Forests

31 pages, 18655 KB

Open AccessArticle

Spatial and Temporal Dynamics of Forest Carbon Sequestration and Spatial Heterogeneity of Influencing Factors: Evidence from the Beiluo River Basin in the Loess Plateau, China

by Lin Dong, Hua Li, Yuanjie Deng, Hao Wu and Hassan Saif Khan

Forests 2025, 16(11), 1719; https://doi.org/10.3390/f16111719 (registering DOI) - 12 Nov 2025

Abstract

To accurately analyze the dynamic response and driving mechanism of forest carbon sequestration in the core area of the Loess Plateau’s Returning Farmland to Forestry Project, this study takes the Beiluo River Basin as the research area. Using spatial autocorrelation, gravity model, a [...] Read more.

To accurately analyze the dynamic response and driving mechanism of forest carbon sequestration in the core area of the Loess Plateau’s Returning Farmland to Forestry Project, this study takes the Beiluo River Basin as the research area. Using spatial autocorrelation, gravity model, a geodetector, and spatiotemporal geographically weighted regression models, it analyzes the spatiotemporal evolution of forest carbon sequestration and the spatial heterogeneity of its influencing factors based on 2000–2023 data. The results show the following: (1) Forest carbon sequestration in the basin increased by 13.55% from 2000 to 2023; its spatial pattern shifted from “middle reaches concentration” to “stable middle reaches core plus significant upper reaches growth”, with the gravity center moving “southeast then northwest”. (2) Forest carbon sequestration had significant positive spatial correlation, with hotspots in soil–rock mountain forest areas and cold spots in ecologically fragile or high-human-activity areas. (3) Natural ecological factors dominated forest carbon sequestration evolution, socioeconomic factors enhanced synergy, and evapotranspiration and NDVI had significant impacts. (4) Factor impacts had spatiotemporal heterogeneity, such as the decaying positive effect of precipitation and the “positive-negative-equilibrium” change in forestry value-added. This study provides scientific guidance for basin and Loess Plateau ecological restoration and “double carbon” goal achievement. Full article

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

20 pages, 2921 KB

Open AccessArticle

Optimal Training Sample Sizes for U-Net-Based Tree Species Classification with Sentinel-2 Imagery

by Heejae Lee, Cheolho Lee, Hanbyol Woo and Sol-E Choi

Forests 2025, 16(11), 1718; https://doi.org/10.3390/f16111718 (registering DOI) - 12 Nov 2025

Abstract

Detecting forest tree species distribution using satellite imagery with deep-learning models is essential for effective forest management. While sufficient training samples are crucial for developing deep-learning-based tree species classification models, creating these training samples requires significant resources. Therefore, understanding the optimal balance between [...] Read more.

Detecting forest tree species distribution using satellite imagery with deep-learning models is essential for effective forest management. While sufficient training samples are crucial for developing deep-learning-based tree species classification models, creating these training samples requires significant resources. Therefore, understanding the optimal balance between model accuracy and training sample size is essential for efficient resource allocation. Here, we determined the optimal training sample size for forest tree species classification using Sentinel-2 imagery and the U-Net model. The study area comprised the Seoul–Gyeonggi region of South Korea, where the nine dominant tree species were selected for classification. We utilized multi-temporal Sentinel-2 imagery, incorporating spectral, vegetation, and textural features. Optimal points were identified using Locally Estimated Scatterplot Smoothing (LOESS) regression. The maximum overall accuracy reached 61%, with 90% and 95% of the maximum accuracy with training sample sizes of 2.37%–2.67% and 4.42%–5.89%, respectively. The congeneric Pinus and Quercus groups had major confusion, with species-specific F1-scores ranging from 0.40 (Robinia pseudoacacia) to 0.75 (Pinus koraiensis). These results provide practical guidelines for efficient resource allocation in tree species classification. Rather than pursuing excessive data collection beyond the optimal point, integrating multiple sensor types can overcome existing limitations and enhance classification accuracy. Full article

(This article belongs to the Special Issue Artificial Intelligence and Machine Learning Applications in Forestry—Second Edition)

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20 pages, 3421 KB

Open AccessArticle

Blue Carbon Investment Potential in Lamu and Kwale Counties of Kenya: Carbon Inventory and Market Prospects

by James Gitundu Kairo, Anthony Mbatha, Gabriel Njoroge Wanyoike, Fredrick Mungai, Brian Kiiru Githinji, Joseph Kipkorir Sigi Lang’at, Gladys Kinya, Gilbert Kiplangat Kosgei, Kisilu Mary and Lisa Oming'o

Forests 2025, 16(11), 1717; https://doi.org/10.3390/f16111717 - 12 Nov 2025

Abstract

Blue carbon ecosystems, particularly mangroves, seagrasses, and salt marshes, play a crucial role in climate regulation by capturing and storing huge stocks of carbon. Together with supporting fisheries production, protecting shorelines from erosion, and supplying timber and non-timber products to communities, blue carbon [...] Read more.

Blue carbon ecosystems, particularly mangroves, seagrasses, and salt marshes, play a crucial role in climate regulation by capturing and storing huge stocks of carbon. Together with supporting fisheries production, protecting shorelines from erosion, and supplying timber and non-timber products to communities, blue carbon ecosystems offer investment opportunities through carbon markets, thus supporting climate change mitigation and sustainable livelihoods. The current study assessed above- and below-ground biomass, sediment carbon, and the capacity of the blue carbon ecosystems in Kwale and Lamu Counties, Kenya, to capture and store carbon. This was followed by mapping of hotspot areas of degradation and the identification of investment opportunities in blue carbon credits. Carbon densities in mangroves were estimated at 560.23 Mg C ha⁻¹ in Lamu and 526.34 Mg C ha⁻¹ in Kwale, with sediments accounting for more than 70% of the stored carbon. In seagrass ecosystems, carbon densities measured 171.65 Mg C ha⁻¹ in Lamu and 220.29 Mg C ha⁻¹ in Kwale, values that surpass the national average but are consistent with global figures. Mangrove cover is declining at 0.49% yr⁻¹ in Kwale and 0.16% yr⁻¹ in Lamu, while seagrass losses in Lamu are 0.67% yr⁻¹, with a 0.34% yr⁻¹ increase in Kwale. Under a business-as-usual scenario, mangrove loss over 30 years will result in emissions of 4.43 million tCO₂e in Kwale and 18.96 million tCO₂e in Lamu. Effective interventions could enhance carbon sequestration from 0.12 to 3.86 million tCO₂e in Kwale and 0.62 to 19.52 million tCO₂e in Lamu. At the same period, seagrass losses in Lamu would emit 5.21 million tCO₂e. With a conservative carbon price of 20 USD per tCO₂e, projected annual revenues from mangrove carbon credits amount to USD 3.59 million in both Lamu and Kwale, and USD 216,040 for seagrass carbon credits in Lamu. These findings highlight the substantial climate and financial benefits of investing in the restoration and protection of the two ecosystems. Full article

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

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20 pages, 6808 KB

Open AccessArticle

High Ecosystem Stability Under Drought Events in National Nature Reserves in China’s Forest Ecosystem

by Yan Lv, Xiaoyong Li and Chaobin Yang

Forests 2025, 16(11), 1716; https://doi.org/10.3390/f16111716 - 12 Nov 2025

Abstract

Forest-type national nature reserves and their surrounding areas have experienced a series of drought events, which have influenced forest ecosystem stability. Assuming that drought events do not cause a shift in the ecosystem’s stable state, we quantified the stability of forest ecosystems in [...] Read more.

Forest-type national nature reserves and their surrounding areas have experienced a series of drought events, which have influenced forest ecosystem stability. Assuming that drought events do not cause a shift in the ecosystem’s stable state, we quantified the stability of forest ecosystems in China’s national nature reserves and their surrounding areas in response to drought events from 2000 to 2018, using satellite-observed Enhanced Vegetation Index (EVI) and Standardized Precipitation Index (SPI) data. We further examined differences in ecosystem stability across regions and forest types, and identified the impacts of environmental factors using correlation analysis, analysis of variance (ANOVA), and random forest models. The results show that both national nature reserves and their surrounding areas primarily experienced single, moderate-intensity drought events, most of which occurred in spring and summer. Compared with surrounding areas, national nature reserves exhibited higher ecosystem stability, with a mean drought resistance index of 31.45 ± 21.09. The difference in ecosystem stability between reserves and their surrounding areas was most pronounced in deciduous forests, which was attributed to their high hydraulic conductivity and distinctive leaf phenological traits. Additionally, climatic factors were the dominant drivers of both resistance and recovery rate, each contributing more than 30% to the overall explained variance. Our results provide valuable guidance for enhancing drought resilience and promoting the sustainable management of China’s national forest reserves. Full article

(This article belongs to the Special Issue Ecological Responses of Forests to Climate Change)

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32 pages, 2070 KB

Open AccessArticle

Trees, Deadwood and Tree-Related Microhabitats Explain Patterns of Alpha and Beta Saproxylic Beetle Diversity in Silver Fir-Beech Forests in Central Italy

by Francesco Parisi, Adriano Mazziotta and Davide Travaglini

Forests 2025, 16(11), 1715; https://doi.org/10.3390/f16111715 - 11 Nov 2025

Abstract

Forest structure, including trees, deadwood and tree-related microhabitats, is a key determinant of forest biodiversity. Their relative contribution in shaping local (alpha) biodiversity and its variation (beta) between sites remains unclear. We assessed how forest characteristics shape alpha and beta diversity of beetle [...] Read more.

Forest structure, including trees, deadwood and tree-related microhabitats, is a key determinant of forest biodiversity. Their relative contribution in shaping local (alpha) biodiversity and its variation (beta) between sites remains unclear. We assessed how forest characteristics shape alpha and beta diversity of beetle communities in mixed silver fir–beech forests within the Vallombrosa Nature Reserve (Tuscany, Italy). We sampled 47 circular plots recording single-tree attributes, deadwood volume and decay stage, and the occurrence of tree-related microhabitats. Beetle assemblages were surveyed using window flight traps, yielding over 11,000 individuals belonging to 187 species, 20% of those known from central-southern Italian forests, 58% of which were listed in the Italian Red List of Saproxylic Beetles and 10% of which were threatened. Statistical models (GLMs and GDMs) revealed that alpha diversity was driven by fine-scale features, including tree species composition, microhabitats (cavities, bark, epiphytes) and deadwood diversity. In contrast, beta diversity was shaped by stand structure and inter-stand heterogeneity. Our results highlight the need for conservation strategies that simultaneously maintain tree-level heterogeneity and secure variation across the landscape. Management should therefore combine retention of microhabitats and diverse deadwood substrates with promotion of structurally diverse, mixed stands to sustain beetle diversity at multiple spatial scales. Full article

(This article belongs to the Special Issue Species Diversity and Habitat Conservation in Forest)

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19 pages, 354 KB

Open AccessReview

Artificial Intelligence in Forest Pathology: Opportunities and Challenges

by Pauline Hessenauer

Forests 2025, 16(11), 1714; https://doi.org/10.3390/f16111714 - 11 Nov 2025

Abstract

Forest diseases threaten tree health, biodiversity, and ecosystem services, with impacts amplified by climate change and global trade. Understanding and managing these threats is difficult due to the longevity of trees, the size and inaccessibility of forests, and the often cryptic or delayed [...] Read more.

Forest diseases threaten tree health, biodiversity, and ecosystem services, with impacts amplified by climate change and global trade. Understanding and managing these threats is difficult due to the longevity of trees, the size and inaccessibility of forests, and the often cryptic or delayed expression of symptoms. This review first introduces the field of forest pathology and the key challenges it faces, including multifactorial declines, root and vascular diseases, and emerging invasive pathogens. We then examine how artificial intelligence (AI) can be applied to biotic, abiotic, and decline-related diseases, integrating remote sensing, imaging, genomics, and ecological data across spatial and temporal scales. Lessons from agricultural systems are discussed, highlighting potential tools and pitfalls for forestry. Finally, we outline future directions, emphasizing the need for interpretable models, incorporation of ecological context, cross-species validation, and coordinated data infrastructures to ensure AI delivers actionable, scalable solutions for complex forest ecosystems. Full article

(This article belongs to the Special Issue Innovative Techniques for Monitoring and Managing Invasive Forest Pests and Pathogens)

33 pages, 58798 KB

Open AccessArticle

Urban Greening Strategies and Ecosystem Services: The Differential Impact of Street-Level Greening Structures on Housing Prices

by Qian Ji, Shengbei Zhou, Longhao Zhang, Yankui Yuan, Lunsai Wu, Fengliang Tang, Jun Wu, Yufei Meng and Yuqiao Zhang

Forests 2025, 16(11), 1713; https://doi.org/10.3390/f16111713 - 11 Nov 2025

Abstract

Street greening is widely recognized as influencing resident well-being and housing prices, and street-view imagery provides a fine-grained data source for quantifying urban microenvironments. However, existing research predominantly relies on single indicators such as the Green View Index (GVI) and overall green coverage/volume [...] Read more.

Street greening is widely recognized as influencing resident well-being and housing prices, and street-view imagery provides a fine-grained data source for quantifying urban microenvironments. However, existing research predominantly relies on single indicators such as the Green View Index (GVI) and overall green coverage/volume lacking a systematic analysis of how the hierarchical structure of trees, shrubs, and grass relates to housing prices. This study examines the high-density block context of Tianjin’s six urban districts. Using the Street Greening Space Structure (SGSS) dataset to construct greening structure configurations, we integrate housing-price data, neighborhood attributes, and 13,280 street-view images from the study area. We quantify how “visibility and hierarchical ratios” are capitalized on in the housing market and identify auditable threshold ranges and contextual gating. We propose an urban–forest structural system centered on visibility and hierarchical ratios that links street-level observability to ecosystem services. Employing an integrated framework combining Geographical-XGBoost (G-XGBoost) and SHapley Additive exPlanations (SHAP), we move beyond average effects to reveal structural detail and contextual heterogeneity in capitalization. Our findings indicate that tree visibility G_TVI is the most robust and readily capitalized price signal: when G_TVI increases from approximately 0.06 to 0.12–0.16, housing prices rise by about 8%–10%. Hierarchical structure is crucial: balanced tree–shrub ratios and moderate shrub–grass ratios translate “visible green” into functional green. Capitalization effects are environmentally conditioned—more pronounced along corridors with high centrality and accessibility—and are likewise common in dense East Asian metropolises (e.g., Beijing, Shanghai, Seoul, and Tokyo) and rapidly motorizing cities (e.g., Bangkok and Jakarta). These patterns suggest parametric prescriptions that prioritize canopy-corridor continuity and keep ratios within actionable threshold bands. We translate these findings into urban greening strategies that prioritize canopy continuity, under-canopy permeability, and maintainability, providing sustainability-oriented, parameterized guidance for converting urban greening structure into ecological capital for sustainable cities. Full article

(This article belongs to the Special Issue Urban Forests and Greening for Sustainable Cities)

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16 pages, 788 KB

Open AccessArticle

Reconciling Above- and Below-Ground Perspectives to Understand Ectomycorrhizal Community Diversity and Function

by Elena Salerni, Debora Barbato, Pamela Leonardi, Claudia Perini and Simona Maccherini

Forests 2025, 16(11), 1712; https://doi.org/10.3390/f16111712 - 10 Nov 2025

Abstract

Forests sustain high levels of biodiversity and essential ecosystem services, yet the impact of management practices on below-ground functioning remains difficult to assess. A comprehensive evaluation of ectomycorrhizal (ECM) fungal diversity is, therefore, required to better understand ecosystem dynamics. This study, conducted within [...] Read more.

Forests sustain high levels of biodiversity and essential ecosystem services, yet the impact of management practices on below-ground functioning remains difficult to assess. A comprehensive evaluation of ectomycorrhizal (ECM) fungal diversity is, therefore, required to better understand ecosystem dynamics. This study, conducted within the SelpiBioLife project, examined ECM community structure in two Pinus nigra J.F. Arnold forests in central Italy by integrating above- and below-ground sampling. Across 108 plots, ECM fruiting bodies (EMFb) were recorded during one fruiting season, and 54 soil cores were collected to characterize ECM root tips (EMRt) through morpho-anatomical analyses and ITS sequencing. Species richness and community composition were compared using rarefaction, PERMANOVA, NMDS, Mantel tests, and SIMPER analysis. A total of 70 EMFb species and 54 EMRt morphotypes were identified, displaying significant differences between sites and sampling types. EMFb surveys revealed greater richness, whereas EMRt reached sampling saturation only at one site, suggesting additional hidden diversity. Distinct community patterns were detected in ordination space, and weak correlations emerged between EMFb and EMRt dissimilarities, indicating complementary ecological information. These findings show that single-method monitoring underrepresents ECM diversity. Combined above- and below-ground investigations provide a more accurate basis for evaluating silvicultural impacts and maintaining forest ecosystem resilience. Full article

(This article belongs to the Special Issue Sustainable and Suitable Ecological Management of Forest Plantation)

14 pages, 1374 KB

Open AccessArticle

Intraspecific Leaf Trait Responses to Habitat Heterogeneity in a Tropical Rainforest

by Shashikala Madhubhani, Mahesha Lakmali, Akshay Surendra, Liza S. Comita and Sisira Ediriweera

Forests 2025, 16(11), 1711; https://doi.org/10.3390/f16111711 - 10 Nov 2025

Abstract

Functional traits provide key insights into plant ecological strategies and responses to environmental heterogeneity, yet the role of intraspecific trait variability (ITV) in tropical rainforests remains underexplored. We examined ITV in six leaf traits—leaf thickness (LT), leaf area (LA), specific leaf area (SLA), [...] Read more.

Functional traits provide key insights into plant ecological strategies and responses to environmental heterogeneity, yet the role of intraspecific trait variability (ITV) in tropical rainforests remains underexplored. We examined ITV in six leaf traits—leaf thickness (LT), leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), and stomatal density (SD)—in saplings of 15 dominant tree species across ridge and valley habitats in a Sri Lankan tropical lowland rainforest. We compared interspecific and intraspecific variation and quantified trait plasticity using the plasticity index. Significant ITV was observed for LT, LA, and SD, with ridge individuals showing smaller, thicker leaves with lower SD. SLA, LDMC, and LNC exhibited no overall habitat-level differences, though species-specific divergent responses were detected. Interspecific variation exceeded ITV for most traits, except for LNC, where ITV accounted for 55% of total variation. Trait plasticity varied among traits, with LNC showing the highest plasticity. These results indicate that individuals adjust leaf traits in response to fine-scale habitat heterogeneity, reflecting shifts in resource-use strategies. Overall, ITV is ecologically meaningful and should be incorporated into community-level studies and ecosystem models to improve predictions of plant community dynamics and ecosystem functioning under environmental change. Full article

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

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27 pages, 10413 KB

Open AccessArticle

Structural Optimization of Windbreak and Sand-Fixing Forests: A Wind Tunnel Study

by Feng Li, Jianjun Yang, Rui Chen, Peng Hou, Zhixi Wang, Yao Qin, Miao He and Qinghong Luo

Forests 2025, 16(11), 1710; https://doi.org/10.3390/f16111710 - 10 Nov 2025

Abstract

This study examined the windbreak effects of different tree–shrub configurations through wind tunnel experiments. Using Populus euphratica Oliv. and Tamarix chinensis Lour. as model species, six rows of front-tree–back-shrub arrangements in a triangular layout were tested under varying spacing patterns. Four [...] Read more.

This study examined the windbreak effects of different tree–shrub configurations through wind tunnel experiments. Using Populus euphratica Oliv. and Tamarix chinensis Lour. as model species, six rows of front-tree–back-shrub arrangements in a triangular layout were tested under varying spacing patterns. Four spacings of P e (7.5 cm × 7.5 cm, 7.5 cm × 10 cm, 7.5 cm × 12.5 cm, 10 cm × 10 cm) and four spacings of T cs (5 cm × 5 cm, 5 cm × 7.5 cm, 5 cm × 10 cm, 7.5 cm × 7.5 cm) were analyzed. Tree–shrub combinations significantly outperformed pure stands. The configuration of P e (7.5 cm × 10 cm) with T c (5 cm × 10 cm) achieved the highest efficiency, with an average of 27.1% and a peak of 47.13% at 7 H. This configuration was effective up to 15 H and showed slower efficiency decline at higher wind speeds. Vertically, most combinations reached maximum efficiency at 20 cm height, while pure T c peaked at 51.96% at 3 cm and pure P e at 36.33% at 20 cm. Overall, the optimal configuration was P e spaced at 7.5 cm × 10 cm and T c at 5 cm × 10 cm, which not only enhanced protective performance but also reduced planting density. These findings provide valuable scientific references for designing windbreak and sand-fixing forests in arid regions, supporting ecological restoration and sustainable land management in desert–oasis transition zones. Full article

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

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21 pages, 11281 KB

Open AccessArticle

Developing Interpretable Deep Learning Model for Subtropical Forest Type Classification Using Beijing-2, Sentinel-1, and Time-Series NDVI Data of Sentinel-2

by Shudan Chen, Xuefeng Wang, Mengmeng Shi, Guofeng Tao, Shijiao Qiao and Zhulin Chen

Forests 2025, 16(11), 1709; https://doi.org/10.3390/f16111709 - 10 Nov 2025

Abstract

Accurate forest type classification in subtropical regions is essential for ecological monitoring and sustainable management. Multimodal remote sensing data provide rich information support, yet the synergy between network architectures and fusion strategies in deep learning models remains insufficiently explored. This study established a [...] Read more.

Accurate forest type classification in subtropical regions is essential for ecological monitoring and sustainable management. Multimodal remote sensing data provide rich information support, yet the synergy between network architectures and fusion strategies in deep learning models remains insufficiently explored. This study established a multimodal deep learning framework with integrated interpretability analysis by combining high-resolution Beijing-2 RGB imagery, Sentinel-1 data, and time-series Sentinel-2 NDVI data. Two representative architectures (U-Net and Swin-UNet) were systematically combined with three fusion strategies, including feature concatenation (Concat), gated multimodal fusion (GMU), and Squeeze-and-Excitation (SE). To quantify feature contributions and decision patterns, three complementary interpretability methods were also employed: Shapley Additive Explanations (SHAP), Grad-CAM++, and occlusion sensitivity. Results show that Swin-UNet consistently outperformed U-Net. The SwinUNet-SE model achieved the highest overall accuracy (OA) of 82.76%, exceeding the best U-Net model by 3.34%, with the largest improvement of 5.8% for mixed forest classification. The effectiveness of fusion strategies depended strongly on architecture. In U-Net, SE and Concat improved OA by 0.91% and 0.23% compared with the RGB baseline, while GMU slightly declined. In Swin-UNet, all strategies achieved higher gains between 1.03% and 2.17%, and SE effectively reduced NDVI sensitivity. SHAP analysis showed that RGB features contributed most (values > 0.0015), NDVI features from winter and spring ranked among the top 50%, and Sentinel-1 features contributed less. These findings reveal how architecture and fusion design interact to enhance multimodal forest classification. Full article

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

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14 pages, 1604 KB

Open AccessArticle

Decoupled Leaf Physiology and Branch-Level BVOC Emissions in Two Tree Species Under Water and Nitrogen Treatments

by Shuangjiang Li, Diao Yan, Xuemei Liu, Maozi Lin and Zhigang Yi

Forests 2025, 16(11), 1708; https://doi.org/10.3390/f16111708 - 9 Nov 2025

Abstract

Soil water availability and nitrogen (N) deposition critically influence biogenic volatile organic compound (BVOC) emissions, thereby affecting atmospheric chemistry. However, their differential short- and long-term effects remain unclear. Here, Ormosia pinnata and Pinus massoniana seedlings were exposed to three water regimes (moderate drought, [...] Read more.

Soil water availability and nitrogen (N) deposition critically influence biogenic volatile organic compound (BVOC) emissions, thereby affecting atmospheric chemistry. However, their differential short- and long-term effects remain unclear. Here, Ormosia pinnata and Pinus massoniana seedlings were exposed to three water regimes (moderate drought, MD; normal irrigation, NI; near-saturated irrigation, NSI) and two nitrogen (N0; 0 kg N ha⁻¹ yr⁻¹; N80; 80 kg N ha⁻¹ yr⁻¹) treatments for 20 months. Branch-level BVOC emissions and leaf physiological and biochemical traits were examined after 8 months (short term) and 16 months (long term). In the short term, P. massoniana predominantly emitted α-pinene, β-pinene, and γ-terpinene, whereas O. pinnata emitted isoprene (ISO). After prolonged exposure, ISO became the dominant in both species. Short-term MD and NSI conditions stimulated ISO emissions in O. pinnata, with N80 addition further amplifying this effect. In contrast, long-term treatments tended to suppress ISO emissions in O. pinnata, particularly under N80. Short-term water treatments had no significant effect on monoterpene (MT) emissions in P. massoniana. Under long-term water treatments, N80 suppressed ISO emissions; nevertheless, ISO emission rates (ISOrate) progressively increased with increasing soil water availability. Although leaf intercellular CO₂ concentration (Ci), stomatal conductance (g_s), and photosynthesis-related enzymes exhibited partial correlations with BVOC emissions, an overall decoupling between leaf traits and emission patterns was evident. Our findings demonstrate the significant changes in both BVOC composition and emission magnitudes under the joint effects of water availability and nitrogen deposition, providing important implications for improving regional air quality modeling and BVOC emission predictions. Full article

(This article belongs to the Special Issue Impacts of Climate Change and Forest Management on Forest Carbon and Nitrogen Budgets)

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11 pages, 1995 KB

Open AccessArticle

Identification of the 2AP Regulatory Gene CnProDH in Aromatic Coconut and Screening of Its Regulatory Factors

by Xiwei Sun, Lixia Zhou, Jing Li, Jinyao Yin, Hao Ding, Xiaomei Liu and Yaodong Yang

Forests 2025, 16(11), 1707; https://doi.org/10.3390/f16111707 - 9 Nov 2025

Abstract

Aromatic coconut is a special variety of coconut. Its unique “pandan-like” aroma has won it great popularity among consumers, endowing it with considerable market potential. In our previous study, 2-acetyl-1-pyrroline (2AP), which serves as the main source of the “pandan-like” aroma in aromatic [...] Read more.

Aromatic coconut is a special variety of coconut. Its unique “pandan-like” aroma has won it great popularity among consumers, endowing it with considerable market potential. In our previous study, 2-acetyl-1-pyrroline (2AP), which serves as the main source of the “pandan-like” aroma in aromatic coconut, was found to exhibit significant variation among distinct aromatic coconut individuals. Now, the regulatory mechanism of 2AP has been clarified in fragrant rice, and the ProDH gene is the key gene for 2AP regulation. To further understand the regulation mechanism of 2AP content in aromatic coconut, we cloned and identified the CnProDH gene, the key gene of 2AP regulation in aromatic coconut. The results showed that the CnProDH gene had the typical ProDH structural domain, and its full-length sequence is 23,667 bp, containing 5 exons and a coding sequence (CDS) of 1599 bp. The CnProDH gene encodes a protein that possesses a β₈α₈ barrel structure, consisting of 532 amino acids (aa), with a molecular mass of 58,076.63 kDa and an isoelectric point of 7.11. To further understand the regulatory mechanism of CnProDH in aromatic coconut, we also constructed a yeast one-hybrid (Y1H) library for aromatic coconut. Through the Y1H experiment, combined with the prediction and analysis of cis-acting elements in the promoter of the CnProDH gene, three possible regulatory factors, including CnYABBY2, CnSAP8, and CnBRD3, were identified. These findings provide a molecular basis for clarifying and solving the problem of variations in 2AP content across different aromatic coconuts. Full article

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

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21 pages, 6090 KB

Open AccessArticle

Interactive Visualizations of Integrated Long-Term Monitoring Data for Forest and Fuels Management on Public Lands

by Kate Jones and Jelena Vukomanovic

Forests 2025, 16(11), 1706; https://doi.org/10.3390/f16111706 - 9 Nov 2025

Abstract

Adaptive forest and fire management in parks and protected areas is becoming increasingly complex as climate change alters the frequency and intensity of disturbances (wildfires, pest and disease outbreaks, etc.), while park visitation and the number of people living adjacent to publicly managed [...] Read more.

Adaptive forest and fire management in parks and protected areas is becoming increasingly complex as climate change alters the frequency and intensity of disturbances (wildfires, pest and disease outbreaks, etc.), while park visitation and the number of people living adjacent to publicly managed lands continues to increase. Evidence-based, climate-adaptive forest and fire management practices are critical for the responsible stewardship of public resources and require the continued availability of long-term ecological monitoring data. The US National Park Service has been collecting long-term fire monitoring plot data since 1998, and has continued to add monitoring plots, but these data are housed in databases with limited access and minimal analytic capabilities. To improve the availability and decision support capabilities of this monitoring dataset, we created the Trends in Forest Fuels Dashboard (TFFD), which provides an implementation framework from data collection to web visualization. This easy-to-use and updatable tool incorporates data from multiple years, plot types, and locations. We demonstrate our approach at Rocky Mountain National Park using the ArcGIS Online (AGOL) software platform, which hosts TFFD and allows for efficient data visualizations and analyses customized for the end user. Adopting interactive, web-hosted tools such as TFFD allows the National Park Service to more readily leverage insights from long-term forest monitoring data to support decision making and resource allocation in the context of environmental change. Our approach translates to other data-to-decision workflows where customized visualizations are often the final steps in a pipeline designed to increase the utility and value of collected data and allow easier integration into reporting and decision making. This work provides a template for similar efforts by offering a roadmap for addressing data availability, cleaning, storage, and interactivity that may be adapted or scaled to meet a variety of organizational and management use cases. Full article

(This article belongs to the Special Issue Long-Term Monitoring and Driving Forces of Forest Cover)

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15 pages, 6868 KB

Open AccessArticle

First Characterization of Megafire Refugia in a South American Subtropical Mountain Forest

by Daihana Soledad Argibay, Ana María Cingolani, Javier Sparacino, Ricardo Suárez, Isabell Hensen and Daniel Renison

Forests 2025, 16(11), 1705; https://doi.org/10.3390/f16111705 - 8 Nov 2025

Abstract

Fire refugia play an important role in post-fire ecosystem recovery because they preserve areas that represent a persistent legacy in the landscape and serve as propagule sources for forest regeneration. Our objective was to identify the pre-fire topographic and land cover conditions that [...] Read more.

Fire refugia play an important role in post-fire ecosystem recovery because they preserve areas that represent a persistent legacy in the landscape and serve as propagule sources for forest regeneration. Our objective was to identify the pre-fire topographic and land cover conditions that determine the presence and quality of megafire refugia in the mountains of central Argentina. In 208 1-ha field-based plots, we assessed pre-fire topographic and land cover variables along with post-fire vegetation responses two years after the megafires. Based on these assessments, we developed a fire refugia quality index ranging from 0 (no refugia) to 5 (high-quality refugia). Using ordinal logistic regression and a model selection approach, we found that high-quality fire refugia were associated with the more humid east mountain flank and east- and north-facing slopes, as well as with smooth terrain, high topographic positions, greater rock cover, steep slopes, and higher tree-to-grass cover proportions. Our findings highlight the importance of topographic and land cover variables in shaping fire refugia and provide insights into post-fire management and the conservation of biodiversity in mountain ecosystems. Full article

(This article belongs to the Special Issue Forest Fire Detection, Prevention and Management)

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26 pages, 2891 KB

Open AccessArticle

In Vitro and Greenhouse Evaluation of Fungicides and Bacillus Antagonists Against Diplodia corticola (Botryosphaeriaceae, Botryosphaeriales) on Quercus suber

by Hanna Rathod Uppara, Dalmau Albó, Carlos Colinas and Emigdio Jordán Muñoz-Adalia

Forests 2025, 16(11), 1704; https://doi.org/10.3390/f16111704 - 8 Nov 2025

Abstract

Cork oak (Quercus suber) forests are threatened by emergent fungal pathogen Diplodia corticola, which causes significant economic and ecological losses. This study evaluates the efficacy of synthetic and natural fungicides, as well as Bacillus antagonistic agents, against this phytopathogen in [...] Read more.

Cork oak (Quercus suber) forests are threatened by emergent fungal pathogen Diplodia corticola, which causes significant economic and ecological losses. This study evaluates the efficacy of synthetic and natural fungicides, as well as Bacillus antagonistic agents, against this phytopathogen in vitro and in vivo. Eighteen fungicidal agents were tested across three concentrations, whereas the bacterial antagonistic agents Bacillus amyloliquefaciens and a mixture of B. amyloliquefaciens + Bacillus mojavensis were tested at a fixed concentration. The assayed chemicals, including penconazole, clove oil, vanillin, and belthanol, showed 100 ± 0.0% radial growth inhibition (n = 24) and conidiation (n = 24), highlighting their potential as alternatives to benomyl and methyl thiophanate (Restricted in the European Union). In vivo assays further validated the efficacy of these agents in reducing symptom incidence and seedling mortality in cork oak seedlings. Similarly, the Bacillus-based treatments showed 47.6 ± 0.9% (n = 35) in vitro antagonistic effects and in vivo application on seedlings (n = 470) significantly reduced disease symptoms and supported physiological stability (GLMs with Tukey HSD post hoc). The study aimed to evaluate chemical, natural and biological control agents against this pathogen to identify effective management alternatives for forest nurseries and cork oak. Full article

(This article belongs to the Special Issue Advances in Biological Control of Forest Diseases and Pests: 2nd Edition)

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17 pages, 3310 KB

Open AccessArticle

Development and Performance Validation of a UWB–IMU Fusion Tree Positioning Device with Dynamic Weighting for Forest Resource Surveys

by Zongxin Cui, Linhao Sun, Ao Xu, Hongwen Yao and Luming Fang

Forests 2025, 16(11), 1703; https://doi.org/10.3390/f16111703 - 7 Nov 2025

Abstract

In forest resource plot surveys, tree relative positioning is a crucial task with profound silvicultural and ecological significance. However, traditional methods such as compasses and total stations suffer from low efficiency, high costs, or poor environmental adaptability, while single-sensor technologies (e.g., UWB or [...] Read more.

In forest resource plot surveys, tree relative positioning is a crucial task with profound silvicultural and ecological significance. However, traditional methods such as compasses and total stations suffer from low efficiency, high costs, or poor environmental adaptability, while single-sensor technologies (e.g., UWB or IMU) struggle to balance accuracy and stability in complex forest environments. To address these challenges, this study designed a multi-sensor fusion-based tree positioning device. By integrating the high-precision ranging capability of Ultra-Wideband (UWB) with the dynamic motion perception advantages of an Inertial Measurement Unit (IMU), a dynamic weight fusion algorithm was proposed, effectively mitigating UWB static errors and IMU cumulative errors. Experimental results demonstrate that the device achieves system biases of −1.54 cm (X-axis) and 1.27 cm (Y-axis), with root mean square errors (RMSE) of 21.34 cm and 23.93 cm, respectively, across eight test plots. The average linear distance error was 26.23 cm. Furthermore, in single-operator mode, the average measurement time per tree was only 20.89 s, approximately three times faster than traditional tape measurements. This study confirms that the proposed device offers high positioning accuracy and practical utility in complex forest environments, providing efficient and reliable technical support for forest resource surveys. Full article

(This article belongs to the Special Issue Smart Forest Inventory, Management and Planning: Intelligent Technologies and Their Applications)

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15 pages, 3216 KB

Open AccessArticle

Bending Properties of Pleated Wood Thermally Treated at 160 °C and 200 °C Temperatures

by Mátyás Báder, Bíbor Júlia Horváth and Miklós Bak

Forests 2025, 16(11), 1702; https://doi.org/10.3390/f16111702 - 7 Nov 2025

Abstract

This study investigates the combined effects of compression along the grain by 20% after steaming (pleating), and thermal treatment on the mechanical and physical properties of beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.). Pleating significantly increased plasticity [...] Read more.

This study investigates the combined effects of compression along the grain by 20% after steaming (pleating), and thermal treatment on the mechanical and physical properties of beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.). Pleating significantly increased plasticity and maximum deflection, reaching 339% of untreated values in beech and 337% in oak. However, it reduced bending strength and modulus of elasticity to about 50%. Keeping the specimen compressed for 5 h (fixation) during the thermo-hydro-mechanical modification process of pleating further decreased the modulus of elasticity to 26%–29% of untreated levels. Thermal treatment at 160 °C increased bending strength of fixated specimens to 120.5% in beech and 125.3% in oak, partially restoring strength, while at 200 °C, it decreased drastically to 26.7% and 21.5%, respectively. Density was reduced by thermal treatment, with oven-dry values decreasing by 6.2% (beech) and 12.7% (oak) at 160 °C, and by 18.2% and 25.1% at 200 °C. The results indicate that high-temperature treatment (200 °C) leads to wood with brittle properties. Full article

(This article belongs to the Special Issue Recent Advances in Wood Modification and Wood Functionalization Research)

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15 pages, 2753 KB

Open AccessArticle

Severe Dieback of European Ash Shelterbelts in Northeastern Bulgaria Associated with Diplodia fraxini

by Aneta Lyubenova and Petya Dimitrova-Mateva

Forests 2025, 16(11), 1701; https://doi.org/10.3390/f16111701 - 7 Nov 2025

Abstract

The Common European ash (Fraxinus excelsior L.) is one of the main species constituting the field protection forest belts in Northeastern Bulgaria. Studies conducted in shelterbelts in Dobrich and Balchik in July 2020 and in Tutrakan and Dulovo in June–July 2022 revealed [...] Read more.

The Common European ash (Fraxinus excelsior L.) is one of the main species constituting the field protection forest belts in Northeastern Bulgaria. Studies conducted in shelterbelts in Dobrich and Balchik in July 2020 and in Tutrakan and Dulovo in June–July 2022 revealed severe dieback of ash. The observed symptoms included density thinning of the crowns, dieback of branches, presence of sunken necrotic cankers, and light green to yellow foliage and premature defoliation. Parts of the shelterbelts were completely destroyed with 100% tree mortality. To determine whether the invasive Hymenoscyphus fraxineus or other pathogens are present in the ash field protective forest belts in Northeastern Bulgaria, fungal isolation was undertaken. Samples were collected from four locations: Dobrich and Balchik in June 2020, and Tutrakan and Dulovo in June–July 2022. The morphology, temperature–growth rate relationships, and pathogenicity of the two pathogenic fungal species isolated in this study—Diplodia fraxini and Diplodia seriata—were examined. Morphological and physiological studies confirm the molecular identification of the obtained plant pathogens. The Diplodia fraxini isolates (Dobrich 3, Tutrakan 2, and Dulovo 4) showed mycelial growth between 5 °C and 35 °C, with minimal growth at 5 °C (0.20–0.27 mm/day) and an optimum growth rate of 3.9–4.5 mm/day at 20–25 °C. Growth declined sharply above 30 °C, ceasing entirely at 35 °C. In contrast, D. seriata (Dulovo 5) exhibited higher growth rates, showing limited growth above 5 °C (~1 mm/day), and maximum growth of approximately 8 mm/day at 25 °C. Growth in D. seriata remained moderate up to 35 °C and ceased near 40 °C, indicating a broader temperature tolerance and higher upper thermal limit than D. fraxini. The results from the pathogenicity tests show that D. fraxini can cause necrosis on ash—both on leaves and twigs—and is likely involved in the investigated ash decline cases. Further studies of the spread and epidemiology of D. fraxini are needed in order to establish its occurrence on the territory of Bulgaria. Full article

(This article belongs to the Special Issue Advances in Fungal Diseases in Forests)

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