Forests

14 pages, 784 KiB

Open AccessArticle

Nitrogen Addition Promotes Soil Carbon Sequestration and Alters Carbon Pool Stability by Affecting Particulate Organic Carbon in a Karst Plantation

by Tao Zhu, Guowei Xia, Yuanshuang Yuan, Qi Lu, Xiaohan Jiang, Chengling Huang and Wei Zhou

Forests 2025, 16(5), 730; https://doi.org/10.3390/f16050730 - 24 Apr 2025

Abstract

Increased global atmospheric nitrogen deposition can affect the accumulation and stability of forest soil organic carbon; however, the pathways and underlying mechanisms are largely unclear. In this study, we sampled soils from a karst plantation with four different nitrogen addition levels (0, 150, [...] Read more.

Increased global atmospheric nitrogen deposition can affect the accumulation and stability of forest soil organic carbon; however, the pathways and underlying mechanisms are largely unclear. In this study, we sampled soils from a karst plantation with four different nitrogen addition levels (0, 150, 300, and 600 kg N ha⁻² yr⁻¹), and we measured the soil organic carbon and chemical properties. We separated the soil organic carbon fractions and calculated the carbon pool lability on the basis of chemical and physical grouping. The results revealed that nitrogen addition significantly increased soil organic carbon and carbon pool lability on the basis of physical grouping, but it significantly decreased carbon pool lability based on chemical grouping. Particulate organic carbon was significantly correlated with the soil organic carbon and carbon pool lability, so it explained a high degree of the variance. In addition, nitrate nitrogen and easily oxidized carbon had significant impacts on soil organic carbon and carbon pool lability, respectively, on the basis of chemical grouping. Therefore, nitrogen addition promotes the soil carbon sequestration capacity and alters carbon pool stability by affecting particulate organic carbon. These findings deepen our understanding of the mechanism of forest soil carbon sequestration and stability in the context of future nitrogen deposition. Full article

(This article belongs to the Section Forest Soil)

16 pages, 4187 KiB

Open AccessArticle

Application of Unmanned Aerial Vehicle and Airborne Light Detection and Ranging Technologies to Identifying Terrain Obstacles and Designing Access Solutions for the Interior Parts of Forest Stands

by Petr Hrůza, Tomáš Mikita and Nikola Žižlavská

Forests 2025, 16(5), 729; https://doi.org/10.3390/f16050729 - 24 Apr 2025

Abstract

We applied UAV (Unmanned Aerial Vehicle) and ALS (Airborne Laser Scanning) remote sensing methods to identify terrain obstacles encountered during timber extraction in the skidding process with the aim of proposing accessibility solutions to the inner parts of forest stands using skidding trails. [...] Read more.

We applied UAV (Unmanned Aerial Vehicle) and ALS (Airborne Laser Scanning) remote sensing methods to identify terrain obstacles encountered during timber extraction in the skidding process with the aim of proposing accessibility solutions to the inner parts of forest stands using skidding trails. At the Vítovický žleb site, located east of Brno in the South Moravian Region of the Czech Republic, we analysed the accuracy of digital terrain models (DTMs) created from UAV LiDAR (Light Detection and Ranging), RGB (Red–Green–Blue) UAV, ALS data taken on site and publicly available LiDAR data DMR 5G (Digital Model of Relief of the Czech Republic, 5th Generation, based on airborne laser scanning, providing pre-classified ground points with an average density of 1 point/m²). UAV data were obtained using two types of drones: a DJI Mavic 2 mounted with an RGB photogrammetric camera and a GeoSLAM Horizon laser scanner on a DJI M600 Pro hexacopter. We achieved the best accuracy with UAV technologies, with an average deviation of 0.06 m, compared to 0.20 m and 0.71 m for ALS and DMR 5G, respectively. The RMSE (Root Mean Square Error) values further confirm the differences in accuracy, with UAV-based models reaching as low as 0.71 m compared to over 1.0 m for ALS and DMR 5G. The results demonstrated that UAVs are well-suited for detailed analysis of rugged terrain morphology and obstacle identification during timber extraction, potentially replacing physical terrain surveys for timber extraction planning. Meanwhile, ALS and DMR 5G data showed significant potential for use in planning the placement of skidding trails and determining the direction and length of timber extraction from logging sites to forest roads, primarily due to their ability to cover large areas effectively. Differences in the analysis results obtained using GIS (Geographic Information System) cost surface solutions applied to ALS and DMR 5G data DTMs were evident on logging sites with terrain obstacles, where the site-specific ALS data proved to be more precise. While DMR 5G is based on ALS data, its generalised nature results in lower accuracy, making site-specific ALS data preferable for analysing rugged terrain and planning timber extractions. However, DMR 5G remains suitable for use in more uniform terrain without obstacles. Thus, we recommend combining UAV and ALS technologies for terrain with obstacles, as we found this approach optimal for efficiently planning the logging-transport process. Full article

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

10 pages, 3143 KiB

Open AccessArticle

Study on Influencing Factors and Low-Temperature Treatment of Walnut Canker Disease in Hotan County, Xinjiang

by Hongtao Sun, Wuerkaixi Yali, Wenyao Wang, Nureya Zupaila, Lili Wang and Rong Ma

Forests 2025, 16(5), 728; https://doi.org/10.3390/f16050728 - 24 Apr 2025

Abstract

The aim of this study was to investigate the factors affecting the occurrence of walnut canker disease and the effect of low-temperature treatment on its occurrence in Hotan County, and provide a theoretical basis for the prevention and control of the disease. The [...] Read more.

The aim of this study was to investigate the factors affecting the occurrence of walnut canker disease and the effect of low-temperature treatment on its occurrence in Hotan County, and provide a theoretical basis for the prevention and control of the disease. The occurrence of canker disease was investigated in walnut plantations of different varieties, plant and row spacing, and diameter at breast height (DBH) from April to August of 2023 and 2024. In laboratory research, the spread area of disease spots on isolated branches of peach was studied under different temperature treatments and different treatment times. The occurrences of walnut canker for the two consecutive years were basically the same. The number of new lesions showed an upward trend in April and May and reached its highest in May. The number of new lesions tended to stabilize in June and July in Hotan County. The walnut variety with more severe disease was “Xinfeng”. The disease was most serious in plots with plant spacing and row spacing of 10 m × 7 m. The DBH of the more susceptible walnut trees was >30 cm. Low-temperature treatment and treatment time had a significant impact on the walnut canker lesion expansion area (p < 0.05). The key factor in lesion expansion was low temperature. The maximum lesion expansion area was 1.70 × 10⁴ mm² under treatment at 20 °C for 5 h. The walnut variety and the plant and row spacing were the key factors affecting the occurrence of walnut canker disease, with low temperature being the main factor affecting its spread. Full article

(This article belongs to the Section Forest Health)

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17 pages, 6887 KiB

Open AccessArticle

Effects of Different Vegetation Management Measures on Soil Organic Carbon Fractions in Hulunbeier Sandy Land

by Yue Liu, Limin Yuan, Xiaohong Dang, Zhongju Meng and Yang Zhao

Forests 2025, 16(5), 727; https://doi.org/10.3390/f16050727 - 24 Apr 2025

Abstract

In order to clarify the change characteristics of soil organic carbon and its components in sandy land after restoration of different artificial vegetation measures, this study took 4 common artificial planting measures in Hulunbuir Sandy Land as the research object and took mobile [...] Read more.

In order to clarify the change characteristics of soil organic carbon and its components in sandy land after restoration of different artificial vegetation measures, this study took 4 common artificial planting measures in Hulunbuir Sandy Land as the research object and took mobile sandy land as the control (CK). The results show the following: (1) The soil organic carbon content of the treatment measures was as follows: arbor-irrigation-grass (22.96 g·kg⁻¹) > single arbor (12.68 g·kg⁻¹) > single shrub (11.17 g·kg⁻¹) > single herb (8.89 g·kg⁻¹) > CK (1.14 g·kg⁻¹). The soil organic carbon showed an increasing trend, and the change was significant. (2) The contents of POC (Particulate Organic Carbon), MBC (Microbial Organic Carbon), DOC (Soluble Organic Carbon) and EOC () in soil were significantly increased by planting treatment measures, and the contents of each component in the combination mode of tree, shrub and grassland were the highest, which were increased by 1541.32%, 302.44%, 340% and 204.88% compared with CK. (3) There Please check that intended meaning has been retained. was a significant positive correlation between SOC and its components, and the correlation coefficients were 0.93, 0.91, 0.93, and 0.93, respectively. TC, TN and TP are all important influencing factors of POC. The correlation coefficient between DOC and MBC, MBC and EOC reached 0.96. (4) The carbon sequestration effect of the combination of trees, shrubs, and grassland is good, and the vegetation growth is good, which is conducive to the accumulation of organic carbon in the surface soil. It is suggested that the combination of treess, shrubs, and grassland should be adopted in the process of sandy land management. Full article

(This article belongs to the Section Forest Soil)

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19 pages, 3703 KiB

Open AccessArticle

Carbon Emission Prediction Following Pinus koraiensis Plantation Surface Fuel Combustion Based on Carbon Consumption Analysis

by Daotong Geng, Jibin Ning, Guang Yang, Shangjiong Ma, Lixuan Wang and Hongzhou Yu

Forests 2025, 16(5), 726; https://doi.org/10.3390/f16050726 - 24 Apr 2025

Abstract

The accurate measurement of surface fire carbon emissions is critical for assessing their impact on carbon sinks and role in climate change. This study aims to investigate the relationships between surface fire behaviour characteristics and carbon consumption for Pinus koraiensis plantation forests and [...] Read more.

The accurate measurement of surface fire carbon emissions is critical for assessing their impact on carbon sinks and role in climate change. This study aims to investigate the relationships between surface fire behaviour characteristics and carbon consumption for Pinus koraiensis plantation forests and construct a carbon consumption prediction model. A total of 288 combustion experiments were conducted on a laboratory burning bed using varying fuel loads, moisture contents, and slope conditions, with measurements taken of surface fire behaviour characteristics and the carbon content of combustion ash. The Byram fireline intensity model was reintegrated to build a predictive model for fuel combustion carbon consumption, and the model parameters were adjusted based on the results of the combustion experiments. The direct use of the Byram fireline intensity model parameters predicted surface fire carbon consumption in Pinus koraiensis plantation forests with significant errors (R² = 0.75; MAE = 0.197 kg m⁻²; MRE = 66.76%). After the parameters were modified using the combustion experiment data, the new model yielded R² = 0.75, MAE = 0.087 kg m⁻², and MRE = 28.28%. This study significantly improved the accuracy of the new model in predicting the carbon consumption of surface fuel combustion in Pinus koraiensis plantation forests. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest—2nd Edition)

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16 pages, 6699 KiB

Open AccessArticle

Cold-Season Precipitation and Latitudinal Differences Are Key Drivers of Salix alba Genetic Diversity in Arid Zones

by Jiajing He, Hegan Dong, Xiaopeng Yang and Tong Liu

Forests 2025, 16(5), 725; https://doi.org/10.3390/f16050725 - 24 Apr 2025

Abstract

Salix alba L. (Linnaeus, 1753; Salicaceae), a widely distributed riparian species, remains understudied regarding its genetic diversity patterns and driving factors in arid zone ecosystems. In this study, 320 Salix alba samples were collected from 10 geographic unit groups in Xinjiang, China, a [...] Read more.

Salix alba L. (Linnaeus, 1753; Salicaceae), a widely distributed riparian species, remains understudied regarding its genetic diversity patterns and driving factors in arid zone ecosystems. In this study, 320 Salix alba samples were collected from 10 geographic unit groups in Xinjiang, China, a typical arid zone, and analyzed using a comprehensive approach that incorporated SSR molecular marker technology with multi-dimensional data on geographic and climatic factors. The analysis revealed that: (1) The genetic diversity of Salix alba in the arid zone was found to be relatively rich, with populations in the humid areas of northern Xinjiang (e.g., Shannon’s index of I = 0.45 in Ili) significantly higher than those in the extreme arid regions of southern Xinjiang (e.g., Hotan), with I = 0.0762 in Yili. Further analysis using both STRUCTURE (K = 3) and PCoA methods confirmed the division of Salix alba populations in Xinjiang into three independent genetic clusters, with 65% of the observed genetic variation originating from differences between these populations. (2) Secondly, climatic factors exhibited higher explanatory power than geographic factors in elucidating variations in genetic distances among individuals. Cold season precipitation differences (Bio19, r = 0.621) and the coefficient of variation of annual precipitation (Bio17, r = 0.588) were identified as the primary drivers of these variations. Conversely, the latitudinal difference (r = 0.487) and geographic distance (r = 0.207) exhibited a significant impact on genetic distance, underscoring the importance of geo-graphic factors in shaping genetic variation. Full article

(This article belongs to the Section Forest Biodiversity)

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12 pages, 2163 KiB

Open AccessArticle

Intra-Plant Variation in Leaf Dry Mass per Area (LMA): Effects of Leaf–Shoot Orientation and Vertical Position on Dry Mass and Area Scaling

by Xuchen Guo, Yiwen Zheng, Yuanmiao Chen, Zhidong Zhou and Jianhui Xue

Forests 2025, 16(5), 724; https://doi.org/10.3390/f16050724 - 24 Apr 2025

Abstract

The intra-plant plasticity of leaves plays a vital role in enabling plants to adapt to changing climatic conditions. However, limited research has investigated the extent of intra-plant leaf trait variation and leaf biomass allocation strategies in herbaceous plants. To address this gap, we [...] Read more.

The intra-plant plasticity of leaves plays a vital role in enabling plants to adapt to changing climatic conditions. However, limited research has investigated the extent of intra-plant leaf trait variation and leaf biomass allocation strategies in herbaceous plants. To address this gap, we collected a total of 1746 leaves from 217 Lamium barbatum Siebold and Zucc. plants and measured their leaf dry mass (M) and leaf area (A). Leaves were categorized by vertical position (upper vs. lower canopy layer) and leaf–shoot orientation (east, south, west, north). ANOVA with Tukey’s HSD test was used to compare differences in M, A, and leaf dry mass per unit area (LMA). Reduced major axis regression was employed to evaluate the scaling relationship between M and A, and the bootstrap percentile method was used to determine differences in scaling exponents. The data indicated that: (i) M, A, LMA, and the scaling exponents of M versus A did not differ significantly among leaf–shoot orientations, and (ii) lower layer leaves exhibited significantly greater M, A, and LMA than upper layer leaves, but their scaling exponents were significantly smaller. These findings highlight that plant vertical growth brings significant intra-plant plasticity in leaf traits and their scaling relationships in herbaceous plants. This plasticity differs from that observed in trees, but is also critical for balancing weight load and optimizing light-use efficiency, potentially enhancing stress resilience in herbaceous plants. Full article

(This article belongs to the Special Issue Forest Phenology Dynamics and Response to Climate Change)

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15 pages, 14931 KiB

Open AccessArticle

UAV-LiDAR-Based Structural Diversity of Subtropical Forests Under Different Management Practices in Southern China

by Xiaobo Hao and Yu Liu

Forests 2025, 16(5), 723; https://doi.org/10.3390/f16050723 - 24 Apr 2025

Abstract

Forest structural diversity, referring to the variety of physical structural traits, has been identified as a critical indicator of both plant species and environmental diversity. Mapping structural diversity serves as a cost-effective proxy for monitoring forest biodiversity and large-scale ecosystem functions like productivity. [...] Read more.

Forest structural diversity, referring to the variety of physical structural traits, has been identified as a critical indicator of both plant species and environmental diversity. Mapping structural diversity serves as a cost-effective proxy for monitoring forest biodiversity and large-scale ecosystem functions like productivity. Light detection and ranging (LiDAR) carried by unmanned aerial vehicles (UAVs) can achieve precise quantification of structural parameters with a resolution of sub-meter at the stand scale, providing robust support for accurately depicting three-dimensional forest structural features. Since forest management influences biodiversity and ecological functions by shaping the physical structure of forests, this study investigates how different forest management strategies affect structural diversity in China’s red soil hilly region. Using point cloud data obtained by unmanned aerial vehicle laser scanning (UAV-LS), we derived structural metrics including canopy volume diversity (CVD), and tree height diversity (THD), which were then used as variables to calculate the Shannon diversity index (SDI) of forests. The study focused on three forest types: close-to-nature broadleaf forest (CNBF), coniferous mature plantations (CPM), and close-to-nature coniferous forest (CNCF). Results revealed that CNBF exhibited the highest structural diversity, with superior values for canopy volume (CVD = 2.09 ± 0.35), tree height (THD = 1.72 ± 0.53), and canopy projected area diversity (CAD = 2.13 ± 0.32), approaching the upper range of the theoretical maximum for SDI (theoretical maximum ≈ 2.3; typical range: 0.5–2.0). This was attributed to optimal understory vegetation and higher biomass. Despite exhibiting greater tree height, CPM demonstrated lower structural diversity, while CNCF recorded a CVD (1.81 ± 0.39) similar to that of CPM but lower than that of CNBF. These results indicate that close-to-nature forest management enhances forest structural diversity. It is implied that the forest structural diversity can serve as an effective tool for evaluating forests biodiversity under different forest management strategies. The study also suggests that improving understory vegetation is a direction in the future management of coniferous plantations. Full article

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

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17 pages, 2142 KiB

Open AccessArticle

Response of Soil Enzyme and Plant Stoichiometry to Root Interactions: Insights from Mixed Plantings of Moso Bamboo

by Yilin Ning, Jie Zhang, Anke Wang, Qifeng Wu, Qunfang Yu, Kaiwen Huang, Yufang Bi and Xuhua Du

Forests 2025, 16(5), 722; https://doi.org/10.3390/f16050722 - 23 Apr 2025

Abstract

Root interactions are crucial in regulating soil microbial metabolism and plant nutrient allocation strategies, especially in mixed plantings. However, the effects of mixed planting and direct root contact on soil properties and plant nutrient allocation remain unclear. Thus, we established potted plants with [...] Read more.

Root interactions are crucial in regulating soil microbial metabolism and plant nutrient allocation strategies, especially in mixed plantings. However, the effects of mixed planting and direct root contact on soil properties and plant nutrient allocation remain unclear. Thus, we established potted plants with Moso bamboo (Phyllostachys edulis) and Phoebe chekiangensis and created a physical barrier to the root system without blocking chemical communication using four treatments: mixed planting with root segregation (MT), mixed planting without root segregation (MS), pure Moso bamboo with root segregation (BT), and pure Moso bamboo without root segregation (BS). We investigated changes in soil and Moso bamboo nutrient content, soil enzyme activity, and microbial metabolic limitation. The results show that mixed planting and root segregation significantly affected soil and plant nutrient content and soil enzyme activities. Compared to the two pure Moso bamboo treatments, mixed planting increased microbial carbon limitation but decreased microbial nitrogen limitation. Physical segregation between roots increased microbial carbon use efficiency (CUE) compared to no segregation. Random forest analyses revealed that the best predictors of soil C and N limitations and CUE were microbial biomass and dissolved organic nitrogen (DON), respectively. Partial least squares path modeling indicated that mixed planting and root separation, directly and indirectly, affected soil microbial metabolic limitation through their effects on soil nutrients, microbial biomass, and enzyme activities. Carbon limitation significantly increased plant nutrient contents. Our study provides further insights into factors influencing nutrient limitation, CUE, and plant nutrient allocation strategies in mixed Moso bamboo plantations. Full article

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

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17 pages, 2151 KiB

Open AccessArticle

Clonal Variation in Growth, Physiology and Ultrastructure of Populus alba L. Seedlings Under NaCl Stress

by Mejda Abassi, Mohammed S. Lamhamedi, Ali Albouchi, Damase Khasa and Zoubeir Bejaoui

Forests 2025, 16(5), 721; https://doi.org/10.3390/f16050721 - 23 Apr 2025

Abstract

Afforestation and reforestation (A/R) of non-agricultural and marginal saline lands by promoting fast-growing and salinity-tolerant woody species are crucial strategies to overcome land degradation and vegetation cover scarcity. To obtain basic information before using Populus alba clones in such degraded areas, morpho-physiological and [...] Read more.

Afforestation and reforestation (A/R) of non-agricultural and marginal saline lands by promoting fast-growing and salinity-tolerant woody species are crucial strategies to overcome land degradation and vegetation cover scarcity. To obtain basic information before using Populus alba clones in such degraded areas, morpho-physiological and cellular responses to salt stress were investigated. The experiment was conducted in a nursery where cuttings of three P. alba clones (MA-104, MA-195 and OG) were grown for 90 days in 100 mM NaCl versus a non-saline control. A global approach highlighting clonal differences in terms of dry mass production and plant physiological performance was achieved by comparing plant water status, gas exchange, ionic selectivity, osmotic adjustment and chloroplast ultrastructure under the two treatments. Dry mass production and eco-physiological processes were reduced in response to salt stress, with substantial clonal variation. Clone MA-104 exhibited salinity-tolerant behaviour in contrast to clone MA-195 and OG’s medium or sensitive behaviour towards the stress. Tolerance mechanisms may be attributed to enhanced stomatal control and osmotic adjustment, thereby enabling the maintenance of turgor in plants subjected to salt stress. The chloroplast ultrastructure also showed modifications that are often involved in adaptation to salinity stress. Full article

(This article belongs to the Special Issue Physiological Mechanisms of Plant Responses to Environmental Stress)

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19 pages, 2929 KiB

Open AccessArticle

Plant–Soil–Microbial Carbon, Nitrogen, and Phosphorus Ecological Stoichiometry in Mongolian Pine-Planted Forests Under Different Environmental Conditions in Liaoning Province, China

by Hui Li, Yi Yang, Xiaohang Weng, Yongbin Zhou, Songzhu Zhang, Liying Liu and Jiubo Pei

Forests 2025, 16(5), 720; https://doi.org/10.3390/f16050720 - 23 Apr 2025

Abstract

Mongolian pine (Pinus sylvestris var. Mongolia) has been widely utilized as a key species for afforestation projects within the Three-North Shelterbelt of Liaoning Province in China. Its impressive ecological resilience has made it a favorite choice for this endeavor. However, as [...] Read more.

Mongolian pine (Pinus sylvestris var. Mongolia) has been widely utilized as a key species for afforestation projects within the Three-North Shelterbelt of Liaoning Province in China. Its impressive ecological resilience has made it a favorite choice for this endeavor. However, as the stands mature and climate conditions shift, some areas are experiencing premature decline or even mortality. Ecological stoichiometry is capable of uncovering the supply and equilibrium of plant and soil nutrients within ecosystems and is extensively utilized in the identification of limiting elements. Therefore, studying its ecological stoichiometry and internal stability dynamics is of crucial significance for clarifying the nutrient cycling process in the Mongolian pine region and alleviating the decline situation. The eastern and northwestern regions of Liaoning differ significantly in precipitation and soil nutrient availability. This study examines Mongolian pine plantations in both regions, analyzing the carbon (C), nitrogen (N), and phosphorus (P) content in plant tissues, soil, microbial biomass, and stoichiometric ratio under distinct environmental conditions. In order to provide a theoretical basis for alleviating the decline of artificial poplar forests and healthy management. Results indicate that (1) leaf C, N, and P contents in the eastern Liaoning region averaged 496.67, 15.19, and 1.66 g·kg⁻¹, respectively, whereas those in northwestern Liaoning were 514.16, 14.82, and 1.23 g·kg⁻¹, respectively. Soil C, N, and P concentrations exhibited notable regional differences, with eastern Liaoning recording 34.54, 2.62, and 0.48 g·kg⁻¹, compared to significantly lower values in northwestern Liaoning (7.74, 0.77, and 0.21 g·kg⁻¹). Similarly, microbial biomass C, N, and P were higher in eastern Liaoning (18.63, 5.09, and 7.72 mg·kg⁻¹) than in northwestern Liaoning (10.18, 3.46, and 4.38 mg·kg⁻¹). (2) The stoichiometric ratio of soil in the Mongolian pine plantations is higher than that in northwestern Liaoning, but the stoichiometric ratio of plants shows the opposite trend. Specifically, microbial carbon-to-nitrogen (MBC/MBN) ratios are higher in eastern Liaoning, whereas microbial carbon-to-phosphorus (MBC/MBP) and nitrogen-to-phosphorus (MBN/MBP) ratios are greater in northwestern Liaoning. Correlation analysis of plant–soil–microbe stoichiometry indicates that plant growth in both regions is co-limited by nitrogen, with Mongolian pine exhibiting strong internal stability. Full article

(This article belongs to the Section Forest Soil)

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22 pages, 7307 KiB

Open AccessArticle

MTL-FSFDet: An Effective Forest Smoke and Fire Detection Model Based on Multi-Task Learning

by Chenyu Zhang, Yunfei Liu, Cong Chen and Junhui Li

Forests 2025, 16(5), 719; https://doi.org/10.3390/f16050719 - 23 Apr 2025

Abstract

Forest fires cause devastating damage to the natural environment, making prompt and precise detection of smoke and fires in forests crucial. When processing forest fire images based on ground and aerial perspectives, current object detection methods still encounter issues, such as inadequate detection [...] Read more.

Forest fires cause devastating damage to the natural environment, making prompt and precise detection of smoke and fires in forests crucial. When processing forest fire images based on ground and aerial perspectives, current object detection methods still encounter issues, such as inadequate detection precision, elevated false detection and omission rates, as well as difficulties in detecting small targets in complex forest environments. Multi-task learning represents a framework in machine learning where a model can handle detection and segmentation tasks concurrently, enhancing the accuracy and generalization capacity for object detection. Therefore, this study proposes a Multi-Task Learning-based Forest Smoke and Fire Detection model (MTL-FSFDet). Firstly, an improved Bilateral Filtering-Multi-Scale Retinex (BF-MSR) method for enhancing images was proposed, to lessen the effect of lighting on smoke images and improve the quality of the dataset. Secondly, a Hybrid Feature Extraction module, which integrates local and global information, was introduced to distinguish between targets and backgrounds, addressing smoke and fire detection in complex backgrounds. Furthermore, Dysample, a method utilizing point sampling, was designed to capture richer feature information when dealing with small targets. In addition, a feature fusion approach based on Context Gate Aggregation (CGA) was proposed to weightedly fuse low-level and high-level features, boosting the precision in detecting small targets. Finally, multi-task learning improves the capability to detect small targets and tackle complex scenarios by sharing the feature extraction module and leveraging refined supervision of the segmentation task. The findings from the experiments show that, in comparison to the baseline model, MTL-FSFDet improved the mAP@0.5 by 5.3%. Full article

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

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14 pages, 1597 KiB

Open AccessArticle

Reproductive Ecology of Lecythis Pisonis in Brazilian Agroforestry Systems: Implications for Conservation and Genetic Diversity

by Zubaria Waqar, Acácia Brasil Rodrigues, Ciro Tavares Florence, Eduardo Mariano Neto and Fernanda Amato Gaiotto

Forests 2025, 16(5), 718; https://doi.org/10.3390/f16050718 - 23 Apr 2025

Abstract

Agroforestry systems are essential in sustainable land use in the face of the growing global food demand and climate change. The southern region of Bahia, Brazil, is one of the places in the world where the tree species is particularly in abundance, primarily [...] Read more.

Agroforestry systems are essential in sustainable land use in the face of the growing global food demand and climate change. The southern region of Bahia, Brazil, is one of the places in the world where the tree species is particularly in abundance, primarily in cocoa agroforestry systems, contributing to biodiversity conservation. Understanding their reproductive patterns is crucial for the survival and sustainability of these trees. This study dealt with Lecythis pisonis (Sapucaia) trees by applying microsatellite markers for mixed-mating mode and paternity analyses for pollen dispersal. In particular, it was found that Lecythis pisonis offspring are produced through outcrossing, as the case may be, while random crossings and no nearby tree fertilization are the remaining factors that play a crucial role in myriad genetic diversity inversions. This phenomenon was indicated by paternity in nine offspring, with full siblings being from the same parents. The average distance of pollen flow was 6 km, which is why the pollinator, the bee Xylocopa frontalis, has a flight range aligning with distance. These data show the influence of habitat fragmentation, the function of Cabruca, and the conservation strategy. Full article

(This article belongs to the Special Issue Genetic Diversity of Forest: Insights on Conservation)

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21 pages, 9428 KiB

Open AccessArticle

Validation of Satellite-Derived Green Canopy Cover in Rubber Plantations Using UAV and Ground Observations for Monitoring Leaf Fall Dynamics

by Masita Dwi Mandini Manessa, Anisya Feby Efriana, Farida Ayu, Fajar Dwi Pamungkas, Charlos Togi Stevanus, Tri Rapani Febbiyanti, Iqbal Putut Ash Shidiq, Rokhmatulloh Rokhmatulloh, Supriatna Supriatna, Retno Lestari, Kiwamu Kase, Minami Matsui, Abdul Azis As Sajjad, Dewo Mustiko Aji, Ariq Anggaraksa Riesnandar, Geraldo Nazar Prakarsa, Rakyan Paksi Nagara, Kuncoro Adi Pradono and Ramanatalia Parhusip

Forests 2025, 16(5), 717; https://doi.org/10.3390/f16050717 - 23 Apr 2025

Abstract

Accurate estimation of green canopy cover (GCC) in rubber plantations is crucial for monitoring vegetation health and assessing stress impacts. This study validates satellite-derived GCC estimates using unmanned aerial vehicle (UAV)-based remote sensing, ground observations, spaceborne remote sensing (satellite imagery), and supervised machine [...] Read more.

Accurate estimation of green canopy cover (GCC) in rubber plantations is crucial for monitoring vegetation health and assessing stress impacts. This study validates satellite-derived GCC estimates using unmanned aerial vehicle (UAV)-based remote sensing, ground observations, spaceborne remote sensing (satellite imagery), and supervised machine learning regression approaches. Sentinel-2 and Landsat imagery were utilized to derive spectral vegetation indices (SVIs) under varying stress conditions, while UAV-based GCC assessments provided high-resolution reference data for validation. The findings revealed that while certain SVIs exhibited strong correlations with canopy density under stable conditions, their predictive accuracy declined significantly during extreme stress events, such as Pestalotiopsis outbreaks and seasonal leaf fall periods. To improve estimation accuracy, supervised machine learning regression models were developed, with Random Forest (RF) outperforming Support Vector Machines (SVMs), Classification and Regression Trees (CARTs), and Linear Regression (LR). RF achieved the highest predictive accuracy (R² = 0.82, RMSE = 6.48, MAE = 4.97), demonstrating its reliability in capturing non-linear interactions between canopy heterogeneity and environmental stressors. These results highlight the limitations of traditional vegetation indices and emphasize the importance of multi-sensor integration and advanced modeling techniques for more precise GCC monitoring. Full article

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

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22 pages, 3961 KiB

Open AccessArticle

Predicting Glossiness of Heat-Treated Wood Using the Back Propagation Neural Network Optimized by the Improved Whale Optimization Algorithm

by Ying Cao, Wei Wang and Yan He

Forests 2025, 16(5), 716; https://doi.org/10.3390/f16050716 - 23 Apr 2025

Abstract

The properties of wood change after heat treatment, affecting its applications. Glossiness, a key aesthetic property, is of great significance in fields like furniture. Precise prediction can optimize the process and improve product quality. Although the traditional back propagation neural network (BPNN) has [...] Read more.

The properties of wood change after heat treatment, affecting its applications. Glossiness, a key aesthetic property, is of great significance in fields like furniture. Precise prediction can optimize the process and improve product quality. Although the traditional back propagation neural network (BPNN) has been applied in the field of wood properties, it still has issues such as poor prediction accuracy. This study proposes an improved whale optimization algorithm (IWOA) to optimize BPNN, constructing an IWOA-BPNN model for predicting the glossiness of heat-treated wood. IWOA uses chaos theory and tent chaos mapping to accelerate convergence, combines with the sine cosine algorithm to enhance optimization, and adopts an adaptive inertia weight to balance search and exploitation. A dataset containing 216 data entries from four different wood species was collected. Through model comparison, the IWOA-BPNN model showed significant advantages. Compared with the traditional BPNN model, the mean absolute error (MAE) value decreased by 66.02%, the mean absolute percentage error (MAPE) value decreased by 64.21%, the root mean square error (RMSE) value decreased by 69.60%, and the R² value increased by 12.87%. This model provides an efficient method for optimizing wood heat treatment processes and promotes the development of the wood industry. Full article

(This article belongs to the Special Issue Wood Properties: Measurement, Modeling, and Future Needs)

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21 pages, 3111 KiB

Open AccessArticle

Unraveling the Spatial Dynamics and Global Climate Change Response of Prominent Tropical Tree Species in Asia: Symplocos cochinchinensis and Beyond

by Haijun Li, Lihao Guo, Jingrui Zhang, Suile Li and Bo Liu

Forests 2025, 16(5), 715; https://doi.org/10.3390/f16050715 - 23 Apr 2025

Abstract

The tropical tree species Symplocos cochinchinensis plays a crucial role in ecological restoration and serves as a resource for traditional medicine, dyeing, and timber production. Assessing its distribution patterns and adaptive responses to global climate change is essential for maintaining ecosystems and developing [...] Read more.

The tropical tree species Symplocos cochinchinensis plays a crucial role in ecological restoration and serves as a resource for traditional medicine, dyeing, and timber production. Assessing its distribution patterns and adaptive responses to global climate change is essential for maintaining ecosystems and developing conservation strategies. This study elucidates the spatial distribution patterns and projects potential geographic shifts of the widely distributed tropical species S. cochinchinensis under climate change scenarios. A compilation of data from global and local herbaria and databases yielded 5050 occurrence records, covering the majority of its native range in the tropics and subtropics. We modeled the species’ potential habitats using the maximum entropy (MaxEnt) principle for current, 2050, and 2070 climate scenarios under high-emission SSP585. Our analysis reveals that sampling bias substantially influences the observed distribution patterns of S. cochinchinensis. Predictions indicate a decrease in barely suitable habitats and an increase in areas deemed highly suitable, suggesting climate change stress and an ecological niche shift towards areas with favorable microclimates with “Precipitation of Wettest Month” (Bio 13) and “Mean Temperature of Wettest Quarter” (Bio 8). Our findings reveal S. cochinchinensis’s adaptive resilience, offering valuable insights for developing strategies and conservation management in Southeast Asia, as well as a reference for the response of other common tropical species to climate change. Full article

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

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18 pages, 4605 KiB

Open AccessArticle

Unveiling Key Factors Shaping Forest Interest and Visits: Toward Effective Strategies for Sustainable Forest Use

by Kimisato Oda, Kazushige Yamaki, Asako Miyamoto, Keita Otsuka, Shoma Jingu, Yuichiro Hirano, Mariko Inoue, Toshiya Matsuura, Kazuhiko Saito and Norimasa Takayama

Forests 2025, 16(5), 714; https://doi.org/10.3390/f16050714 - 23 Apr 2025

Abstract

This study investigates the factors influencing urban residents’ interest in and visits to forests and explores strategies to promote forest space utilization. A survey was conducted among 5000 residents of Tokyo’s 23 wards, one of the world’s most densely populated urban areas, using [...] Read more.

This study investigates the factors influencing urban residents’ interest in and visits to forests and explores strategies to promote forest space utilization. A survey was conducted among 5000 residents of Tokyo’s 23 wards, one of the world’s most densely populated urban areas, using an online questionnaire. The collected data were analyzed using least absolute shrinkage, selection operator (LASSO) logistic regression, and piecewise structural equation modeling (pSEM). The analysis revealed that nature experiences in current travel destinations, particularly scenic walks, had a significant positive effect on both forest interest (standardized path coefficient = 0.19) and forest visits (0.30). These experiences were also significantly influenced by childhood nature experiences and frequent local walks. Conversely, factors negatively affecting forest visits included the lack of private vehicle ownership (−0.13) and increasing age (−0.21). While previous studies suggest that older individuals tend to visit natural areas more frequently, our findings indicate the opposite trend. One possible explanation is the low car ownership rate among Tokyo residents, which may limit accessibility to forests. These findings provide valuable insights for policy design, particularly regarding strategies to enhance forest accessibility and engagement among urban populations. Full article

(This article belongs to the Special Issue Multiple-Use and Ecosystem Services of Forests—2nd Edition)

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32 pages, 6516 KiB

Open AccessSystematic Review

Evidence on the Social, Economic, and Environmental Impact of Interventions That Facilitate Bamboo Industry Development for Sustainable Livelihoods: A Systematic Map

by Lucy Binfield, Tamara L. Britton, Chunping Dai and John L. Innes

Forests 2025, 16(5), 713; https://doi.org/10.3390/f16050713 - 22 Apr 2025

Abstract

Bamboo’s perceived potential in livelihood development has led to development interventions that aim to strengthen the bamboo industry via activities such as training participants in bamboo management, strengthening institutions, and raising awareness. Using the Campaign for Environmental Evidence’s guidelines, we systematically map the [...] Read more.

Bamboo’s perceived potential in livelihood development has led to development interventions that aim to strengthen the bamboo industry via activities such as training participants in bamboo management, strengthening institutions, and raising awareness. Using the Campaign for Environmental Evidence’s guidelines, we systematically map the available evidence of the impact of these interventions. The evidence is scattered across peer-reviewed and grey literature, with no universal reporting standards. Search sources for this systematic evidence map include a bibliographic database, CABdirect (now known as CABI Digital Library); a search platform for peer-reviewed literature, the Web of Science Core Collection; a bibliographic database for academic literature on agriculture and related fields, SEARCH by the USDA National Agricultural Library; a public search engine for scholarly literature, Google Scholar; a general search engine, Google; and the websites of 37 organizations, with both proprietary search engines and Google used to search for pdf files. Overall, 36 documents are included in the final review, describing 28 unique interventions from 13 countries. Most evidence is found outside the peer-reviewed literature. Outcomes including income changes, increased participation and engagement, and policy changes are reported, with economic impacts dominating the evidence base. Very little evidence of negative outcomes is found, likely constrained by reporting bias. Reporting on evidence of these interventions is limited, with many interventions being excluded from the database due to a lack of identifiable evidence of outcomes or impact. Full article

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

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23 pages, 4503 KiB

Open AccessArticle

Moisture-Dependent Transverse Isotropic Elastic Constants of Wood S2 Secondary Cell Wall Layers Determined Using Nanoindentation

by Xavier Arzola-Villegas, Nayomi Z. Plaza, Nathan J. Bechle, Yikai Wang, Roderic Lakes, Donald S. Stone and Joseph E. Jakes

Forests 2025, 16(5), 712; https://doi.org/10.3390/f16050712 - 22 Apr 2025

Abstract

Moisture- and orientation-dependent mechanical properties of the S2 secondary cell wall layer are needed to better understand wood mechanical properties and advance wood utilization. In this work, nanoindentation was used to assess the orientation-dependent elastic moduli and Meyer hardness of the loblolly pine [...] Read more.

Moisture- and orientation-dependent mechanical properties of the S2 secondary cell wall layer are needed to better understand wood mechanical properties and advance wood utilization. In this work, nanoindentation was used to assess the orientation-dependent elastic moduli and Meyer hardness of the loblolly pine (Pinus taeda) S2 layer under environmental conditions ranging from 0% to 94% relative humidity (RH). The elastic moduli were fit to a theoretical transverse isotropic elasticity model to calculate the longitudinal elastic modulus, transverse elastic modulus, axial shear modulus, and transverse shear modulus for the S2 layer at 0%, 33%, 75%, and 94% RH and 26 °C. The longitudinal elastic modulus was consistently higher than the transverse elastic modulus because of the orientation of the stiff cellulose microfibrils in the S2 layer. The axial shear modulus was consistently higher than the transverse shear modulus. The Meyer hardness had a much smaller orientation dependence than the elastic properties. Moisture generally plasticized the S2 layer. Over the range of RH tested, the longitudinal elastic modulus decreased by 30%, the transverse elastic modulus and transverse shear modulus decreased by 83%, the axial shear modulus did not have an observable trend with RH, and the hardness decreased by 68% to 82% with the hardness in the longitudinal direction softening less than in the transverse direction. Full article

(This article belongs to the Special Issue Wood Quality and Mechanical Properties: 2nd Edition)

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