoring data are essential to develop insights into mechanisms and possibly reveal emerging trends, these time series provide limited insights into long-term – i.e., decadal–centennial–millennial – dynamics that enable defining reference conditions and possible underlying trajectories, which are required for identifying ongoing super-imposed changes. Since national monitoring programs in Sweden began in the early-1980’s, lake-water organic carbon (LW-TOC; Fig. 1) has been increasing in many lakes (de Wit et al. 2016), which affects light penetration and freshwater ecology (Horppila et al. 2024). Increasing LW-TOC has been attributed to decreasing S deposition, increasing temperature and wetness (de Wit et al. 2016, Monteith et al. 2007), and increasing forest cover (Finstad et al. 2016). Since precipitation monitoring began in 1978–1980, S deposition has decreased and precipitation pH increased by ~0.75–1 pH units. Temperatures have been increasing over the timeframe available from the longest continuous time series: in Lund, southern Sweden, June temperatures have increased 2°C since 1859, and in Mora, central Sweden, show a similar ~2°C increase since 1941. Finally, the Swedish National Forest Inventory indicates forests in southwestern Sweden have increased 2–4 fold and in central Sweden by ~60% since 1923. Because these long-term data for S deposition, climate, and forest growth have been changing at the same time as LW-TOC increases (Fig. 1), disentangling the relative importance of these factors. Furthermore, none of these time series provide information on reference conditions or the full timeframe of current trajectories. Using monitoring data from Sweden and specifically LW-TOC, we demonstrate the importance of integrating contemporary instrumental data with sedimentary records; that is, bridging instrumental and paleolimnological timescales (Fig. 2). This research has entailed developing calibrations between instrumental data and sediment proxies (VNIRS-inferred LW-TOC; (Meyer-Jacob et al. 2015, Meyer-Jacob et al. 2017, Rosén 2005), demonstrating the proxy signal is preserved in sediments, and assessing the trends from monitoring in relation to longer-term patterns (Meyer-Jacob et al. 2015, Meyer-Jacob et al. 2019, Meyer-Jacob et al. 2017, Myrstener et al. 2021). Our research has shown the importance of acidification/recovery, climate changes, and/or land-use changes has varied within Sweden and in other northern areas. Focusing on data from Sweden (Fig. 3), LW-TOC increased with post-glacial landscape development and thereafter remained high and stable through most of the Holocene (Meyer-Jacob et al. 2015, Myrstener et al. 2021). In northern Finland LW-TOC was also associated climate (). However, in Sweden, centuries-long traditional use led to declining LW-TOC, which began c. 700 CE in southwestern Sweden and c. 1400 in central Sweden – declining by ~50% by the 1800’s. The association with human impacts is evidenced by declining arboreal pollen, increasing pollen of plants favored by human disturbance, and occurrence of pollen from cultivated plants. In southwestern Sweden, where 20th-century impacts of acidification were greatest, LW-TOC decreased even further. The current levels of LW-TOC in these lakes are still far below the ‘natural’ levels preceding human impacts. In Canada, where historical land uses did not have the same impact as in Sweden, it has been possible to tease apart the influence of acidification and climate on recent increases in LW-TOC (Meyer-Jacob et al. 2019). During the 20th century acidification in the highest S deposition areas has been the most important driver of LW-TOC decreases – similar to the 20th-century decline in southwestern Sweden. Thus, increasing LW-TOC is mainly a response to acidification recovery. In contrast, outside of high S deposition areas LW-TOC decreased less during the mid-20th century due to S deposition, the increasing LW-TOC has in some cases exceeded pre-acidification values, indicating a climate contribution to the trend. Taken together, these centennial–millennial long records of past environmental changes have been able to identify important long-term patterns and levels in LW-TOC, and to disentangle the importance of key processes identified through field and experimental studies. The paleolimnological studies indicate there are regionally different drivers underlying the observed increases in LW-TOC in northern lakes.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Richard Bindler + 1
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Еvaluation of environmental research infrastructures services to address impacts on forest health and biodiversity

The potential of environmental research infrastructures (RIs) to fully implement the FAIR (Findable, Accessible, Interoperable, and Reusable) principles remains underutilised in addressing diverse challenges on global forest health and biodiversity. This study aims to characterise environmental RIs and their data services in tackling the effects of extreme climatic conditions on global forests. It examines the primary drivers of forest challenges across tropical, temperate, and boreal forest types, identifies the critical data required to understand these challenges, and explores the role and potential of environmental RIs in providing such data. A systematic literature search and review spanning 2013–2023 was conducted using sources such as Google, Google Scholar, and Scopus to identify documented key drivers of forest impacts, along with the relevant data types and sources utilised in the selected articles. The result has been organised in these four categories of drivers: biophysical, biological, human-induced, and socioeconomic. Furthermore, the numerous forest impacts identified are grouped into ecological, physiological, socioeconomic, and climate-related impacts. Different data types were considered in this study, ranging from carbon flux data to other various forms of experimental and field observation data. Data sources ranged from local and national forest inventories to specialized monitoring networks and research infrastructures. Four terrestrial biosphere RIs—ICOS, AnaEE, LifeWatch, and eLTER—were assessed through their websites, annual reports, and impact assessments to evaluate their data services and potential contributions to climate change on global forests. The analysis explored the frequency and significance of integrating cross-RI multidisciplinary services. The study ultimately highlights existing gaps in RI data availability, accessibility, integration, and interoperability to address interconnected and overlapping global forest challenges.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Omobola Eko + 2
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Forest 4.0 – Research Infrastructure to Support the Operationalization of Digitalization in Maintenance and Management of Forest Ecosystems

Forest ecosystems and forestry face challenges from increased timber demand, climate change, evolving global markets, rural depopulation, and growing emphasis on forests' social values. As critical carbon sinks, biodiversity reservoirs, and sources of sustainable materials, forests are vital for climate change mitigation and rural employment. However, climate change and past management practices are intensifying natural disturbances, such as storms, droughts, and wildfires. Addressing these challenges requires innovative approaches, including the integration of advanced digital technologies associated with the Fourth Industrial Revolution, such as Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and big data analytics. These technologies collectively form the foundation of the Forest 4.0 concept, which aims to enhance forest management practices. This presentation introduces the ambitions and achievements of the newly established Lithuanian research infrastructure, Forest 4.0. Developed as part of the Forest 4.0 Teaming for Excellence project, this initiative integrates research facilities and expertise from major forestry research centers at Vytautas Magnus University and the Lithuanian Research Centre for Agriculture and Forestry. The presentation highlights several case studies showcasing innovative methods for collecting, integrating, and analyzing heterogeneous environmental data. One example is the modernization of the Lithuanian National Forest Inventory to explore new aspects of forest ecosystems, such as carbon sequestration, tree micro-habitat assessment, and genetic diversity monitoring. Another example involves the digitalization of observation processes at the Aukštaitija and Žemaitija stations of integrated monitoring, which are part of the Lithuanian eLTER network. Research topics covered in these cases include forest ecosystem dynamics under a changing climate, AI-driven monitoring and prediction techniques for forest management and threat detection, the use of remote sensing and ubiquitous computing to advance geospatial methods, modeling forest processes, conducting multimodal data analyses, and developing decision-support tools to improve forest management practices.

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  • Journal IconARPHA Conference Abstracts
  • Publication Date IconMay 28, 2025
  • Author Icon Gintautas Mozgeris + 12
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Non-Linear Models Applied to Volume Estimation of Peking Wood (Caryocar villosum)

Objective: Our purpose here is to compare nonlinear models applied to estimate the wood volume of the species Caryocar villosum (popularly known as Pequiá) to indicate which one has the best goodness of fit for the location studied. Theoretical Framework: For any planning of sustainable forest management in the Amazon, Brazilian legislation requires inspection and control procedures such as the calculation of the wood volume. It is acceptable to use both the Form Factor and specifically developed equations. In the current literature, there are several volumetric models used to estimate the commercial wood volume. However, commonly used models are not particular to species and localities. Method: All data were obtained through forest inventory with all individuals located in the Caxiuanã National Forest, PA. We evaluated the models through the metrics of goodness of fit: least error of estimation, Akaike’s Information Criterion, coefficient of determination (R2 and R2adjusted), root-mean squared error, profile likelihood, intrinsic curvature and parameter effects curvature, and k-folds cross-validation. Results and Discussion: The model chosen to estimate the volume of the species Caryocar villosum was Husch model which resulted in the equation where V is the commercial wood volume and d is the diameter at breast height (DBH). Research Implications: Equation to estimate the commercial wood volume of Pequiá (Caryocar villosum) in the Caxiuanã National Forest. Originality/Value: Environmental compliance in Brazilian Amazon rainforest with a model which has the main advantage of only needing the diameter variable to estimate the volume.

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  • Journal IconRevista de Gestão Social e Ambiental
  • Publication Date IconMay 27, 2025
  • Author Icon Paulo Guilherme Pinheiro Dos Santos + 1
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Sample selection bias due to omitting short trees for tree height estimation in forest inventories: A case study on Pinus koraiensis plantations in South Korea.

This study investigates the impact of omitting short tree data on tree height estimation in conventional forest inventories, focusing on Pinus koraiensis plantations in South Korea. Twenty height-diameter models were tested on both datasets: the complete data and the short tree-free data. The models were divided into Group 1 (with two model parameters) and Group 2 (with three model parameters) to examine whether the omission of short tree data affects model performance based on the number of parameters. Results demonstrated that excluding short tree data led to significant overestimation of tree height in small diameter ranges, with Group 2 models showing greater sensitivity to the omission. This omission also caused substantial variations in model rankings between the Full and short tree-free datasets, leading to specification errors and suboptimal model selection. Despite the small sample size difference, half of the Group 2 models produced non-significant parameter estimates when fitted to the short tree-free data, underscoring the influence of sample distribution on statistical outcomes. While most models maintained consistent height-diameter relationships during extrapolation, some generated unrealistic results, including negative or excessively large tree height estimates and inverse relationships in small diameter ranges. These findings emphasize the necessity of including short trees in forest inventory samples to mitigate biases in tree height estimation, which is critical for accurate biomass and carbon stock assessments.

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  • Journal IconPloS one
  • Publication Date IconMay 9, 2025
  • Author Icon Joonghoon Shin + 4
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Can extended rotations promote the reconciliation of multiple management goals set for production forests in Nordic countries?

ABSTRACT We studied the ability of extended rotations as a measure to promote sustainable management of production forests in Nordic countries. We carried out scenario analyses for three large forest regions in Southern Finland, Central Sweden, and South-Eastern Norway, where forestry has a high socioeconomic value. We analyzed the effects on wood production, carbon sequestration, and the amount of produced deadwood over the 50 years. In the reference scenario (BAU), the prevailing management of production forests was applied. In the scenario for extended rotations (EXT), rotation lengths were extended by 30 years, on average. We used data from national forest inventories to represent the current stage of the regions’ forests and produced future forecasts using local models, which have been widely applied in large-scale analyses. The increase in carbon sequestration and production of deadwood in production forests can be achieved by lengthening rotations but only at the expense of harvesting removals. The increase in annual carbon sequestration is between 0.7 and 1.6 Mg CO2 eq ha−1. Natural mortality increases by 20–30% along with the amount of deadwood by 0.15 m3 ha−1 a−1, on average. The decrease in the mean annual harvesting removals varies from 0.4 to 1.6 m3 ha−1 a−1 from region to region.

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  • Journal IconScandinavian Journal of Forest Research
  • Publication Date IconMay 8, 2025
  • Author Icon Jari Hynynen + 11
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Comparison of Field Sampling- and Airborne Laser Scanning-Derived Stand-Level Inventories in a Mixed Conifer Forest and Volume Validation Using Log Scaling Data

Forest managers need stand-level forest inventories to make operational decisions and model growth and yield to inform long-term planning. However, few studies have quantified errors in field sampling- and airborne laser scanning (ALS)-derived inventories at the stand level, particularly in species-diverse and structurally diverse mixed conifer forests. In this study, we compared stand-level metrics derived from field cruise measurements of a forest-wide stratified sample of variable-radius plots, an ALS-derived area-based approach (ABA) trained and tested using an independent sample of fixed-area stem-mapped plots, and two ALS-derived individual tree approaches. Inventory volume estimates were validated using the gross volume of harvested logs from multi-stand harvest data, tracked by load and location and scaled at the processing mill. Results show that the ABA and individual tree approaches produced stand-level volume estimates with similar errors (−8 to 6%) to the cruise estimated volume (−16 to 6%) when compared with scaled volume. Across the entire forest, regression-based equivalence tests showed that merchantable and total stand volume estimates between the cruise and ALS-derived individual tree methods were more similar than between cruise and ABA methods, potentially due to underestimation of trees by both cruise and individual tree methods in some areas of the study area. Our results also highlight important differences between conventional cruise inventories and ALS-derived inventories, such as the spatial variability of within-stand attributes that ALS inventories provide. Overall, this study improves our understanding of the limitations and advantages of conventional and ALS-derived stand-level inventories in mixed conifer, structurally diverse forests.

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  • Journal IconForests
  • Publication Date IconMay 7, 2025
  • Author Icon Aaron M Sparks + 4
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Mapping old-growth forests using airborne lidar data and satellite images: How do plot size and rarity affect accuracy?

Old-growth forests have become rare and fragmented in the boreal biome. Their precise locations are not currently known with sufficient accuracy to support forest conservation and forest management. We studied the mapping of old-growth forests using airborne lidar data and satellite images in the Finnish coniferous forests. We investigated how plot size and the rarity of old-growth forests affect the accuracy of old-growth forest detection. We employed a Gaussian process classifier to distinguish old-growth from managed forests. Our field data consisted of 176 old-growth and 1082 managed forest plots. The results showed that an increase in plot size from 20m×20m to 60m×60m improved the performance of the classifier, because the larger plots more likely contain spatial patterns of trees and crown features indicative of forest naturalness. The largest F1-score (0.74) was achieved by data augmentation that generates additional training plots located inside forest boundaries. We also showed that the detection accuracy of old-growth forests decreases as they become rarer in the population. This rarity effect is crucial to understand, because the occurrence of old-growth forests can vary regionally due to different land use pressures. The mapping procedure proposed here can assist in the planning of field-based inventories of old-growth forests.

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  • Journal IconCanadian Journal of Forest Research
  • Publication Date IconMay 6, 2025
  • Author Icon Janne Räty + 4
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A hybrid method for tree-level forest planning

Forest inventory is increasingly producing information on the locations and sizes of individual trees. This information can be acquired by airborne or terrestrial laser scanning or analyzing photogrammetric data. However, all trees are seldom detected, especially in young, dense, or multi-layered stands. On the other hand, the complete size distributions of trees can be predicted with various methods, for instance, kNN data imputation in an area-based LiDAR inventory, predicting the parameters of a distribution function from remote sensing data, field sampling, or using histogram matching and calibration methods. The predicted distribution can be used to estimate the number and sizes of the non-detected trees. The study’s objective was to develop a method for forest planning that efficiently uses the available tree-level data in management optimization. The study developed a two-stage hierarchical method for tree-level management optimization for cases where only part of the trees is detected or measured individually. Cutting years and harvest rate curves for the non-detected trees are optimized at the higher level, and the cutting events of the detected trees are optimized at the lower level. The study used differential evolution at the higher level and simulated annealing at the lower level. The method was tested and demonstrated in even-aged Larix olgensis plantations in the Heilongjiang province of China. The optimizations showed that optimizing the harvest decisions at the tree level improves the profitability of management compared to optimizations in which only the dependence of thinning intensity on tree diameter is optimized. The approach demonstrated in this study provides feasible options for tree-level forest planning based on LiDAR inventories. The method is immediately applicable to forestry practice, especially in plantations.

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  • Journal IconJournal of Forestry Research
  • Publication Date IconMay 5, 2025
  • Author Icon Yusen Sun + 3
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Tree age estimation across the U.S. using forest inventory and analysis database

Tree age estimation across the U.S. using forest inventory and analysis database

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  • Journal IconForest Ecology and Management
  • Publication Date IconMay 1, 2025
  • Author Icon Jiaming Lu + 4
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Ecosystem multifunctionality in temperate forests of South Korea is primarily controlled by structural diversity and potential moisture availability with synergy effects between ecosystem functions.

Ecosystem multifunctionality in temperate forests of South Korea is primarily controlled by structural diversity and potential moisture availability with synergy effects between ecosystem functions.

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  • Journal IconJournal of environmental management
  • Publication Date IconMay 1, 2025
  • Author Icon Min-Ki Lee + 2
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Evaluating multi-seasonal SAR and optical imagery for above-ground biomass estimation using the national forest inventory of Zambia

Evaluating multi-seasonal SAR and optical imagery for above-ground biomass estimation using the national forest inventory of Zambia

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  • Journal IconInternational Journal of Applied Earth Observation and Geoinformation
  • Publication Date IconMay 1, 2025
  • Author Icon Kennedy Kanja + 2
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