Forests

21 pages, 633 KiB

Open AccessArticle

Human and Machine Reliability in Postural Assessment of Forest Operations by OWAS Method: Level of Agreement and Time Resources

by Gabriel Osei Forkuo, Marina Viorela Marcu, Nopparat Kaakkurivaara, Tomi Kaakkurivaara and Stelian Alexandru Borz

Forests 2025, 16(5), 759; https://doi.org/10.3390/f16050759 (registering DOI) - 29 Apr 2025

Abstract

In forest operations, traditional ergonomic studies have been carried out by assessing body posture manually, but such assessments may suffer in terms of efficiency and reliability. Advancements in machine learning provided the opportunity to overcome many of the limitations of the manual approach. [...] Read more.

In forest operations, traditional ergonomic studies have been carried out by assessing body posture manually, but such assessments may suffer in terms of efficiency and reliability. Advancements in machine learning provided the opportunity to overcome many of the limitations of the manual approach. This study evaluated the intra- and inter-reliability of postural assessments in manual and motor-manual forest operations using the Ovako Working Posture Analysing System (OWAS)—which is one of the most used methods in forest operations ergonomics—by considering the predictions of a deep learning model as reference data and the rating inputs of three raters done in two replicates, over 100 images. The results indicated moderate to almost perfect intra-rater agreement (Cohen’s kappa = 0.48–1.00) and slight to substantial agreement (Cohen’s kappa = 0.02–0.64) among human raters. Inter-rater agreement between pairwise human-model datasets ranged from poor to fair (Cohen’s kappa = −0.03–0.34) and from fair to moderate when integrating all the human ratings with those of the model (Fleiss’ kappa = 0.28–0.49). The deep learning (DL) model highly outperformed human raters in assessment speed, requiring just one second per image, which, on average, was 19 to 53 times faster compared to human ratings. These findings highlight the efficiency and potential of integrating DL algorithms into OWAS assessments, offering a rapid and resource-efficient alternative while maintaining comparable reliability. However, challenges remain regarding subjective interpretations of complex postures. Future research should focus on refining algorithm parameters, enhancing human rater training, and expanding annotated datasets to improve alignment between model outputs and human assessments, advancing postural assessments in forest operations. Full article

(This article belongs to the Section Forest Operations and Engineering)

17 pages, 12209 KiB

Open AccessArticle

Comparative Analysis of Endophytic Bacterial Microbiomes in Healthy and Phytoplasma-Infected European Blueberry Plants

by Martynas Dėlkus, Juliana Lukša-Žebelovič, Marija Žižytė-Eidetienė, Algirdas Ivanauskas, Deividas Valiūnas and Elena Servienė

Forests 2025, 16(5), 758; https://doi.org/10.3390/f16050758 (registering DOI) - 29 Apr 2025

Abstract

Phytoplasma infections pose a significant threat to the ecological equilibrium and economic worth of Vaccinium myrtillus L., the plant’s overall well-being and capacity for fruit production. This study utilized next-generation sequencing techniques targeting the V3–V4 region of 16S rRNA genes to examine the [...] Read more.

Phytoplasma infections pose a significant threat to the ecological equilibrium and economic worth of Vaccinium myrtillus L., the plant’s overall well-being and capacity for fruit production. This study utilized next-generation sequencing techniques targeting the V3–V4 region of 16S rRNA genes to examine the endophytic bacterial communities present in both healthy and infected samples with ‘Candidatus Phytoplasma pruni’ and ‘Candidatus Phytoplasma trifolii’ related strains. Our findings revealed a total of 1.286 million raw paired-end reads across sequenced samples, which, after quality filtering, resulted in 58,492 high-quality reads without chloroplasts and 1670 amplicon sequence variants (ASVs). Infected plants exhibited statistically higher ASV richness (325 ± 71.5) than healthy plants (231 ± 21.9). This divergence suggests that, although more unique taxa were present in infected plants, their distribution was uneven or phylogenetically clustered, resulting in no significant differences in other diversity indices. However, other alpha diversity metrics did not show significant differences between the groups. Beta diversity analyses also indicated no significant differences in community composition between healthy and infected samples. The taxonomic analysis revealed that both groups were dominated by the Pseudomonadota phylum (~47.6%). However, infected plants displayed a higher prevalence of the Acidobacteriota and Myxococcota phyla, whereas healthy plants exhibited a higher prevalence of the Actinomycetota phylum. The data presented in this study suggest that ‘Candidatus Phytoplasma’ infection may result in mild changes to the bacterial community structure within V. myrtillus. These data provide insights into phytoplasma disease-related changes in the microbial diversity of the plant host. Full article

(This article belongs to the Special Issue Recent Scientific Developments in Forest Pathology)

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20 pages, 2591 KiB

Open AccessArticle

Influence of Canopy Environmental Characteristics on Regen-eration of Nine Tree Species in Broadleaved Korean Pine Forests

by Xin Du, Yelin Zhang, Huiwu Jiang and Xue Dong

Forests 2025, 16(5), 757; https://doi.org/10.3390/f16050757 (registering DOI) - 29 Apr 2025

Abstract

This study aimed to investigate the impact of local canopy environmental characteristics on the regeneration of common tree species in the understory of broadleaved Korean pine forests, thus deepening the understanding of species coexistence and forest growth cycle mechanisms. This study focused on [...] Read more.

This study aimed to investigate the impact of local canopy environmental characteristics on the regeneration of common tree species in the understory of broadleaved Korean pine forests, thus deepening the understanding of species coexistence and forest growth cycle mechanisms. This study focused on nine tree species found in the Liangshui National Nature Reserve in Heilongjiang Province, China. We stratified trees by height and simulated the LAI distribution of each class using Voronoi polygons. These layers were overlaid to generate an integrated LAI spatial map. All these procedures were integrated into the self-developed R package Broadleaf.Korean.pine.LAI, which was used to calculate individual-level canopy environment indicators, including average local LAI, local LAI standard deviation, canopy percent, vertical distribution tendency degree, local coniferous LAI, and local broadleaf LAI. These indicators were then compared with the average values of uniformly distributed understory sampling points. A principal component analysis (PCA) was conducted to reduce the dimensionality of the local canopy environmental characteristics for both the uniformly distributed points and regeneration habitats of each tree species, resulting in comprehensive canopy environmental characteristics. Wilcoxon rank-sum tests were applied to assess the significance of differences between the regeneration habitats and the understory average, as well as between the regeneration habitats of seedlings and saplings within the same species. Cliff’s delta effect size was used to evaluate the impact of each environmental factor on the transition of regeneration from seedlings to saplings. The results showed that, based on both individual canopy environmental indicators and composite indices derived from principal component analysis, seedlings tended to regenerate in areas with higher canopy coverage, whereas saplings were more commonly established in relatively open habitats. Clear differences exist between the regeneration habitats of coniferous and broadleaf species, with coniferous species tending to regenerate in areas with higher local broadleaf LAIs compared with broadleaf species. The effect size analysis showed that canopy percent, vertical distribution tendency degree, average local LAI, and local coniferous LAI have greater impacts on the transition from seedlings to saplings, while the effect of local broadleaf LAI is relatively small. These findings suggest that strong shade tolerance allows species to establish seedling banks under canopy patches, while interspecific differences in growth response to microhabitats shape their roles in the forest growth cycle. Future research should explore the physiological responses and trait characteristics of tree regeneration under varying canopy patch environments. Long-term monitoring of regeneration processes—including invasion, growth, and mortality—across different canopy patches will help elucidate the mechanisms shaping understory spatial patterns. Full article

(This article belongs to the Section Forest Ecology and Management)

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17 pages, 2250 KiB

Open AccessArticle

Long-Term Carbon Sequestration and Climatic Responses of Plantation Forests Across Jiangsu Province, China

by Yuxue Cui, Miaomiao Wu, Zhongyi Lin, Yizhao Chen and Honghua Ruan

Forests 2025, 16(5), 756; https://doi.org/10.3390/f16050756 (registering DOI) - 28 Apr 2025

Abstract

Plantation forests (PFs) play a crucial role in China’s climate change mitigation strategy due to their significant capacity to sequestrate carbon (C). Understanding the long-term trend in PFs’ C uptake capacity and the key drivers influencing it is crucial for optimizing PF management [...] Read more.

Plantation forests (PFs) play a crucial role in China’s climate change mitigation strategy due to their significant capacity to sequestrate carbon (C). Understanding the long-term trend in PFs’ C uptake capacity and the key drivers influencing it is crucial for optimizing PF management and planning for climate mitigation. In this study, we quantified the long-term (1981–2019) C sequestration of PFs in Jiangsu Province, where PFs have expanded considerably in recent decades, particularly since 2015. Seasonal and interannual variations in gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem productivity (NEP) were assessed using the boreal ecosystem productivity simulator (BEPS), a process-based terrestrial biogeochemical model. The model integrates multiple sources of remote-sensing datasets, such as leaf area index and land cover data, to simulate the critical biogeochemical processes governing land surface dynamics, enabling the quantification of vegetation and soil C stocks and nutrient cycling patterns. The results indicated a significant increasing trend in GPP, NPP, and NEP over the past four decades, suggesting enhanced C sequestration by PFs across the study region. The interannual variability in these indicators was associated with that of nitrogen (N) deposition in recent years, implying that nutrient availability could be a limiting factor for plantation productivity. Seasonal GPP and NPP exhibited peak values in spring (April to May) or late summer (August to September), with increases in growing season productivity in recent years. In contrast, NEP peaked in spring (April to May) but declined to negative values in early summer (July to August), indicating a seasonal C source–sink transition. All three indicators showed a general negative correlation with late-growing-season temperature (August to September), suggesting that summer droughts probably highly constrained the C sequestration of the existing PFs. These findings provide insights for the strategic implementation and management of PFs, particularly in regions with a warm temperate climate undergoing afforestation expansion. Full article

(This article belongs to the Section Forest Ecology and Management)

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14 pages, 12730 KiB

Open AccessArticle

Study on the Synergistic Effect of Plant Dyes and Mordants on the Dyeing and Anti-Mold Effect of Moso Bamboo

by Shan Li, Jianwen Xiong, Lilang Zheng, Yuxing Han, Song Sun, Yuxiang Peng, Kaimeng Xu and Taian Chen

Forests 2025, 16(5), 755; https://doi.org/10.3390/f16050755 (registering DOI) - 28 Apr 2025

Abstract

Bamboo’s single color and susceptibility to mold substantially limit its wide application. Therefore, dyeing and mold prevention have become pivotal technologies for the high-value-added utilization of bamboo. This study selected the extracts of three plants (Caesalpinia sappan L. (Cs), Rubia cordifolia L. [...] Read more.

Bamboo’s single color and susceptibility to mold substantially limit its wide application. Therefore, dyeing and mold prevention have become pivotal technologies for the high-value-added utilization of bamboo. This study selected the extracts of three plants (Caesalpinia sappan L. (Cs), Rubia cordifolia L. (Rc), and Carthamus tinctorius L. (Ct)) for dyeing and mold prevention experiments. The results showed that the three extracts had good dyeing effects on bamboo, with total color differences (ΔE*) of 31.69, 21.61, and 32.29 compared to untreated bamboo, respectively. Additionally, these had a moderate inhibitory effect on mold. The introduction of metal mordants effectively enhances the dyeing effect of plant dyes and the effectiveness of mold inhibition. Through the joint modification of Cs and Cu, the color fixation rate increased from 3.12% to 9.20% compared with the Cs extract. A Cu 1 g:300 mL Cs extract impregnation of bamboo can completely inhibit the growth of Aspergillus niger, and a 1 g:1100 mL ratio can completely inhibit the growth of Trichoderma viride. This study provides a new concept for applying plant dyes in the dyeing and mold prevention treatment of bamboo. The dual-effect treatment of dyeing and mold prevention enhances the visual characteristics of bamboo while imparting it with good mold prevention performance. Full article

(This article belongs to the Section Forest Ecophysiology and Biology)

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31 pages, 15699 KiB

Open AccessArticle

Preliminary Machine Learning-Based Classification of Ink Disease in Chestnut Orchards Using High-Resolution Multispectral Imagery from Unmanned Aerial Vehicles: A Comparison of Vegetation Indices and Classifiers

by Lorenzo Arcidiaco, Roberto Danti, Manuela Corongiu, Giovanni Emiliani, Arcangela Frascella, Antonietta Mello, Laura Bonora, Sara Barberini, David Pellegrini, Nicola Sabatini and Gianni Della Rocca

Forests 2025, 16(5), 754; https://doi.org/10.3390/f16050754 (registering DOI) - 28 Apr 2025

Abstract

Ink disease, primarily caused by the pathogen Phytophthora xcambivora, significantly threatens the health and productivity of sweet chestnut (Castanea sativa Mill.) orchards, highlighting the need for accurate detection methods. This study investigates the efficacy of machine learning (ML) classifiers combined with high-resolution [...] Read more.

Ink disease, primarily caused by the pathogen Phytophthora xcambivora, significantly threatens the health and productivity of sweet chestnut (Castanea sativa Mill.) orchards, highlighting the need for accurate detection methods. This study investigates the efficacy of machine learning (ML) classifiers combined with high-resolution multispectral imagery acquired via unmanned aerial vehicles (UAVs) to assess chestnut tree health at a site in Tuscany, Italy. Three machine learning algorithms—support vector machines (SVMs), Gaussian Naive Bayes (GNB), and logistic regression (Log)—were evaluated against eight vegetation indices (VIs), including NDVI, GnDVI, and RdNDVI, to classify chestnut tree crowns as either symptomatic or asymptomatic. High-resolution multispectral images were processed to derive vegetation indices that effectively captured subtle spectral variations indicative of disease presence. Ground-truthing involved visual tree health assessments performed by expert forest pathologists, subsequently validated through leaf area index (LAI) measurements. Correlation analysis confirmed significant associations between LAI and most VIs, supporting LAI as a robust physiological metric for validating visual health assessments. GnDVI and RdNDVI combined with SVM and GNB classifiers achieved the highest classification accuracy (95.2%), demonstrating their superior sensitivity in discriminating symptomatic from asymptomatic trees. Indices such as MCARI and SAVI showed limited discriminative power, underscoring the importance of selecting appropriate VIs that are tailored to specific disease symptoms. This study highlights the potential of integrating UAV-derived multispectral imagery and machine learning techniques, validated by LAI, as an effective approach for the detection of ink disease, enabling precision forestry practices and informed orchard management strategies. Full article

(This article belongs to the Special Issue Advances in Detection and Identification of Insect Pests and Pathogens)

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16 pages, 4821 KiB

Open AccessArticle

Pilot Performance Testing of a Battery-Powered Salamander Micro-Skidder in Timber Harvesting

by Grzegorz Szewczyk, Jozef Krilek, Paweł Tylek, Ján Hanes, Slavomír Petrenec, Miłosz Szczepańczyk and Dominik Józefczyk

Forests 2025, 16(5), 753; https://doi.org/10.3390/f16050753 (registering DOI) - 28 Apr 2025

Abstract

The objective of our research was to ascertain the time intensity of timber skidding with a prototype ATV Salamander 600 4 × 4 micro-skidder and to characterize the operator’s field of view. The time intensity of skidding amounts to approximately 20 min/m³ [...] Read more.

The objective of our research was to ascertain the time intensity of timber skidding with a prototype ATV Salamander 600 4 × 4 micro-skidder and to characterize the operator’s field of view. The time intensity of skidding amounts to approximately 20 min/m³ at a distance of 20 m when skidding timber from the forest stand and approximately 10 min/m³ when skidding along the skid trail for a distance of 80 m, which is comparable to other machines of this type, despite reported problems with raw material causing jamming on rugged terrain in the first phase of the skidding process. The significant discrepancy (6%) in wheel slippage between the front and rear axles was particularly pronounced during the process of pulling timber up to the skid trail. This can be attributed to the transport hitch being positioned excessively high, thereby relieving the force on the hitch and causing the front axle to be affected. The observed difficulties in skidding resulted in the need to scan a wide visual scene when working in the stand. The initial phase of timber skidding in the forest stand exhibited a deficiency in its smooth flow, which led to an augmentation in mental workload, as indicated by the elongation of saccades. On average, these saccades were approximately 80% longer compared to those in work conducted on the skid trail. Full article

(This article belongs to the Section Forest Operations and Engineering)

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23 pages, 2317 KiB

Open AccessArticle

Evaluating Nature-Based Versus Generic Physical Activity Programs to Address Chronic Health Conditions: Lessons from an Oregon (USA) Pilot Study

by Randall Bluffstone, Ma Chan, Cort Cox, Melinda M. Davis, Caitlin Dickinson, Sahan T. M. Dissanayake, Jeffrey D. Kline, Citlactli Carrera López, Himani Ojha, Sterling Stokes, Saurabh S. Thosar and Srilakshmi Vedantam

Forests 2025, 16(5), 752; https://doi.org/10.3390/f16050752 (registering DOI) - 28 Apr 2025

Abstract

Evidence appears to be building that direct exposure to natural landscapes characterized by significant green cover, such as forests, can help to reduce chronic health conditions such as obesity, stress, hypertension, chronic cardiovascular conditions, depression, anxiety, cancer, and diabetes. One way to encourage [...] Read more.

Evidence appears to be building that direct exposure to natural landscapes characterized by significant green cover, such as forests, can help to reduce chronic health conditions such as obesity, stress, hypertension, chronic cardiovascular conditions, depression, anxiety, cancer, and diabetes. One way to encourage greater exposure to nature may be through the use of nature prescriptions, whereby clinicians formally recommend (or prescribe) time in nature to their patients. Based on self-reported data, we describe the implementation and lessons learned from a pilot field experiment examining the clinical use of nature-based versus conventional exercise recommendations in rural Oregon. We discuss the potential benefits of such recommendations, as well as identify several challenges and opportunities associated with field experiments seeking to evaluate whether nature prescriptions, offered as one part of patients’ overall treatment plans, meaningfully improve human health outcomes in clinical settings. We conclude with several recommendations for practitioners and researchers interested in implementing and evaluating nature-based exercise programs to improve public health. Full article

(This article belongs to the Special Issue Forests and Human Health: Effects on Acute and Chronic Illness, and Public Health)

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17 pages, 1466 KiB

Open AccessArticle

Regeneration Patterns in Cork Oak (Quercus suber L.) Stands: Insights from Transect and Cluster Sampling Inventory Designs

by Angelo Fierravanti and Teresa Fidalgo Fonseca

Forests 2025, 16(5), 751; https://doi.org/10.3390/f16050751 (registering DOI) - 28 Apr 2025

Abstract

The resilience and regeneration of cork oak (Quercus suber L.) play a central role in sustaining the European oak landscape, particularly within the socio-economic and ecological frameworks of the Western Mediterranean. This species has a noticeable ability to withstand drought and temperature [...] Read more.

The resilience and regeneration of cork oak (Quercus suber L.) play a central role in sustaining the European oak landscape, particularly within the socio-economic and ecological frameworks of the Western Mediterranean. This species has a noticeable ability to withstand drought and temperature extremes. However, its natural regeneration is increasingly challenged by climate change and associated extreme weather events, as well as by competition among individuals for light, water, and nutrients. Monitoring this process in the field can be time-consuming, requiring the use of sampling techniques and the identification of appropriate inventory sampling design (ISD) schemes. Line transect (LT) and radial cluster (RC) inventory designs are widely used in ecological studies, botanical research, and plant species distribution assessments, as well as other environmental forestry studies. This research compares two inventory sampling designs (line transect vs. radial cluster) for inventorying and monitoring the dynamics of natural regeneration at the initial development stages of cork oak. In particular, this study evaluates the influences of inventory sampling design, time, and acorn density on the total living and dead seedlings over a two-year period, using the cork oak as a reference species in the Mediterranean climate of Northern Portugal. The results confirm the critical role of acorn availability in seedling regeneration dynamics within cork oak ecosystems and emphasize a temporal increase in the death of seedlings, markedly influenced by the day of year. The temporal component had a substantial impact on seedling mortality, which increased by 5.00‰ per day, meaning that one seedling died approximately every 200 days, whereas mortality spikes occur on specific days, suggesting temporal factors affecting seedling viability. The study also shows differences in regeneration estimates between the inventory designs. The line transect design records lower acorn density and seedlings than the radial cluster design. The results highlight an important but often overlooked source of variation in forest regeneration studies, emphasizing the need for careful consideration of inventory methods to ensure effective data collection and accurate representation of natural regeneration dynamics, ultimately supporting efforts to enhance cork oak regeneration and resilience against climate change and competitive pressures. Full article

(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)

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17 pages, 4027 KiB

Open AccessArticle

The Effect of Hydrometeorological Factors on Tree Growth (Abies borisii-regis Mattf.) in Mountainous Watersheds (Central Greece)

by Aristeidis Kastridis, Dimitrios Koutsianitis and Dimitrios Stathis

Forests 2025, 16(5), 750; https://doi.org/10.3390/f16050750 (registering DOI) - 27 Apr 2025

Abstract

Tree ring chronologies (tree ring width—TRW, earlywood—EW, latewood—LW) were constructed to investigate fir’s (Abies borisii-regis Mattf.) response to key hydrometeorological factors, namely precipitation, temperature and drought (12-month Standardized Precipitation Evapotranspiration Index, SPEI-12). There has been only one previously published study conducted in [...] Read more.

Tree ring chronologies (tree ring width—TRW, earlywood—EW, latewood—LW) were constructed to investigate fir’s (Abies borisii-regis Mattf.) response to key hydrometeorological factors, namely precipitation, temperature and drought (12-month Standardized Precipitation Evapotranspiration Index, SPEI-12). There has been only one previously published study conducted in the northern area of the species’ expansion (Albania). The current study was conducted in the southern area of the species’ expansion (Central Greece). Precipitation was the most important factor that affected tree growth. May precipitation was positively correlated with LW, while June and July precipitation was positively correlated with both EW and LW. Previous September precipitation was positively correlated with EW and LW. Interestingly, the current September precipitation was negatively correlated with EW. High temperatures in April showed a positive relation with LW, high temperatures in June negatively affected all chronologies, while high temperatures July and August were negatively related with LW. High autumn temperatures in the previous year significantly (negatively) influenced all tree ring chronologies. The SPEI index revealed that wet conditions during May and June positively correlated with high tree growth for both EW and LW, while wet conditions in July and August significantly affect LW formation. Wet conditions in the previous September also had a positive effect on tree growth. SPEI showed similar behavior with precipitation, showing that precipitation is the driving factor in fir growth. The results highlight the importance of summer rainfall and temperature in controlling tree growth in Mediterranean regions. The study revealed significant knowledge on the susceptibility of Abies borisii-regis Mattf. to climate variability and highlighted its consequences for future forest management plans. Full article

(This article belongs to the Section Forest Meteorology and Climate Change)

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25 pages, 19913 KiB

Open AccessArticle

Genome-Wide Identification, Evolution and Expression Analysis of the U-Box E3 Ubiquitin Ligases Gene Family in Poplar (Populus alba × P. tremula var. glandulosa)

by Bobo Song, Qixuan Wei, Xudong Liu, Kexin Sun, Lingdou Liao, Anning Zu, Yifan Wei, Qian Liu, Fangfang Fu and Meiling Ming

Forests 2025, 16(5), 749; https://doi.org/10.3390/f16050749 (registering DOI) - 27 Apr 2025

Abstract

Plant U-box E3 ubiquitin ligases (PUBs) serve as crucial regulators of protein degradation and are fundamentally involved in plant developmental processes and stress response mechanisms. Despite their well-characterized roles in model plant species, the PUB gene family in the hybrid poplar (Populus [...] Read more.

Plant U-box E3 ubiquitin ligases (PUBs) serve as crucial regulators of protein degradation and are fundamentally involved in plant developmental processes and stress response mechanisms. Despite their well-characterized roles in model plant species, the PUB gene family in the hybrid poplar (Populus alba × P. tremula var. glandulosa) remains poorly understood. By conducting a comprehensive genome-wide analysis, we identified 152 PUB genes in poplar and phylogenetically classified them into five distinct clades based on a comparative analysis with Arabidopsis thaliana and tomato PUB homologs. The structural characterization revealed that numerous PagPUB proteins possess additional functional domains, including ARM and WD40 repeats, which are indicative of potential functional diversification. Genomic distribution and synteny analyses demonstrated that the expansion of the PUB gene family predominantly resulted from whole-genome duplication (WGD) events, with evolutionary constraint analyses (Ka/Ks ratios < 1) suggesting strong purifying selection. An examination of the promoter region uncovered an abundance of stress-responsive cis-elements, particularly ABRE and MYB binding sites associated with abiotic stress and hormonal regulation. Transcriptome profiling demonstrated both tissue-specific expression patterns and dynamic regulation under diverse stress conditions, including drought, salinity, temperature extremes, and pathogen infection. Our findings provide the first systematic characterization of the PUB gene family in poplar and establish a valuable framework for elucidating their evolutionary history and functional significance in environmental stress adaptation. Full article

(This article belongs to the Section Genetics and Molecular Biology)

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19 pages, 3695 KiB

Open AccessArticle

Contextualizing Estimated Tree Densities and Expert-Classified Ecosystems in the Historical Midwestern United States, a Region with Exposure to Frequent Fires

by Brice B. Hanberry, Charles M. Ruffner and Robert Tatina

Forests 2025, 16(5), 748; https://doi.org/10.3390/f16050748 (registering DOI) - 27 Apr 2025

Abstract

Many ecosystems have been altered since European colonization, resulting in the loss of historical ecosystems along with information about historical ecosystems. Tree density estimation from historical land surveys with alignment to expert classifications of historical vegetation strengthen reconstructions of vegetation history through research [...] Read more.

Many ecosystems have been altered since European colonization, resulting in the loss of historical ecosystems along with information about historical ecosystems. Tree density estimation from historical land surveys with alignment to expert classifications of historical vegetation strengthen reconstructions of vegetation history through research triangulation. For the midwestern United States, we extended historical tree density estimates (≥12.7 cm in diameter) to contextualize expert classifications of vegetation types in Illinois and Minnesota, part of the historical Great Plains grasslands with very frequent fire exposure, and Indiana and southern Michigan, which were more protected from fire. We also identified a tree density threshold between grasslands and savannas and contrasted density estimates with two alternate density estimates. After refining expert-classified vegetation types, out of 14 major historical ecosystems in this region, 11 were grasslands, savannas, or woodlands. The three additional ecosystems were American beech (Fagus grandifolia) closed woodlands and forests in Indiana and American beech-oak (Quercus) closed woodlands and forests and tamarack (Larix laricina) and ash (Fraxinus) swamp forests in southern Michigan. Because tree densities in the grasslands of Illinois and Minnesota did not exceed 4 trees/ha and tree densities in the savannas of Indiana, Michigan, and Minnesota ranged from 23 trees/ha to 78 trees/ha, around 15 trees/ha may be a reasonable threshold between grasslands and savannas. Density estimates generally matched with two other sources of density estimates, despite using different approaches, supporting the reliability of density estimation. Anchoring density estimates from land surveys to other sources of historical vegetation establishes the validity of density estimation, while supplementing expert-classified ecosystems. Full article

(This article belongs to the Section Forest Ecology and Management)

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29 pages, 4155 KiB

Open AccessReview

Global Meta-Analysis of Mangrove Primary Production: Implications for Carbon Cycling in Mangrove and Other Coastal Ecosystems

by Daniel M. Alongi

Forests 2025, 16(5), 747; https://doi.org/10.3390/f16050747 (registering DOI) - 27 Apr 2025

Abstract

Mangrove forests are among the most productive vascular plants on Earth. The gross (GPP) and aboveground forest net primary production (ANPP) correlate positively with precipitation. ANPP also correlates inversely with porewater salinity. The main drivers of the forest primary production are the porewater [...] Read more.

Mangrove forests are among the most productive vascular plants on Earth. The gross (GPP) and aboveground forest net primary production (ANPP) correlate positively with precipitation. ANPP also correlates inversely with porewater salinity. The main drivers of the forest primary production are the porewater salinity, rainfall, tidal inundation frequency, light intensity, humidity, species age and composition, temperature, nutrient availability, disturbance history, and geomorphological setting. Wood production correlates positively with temperature and rainfall, with rates comparable to tropical humid forests. Litterfall accounts for 55% of the NPP which is greater than previous estimates. The fine root production is highest in deltas and estuaries and lowest in carbonate and open-ocean settings. The GPP and NPP exhibit large methodological and regional differences, but mangroves are several times more productive than other coastal blue carbon habitats, excluding macroalgal beds. Mangroves contribute 4 to 28% of coastal blue carbon fluxes. The mean and median canopy respiration equate to 1.7 and 2.7 g C m⁻² d⁻¹, respectively, which is higher than previous estimates. Mangrove ecosystem carbon fluxes are currently in balance. However, the global mangrove GPP has increased from 2001 to 2020 and is forecast to continue increasing to at least 2100 due to the strong fertilization effect of rising atmospheric CO₂ concentrations. Full article

(This article belongs to the Special Issue Mangrove Forest Ecosystems: Present Status, Challenges, and Future Directions)

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13 pages, 1869 KiB

Open AccessArticle

Classification of the Vegetation of Pinus densiflora Forests Distributed in Baekdudaegan (From Hyangrobong to Cheonwangbong), South Korea

by Jeong-Eun Lee, Ju-Hyeon Song, Ho-Jin Kim, Hyun-Je Cho, Wan-Geun Park and Chung-Weon Yun

Forests 2025, 16(5), 746; https://doi.org/10.3390/f16050746 (registering DOI) - 27 Apr 2025

Abstract

Pinus densiflora and Quercus mongolica are representative forest vegetation communities in Baekdudaegan, South Korea. Recently, signs of deterioration, such as natural succession, disease, and insect pests, have been detected. Therefore, this study aims to classify the vegetation types and elucidate the vegetation structure [...] Read more.

Pinus densiflora and Quercus mongolica are representative forest vegetation communities in Baekdudaegan, South Korea. Recently, signs of deterioration, such as natural succession, disease, and insect pests, have been detected. Therefore, this study aims to classify the vegetation types and elucidate the vegetation structure across the entire South Korean section of the Baekdudaegan, from Hyangrobong to Cheonwangbong, while also proposing strategies for vegetation conservation and management. A vegetation survey was conducted in 341 plots investigated from 2016 to 2020. Cluster analysis revealed nine community types, with a single indicator species, Rhododendron schlippenbachii, in Community 1 (C1); two, Fraxinus sieboldiana and Calamagrostis arundinacea, in C2; six, including Carex humilis var. nana, Polygonatum odoratum var. pluriflorum, and Quercus variabilis, in C3; three, Sasa borealis, Q. mongolica, and Erigeron annuus, in C4; two, Rhododendron mucronulatum and Vaccinium koreanum, in C5; twelve, including Lespedeza maximowiczii, Tripterygium regelii, and Fraxinus rhynchophylla, in C6; two, Toxicodendron trichocarpum and P. densiflora, in C7; twenty, including Acer pseudosieboldianum, Acer pictum var. mono, Staphylea bumalda, and Carex pediformis, in C8; and thirteen species, including Oplismenus undulatifolius, Castanea crenata, and Smilax china, in C9. Our findings highlight the need for management plans that consider each vegetation type’s community structural characteristics. Full article

(This article belongs to the Section Forest Biodiversity)

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20 pages, 10060 KiB

Open AccessArticle

Biodiversity and Soil Jointly Drive Ecosystem Multifunctionality in Larch Forests

by Yang Zhang, Ruihan Wang, Chang Liu, Qiang Liu, Minghao Li and Zhidong Zhang

Forests 2025, 16(5), 745; https://doi.org/10.3390/f16050745 (registering DOI) - 26 Apr 2025

Abstract

Forests can simultaneously provide a variety of ecosystem functions and services (ecosystem multifunctionality, EMF). Different stand types, influenced by biotic and abiotic factors, play a key role in determining EMF. To clarify the impact of stand type, as well as biotic and abiotic [...] Read more.

Forests can simultaneously provide a variety of ecosystem functions and services (ecosystem multifunctionality, EMF). Different stand types, influenced by biotic and abiotic factors, play a key role in determining EMF. To clarify the impact of stand type, as well as biotic and abiotic factors, on EMF, this study quantified EMF across three stand types: Betula platyphylla pure forest (BP), B. platyphylla–Larix principis-rupprechtii mixed forest (BL), and L. principis-rupprechtii pure forest (LP). The multiple-threshold approach was employed to quantify EMF, while structural equation modeling was used to analyze the primary factors influencing EMF. The results indicated the following: (1) BL had higher stand productivity than both BP and LP; (2) BL exhibited significantly higher functional diversity and soil fertility maintenance compared to LP, with no significant difference between BP and BL; (3) BP demonstrated a significantly stronger nutrient cycling function than LP, with no significant difference between LP and BL; (4) the ranking of EMF at all threshold levels was BL > BP > LP; (5) soil was an effective driver of EMF across all threshold levels; and (6) both the niche complementarity effect and the mass ratio effect jointly drove EMF at the low threshold (<50%), with the influence of both effects diminishing as the threshold increased. This study enhances our understanding of the key drivers of EMF in forest ecosystems and provides valuable insights for informing multifunctional forest management practices. Full article

(This article belongs to the Section Forest Ecology and Management)

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26 pages, 3287 KiB

Open AccessArticle

A Configurational Analysis of Green Development in Forestry Enterprises Based on the Technology–Organization–Environment (TOE) Framework

by Dayu Xu, Beining Huang, Si Shi and Xuyao Zhang

Forests 2025, 16(5), 744; https://doi.org/10.3390/f16050744 (registering DOI) - 26 Apr 2025

Abstract

The construction of ecological civilization is intrinsically connected to green development. The green development of forestry enterprises serves as a key approach to achieving this goal. The research purpose of this paper is to explore the realization path of green development of forestry [...] Read more.

The construction of ecological civilization is intrinsically connected to green development. The green development of forestry enterprises serves as a key approach to achieving this goal. The research purpose of this paper is to explore the realization path of green development of forestry enterprises. First, an improved CRITIC (Criteria Importance Through Intercriteria Correlation)–entropy weight method was used to construct a reasonable input-output indicator system. Next, a three-stage data envelopment analysis (DEA) model was employed to evaluate the comprehensive technical efficiency of green development across 33 forestry enterprises in China, using panel data from 2017 to 2022. Finally, the study explored various configurational pathways for achieving green development by integrating the Technology–Organization–Environment (TOE) framework with dynamic qualitative comparative analysis (QCA). The findings reveal that green development in forestry enterprises is shaped by the interplay of multiple factors. Four distinct configurations were identified as instrumental in driving high green development. These configurations could be classified into two categories: the environment–organization synergistic development model and the technology–organization dual-driven model. This study provides empirical insights into the complex configurational relationships underlying green development in forestry enterprises, offering valuable guidance for optimizing development strategies. Full article

(This article belongs to the Section Forest Economics, Policy, and Social Science)

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24 pages, 11423 KiB

Open AccessArticle

YOLO-UFS: A Novel Detection Model for UAVs to Detect Early Forest Fires

by Zitong Luo, Haining Xu, Yanqiu Xing, Chuanhao Zhu, Zhupeng Jiao and Chengguo Cui

Forests 2025, 16(5), 743; https://doi.org/10.3390/f16050743 (registering DOI) - 26 Apr 2025

Abstract

Forest fires endanger ecosystems and human life, making early detection crucial for effective prevention. Traditional detection methods are often inadequate due to large coverage areas and inherent limitations. However, drone technology combined with deep learning holds promise. This study investigates using small drones [...] Read more.

Forest fires endanger ecosystems and human life, making early detection crucial for effective prevention. Traditional detection methods are often inadequate due to large coverage areas and inherent limitations. However, drone technology combined with deep learning holds promise. This study investigates using small drones equipped with lightweight deep learning models to detect forest fires early. A high-quality dataset constructed through aerial image analysis supports robust model training. The proposed YOLO-UFS network, based on YOLOv5s, integrates enhancements such as the C3-MNV4 module, BiFPN, AF-IoU loss function, and NAM attention mechanism. These modifications achieve a 91.3% mAP on the self-built early forest fire dataset. Compared to the original model, YOLO-UFS improves accuracy by 3.8%, recall by 4.1%, and average accuracy by 3.2%, while reducing computational parameters by 74.7% and 78.3%. It outperforms other mainstream YOLO algorithms on drone platforms, balancing accuracy and real-time performance. In generalization experiments using public datasets, the model’s mAP0.5 increased from 85.2% to 86.3%, and mAP0.5:0.95 from 56.7% to 57.9%, with an overall mAP gain of 3.3%. The optimized model runs efficiently on the Jetson Nano platform with 258 GB of RAM, 7.4 MB of storage memory, and an average frame rate of 30 FPS. In this study, airborne visible light images are used to provide a low-cost and high-precision solution for the early detection of forest fires, so that low-computing UAVs can achieve the requirements of early detection, early mobilization, and early extinguishment. Future work will focus on multi-sensor data fusion and human–robot collaboration to further improve the accuracy and reliability of detection. Full article

(This article belongs to the Section Natural Hazards and Risk Management)

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27 pages, 10030 KiB

Open AccessArticle

Enhancing Deforestation Detection Through Multi-Domain Adaptation with Uncertainty Estimation

by Luiz Fernando de Moura, Pedro Juan Soto Vega, Gilson Alexandre Ostwald Pedro da Costa and Guilherme Lucio Abelha Mota

Forests 2025, 16(5), 742; https://doi.org/10.3390/f16050742 (registering DOI) - 26 Apr 2025

Abstract

Deep learning models have shown great potential in scientific research, particularly in remote sensing for monitoring natural resources, environmental changes, land cover, and land use. Deep semantic segmentation techniques enable land cover classification, change detection, object identification, and vegetation health assessment, among other [...] Read more.

Deep learning models have shown great potential in scientific research, particularly in remote sensing for monitoring natural resources, environmental changes, land cover, and land use. Deep semantic segmentation techniques enable land cover classification, change detection, object identification, and vegetation health assessment, among other applications. However, their effectiveness relies on large labeled datasets, which are costly and time-consuming to obtain. Domain adaptation (DA) techniques address this challenge by transferring knowledge from a labeled source domain to one or more unlabeled target domains. While most DA research focuses on single-target single-source problems, multi-target and multi-source scenarios remain underexplored. This work proposes a deep learning approach that uses Domain Adversarial Neural Networks (DANNs) for deforestation detection in multi-domain settings. Additionally, an uncertainty estimation phase is introduced to guide human review in high-uncertainty areas. Our approach is evaluated on a set of Landsat-8 images from the Amazon and Brazilian Cerrado biomes. In the multi-target experiments, a single source domain contains labeled data, while samples from the target domains are unlabeled. In multi-source scenarios, labeled samples from multiple source domains are used to train the deep learning models, later evaluated on a single target domain. The results show significant accuracy improvements over lower-bound baselines, as indicated by F1-Score values, and the uncertainty-based review showed a further potential to enhance performance, reaching upper-bound baselines in certain domain combinations. As our approach is independent of the semantic segmentation network architecture, we believe it opens new perspectives for improving the generalization capacity of deep learning-based deforestation detection methods. Furthermore, from an operational point of view, it has the potential to enable deforestation detection in areas around the world that lack accurate reference data to adequately train deep learning models for the task. Full article

(This article belongs to the Special Issue Modeling Forest Dynamics)

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26 pages, 12687 KiB

Open AccessArticle

Operator Exposure to Vibration and Noise During Steep Terrain Harvesting

by Luka Pajek, Marijan Šušnjar and Anton Poje

Forests 2025, 16(5), 741; https://doi.org/10.3390/f16050741 - 25 Apr 2025

Abstract

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) [...] Read more.

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article

(This article belongs to the Special Issue Addressing Forest Ergonomics Issues: Laborers and Working Conditions)

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