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Forests, Volume 16, Issue 4 (April 2025) – 133 articles

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18 pages, 2005 KiB  
Article
Comparison of Growth Strategies and Biomass Allocation in Chinese Fir Provenances from the Subtropical Region of China
by Zhibing Wan, Ning Liu, Chenggong Liu, Meiman Zhang, Chengcheng Gao, Lingyu Yang, Liangjin Yao and Xueli Zhang
Forests 2025, 16(4), 687; https://doi.org/10.3390/f16040687 (registering DOI) - 16 Apr 2025
Abstract
This study aims to evaluate the growth characteristics of six Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) provenances (S1–S6) from different climatic regions in subtropical China in order to select superior provenances with strong adaptability, fast growth, and reasonable biomass allocation. These results [...] Read more.
This study aims to evaluate the growth characteristics of six Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) provenances (S1–S6) from different climatic regions in subtropical China in order to select superior provenances with strong adaptability, fast growth, and reasonable biomass allocation. These results will provide references for genetic improvement and resource utilization of Chinese fir plantations. A total of 385 trees, aged 26 to 48 years, were selected from the Chinese fir gene bank in Anhui. Wood core sampling was used to obtain tree ring width and early/latewood width data. Growth rate, fast-growth period, and biomass allocation of each provenance were analyzed using methods such as the logistic growth equation, BAI (basal area increment), latewood percentage, and biomass estimation. The fast-growth period of Chinese fir starts from the 2nd to the 4th year, with significant growth occurring around the 14th year and growth stabilizing between 30 and 50 years. Provenance S2 showed clear advantages in growth rate and biomass, while S6 was relatively weak. BAI analysis revealed that the provenances reached their growth peak around 10 years of age, with a gradual decline afterward, but S2 maintained higher growth levels for a longer period. Root-shoot ratio analysis showed that S2 had the most balanced ratio, promoting stable growth and efficient water and nutrient absorption, while S6 had a higher root-shoot ratio, indicating growth limitations. Furthermore, S2 demonstrated continuous biomass increase after 30 years, indicating excellent growth potential. This study provides quantitative analysis of the growth characteristics and adaptability of different Chinese fir provenances, offering scientific support for the construction and breeding of Chinese fir plantations, and contributing to enhancing the productivity and ecological adaptability of Chinese fir plantations for sustainable resource utilization. Full article
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15 pages, 2783 KiB  
Article
Establishing Models for Predicting Above-Ground Carbon Stock Based on Sentinel-2 Imagery for Evergreen Broadleaf Forests in South Central Coastal Ecoregion, Vietnam
by Nguyen Huu Tam, Nguyen Van Loi and Hoang Huy Tuan
Forests 2025, 16(4), 686; https://doi.org/10.3390/f16040686 - 15 Apr 2025
Abstract
In Vietnam, models for estimating Above-Ground Biomass (AGB) to predict carbon stock are primarily based on diameter at breast height (DBH), tree height (H), and wood density (WD). However, remote sensing has increasingly been recognized as a cost-effective and accurate alternative. Within this [...] Read more.
In Vietnam, models for estimating Above-Ground Biomass (AGB) to predict carbon stock are primarily based on diameter at breast height (DBH), tree height (H), and wood density (WD). However, remote sensing has increasingly been recognized as a cost-effective and accurate alternative. Within this context, the present study aimed to develop correlation equations between Total Above-Ground Carbon (TAGC) and vegetation indices derived from Sentinel-2 imagery to enable direct estimation of carbon stock for assessing emissions and removals. In this study, the remote sensing indices most strongly associated with TAGC were identified using principal component analysis (PCA). TAGC values were calculated based on forest inventory data from 115 sample plots. Regression models were developed using Ordinary Least Squares and Maximum Likelihood methods and were validated through Monte Carlo cross-validation. The results revealed that Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Near Infrared Reflectance (NIR), as well as three variable combinations—(NDVI, ARVI), (SAVI, SIPI), and (NIR, EVI — Enhanced Vegetation Index)—had strong influences on TAGC. A total of 36 weighted linear and non-linear models were constructed using these selected variables. Among them, the quadratic models incorporating NIR and the (NIR, EVI) combination were identified as optimal, with AIC values of 756.924 and 752.493, R2 values of 0.86 and 0.87, and Mean Percentage Standard Errors (MPSEs) of 22.04% and 21.63%, respectively. Consequently, these two models are recommended for predicting carbon stocks in Evergreen Broadleaf (EBL) forests within Vietnam’s South Central Coastal Ecoregion. Full article
18 pages, 3894 KiB  
Article
Carbon in Woody Debris and Charcoal Layer in Cold Temperate Coniferous Forest 13 Years After a Severe Wildfire
by Yuanchun Peng, Lina Shi, Xingyu Hou and Yun Zhang
Forests 2025, 16(4), 685; https://doi.org/10.3390/f16040685 (registering DOI) - 15 Apr 2025
Abstract
Pyrogenic carbon (PyC) is generated from the incomplete combustion of biomass and fossil fuels. Pyrogenic carbon is highly stable and is often referred to as a missing carbon sink. It plays a crucial role in global carbon cycling and climate change research. We [...] Read more.
Pyrogenic carbon (PyC) is generated from the incomplete combustion of biomass and fossil fuels. Pyrogenic carbon is highly stable and is often referred to as a missing carbon sink. It plays a crucial role in global carbon cycling and climate change research. We analyzed the storage of PyC and uncharred biological organic carbon (BOC) within woody debris (WD) and the charcoal layer, as well as the properties of PyC, across four forest types in the cold temperate coniferous forest of the Greater Khingan Mountains. Pyrogenic carbon in WD appears as charred, blackened material, while PyC in the charcoal layer was extracted through chemical oxidation using HF/HCl treatment. Our methodology included particle size separation through dry sieving, followed by the analysis of four size fractions (>2 mm, 2–1 mm, 1–0.5 mm and <0.5 mm) for elemental composition, and the chemical composition was analyzed using DRIFT. With respect to WD, PyC storage ranged from 0.040 to 0.179 Mg·ha−1, whereas BOC storage ranged from 3.1 to 16.8 Mg·ha−1. In the charcoal layer, PyC storage ranged from 7.9 to 44.3 Mg·ha−1, and BOC storage ranged from 3.8 to 11.6 Mg·ha−1. Pyrogenic carbon storage in the charcoal layer dominated (>99%) on the above-ground in each forest type. The DRIFT analysis confirmed that the coarse fraction (>2 mm) contain more polymeric aromatic structures, and most likely indicated the presence of benzene carboxylic compounds (1710 cm−1), which may originate from the charred plant material. Our research aims to enhance the understanding of the retention effects of recalcitrant carbon in WD and charcoal layer of cold temperate coniferous forest, thereby providing new insights into the impact of fire disturbances on carbon cycling within forest ecosystems. Full article
(This article belongs to the Section Forest Meteorology and Climate Change)
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20 pages, 3964 KiB  
Article
Response of Litter Decomposition and Nutrient Release Characteristics to Simulated N Deposition in Pinus yunnanensis Franch. Forest in Central Yunnan Plateau
by Yaoping Nian, Wen Chen, Yangyi Zhao, Zheng Hou, Long Zhang, Xiaoling Liang and Yali Song
Forests 2025, 16(4), 684; https://doi.org/10.3390/f16040684 - 15 Apr 2025
Abstract
Nitrogen deposition can significantly impact soil biogeochemical cycling; however, its effects on the decomposition processes and nutrient release from leaf and twig litter in subtropical plantations remain inadequately understood. In this study, we focused on the Pinus yunnanensis Franch. forest in the central [...] Read more.
Nitrogen deposition can significantly impact soil biogeochemical cycling; however, its effects on the decomposition processes and nutrient release from leaf and twig litter in subtropical plantations remain inadequately understood. In this study, we focused on the Pinus yunnanensis Franch. forest in the central Yunnan Plateau, southwestern China, and explored how nitrogen addition influences litter decomposition nutrient release over two years, under four levels: control (CK, 0 g·m−2·a−1), low nitrogen (LN, 10 g·m−2·a−1), medium nitrogen (MN, 20 g·m−2·a−1), and high nitrogen (HN, 25 g·m−2·a−1). The results indicate that after 24 nitrogen application treatments, the rates of remaining mass in both leaf and twig litters followed the pattern: LN < CK = MN < HN. Under all nitrogen application treatments, the rate of remaining mass in leaf litters was significantly lower than that of twig litters (p < 0.05). Under LN, the mass retention in leaf and twig litters decreased by 3.96% and 8.41%, respectively, compared to CK. In contrast, under HN treatments, the rates of remaining mass in leaf and twig litters increased by 8.57% and 5.35%, respectively. This demonstrates that low nitrogen accelerates decomposition, whereas high nitrogen inhibits it. Significant differences in the remaining amounts of lignin and cellulose in both leaf and twig litters were observed when compared to CK (p < 0.05). Additionally, decomposition time and nitrogen deposition had significant effects on the remaining rates of nutrients (C, N, P) and their C/N, C/P, and N/P in litters (p < 0.05). Following nitrogen application, the C/N of the litters significantly reduced, while the N/P increased. The results suggest that nitrogen addition alleviates the nitrogen limitation on the litters while intensifying the phosphorus limitation. Full article
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14 pages, 1827 KiB  
Article
Effectiveness of Silvicultural Options in Renewal of Trembling Aspen–Jack Pine Mixedwood Stands, 21 Years After Treatment
by Rongzhou Man
Forests 2025, 16(4), 683; https://doi.org/10.3390/f16040683 - 15 Apr 2025
Abstract
Regenerating conifers after harvest through planting and postharvest broadcast application of herbicide is effective in ensuring the survival and growth of seedlings, but faces challenges in meeting broad social and ecological objectives of forest management. This study reports the effectiveness of alternative options [...] Read more.
Regenerating conifers after harvest through planting and postharvest broadcast application of herbicide is effective in ensuring the survival and growth of seedlings, but faces challenges in meeting broad social and ecological objectives of forest management. This study reports the effectiveness of alternative options in regenerating jack pine (Pinus banksiana Lamb.), 21 years after harvest of trembling aspen (Populus tremuloides Michx.)-dominated boreal mixedwood stands. The treatment options included (i) preharvest spray—aerial broadcast spray prior to harvest, (ii) postharvest partial spray—ground herbicide application in strips, (iii) partial harvest in strips, (iv) postharvest aerial broadcast, and (v) uncut reference. Twenty-one years after treatments, the four harvest treatments were similar in overstory density (4000 stems/ha) and basal area (BA, 20 m2/ha), but differed in composition and structure. The preharvest spray had an intimate mixture of aspen and jack pine (22% and 57% by BA, respectively), compared to spatial mosaics of aspen and pine corridors in the partial spray (36% and 41%), and aspen and maple corridors in the partial cut (21% and 31%). While the postharvest broadcast was pine-dominated (74% by BA) as expected, uncut and partial cut were similar in pine composition (10% by BA), which is inadequate for aspen and pine mixedwood stands. The early positive effects of preharvest spray and partial harvest on understory species abundance and diversity became neutral 21 years postharvest. The implications of these findings are discussed with respect to stand conditions before harvest, postharvest regeneration dynamics, and treatment objectives for the renewal of trembling aspen and jack pine mixedwood stands after harvest. Full article
(This article belongs to the Special Issue Forest Growth and Regeneration Dynamics)
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17 pages, 8791 KiB  
Article
The Estimation of Carbon Storage and Volume in Forest Stands: A Model Incorporating Species Composition and Site Quality
by Weiping Hua, Tian Qiu, Xidian Jiang, Junzhong Pan and Baoyin Li
Forests 2025, 16(4), 682; https://doi.org/10.3390/f16040682 - 14 Apr 2025
Viewed by 38
Abstract
We developed a model for estimating the carbon storage and volume of entire forest stands at the provincial level, aiming to improve the accuracy of regional productivity assessments. Based on data from the branches, roots, leaves, and trunks of eight dominant tree species [...] Read more.
We developed a model for estimating the carbon storage and volume of entire forest stands at the provincial level, aiming to improve the accuracy of regional productivity assessments. Based on data from the branches, roots, leaves, and trunks of eight dominant tree species (grouped by origin) in Fujian Province, combined with plot-level data, we developed a compatible carbon storage estimation model. This model integrates species composition coefficients and uses stand volume as the independent variable. We estimated the model parameters using a combination of the immune evolutionary algorithm and an improved simplex method, which enhances convergence speed and solution stability compared to the traditional version. The accuracy of the model was validated by cross-model validation and concurrent testing. Applying the model to forest stand data from Wuyishan City, we simulated theoretical logging volumes to demonstrate its practical utility. The results demonstrated that the model exhibited high accuracy in fitting the observed data, with reliable predictions of carbon storage and volume across different forest components. In the case study area, the volume was 21.0521 million cubic meters and the carbon storage was 7.3238 million tons, both of which increased with decreasing interval periods. When logging factors were considered, the increases in carbon storage fluctuated as the interval periods increased and were higher than those when logging factors were not considered. This study confirmed that the developed models were effective for predicting land carbon storage and volume, and the simulation method successfully overcame the challenges associated with model estimation. Full article
(This article belongs to the Special Issue Research Advances in Management and Design of Forest Operations)
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24 pages, 14653 KiB  
Article
Heterogeneity and Influencing Factors of Carbon Sequestration Efficiency of Green Space Patterns in Urban Riverfront Residential Blocks
by Yunfang Jiang, Di Xu, Lixian Peng, Xianghua Li, Tao Song and Fangzhi Zhan
Forests 2025, 16(4), 681; https://doi.org/10.3390/f16040681 - 14 Apr 2025
Viewed by 34
Abstract
Green spaces in waterfront residential blocks, where the water landscape and green space intersect, have a special carbon sequestration effect due to the distinct ecological interaction between water bodies and green spaces. Studying the carbon sequestration efficiency of green space patterns is crucial [...] Read more.
Green spaces in waterfront residential blocks, where the water landscape and green space intersect, have a special carbon sequestration effect due to the distinct ecological interaction between water bodies and green spaces. Studying the carbon sequestration efficiency of green space patterns is crucial for enhancing urban ecological quality. Herein, 100 residential blocks adjacent to water bodies in Shanghai were selected as case areas, and green space pattern classification, random forest algorithm and spatial configuration quantitative analysis were used to analyse the impact of spatial morphology factors, surrounding building environment and water–green coupling environment on the CS efficiency of the green space in residential blocks. The results showed that the importance of the green space morphology index influencing CS is significantly greater than that of the building environment index. Among the indices, the fraction vegetation coverage, coverage ratio of evergreen broadleaved trees and canopy coverage of the green space have a more significant effect. Moreover, the different types and compositions of tree species in residential green spaces have different impacts on CS. Residential blocks with higher levels of water surface ratio (Wr) have a slightly higher CS of the internal green space. In residential blocks 500 m from water bodies, Wr has a significant impact on the CS capacity of the green space. The blocks with an external greenway pattern and external greenway–green grid pattern provide an advantageous environment for CS. This study provides a reasonable basis for the development of riverfront green spaces to increase carbon sequestrations. Full article
(This article belongs to the Special Issue The Role of Urban Trees in Ecology Protection)
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21 pages, 28617 KiB  
Article
The Influence of Different Moisture Contents on the Acoustic Vibration Characteristics of Wood
by Hongru Qiu, Yunqi Cui, Liangping Zhang, Tao Ding and Nanfeng Zhu
Forests 2025, 16(4), 680; https://doi.org/10.3390/f16040680 - 14 Apr 2025
Viewed by 121
Abstract
This study investigates the vibrational and acoustic properties of Sitka spruce (Picea sitchensis (Bong.) Carr.) and Indian rosewood (Dalbergia latifolia Roxb.), two common musical instrument woods, at moisture contents of 2%, 7%, and 12%. The specimens with dimensions of 400mm (longitudinal) [...] Read more.
This study investigates the vibrational and acoustic properties of Sitka spruce (Picea sitchensis (Bong.) Carr.) and Indian rosewood (Dalbergia latifolia Roxb.), two common musical instrument woods, at moisture contents of 2%, 7%, and 12%. The specimens with dimensions of 400mm (longitudinal) × 25 mm (radial) × 10 mm (tangential) were tested under cantilever beam conditions using non-contact magnetic field excitation to generate sinusoidal and pulse signals. Vibration data were collected via acceleration sensors and FFT analyzers. The test method was based on ASTM D6874-12 standard. Results indicate that increasing moisture content reduces acoustic vibration characteristics, with hardwoods exhibiting higher declines than softwoods. From 2% to 12% moisture content, the first-order sound radiation quality factor of Sitka spruce and Indian rosewood decreased by 15.41% and 15.57%, respectively, while the sound conversion rate declined by 41.91% and 43.21%. Increased moisture content lowers first-order and second-order resonance frequencies, amplitude ratios, dynamic elastic modulus, vibration propagation velocity, acoustic radiation quality factor, and acoustic conversion efficiency, while increasing acoustic impedance and the loss factor. With excitation frequency increases from 100 Hz to 1500 Hz, vibration propagation velocity rises slightly, while the loss factor declines. Full article
(This article belongs to the Section Wood Science and Forest Products)
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25 pages, 4527 KiB  
Article
Optimizing Urban Green Spaces for Vegetation-Based Carbon Sequestration: The Role of Landscape Spatial Structure in Zhengzhou Parks, China
by Chenyu Du, Shidong Ge, Peihao Song, Sándor Jombach, Albert Fekete and István Valánszki
Forests 2025, 16(4), 679; https://doi.org/10.3390/f16040679 - 13 Apr 2025
Viewed by 95
Abstract
Urban parks serve as essential carbon sinks in cities, mitigating climate change by sequestering atmospheric CO2. Maximizing the carbon sequestration potential within constrained urban spaces is a critical step toward carbon neutrality. However, few studies have systematically examined how the internal [...] Read more.
Urban parks serve as essential carbon sinks in cities, mitigating climate change by sequestering atmospheric CO2. Maximizing the carbon sequestration potential within constrained urban spaces is a critical step toward carbon neutrality. However, few studies have systematically examined how the internal spatial composition and shape of green spaces affect their vegetation carbon sequestration capacity. This study analyzes the relationship between landscape indices and vegetation carbon sequestration density (VCSD) using field surveys and high-resolution remote sensing data from 123 urban parks in Zhengzhou, China. The results indicate that Zhengzhou’s parks sequester 14.03 Gg C yr−1, with a VCSD of 0.53 kg C m−2 yr−1. Significant differences in VCSD were observed among park types, with theme parks having the highest average VCSD (0.69 kg C m−2 yr−1) and community parks the lowest (0.43 kg C m−2 yr−1). The key drivers primarily consist of landscape indices that characterize green space distribution and configuration, including the proportion of green space (Pg), largest green patch index (LPI), number of green patches (NP), green patch dispersion index (SPL), and landscape shape index (LSI), with specific thresholds identified for each. Based on these findings, category-specific spatial composition strategies are proposed to precisely enhance the carbon sequestration of park vegetation. This study provides actionable guidance for urban park designers to maximize the carbon sequestration potential of green spaces, thereby mitigating climate change and promoting human health and well-being through green space design. Full article
(This article belongs to the Special Issue Designing Urban Green Spaces in a Changing Climate)
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20 pages, 3961 KiB  
Article
Spatial Heterogeneity of Soil Respiration and Its Relationship with the Spatial Distribution of the Forest Ecosystem at the Fine Scale
by Zhihao Chen, Yue Cai, Chunyu Pan, Hangjun Jiang, Zichen Jia, Chong Li and Guomo Zhou
Forests 2025, 16(4), 678; https://doi.org/10.3390/f16040678 - 12 Apr 2025
Viewed by 66
Abstract
Forest soil respiration plays a crucial role in the global carbon cycle. However, accurately estimating regional soil carbon fluxes is challenging due to the spatial heterogeneity of soil respiration at the stand level. This study examines the spatial variation of soil respiration and [...] Read more.
Forest soil respiration plays a crucial role in the global carbon cycle. However, accurately estimating regional soil carbon fluxes is challenging due to the spatial heterogeneity of soil respiration at the stand level. This study examines the spatial variation of soil respiration and its driving factors in subtropical coniferous and broad-leaved mixed forests in southern China, aiming to provide insights into accurately estimating regional carbon fluxes. The findings reveal that the coefficient of variation (CV) of soil respiration at a scale of 50 m × 50 m is 18.82%, indicating a moderate degree of spatial variation. Furthermore, 52% of the spatial variation in soil respiration can be explained by the variables under investigation. The standardized total effects of the main influencing factors are as follows: soil organic carbon (0.71), diameter at breast height within a radius of 5 m (0.31), soil temperature (0.27), and soil bulk density (−0.25). These results imply that even in relatively homogeneous areas with flat terrain, fine-scale soil respiration exhibits significant spatial heterogeneity. The spatial distribution of woody plant resources predominantly regulates this variation, with root distribution, shading effects, and changes in soil physical and chemical properties being the main influencing mechanisms. The study emphasizes the importance of simulations at different microscales to unravel the potential mechanisms governing macroscopic phenomena. Additionally, it highlights the need for incorporating a more comprehensive range of variables to provide more meaningful references for regional soil carbon flux assessment. Full article
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16 pages, 4421 KiB  
Article
Genome-Wide Profiling of the Genes Resistant to Bursaphelenchus xylophilus in Pinus tabuliformis Carriere
by Mengtian Li, Mengjia Yang, Lei Wang, Longfeng Gong, Yuxi Chen and Jichen Xu
Forests 2025, 16(4), 677; https://doi.org/10.3390/f16040677 - 12 Apr 2025
Viewed by 64
Abstract
Bursaphelenchus xylophilus is a pine wood nematode capable of destroying pine forests. Exploring the genes providing resistance to this pathogen and understanding their resistance mechanisms is thus necessary and constitutes an effective way to tackle this problem. We used Pinus tabuliformis Carriere to [...] Read more.
Bursaphelenchus xylophilus is a pine wood nematode capable of destroying pine forests. Exploring the genes providing resistance to this pathogen and understanding their resistance mechanisms is thus necessary and constitutes an effective way to tackle this problem. We used Pinus tabuliformis Carriere to dissect its response to B. xylophilus strain BxFC. The 30 d inoculation results showed that the P. tabuliformis germplasms exhibited a wide resistance spectrum. Some lines were sensitive with the needles fully wilted and the MDA content and the relative conductivity of needles greatly increased, while some lines demonstrated strong resistance with good needle vigor and better physiological conditions. Moreover, the transcriptome analysis revealed 7928 differentially expressed genes (DEGs) between the resistant and sensitive germplasm pools, including 3754 upregulated and 4174 downregulated genes in the resistant lines. These DEGs were specially enriched in the pathways of plant–pathogen interaction (318 genes), phenylpropanoid biosynthesis (108 genes), ubiquitin-mediated proteolysis (47 genes), carotenoid biosynthesis (18 genes), and monoterpenoid biosynthesis (9 genes). Accordingly, P. tabuliformis utilized multiple ways to control the proliferation and activity of B. xylophilus, such as immune response, ubiquitination, thickening plant cell walls, and increasing its terpenoid and antioxidant contents. Our results could thus help in better understanding the resistance process of P. tabuliformis against B. xylophilus and offer some new strategies and gene resources for a molecular breeding program of resistant P. tabuliformis. Full article
(This article belongs to the Special Issue Latest Progress in Research on Forest Tree Genomics)
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23 pages, 6453 KiB  
Article
Characterization of Shrub Fuel Structure and Spatial Distribution Using Multispectral and 3D Multitemporal UAV Data
by Ramón Alberto Díaz-Varela, Cecilia Alonso-Rego, Stéfano Arellano-Pérez, Carlos Iván Briones-Herrera, Juan Gabriel Álvarez-González and Ana Daría Ruiz-González
Forests 2025, 16(4), 676; https://doi.org/10.3390/f16040676 - 12 Apr 2025
Viewed by 134
Abstract
Shrubland vegetation plays a crucial role in ecological processes, but its conservation is facing threats due to climate change, wildfires, and human activities. Unmanned Aerial Vehicles (UAVs), or ‘drones’, have become valuable tools for detailed vegetation mapping, providing high-resolution imagery and 3D models [...] Read more.
Shrubland vegetation plays a crucial role in ecological processes, but its conservation is facing threats due to climate change, wildfires, and human activities. Unmanned Aerial Vehicles (UAVs), or ‘drones’, have become valuable tools for detailed vegetation mapping, providing high-resolution imagery and 3D models despite challenges such as legal restrictions and limited coverage. We developed a methodology for estimating vegetation height, map vegetation classes, and fuel models by using multitemporal UAV data (imagery and point clouds from the imagery) and other ancillary data to provide insights into habitat condition and fuel characteristics. Two different random forest classification methods (an object- and a pixel-based approach) for discriminating between vegetation classes and fuel models were developed and compared. The method showed promise for characterizing vegetation structure (shrub height), with an RMSE of less than 0.3 m and slight overestimation of taller heights. For discriminating between vegetation classes and fuel models, the best results were obtained with the object-based random forest approach, with overall accuracies of 0.96 and 0.93, respectively. Although some difficulties were encountered in distinguishing low shrubs and brackens and in distinguishing low-height fuel models due to the spatial mixture, accurate results were obtained for most classes. Future improvements include refining terrain models by including data acquired with UAV aerial scanners and exploring different phenological stages and machine learning approaches for classification. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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21 pages, 1574 KiB  
Article
Genetics of Growth and Stem Straightness Traits in Pinus taeda in Argentina: Exploring Genetic Competition Across Ages and Sites
by Ector C. Belaber, Nuno M. Borralho and Eduardo P. Cappa
Forests 2025, 16(4), 675; https://doi.org/10.3390/f16040675 - 12 Apr 2025
Viewed by 42
Abstract
Traditional quantitative genetic models in forestry often overlook the influence of an individual’s genes on neighboring trees. However, genetic competition models help bridge this gap. Competition varies among populations, over time, and across environments, yet forest breeders rarely monitor these dynamics or their [...] Read more.
Traditional quantitative genetic models in forestry often overlook the influence of an individual’s genes on neighboring trees. However, genetic competition models help bridge this gap. Competition varies among populations, over time, and across environments, yet forest breeders rarely monitor these dynamics or their effects on selected genotypes. We investigated the effects of competition on genetic variances, breeding value accuracy, and selection response in 14 Pinus taeda L. progeny tests using spatial (Spa) and spatial-competition (Spa-Comp) individual-tree mixed models. Our analysis covered traits such as diameter at breast height (DBH), total height (TH), and stem straightness (STR) across ages (3–21 years) and sites (altitude, soil texture, drainage). DBH was more affected by genetic competition than TH and STR, with effects varying across ages and sites. Direct-competition genetic correlations were negative for DBH from age 5 onward but positive for TH, reducing total heritable variance for DBH (<43.1%) while increasing for TH (<95.7%). Genetic competition accounted for less than 26% of direct additive variance. For DBH, the Spa-Comp model slightly improved breeding value accuracy (<~4%), while Spa inflated selection response (<3.83 percentage points), yet rank changes were minimal (common selected trees > 89%). These findings indicate that while competition inflates genetic gains, its impact on selection efficiency is minimal. Full article
(This article belongs to the Special Issue Functional Genomics of Forest Trees—2nd Edition)
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14 pages, 2756 KiB  
Article
Characteristics of Tree Growth at the Early Stage of Natural Succession on Abandoned Farmland in Southwest China’s Karst Region
by Xianli Cai, Yanwei Wang, Weijun Luo, Yangyang Wu, Anyun Cheng, Jia Chen, Lin Zhang and Shijie Wang
Forests 2025, 16(4), 674; https://doi.org/10.3390/f16040674 - 12 Apr 2025
Viewed by 107
Abstract
Southwest China’s karst region represents a global hotspot for ecological restoration, with natural succession on abandoned farmland emerging as a pivotal mechanism under recent land-use transitions. Despite its ecological significance, empirical data remain scarce regarding tree growth characteristics in this fragile ecosystem. This [...] Read more.
Southwest China’s karst region represents a global hotspot for ecological restoration, with natural succession on abandoned farmland emerging as a pivotal mechanism under recent land-use transitions. Despite its ecological significance, empirical data remain scarce regarding tree growth characteristics in this fragile ecosystem. This seven-year study (2018–2024) at Puding Karst Ecosystem Research Station quantified the spatiotemporal patterns of tree growth through monthly diameter at breast height (DBH) measurements for dominant species, coupled with microhabitat characterization (rock exposure, competition indices, and canopy architecture). Key findings revealed that the mean annual DBH increment was 5.74 mm/a, while biomass accumulation averaged 9.38 kg/a; growing-season drought duration significantly modulated interannual growth variation; and microhabitat heterogeneity and tree size significantly influenced the spatial variance of tree growth. These results substantiate natural succession as an effective carbon sequestration strategy, particularly in nutrient-depleted karst terrains. We advocate for the policy prioritization of passive restoration over active afforestation in marginal croplands. Full article
(This article belongs to the Section Forest Ecology and Management)
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15 pages, 2913 KiB  
Article
Extension of Cut-to-Length Logging Trails on Salvage Logging Operations: An Overview of the Northeastern Italian Alps
by Nicolò Di Marzio, Davide Imperiali, Luca Marchi and Stefano Grigolato
Forests 2025, 16(4), 673; https://doi.org/10.3390/f16040673 - 12 Apr 2025
Viewed by 122
Abstract
Climate change is increasing the frequency and severity of disturbances, calling for extensive salvage logging operations. This study examines fully mechanized cut-to-length operations in the northeastern Italian Alps as a response to windthrow and bark beetle outbreaks following Storm Vaia. Using high-resolution orthophotos, [...] Read more.
Climate change is increasing the frequency and severity of disturbances, calling for extensive salvage logging operations. This study examines fully mechanized cut-to-length operations in the northeastern Italian Alps as a response to windthrow and bark beetle outbreaks following Storm Vaia. Using high-resolution orthophotos, logging trail extent, density, and configuration were analyzed in relation to terrain and ecological sensitivity. A total of 29 forest sites, covering a worksite area of 1078 hectares, were analyzed, with a combined trail length exceeding 700 km. Results indicate an average logging trail density of 500 m/ha, and a machine-trafficked area percentage of 22%. Terrain analysis revealed that 68% of the worksite area was below a 30% slope, facilitating machinery operations, while 32% of the site required adaptive strategies for steeper terrain. Additionally, depth-to-water maps were implemented to assess sensitive zones according to different moisture conditions, revealing that one-fifth of the trafficked zones were at higher risk of soil disturbances due to potentially high moisture levels. This study provides critical baseline data on mechanized salvage logging effects at a large scale, offering insights for future data-driven decision making for efficient planning under sustainable forest management. Full article
(This article belongs to the Section Forest Operations and Engineering)
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27 pages, 8601 KiB  
Article
Pixel-Based Mapping of Rubber Plantation Age at Annual Resolution Using Supervised Learning for Forest Inventory and Monitoring
by Sangdao Wongsai, Manatsawee Sanpayao, Supet Jirakajohnkool and Noppachai Wongsai
Forests 2025, 16(4), 672; https://doi.org/10.3390/f16040672 - 11 Apr 2025
Viewed by 85
Abstract
Accurate mapping of rubber plantation stand age is essential for forest inventory, land use monitoring, and carbon stock estimation. This study proposes a pixel-based approach that integrates the Bare Soil Index (BSI) with Normalized Difference Vegetation Index (NDVI) time series to detect land [...] Read more.
Accurate mapping of rubber plantation stand age is essential for forest inventory, land use monitoring, and carbon stock estimation. This study proposes a pixel-based approach that integrates the Bare Soil Index (BSI) with Normalized Difference Vegetation Index (NDVI) time series to detect land clearance events and predict stand age. The methodology involves feature engineering, selection, and evaluation of three tree-based and one non-parametric supervised machine learning models. Predictive features were extracted from interannual spectral index profiles, with an optimal subset selected using Recursive Feature Elimination (RFE). The best-performing model, optimized using a grid search matrix, was trained and applied to stacked images for pixel-level land clearance prediction over 37 years of NDVI and BSI time series. By aggregating predictions and performing post-classification analysis, a spatially explicit stand-age map was generated. The result was validated using secondary rubber farmer registration data, achieving an overall prediction accuracy of 84.5% and a root mean squared error (RMSE) of 1.86 years. The findings highlight the effectiveness of machine learning with NDVI and BSI time series for stand-age estimation, contributing to advancing remote sensing methodologies for forest inventory and support furfure high-precision carbon stock assessments. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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21 pages, 7826 KiB  
Article
Spatiotemporal Dynamics of Forest Vegetation in Northern China and Their Responses to Climate Change
by Erlun Ma, Zhongke Feng, Panpan Chen and Liang Wang
Forests 2025, 16(4), 671; https://doi.org/10.3390/f16040671 - 11 Apr 2025
Viewed by 64
Abstract
Forests play a crucial role in the global carbon cycle, climate regulation, and biodiversity conservation, making them essential for understanding ecosystem responses to environmental change. However, the spatiotemporal dynamics of forest vegetation and their responses to climate change have yet to be fully [...] Read more.
Forests play a crucial role in the global carbon cycle, climate regulation, and biodiversity conservation, making them essential for understanding ecosystem responses to environmental change. However, the spatiotemporal dynamics of forest vegetation and their responses to climate change have yet to be fully explored. This study assessed the spatiotemporal dynamics and adaptation of forest vegetation from Northern China by extracting changes in forest vegetation and phenological characteristics from 2001 to 2023 with the time-series MODIS Normalized Difference Vegetation Index (NDVI) data and analyzing the impact of climate variables on these changes. The linear regression analysis method and the four-parameter double logistic model were employed to assess forest vegetation changes and identify forest vegetation phenological phases, respectively. Partial correlation analysis was used to assess the relationship between forest vegetation and climate variables. The results of this study indicate that over the past two decades, the annual mean NDVI of forest vegetation has exhibited a slow increasing trend of approximately 0.002 yr−1, with a spatial distribution pattern that gradually decreases from south to north, showing a significant correlation with latitude. The magnitude of annual mean NDVI changes varies considerably among different forest vegetation types. However, except for evergreen broadleaf forests, the NDVI of all other forest types has shown a significant increasing trend. Additionally, central North China and southeastern Tibet exhibit higher NDVI values in both spring (>0.55) and autumn (>0.65) than other areas, while the NDVI values in Northeast China and North China are higher in summer (>0.8) compared to other areas. The study reveals substantial spatial heterogeneity in the average phenological phases and NDVI values of forest vegetation across different regions, influenced by latitude, altitude, and regional climatic conditions. The spatial distribution patterns of NDVI during the green-up and senescence phases remain relatively consistent, yet significant regional differences exist within the same phenological phase. Partial correlation analysis indicates that forest vegetation in different regions responds distinctly to meteorological factors. These findings contribute to a deeper understanding of the spatiotemporal dynamics of vegetation change and its complex interactions with climate change, offering valuable insights for forest ecosystem management and climate adaptation of forest vegetation. Full article
(This article belongs to the Special Issue Integrated Measurements for Precision Forestry)
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17 pages, 7103 KiB  
Article
Standardized Protocol for Somatic Embryogenesis from Vegetative Organs in Hybrid Sweetgum (L. styraciflua × L. formosana)
by Hongxuan Li, Yingming Fan, Jindian Kang, Shuaizheng Qi, Fen Bao, Ying Li, Long Cheng, Dingju Zhan, Zhenwu Pang, Jian Zhao and Jinfeng Zhang
Forests 2025, 16(4), 670; https://doi.org/10.3390/f16040670 - 11 Apr 2025
Viewed by 58
Abstract
Embryos propagated from vegetative organs can maintain the excellent characteristics of the ortet tree and can make full use of the advantages of somatic embryogenesis technology in the large-scale clonal propagation of forest trees. However, in forest trees, a major obstacle to reproducing [...] Read more.
Embryos propagated from vegetative organs can maintain the excellent characteristics of the ortet tree and can make full use of the advantages of somatic embryogenesis technology in the large-scale clonal propagation of forest trees. However, in forest trees, a major obstacle to reproducing seedlings through somatic embryogenesis is the challenge of inducing somatic embryos using vegetative organs as explants. In this study, we have successfully developed a procedure to induce somatic embryogenesis (SE) in adult hybrid sweetgum trees for the first time. Leaves, petioles, and stem segments isolated from test-tube seedlings of three genotypes of hybrid sweetgum trees were used as explants to induce SE. The induction of SE was significantly influenced by genotype, explant type, and medium composition. The highest induction and proliferation efficiencies were achieved using a modified Blaydes’ medium supplemented with 1.0 mg/L 2,4-D and 0.5 mg/L 6-BA. Mature somatic embryos were obtained in media without plant growth regulators (PGRs). Among the three genotypes, only FX-12 failed to induce somatic embryos in all the explants. Petiole explants of FX-2 yielded 22 somatic embryos per gram. In FX-54, somatic embryos were induced from both leaf and petiole explants. The PGR concentration in the germination medium significantly affected the efficiency of somatic embryo germination, with the best germination results observed in modified Blaydes’ medium containing 0.5 mg/L 6-BA. This procedure resulted in over 60% of somatic embryos developing normally into plantlets. This study develops an SE system using vegetative organs as explants for the first time, providing technical support for large-scale asexual propagation and molecular breeding in hybrid sweetgum. Full article
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18 pages, 4389 KiB  
Article
How Vegetation Structure Shapes the Soundscape: Acoustic Community Partitioning and Its Implications for Urban Forestry Management
by Yilin Zhao, Zhenkai Sun, Zitong Bai, Jiali Jin and Cheng Wang
Forests 2025, 16(4), 669; https://doi.org/10.3390/f16040669 - 11 Apr 2025
Viewed by 52
Abstract
Urban green spaces are critical yet understudied areas where anthropogenic and biological sounds interact. This study investigates how vegetation structure mediates the acoustic partitioning of urban soundscapes and informs sustainable forestry management. Through the principal component analysis (PCA) of 1–11 kHz frequency bands, [...] Read more.
Urban green spaces are critical yet understudied areas where anthropogenic and biological sounds interact. This study investigates how vegetation structure mediates the acoustic partitioning of urban soundscapes and informs sustainable forestry management. Through the principal component analysis (PCA) of 1–11 kHz frequency bands, we identified anthropogenic sounds (1–2 kHz) and biological sounds (2–11 kHz). Within bio-acoustic communities, PCA further revealed three positively correlated sub-clusters (2–4 kHz, 5–6 kHz, and 6–11 kHz), suggesting cooperative niche partitioning among avian, amphibian, and insect vocalizations. Linear mixed models highlighted vegetation’s dual role: mature tree stands (explaining 19.9% variance) and complex vertical structures (leaf-height diversity: 12.2%) significantly enhanced biological soundscapes (R2m = 0.43) while suppressing anthropogenic noise through canopy stratification (32.3% variance explained). Based on our findings, we suggest that an acoustic data-driven framework—comprising (1) the preservation of mature stands with multi-layered canopies to enhance bioacoustic resilience, (2) strategic planting of mid-story vegetation to disrupt low-frequency noise propagation, and (3) real-time soundscape monitoring to balance biophony and anthropophony allocation—can contribute to promoting sustainable urban forestry management. Full article
(This article belongs to the Section Urban Forestry)
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17 pages, 4381 KiB  
Article
Monitoring Pine Shoot Beetle Damage Using UAV Imagery and Deep Learning Semantic Segmentation Under Different Forest Backgrounds
by Lixia Wang, Yang Gao, Yujie Liu, Lihui Zhong, Shichunyun Wang, Yunqiang Ma and Zhongyi Zhan
Forests 2025, 16(4), 668; https://doi.org/10.3390/f16040668 - 11 Apr 2025
Viewed by 74
Abstract
The outbreak of Pine Shoot Beetle (PSB, Tomicus spp.) posed a significant threat to the health of Yunnan pine forests, necessitating the development of an efficient and accurate remote sensing monitoring method. The integration of unmanned aerial vehicle (UAV) imagery and deep learning [...] Read more.
The outbreak of Pine Shoot Beetle (PSB, Tomicus spp.) posed a significant threat to the health of Yunnan pine forests, necessitating the development of an efficient and accurate remote sensing monitoring method. The integration of unmanned aerial vehicle (UAV) imagery and deep learning algorithms shows great potential for monitoring forest-damaged trees. Previous studies have utilized various deep learning semantic segmentation models for identifying damaged trees in forested areas; however, these approaches were constrained by limited accuracy and misclassification issues, particularly in complex forest backgrounds. This study evaluated the performance of five semantic segmentation models in identifying PSB-damaged trees (UNet, UNet++, PAN, DeepLabV3+ and FPN). Experimental results showed that the FPN model outperformed the others in terms of segmentation precision (0.8341), F1 score (0.8352), IoU (0.7239), mIoU (0.7185) and validation accuracy (0.9687). Under the pure Yunnan pine background, the FPN model demonstrated the best segmentation performance, followed by mixed grassland-Yunnan pine backgrounds. Its performance was the poorest in mixed bare soil-Yunnan pine background. Notably, even under this challenging background, FPN still effectively identified diseased trees, with only a 1.7% reduction in precision compared to the pure Yunnan pine background (0.9892). The proposed method in this study contributed to the rapid and accurate monitoring of PSB-damaged trees, providing valuable technical support for the prevention and management of PSB. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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29 pages, 101840 KiB  
Article
TreeDBH: Dual Enhancement Strategies for Tree Point Cloud Completion in Medium–Low Density UAV Data
by Yunlian Su, Zhibo Chen and Xiaojing Xue
Forests 2025, 16(4), 667; https://doi.org/10.3390/f16040667 - 11 Apr 2025
Viewed by 66
Abstract
Medium–low density UAV point clouds often suffer from incomplete lower canopy structures and sparse distributions due to self-occlusion. While existing point cloud completion models achieve high metric accuracy, they inadequately address missing regions in trunks and lower canopy areas. To resolve these issues, [...] Read more.
Medium–low density UAV point clouds often suffer from incomplete lower canopy structures and sparse distributions due to self-occlusion. While existing point cloud completion models achieve high metric accuracy, they inadequately address missing regions in trunks and lower canopy areas. To resolve these issues, this paper proposes a hierarchical random sampling strategy and a spatially constrained loss function. First, we dynamically stratify point clouds based on density distribution characteristics, employing hierarchical random sampling to preserve proportional representation of lower-level points, thereby effectively retaining basal tree structure information. Second, we introduce a distance constraint term for mid-lower point clouds into the symmetrical Chamfer distance (CD) loss, compelling models to prioritize completion quality in trunk base regions. Experiments on the FOR-instance-created completion dataset and Xiong’an dataset demonstrate that our method significantly enhances structural recovery capability at tree trunk bases, with visual results outperforming the baseline SeedFormer model. Additionally, we refer to existing point cloud-based diameter at breast height (DBH) calculation methods to measure the completed trees and compare the computed results with the measured values to evaluate the accuracy of the completion effect. Experimental results show that, after integrating our proposed strategies with existing completion methods, the accuracy of DBH measurement from point clouds is significantly improved. This study provides novel insights for addressing structural bias in tree point cloud completion and offers valuable references for digital forestry resource management. Full article
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17 pages, 9477 KiB  
Article
Semi-Automatic Stand Delineation Based on Very-High-Resolution Orthophotographs and Topographic Features: A Case Study from a Structurally Complex Natural Forest in the Southern USA
by Can Vatandaslar, Pete Bettinger, Krista Merry, Jonathan Stober and Taeyoon Lee
Forests 2025, 16(4), 666; https://doi.org/10.3390/f16040666 - 11 Apr 2025
Viewed by 84
Abstract
In the management of forests, the boundaries of individual units of land containing similar forest resources (e.g., stands) are delineated and used to guide the implementation of management activities. Traditionally, stand boundaries are drawn or digitized by hand; however, work recently has been [...] Read more.
In the management of forests, the boundaries of individual units of land containing similar forest resources (e.g., stands) are delineated and used to guide the implementation of management activities. Traditionally, stand boundaries are drawn or digitized by hand; however, work recently has been conducted to automate the process using aerial imagery or airborne light detection and ranging (LiDAR) data as supporting resources. The work described here applies an object-based image analysis (OBIA) process to aerial imagery and to a landform index database. The size and shape of stands in the outcomes of these applications are then adjusted to conform to the desired product of land managers. These products are then intersected as they each contain information of value in the stand delineation process. The intersected database is then adjusted once again to conform to the desired product of land managers. Conformity of the size and shape of the resulting stand boundaries to a reference database drawn subjectively by hand was low to moderate. Specifically, the overall agreement for spatial and thematic (class names) accuracies was 43.0% and 56.8%, respectively. Nevertheless, the process of automating the stand delineation effort remains promising for achieving an efficient and non-subjective characterization of a structurally complex forested environment. Full article
(This article belongs to the Special Issue Modeling of Biomass Estimation and Stand Parameters in Forests)
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20 pages, 15686 KiB  
Article
Soil Moisture Loss in Planted Forests and Its Driving Factors: A Case Study of the Nanpan River Basin
by Huan Yu, Wengang Cui, Zhonghua He, Mei Yang, Hongmei Tan and Qiuyun Yang
Forests 2025, 16(4), 665; https://doi.org/10.3390/f16040665 - 10 Apr 2025
Viewed by 77
Abstract
Soil moisture is a critical factor influencing the growth and development of terrestrial ecosystems and vegetation. In this study, we utilized data on meteorology, soil moisture, soil texture, and the spatial distribution of planted and natural forests to examine the spatial distribution characteristics [...] Read more.
Soil moisture is a critical factor influencing the growth and development of terrestrial ecosystems and vegetation. In this study, we utilized data on meteorology, soil moisture, soil texture, and the spatial distribution of planted and natural forests to examine the spatial distribution characteristics of soil moisture across soils with varying textures and depths. Geodetector models were constructed to analyze the driving mechanisms behind soil moisture dynamics. The key findings are as follows: (1) Soil moisture consumption in planted forests was significantly higher than in natural forests, with the magnitude of the difference taking the following order: coarse-textured soils > medium-textured soils > fine-textured soils. (2) The spatial differentiation of moisture content across soil layers was primarily determined by the 10–40 cm layer, while soil moisture in the 0–10 cm layer was more strongly influenced by wind speed. (3) The dominant plantation species in the watershed, Eucalyptus and Cunninghamia, have main roots extending to depths of 100–200 cm. The presence of these species in this soil layer contributes significantly to the spatial differentiation of soil moisture. This study reveals that planted forests planting consumes huge amount of soil moisture and affects the spatial differentiation of soil moisture, which provides theoretical guidance for the management of ecological restoration projects in this area. Full article
(This article belongs to the Special Issue Forest Growth, Soil Properties and Climate)
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21 pages, 7372 KiB  
Article
Elevational Distribution of Ants Across Seasons in a Subtropical Rainforest of Eastern Australia
by Pitoon Kongnoo, Chris J. Burwell, Benjamin D. Blanchard, Laksamee Punthuwat, Mark Jun M. Alcantara, Louise A. Ashton, Roger L. Kitching, Min Cao and Akihiro Nakamura
Forests 2025, 16(4), 664; https://doi.org/10.3390/f16040664 - 10 Apr 2025
Viewed by 241
Abstract
Elevational gradients are widely studied to understand environmental variability and species distribution. Ants play vital roles in ecosystems and are frequently included in elevational biogeography studies. Despite their ecological importance and well-documented elevational patterns, little is known about their temporal variability across elevations. [...] Read more.
Elevational gradients are widely studied to understand environmental variability and species distribution. Ants play vital roles in ecosystems and are frequently included in elevational biogeography studies. Despite their ecological importance and well-documented elevational patterns, little is known about their temporal variability across elevations. We surveyed ground and arboreal ants in austral summer, autumn, spring, and winter in a subtropical rainforest of Lamington National Park, Queensland, Australia. Given their physiological and microhabitat differences, ground and arboreal ants may exhibit distinct spatiotemporal patterns. Using litter extraction for ground ants and bark spraying for arboreal ants, we collected 14,916 individuals from 124 species. Species richness and abundance were lowest in austral winter, particularly for arboreal ants. Both richness and abundance declined with elevation, and this pattern remained consistent across seasons. While seasonal and elevational differences significantly influenced species composition, seasonal variation did not cause major shifts in the elevational distribution of ground or arboreal ants. A total of 43 species were identified as indicators of specific elevations, with species such as Notoncus capitatus and Colobostruma biconvexa being specialists of low elevations, and undescribed Monomorium and Discothyrea species being specialists of high elevations. In contrast, only two species were identified as seasonal indicators, which were undescribed Tapinoma and Anonychomyrma species, specialists of the warm season. Our findings suggest that ants reduce activity in winter but maintain stable elevational distributions regardless of season or microhabitat use, making their distributions a reliable indicator of their climatic niches. Full article
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17 pages, 4433 KiB  
Article
Growing Stock Volume Estimation in Forest Plantations Using Unmanned Aerial Vehicle Stereo Photogrammetry and Machine Learning Algorithms
by Mei Li, Zengyuan Li, Qingwang Liu and Erxue Chen
Forests 2025, 16(4), 663; https://doi.org/10.3390/f16040663 - 10 Apr 2025
Viewed by 60
Abstract
Currently, it is very important to accurately estimate growing stock volumes; it is crucial for quantitatively assessing forest growth and formulating forest management plans. It is convenient and quick to use the Structure from Motion (SfM) algorithm in computer vision to obtain 3D [...] Read more.
Currently, it is very important to accurately estimate growing stock volumes; it is crucial for quantitatively assessing forest growth and formulating forest management plans. It is convenient and quick to use the Structure from Motion (SfM) algorithm in computer vision to obtain 3D point cloud data from captured highly overlapped stereo photogrammetry images, while the optimal algorithm for estimating growing stock volume varies across different data sources and forest types. In this study, the performance of UAV stereo photogrammetry (USP) in estimating the growing stock volume (GSV) using three machine learning algorithms for a coniferous plantation in Northern China was explored, as well as the impact of point density on GSV estimation. The three machine learning algorithms used were random forest (RF), K-nearest neighbor (KNN), and support vector machine (SVM). The results showed that USP could accurately estimate the GSV with R2 = 0.76–0.81, RMSE = 30.11–35.46, and rRMSE = 14.34%–16.78%. Among the three machine learning algorithms, the SVM showed the best results, followed by RF. In addition, the influence of point density on the estimation accuracy for the USP dataset was minimal in terms of R2, RMSE, and rRMSE. Meanwhile, the estimation accuracies of the SVM became stable with a point density of 0.8 pts/m2 for the USP data. This study evidences that the low-density point cloud data derived from USP may be a good alternative for UAV Laser Scanning (ULS) to estimate the growing stock volume of coniferous plantations in Northern China. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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23 pages, 5096 KiB  
Review
Engineered Bamboo Building Materials: Types, Production, and Applications
by Mahdi Hosseini, Milan Gaff, Yang Wei and Chaoyu Tu
Forests 2025, 16(4), 662; https://doi.org/10.3390/f16040662 - 10 Apr 2025
Viewed by 142
Abstract
The challenges highlighted at the 29th Conference of the Parties (COP29) emphasize the importance of using renewable resources in the architecture, engineering, and construction (AEC) industry. The building and construction sector is a major contributor to environmental pollution, with most emissions stemming from [...] Read more.
The challenges highlighted at the 29th Conference of the Parties (COP29) emphasize the importance of using renewable resources in the architecture, engineering, and construction (AEC) industry. The building and construction sector is a major contributor to environmental pollution, with most emissions stemming from the extraction, transportation, production, and disposal of construction materials. As a result, developing renewable building materials is essential. In the past decade, bamboo has gained significant attention from researchers due to its strength, sustainability, high yield, and rapid growth. Bamboo in its original form has been used in construction for centuries, and recent innovations have led to the creation of engineered bamboo materials designed for more versatile applications. Researchers have been focused on understanding the physical and mechanical properties of engineered bamboo to assess its potential as a sustainable alternative to traditional building materials. However, modern practitioners are still unfamiliar with engineered bamboo materials, their types, and where they can be used. This article highlights the most widely researched engineered bamboo materials that have been used in the construction of small architectural forms and bigger structures. It provides an overview of common engineered bamboo building materials, namely laminated bamboo lumber, laminated bamboo sheets, parallel strand bamboo, bamboo mat boards, and bamboo particleboards, and their manufacturing processes and applications, offering valuable information for current practitioners and future research. Full article
(This article belongs to the Special Issue Novelties in Wood Engineering and Forestry—2nd Edition)
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21 pages, 5894 KiB  
Article
Carbon Flux Modeling with the Calibrated Biome-BGCMuSo in China’s Tropical Forests: Natural and Rubber-Planted Forests
by Fan Yang, Li Zhang, Min Yan, Linlin Ruan and Bowei Chen
Forests 2025, 16(4), 661; https://doi.org/10.3390/f16040661 - 10 Apr 2025
Viewed by 85
Abstract
Tropical forests are abundant in biodiversity and carbon stock, and the simulation of carbon flux in tropical forests is particularly challenged due to their immense biodiversity, complex and dynamic ecological processes, diverse soil and hydrological profiles, complex microclimate, and frequent human disturbance. Therefore, [...] Read more.
Tropical forests are abundant in biodiversity and carbon stock, and the simulation of carbon flux in tropical forests is particularly challenged due to their immense biodiversity, complex and dynamic ecological processes, diverse soil and hydrological profiles, complex microclimate, and frequent human disturbance. Therefore, the process-based Biome-BGCMuSo model was applied in this study to obtain accurate regional forest carbon fluxes. The model was first calibrated using eddy covariance data and a Gaussian process regression algorithm by the most sensitivity parameters for natural forests and rubber plantations. The results from the calibrated Biome-BGCMuSo model were validated against observed carbon fluxes. Finally, the carbon sink differences between natural forests and plantations were deeply analyzed. The results showed the following: (1) Sensitivity parameters varied in natural and rubber plantations. The key parameters of carbon flux in natural forests were sensitive to specific leaf area (SLA) and light extinction coefficient (k); carbon fluxes of rubber plantations were mainly affected by maintenance respiration per nitrogen (MRpern). This difference played a role in calibrating the model parameters. (2) The simulation of carbon fluxes improved through the calibrated Biome-BGCMuSo model, with the average RMSE between simulated and observed carbon fluxes reduced by 60.23%. (3) The calibration effect of the model in natural forests is better than that in plantations with less standard deviation. In summary, this study developed a region-specific calibration of the Biome-BGCMuSo model designed to enhance the precision of carbon flux estimations within tropical forests. This advancement refines the understanding of carbon dynamics and lays a pivotal foundation for scaling up to regional modeling frameworks. Full article
(This article belongs to the Section Forest Biodiversity)
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17 pages, 5413 KiB  
Article
Integrated Multi-Omics Analysis Reveals Photosynthetic Acclimation and Metabolic Reprogramming in Populus ussuriensis kom. Under Cold Stress
by Jingjing Li, Wanxin Li, Zhuolong Li, Lu Yang, Wenhui Zhuang, Jingjing Zhang, Zhaohan Zhang, Zihan Fan, Fude Wang, Shicheng Zhao and Jingli Yang
Forests 2025, 16(4), 660; https://doi.org/10.3390/f16040660 - 10 Apr 2025
Viewed by 76
Abstract
Low temperature is a major stress that severely affects tree growth and development. Despite the fact that the molecular mechanisms behind cold tolerance and associated regulatory networks in these trees remain largely unexplored, we conducted a study to examine the overall changes in [...] Read more.
Low temperature is a major stress that severely affects tree growth and development. Despite the fact that the molecular mechanisms behind cold tolerance and associated regulatory networks in these trees remain largely unexplored, we conducted a study to examine the overall changes in metabolites and regulatory pathways of Populus ussuriensis kom. when exposed to cold stress, utilizing a comprehensive multi-omics approach. Transcriptomes exposed to cold stress reveal that most of the candidate genes related to the Calvin–Benson–Bassham cycle and flavonoid synthesis were upregulated. Joint analysis revealed that within 6–48 h of low-temperature treatment, differential genes (such as PAL and CHS) in the flavonoid biosynthesis pathway and metabolites (such as quercetin) were significantly upregulated, indicating a positive correlation under short-term stress. However, prolonged treatment (72 h) may trigger metabolic feedback, leading to a decrease in flavonoid content. In addition, the measurements of gas exchange and metabolite assays of P. ussuriensis showed that photosynthetic acclimation led to a change in the sugar accumulation and starch degradation in response to low temperature, indicating that extensive changes occurred due to the cold and improved tolerance in P. ussuriensis. This study provides a new basis for future studies on the molecular mechanism of cold tolerance at the transcriptional and metabolic levels. Full article
(This article belongs to the Special Issue Genomic Analysis of Growth and Stress Adaptation in Forest Trees)
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18 pages, 1712 KiB  
Article
Characteristics of Nocturnal Insect Communities in Semi-Arid Regions: A Case Study at the Habahu National Nature Reserve of Ningxia, China
by Kang Lou, Dian Yu, Caihua Zhang and Houhun Li
Forests 2025, 16(4), 659; https://doi.org/10.3390/f16040659 - 10 Apr 2025
Viewed by 69
Abstract
To explore the spatiotemporal niche characteristics and changing regularities of insect communities under lamps in a semi-arid region, this paper analyzed Levins’ niche breadth index and the Pianka niche overlap index of 10 orders and 19 selected common families or superfamilies of insect [...] Read more.
To explore the spatiotemporal niche characteristics and changing regularities of insect communities under lamps in a semi-arid region, this paper analyzed Levins’ niche breadth index and the Pianka niche overlap index of 10 orders and 19 selected common families or superfamilies of insect communities under lamps from April to September 2018 at six vegetation sites in the Habahu National Nature Reserve, a rare desert grassland–wetland reserve in China. The results indicated the following: (1) Different taxa possess varying spatiotemporal, temporal, and spatial niche breadths, suggesting that insects effectively utilized resources in the Habahu Nature Reserve. (2) Among these groups, in terms of the orders aspect, Lepidoptera had the largest temporal niche breadth, the Hemiptera had the largest spatial niche breadth, and Lepidoptera, Coleoptera, and Hemiptera had relatively large spatiotemporal niche breadths, while Odonata had the smallest niche breadth in all three aspects. The orders of Coleoptera and Lepidoptera had the largest spatiotemporal niche overlap value, while Odonata and Diptera had the smallest. (3) In terms of the common families (superfamilies) aspect, Noctuidae had the largest temporal niche breadth and spatiotemporal niche breadth, while Hydrophilidae had the smallest. The spatial niche breadth of Sphingidae was the largest, while Corixidae was the smallest. Noctuidae and Pyraloidea had the largest spatiotemporal niche overlap value among these herbivore groups, Miridae and Chrysopidae, among the herbivore to predatory groups, and Noctuidae and Braconidae, among the herbivore to parasitic groups. This lays a theoretical foundation for developing Chrysopidae and Braconidae as biological control taxa in the Habahu Nature Reserve. Full article
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16 pages, 7307 KiB  
Article
Rainfall Partitioning by Two Alpine Shrubs in the Qilian Mountains, Northwest China: Implications for Hydrological Modeling in Cold Regions
by Zhangwen Liu, Yongxin Tian, Jinxian Qi, Zhiying Dang, Rensheng Chen, Chuntan Han and Yong Yang
Forests 2025, 16(4), 658; https://doi.org/10.3390/f16040658 - 10 Apr 2025
Viewed by 48
Abstract
Understanding rainfall partitioning by shrub canopies is essential for assessing water balance and improving hydrological models in cold regions. From 2010 to 2012, field experiments were conducted in the Hulu catchment of the Qilian Mountains, focusing on Potentilla fruticosa and Caragana jubata during [...] Read more.
Understanding rainfall partitioning by shrub canopies is essential for assessing water balance and improving hydrological models in cold regions. From 2010 to 2012, field experiments were conducted in the Hulu catchment of the Qilian Mountains, focusing on Potentilla fruticosa and Caragana jubata during the growing season. Throughfall, stemflow, and interception loss were measured using rain gauges, stemflow collars, and a water balance approach. A total of 197 natural rainfall events were recorded, and precipitation partitioning characteristics were analyzed in relation to rainfall intensity, amount, and vegetation traits. One-way ANOVA and regression analyses were used to test differences and correlations. The results showed that the critical rainfall threshold for generating throughfall and stemflow was 1.9 mm. For P. fruticosa, throughfall, stemflow, and interception loss accounted for 66.96%, 3.51%, and 29.53% of gross rainfall, respectively; the corresponding values for C. jubata were 67.31%, 7.27%, and 25.42%. Significant differences (p < 0.05) in stemflow were observed between species. Partitioning components were positively correlated with rainfall amount and stabilized at ~4 mm h−1 intensity. Interception loss percentage decreased with intensity and plateaued at 2 mm h−1 for P. fruticosa and 5 mm h−1 for C. jubata. These findings provide empirical evidence for modeling shrub canopy rainfall redistribution in alpine environments. Full article
(This article belongs to the Special Issue Hydrological Modelling of Forested Ecosystems)
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