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  • Rural Digital Europe
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Andrii Bilous; Roman Zadorozhniuk; Anatolii Makarevych; Viktor Svynchuk; +4 Authors

    The sustainable management of urban green areas requires clear and efficient protocols for measuring the biometric properties of tree vegetation. Specifically, operational in situ sampling solutions are essential to inventory forked (multi-stemmed) trees. This study aimed to assess the efficiency of two different sampling protocols for mean tree diameter at breast height (DBH) measurement of forked urban trees. The protocols were tested on a dataset of 76 forked trees, each having more than three stems and sampled in urban areas of Kyiv, Ukraine. First, we tested the efficiency of mean tree DBH estimations using measurements of randomly selected one, two, or three stems (random sampling, or RSM). Second, we examined different combinations of the thinnest, thickest, and average stems (identified visually) for each tree to estimate mean tree DBH (targeted sampling, or TSM). The distributions of mean tree DBH and root mean square errors (RMSE) were utilized to compare the utility of the two approaches. The TSM of three stems (the thinnest, thickest, and average) provided the highest accuracy of mean tree DBH estimation (RMSE% = 6.3% of the mean), compared to the RSM (RMSE% = 12.1%). The TSM of the four thickest stems demonstrated the overestimation of mean tree DBH for forked trees with five or more stems. Accurate mean tree DBH estimates can be derived with negligible systematic errors applying the RSM over a large number of measured trees. However, these estimates will not likely match the measurements from previous inventories due to random stem selection. We recommend using the TSM with measuring three specific stems as a balanced solution in terms of estimation accuracy, bias, and time costs.

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    Forests
    Article . 2024 . Peer-reviewed
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      Forests
      Article . 2024 . Peer-reviewed
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    Authors: Junxiang Zhang; Cui Zhou; Gui Zhang; Zhigao Yang; +2 Authors

    The estimation of forest above-ground biomass (AGB) can be significantly improved by leveraging remote sensing (RS) and deep learning (DL) techniques. In this process, it is crucial to obtain appropriate RS features and develop a suitable model. However, traditional methods such as random forest (RF) feature selection often fail to adequately consider the complex relationships within high-dimensional RS feature spaces. Moreover, challenges related to parameter selection and overfitting inherent in DL models may compromise the accuracy of AGB estimation. Therefore, this study proposes a novel framework based on freely available Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical data. Firstly, we designed new indices through the formula analogous with vegetation index calculation to integrate multidimensional spectral and structural information. Then, leveraging the simplicity of computational principles, a pigeon-inspired optimization algorithm (PIO) was introduced into a bi-directional long short-term memory neural network (PIO-BiLSTM), which achieved the set objective function through repeated iteration and validation to obtain the optimal model parameters. Finally, to verify the framework’s effect, we conducted experiments in two different tree species and compared another seven classical optimization algorithms and machine learning models. The results indicated that the new indices significantly improved the inversion accuracy of all models in both categories, and the PIO-BiLSTM model achieved the highest accuracy (Category-1: R2 = 0.8055, MAE = 8.8475 Mg·ha−1, RMSE = 12.2876 Mg·ha−1, relative RMSE = 18.1715%; Category-2: R2 = 0.7956, MAE = 1.7103 Mg·ha−1, RMSE = 2.2887 Mg·ha−1, relative RMSE = 9.3000%). Compared with existing methods, the proposed framework greatly reduced the labor costs in parameter selection, and its potential uncertainty also decreased by up to 9.0%. Furthermore, the proposed method has a strong generalization ability and is independent of tree species, indicating its great potential for future forest AGB inversion in wider regions with diverse forest types.

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    Forests
    Article . 2024 . Peer-reviewed
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      Forests
      Article . 2024 . Peer-reviewed
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    Authors: Ting Gao; Changming Chen; Zhen Zhu;

    In recent years, stricter environmental rules have affected the entire bamboo industry in China. The increased costs for managing environmental issues hinder the growth of the bamboo forest harvesting and transportation sector in the upstream part of the industry chain. Analyzing how environmental changes affect the entire bamboo industry can give a deeper understanding of the regional transfer within the bamboo industry in China, and it can give more experience to the bamboo industry in developing countries. This study, based on the Pollution Haven Hypothesis and the theory of externalities, collected panel data from 16 provinces in China from 2000 to 2020 and examined the discrepancies in bamboo industry development and the varying intensities of market-oriented environmental regulation (MER). By constructing a fixed effects model and employing econometric methods, this study analyzed the spatiotemporal impact of MER on the output value of the bamboo harvesting and transportation industry (BHTI) and explored whether MER is a crucial factor causing the transfer of the bamboo industry across regions. The findings indicate that there is a noticeable shift of BHTI from the eastern to the central and western regions. Additionally, there is a substantial adverse effect of MER on the BHTI output value, especially in the eastern region. This confirms the transfer of industries between regions, which is a novel contribution of this article. Based on the findings of this study, some recommendations have been given for the response to the environmental regulation for bamboo industries in the future.

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    Forests
    Article . 2024 . Peer-reviewed
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      Article . 2024 . Peer-reviewed
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    Authors: Chunjie Zhou; Danmei Chen; Lipeng Zang; Guangqi Zhang; +9 Authors

    Microorganisms play a pivotal role in transforming and making phosphorus (P) available in soil through various mechanisms. However, their specific contributions to alleviating P limitation and enhancing P utilization efficiency in plants within the context of a P-deficient karst ecosystem remains unclear. In this study, eco-stoichiometric methods were employed to evaluate the P utilization efficiency of plants grown in the surveyed karst forest located in Guizhou Province, China. Metagenomic sequencing was utilized to further explore the functional genes and microorganisms involved in soil P cycling. The N:P ratio for 18 out of the 20 surveyed plants exceeded 16, indicating widespread P limitation in karst plants. Among them, plants with high P utilization efficiencies (Nandina domestica Thunb.; Mahonia bodinieri Gagnep.; Pyracantha fortuneana (Maxim.) Li) exhibited higher relative abundances of genes involved in soil P cycling compared to plants with low P utilization efficiencies (Tirpitzia sinensis (Hemsl.) Hallier f.; Albizia kalkora (Roxb.) Prain; Morella rubra Lour.), indicating greater potentials within their rhizosphere microbiomes for soil P transformation. The relative abundance of these functional genes had a significant and positive effect on plant P utilization efficiencies. Structural equation modeling further indicated that microbial P cycling gene abundance directly drove the increase in plant P utilization efficiencies. Specifically, genes involved in soil organic P mineralization (G6PD, suhB, phoD, ppx) and the P uptake and transform system (pstS, pstA, pstB, pstC) contributed to the enhancement of plant P utilization efficiencies. Soil microbial communities involved in P cycling were predominately attributed to Proteobacteria (45.16%–60.02%), Actinobacteria (9.45%–25.23%), and Acidobacteria (5.90%–9.85%), although their contributions varied among different plants. The rhizosphere functional microbial community can thus alleviate P limitation in karst plants, thereby enhancing plant P utilization efficiencies. This study investigated the strong synergism between karst plants and rhizosphere microorganisms and their associated underlying mechanisms from genetic and microbial perspectives.

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    Forests
    Article . 2024 . Peer-reviewed
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    Authors: María José Aroca-Fernández; José Alfredo Bravo-Fernández; Juan Ignacio García-Viñas; Rafael Serrada;

    The effects of machinery and livestock on forest soil compaction have mostly been studied at short-term and local scales. A better understanding of the long-term effects of compaction in mature stands at the management scale is needed, especially in hot and dry climates. This study aims to analyze (1) soil compaction in a Mediterranean Scots pine (Pinus sylvestris L.) forest subjected to mechanized logging and grazing for more than 50 years and (2) forest productivity trends during these 50 years of disturbance. Soil penetration resistance (0–10 cm and 10–20 cm) and soil moisture (0–12 cm) were measured in 181 randomly selected points affected by “high machinery traffic”, “high cattle traffic” or “low traffic”. Decennial forest inventory data on density, timber volume, and recruitment were collected and analyzed over the five decades preceding soil measurements. Soil penetration resistance exceeded 2500 kPa at a significant portion of the sampled points, although the highest levels of compaction tended to be concentrated in the subsurface layer of the high-traffic areas. Cattle and machinery caused significant compaction in these areas and increased penetration resistance in the range of 350–450 kPa. However, despite the long period of disturbance and the increase in penetration resistance observed, no signs of productivity decline were detected in the forest.

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    Article . 2024 . Peer-reviewed
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      Article . 2024 . Peer-reviewed
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    Authors: Qiaoling Li; Zhiyuan Huang; Zheke Zhong; Fangyuan Bian; +1 Authors

    Bamboo shoot processing wastewater (BBPW) is rich in organic matter and organic acids and can be used as a nutrient source for microbial growth and biofertilization. In this study, Pseudomonas K22-D and Terribacillus goriness CS3 were isolated from bamboo forest soil with plant growth-promoting properties. Biofertilizers were prepared by inoculating bacteria into BBPW, and the effects of their application in a bamboo forest were evaluated. The chemical oxygen demand, TOC, TN, and NH4-N contents decreased after inoculation, indicating that the bacteria were able to degrade macromolecules in BBPW. The BBPW biofertilizer produced by mixed bacteria (CS3 + K22-D) significantly improved the soil organic carbon and mineral-associated organic carbon content and reduced the pH, alkali-hydrolysable nitrogen, available phosphorus, and available potassium content of the soils in the bamboo forest, which might be attributed to the high C:N ratio and microbial synergism in the biofertilizer and the fast growth period of bamboo shoots. Notably, the CS3 biofertilizer significantly increased soil-available phosphorus (90.25%), and the K22-D biofertilizer significantly decreased soil-available phosphorus (70.33%) compared with CK, suggesting that the presence of inorganic phosphorus-solubilizing bacteria can promote soil P. We believe that the return of inoculated bamboo shoot processing wastewater to bamboo plantations can be an eco-friendly, sustainable practice for bamboo forest management.

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    Authors: Jinhai Yu; Qinghe Zhao; Zaihui Yu; Yi Liu; +1 Authors

    Forest roads are a common land use feature with a significant impact on sediment yield and the water sediment transport processes within a watershed, seriously disrupting the safety and stability of the watershed. Previous studies have focused on the sediment production processes within the road prism. However, there has been limited attention given to the transport processes of road-eroded sediment at various scales, which is crucial for understanding the off-site effects of road erosion. This paper reviews research conducted on forest road erosion over the past two decades. It summarizes the mechanisms of sediment production from road erosion and provides a detailed analysis of the transport mechanisms of eroded sediments from roads to streams at the watershed scale. The paper also examines the ecological and hydrological effects, research methods, and control measures related to sediment transport caused by forest road erosion. It identifies current research limitations and outlines future research directions. The findings of this review highlight several key points: (1) Most research on forest road erosion tends to be specific and unilateral, often neglecting the broader interaction between roads and the watershed in terms of water–sediment dynamics. (2) Various research methods are employed in the study of forest road erosion, including field monitoring, artificial simulation experiments, and road erosion prediction models. Each method has its advantages and disadvantages, but the integration of emerging technologies like laser scanning and fingerprint recognition remains underutilized, hindering the simultaneous achievement of convenience and accuracy. (3) The transport processes of forest road-eroded sediment, particularly on road–stream slopes, are influenced by numerous factors, including terrain, soil, and vegetation. These processes exhibit significant spatial and temporal variability, and the precise quantification of sediment transport efficiency to the stream remains challenging due to a lack of long-term and stable investigation and monitoring methods. The establishment and operation of runoff plots and sedimentation basins may help offer a solution to this challenge. (4) Both biological and engineering measures have proven effective in reducing and limiting sediment erosion and transport. However, the costs and economic benefits associated with these regulation measures require further investigation. This review provides a comprehensive summary of relevant research on sediment erosion and transport processes on unpaved forest roads, enhancing our understanding of sediment yield in watersheds and offering valuable insights for reducing sediment production and transport to streams.

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    Forests
    Article . 2024 . Peer-reviewed
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      Forests
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    Authors: Jiafeng Yang; Shutong Zhang; Yun Qian; Haili Chen; +2 Authors

    The utilization of wood as a construction material offers inherent advantages, including its renewability, good process property, wide availability, and carbon sequestration. However, its susceptibility to combustion and limited mechanical properties also constrain its applications. In this work, calcium phosphate was in situ deposited in dignified Chinese fir wood, followed by hot-pressed densification. Thermogravimetric analysis (TG) reveals that mineralization and densification alleviate the thermal decomposition and combustion behavior of wood, which greatly promotes the formation of the dense char layer during wood combustion. Therefore, the maximum heat release rate (HRR), total heat release rate (THR), and total smoke production rate (TSP) of the as-prepared mineralized dense wood were significantly reduced by 37%, 32%, and 56% compared with the control one. Further, the mineralized dense wood showed a remarkable enhancement in flexural strength and flexural modulus of elasticity, 203% and 220% higher than the natural wood, respectively. This study demonstrated a straightforward and eco-friendly approach to fabricating structural wood possessing exceptional flame retardancy and mechanical characterization, which holds immense potential for application in energy-efficient green buildings.

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    Forests
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      Forests
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    Authors: Sol-E Choi; Sunjeoung Lee; Jeongmook Park; Suyeon Lee; +2 Authors

    This study provides the methodology for the development of sustainable forest management activities and systematic strategies using national spatial data, satellite imagery, and a random forest machine learning classifier. This study conducts a regional province-scale approach that can be used to analyze forest clear-cutting in South Korea; we focused on the Chungcheongnam-do region. Based on spatial information from digital forestry data, Sentinel-2 satellite imagery, random forest (RF) classifier, and digital forest-type maps (DFTMs), we detected and analyzed the characteristics of clear-cut areas. We identified forest clear-cut areas (accounting for 2.48% of the total forest area). The methodology integrates various vegetation indices and the RF classifier to ensure the effective detection of clear-cut areas at the provincial level with an accuracy of 92.8%. Specific leaf area vegetation index (SLAVI) was determined as the most important factor for accurately detecting clear-cut areas. Moreover, using a DFTM, we analyzed clear-cutting characteristics in different forest types (including private, national, natural, and planted forests), along with age class and diameter-at-breast-height class. Our method can serve as a basis for forest management and monitoring by analyzing tree-cutting trends in countries with forest areas, such as Republic of Korea.

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    Forests
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    Authors: Mingqian Liu; Yihong Zhu; Rongrong Pang; Lushuang Gao;

    Large trees dominate stand-level biomass but their growth suffers more from droughts, while sheltering small trees during droughts. Under a warmer and drier climate, whether the growth decline of large trees could be compensated by prompted small trees’ growth remains unknown. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) series, drought characteristics were determined, and two drought events were selected. We reconstructed historical diameters at breast height (DBH) and the aboveground biomass of Larix gmelinii through tree ring data allometric equations. To clarify the difference in the responses of tree size to drought, we calculated resistance, recovery, and resilience in each diameter class. We used a growth dominance coefficient (GDC) to exhibit the contributions of different-sized individuals to stand growth and demonstrated the growth dynamics of both the individual and stand level. The results proved that large trees were more vulnerable to local droughts, the resilience of larch had a negative relationship with the DBH (p < 0.05), and small trees could recover to even exceed their pre-drought growth level. Most plots had a negative GDC and small trees contributed more to stand growth compared with their size, but their AGB growth was far less than that of large trees, which made it difficult to compensate for stand growth decline. Our results indicate that tree resilience has a negative relationship with their pre-drought sizes, as large trees in the stand fail to regain their growth level before drought. Even with a larger relative contribution and higher resilience, small trees cannot cover deficits in large trees’ growth. Under more frequent droughts, the total aboveground biomass growth of larches would decline.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Andrii Bilous; Roman Zadorozhniuk; Anatolii Makarevych; Viktor Svynchuk; +4 Authors

    The sustainable management of urban green areas requires clear and efficient protocols for measuring the biometric properties of tree vegetation. Specifically, operational in situ sampling solutions are essential to inventory forked (multi-stemmed) trees. This study aimed to assess the efficiency of two different sampling protocols for mean tree diameter at breast height (DBH) measurement of forked urban trees. The protocols were tested on a dataset of 76 forked trees, each having more than three stems and sampled in urban areas of Kyiv, Ukraine. First, we tested the efficiency of mean tree DBH estimations using measurements of randomly selected one, two, or three stems (random sampling, or RSM). Second, we examined different combinations of the thinnest, thickest, and average stems (identified visually) for each tree to estimate mean tree DBH (targeted sampling, or TSM). The distributions of mean tree DBH and root mean square errors (RMSE) were utilized to compare the utility of the two approaches. The TSM of three stems (the thinnest, thickest, and average) provided the highest accuracy of mean tree DBH estimation (RMSE% = 6.3% of the mean), compared to the RSM (RMSE% = 12.1%). The TSM of the four thickest stems demonstrated the overestimation of mean tree DBH for forked trees with five or more stems. Accurate mean tree DBH estimates can be derived with negligible systematic errors applying the RSM over a large number of measured trees. However, these estimates will not likely match the measurements from previous inventories due to random stem selection. We recommend using the TSM with measuring three specific stems as a balanced solution in terms of estimation accuracy, bias, and time costs.

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    Authors: Junxiang Zhang; Cui Zhou; Gui Zhang; Zhigao Yang; +2 Authors

    The estimation of forest above-ground biomass (AGB) can be significantly improved by leveraging remote sensing (RS) and deep learning (DL) techniques. In this process, it is crucial to obtain appropriate RS features and develop a suitable model. However, traditional methods such as random forest (RF) feature selection often fail to adequately consider the complex relationships within high-dimensional RS feature spaces. Moreover, challenges related to parameter selection and overfitting inherent in DL models may compromise the accuracy of AGB estimation. Therefore, this study proposes a novel framework based on freely available Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical data. Firstly, we designed new indices through the formula analogous with vegetation index calculation to integrate multidimensional spectral and structural information. Then, leveraging the simplicity of computational principles, a pigeon-inspired optimization algorithm (PIO) was introduced into a bi-directional long short-term memory neural network (PIO-BiLSTM), which achieved the set objective function through repeated iteration and validation to obtain the optimal model parameters. Finally, to verify the framework’s effect, we conducted experiments in two different tree species and compared another seven classical optimization algorithms and machine learning models. The results indicated that the new indices significantly improved the inversion accuracy of all models in both categories, and the PIO-BiLSTM model achieved the highest accuracy (Category-1: R2 = 0.8055, MAE = 8.8475 Mg·ha−1, RMSE = 12.2876 Mg·ha−1, relative RMSE = 18.1715%; Category-2: R2 = 0.7956, MAE = 1.7103 Mg·ha−1, RMSE = 2.2887 Mg·ha−1, relative RMSE = 9.3000%). Compared with existing methods, the proposed framework greatly reduced the labor costs in parameter selection, and its potential uncertainty also decreased by up to 9.0%. Furthermore, the proposed method has a strong generalization ability and is independent of tree species, indicating its great potential for future forest AGB inversion in wider regions with diverse forest types.

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    Authors: Ting Gao; Changming Chen; Zhen Zhu;

    In recent years, stricter environmental rules have affected the entire bamboo industry in China. The increased costs for managing environmental issues hinder the growth of the bamboo forest harvesting and transportation sector in the upstream part of the industry chain. Analyzing how environmental changes affect the entire bamboo industry can give a deeper understanding of the regional transfer within the bamboo industry in China, and it can give more experience to the bamboo industry in developing countries. This study, based on the Pollution Haven Hypothesis and the theory of externalities, collected panel data from 16 provinces in China from 2000 to 2020 and examined the discrepancies in bamboo industry development and the varying intensities of market-oriented environmental regulation (MER). By constructing a fixed effects model and employing econometric methods, this study analyzed the spatiotemporal impact of MER on the output value of the bamboo harvesting and transportation industry (BHTI) and explored whether MER is a crucial factor causing the transfer of the bamboo industry across regions. The findings indicate that there is a noticeable shift of BHTI from the eastern to the central and western regions. Additionally, there is a substantial adverse effect of MER on the BHTI output value, especially in the eastern region. This confirms the transfer of industries between regions, which is a novel contribution of this article. Based on the findings of this study, some recommendations have been given for the response to the environmental regulation for bamboo industries in the future.

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    Authors: Chunjie Zhou; Danmei Chen; Lipeng Zang; Guangqi Zhang; +9 Authors

    Microorganisms play a pivotal role in transforming and making phosphorus (P) available in soil through various mechanisms. However, their specific contributions to alleviating P limitation and enhancing P utilization efficiency in plants within the context of a P-deficient karst ecosystem remains unclear. In this study, eco-stoichiometric methods were employed to evaluate the P utilization efficiency of plants grown in the surveyed karst forest located in Guizhou Province, China. Metagenomic sequencing was utilized to further explore the functional genes and microorganisms involved in soil P cycling. The N:P ratio for 18 out of the 20 surveyed plants exceeded 16, indicating widespread P limitation in karst plants. Among them, plants with high P utilization efficiencies (Nandina domestica Thunb.; Mahonia bodinieri Gagnep.; Pyracantha fortuneana (Maxim.) Li) exhibited higher relative abundances of genes involved in soil P cycling compared to plants with low P utilization efficiencies (Tirpitzia sinensis (Hemsl.) Hallier f.; Albizia kalkora (Roxb.) Prain; Morella rubra Lour.), indicating greater potentials within their rhizosphere microbiomes for soil P transformation. The relative abundance of these functional genes had a significant and positive effect on plant P utilization efficiencies. Structural equation modeling further indicated that microbial P cycling gene abundance directly drove the increase in plant P utilization efficiencies. Specifically, genes involved in soil organic P mineralization (G6PD, suhB, phoD, ppx) and the P uptake and transform system (pstS, pstA, pstB, pstC) contributed to the enhancement of plant P utilization efficiencies. Soil microbial communities involved in P cycling were predominately attributed to Proteobacteria (45.16%–60.02%), Actinobacteria (9.45%–25.23%), and Acidobacteria (5.90%–9.85%), although their contributions varied among different plants. The rhizosphere functional microbial community can thus alleviate P limitation in karst plants, thereby enhancing plant P utilization efficiencies. This study investigated the strong synergism between karst plants and rhizosphere microorganisms and their associated underlying mechanisms from genetic and microbial perspectives.

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      Forests
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    Authors: María José Aroca-Fernández; José Alfredo Bravo-Fernández; Juan Ignacio García-Viñas; Rafael Serrada;

    The effects of machinery and livestock on forest soil compaction have mostly been studied at short-term and local scales. A better understanding of the long-term effects of compaction in mature stands at the management scale is needed, especially in hot and dry climates. This study aims to analyze (1) soil compaction in a Mediterranean Scots pine (Pinus sylvestris L.) forest subjected to mechanized logging and grazing for more than 50 years and (2) forest productivity trends during these 50 years of disturbance. Soil penetration resistance (0–10 cm and 10–20 cm) and soil moisture (0–12 cm) were measured in 181 randomly selected points affected by “high machinery traffic”, “high cattle traffic” or “low traffic”. Decennial forest inventory data on density, timber volume, and recruitment were collected and analyzed over the five decades preceding soil measurements. Soil penetration resistance exceeded 2500 kPa at a significant portion of the sampled points, although the highest levels of compaction tended to be concentrated in the subsurface layer of the high-traffic areas. Cattle and machinery caused significant compaction in these areas and increased penetration resistance in the range of 350–450 kPa. However, despite the long period of disturbance and the increase in penetration resistance observed, no signs of productivity decline were detected in the forest.

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    Forests
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      Forests
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    Authors: Qiaoling Li; Zhiyuan Huang; Zheke Zhong; Fangyuan Bian; +1 Authors

    Bamboo shoot processing wastewater (BBPW) is rich in organic matter and organic acids and can be used as a nutrient source for microbial growth and biofertilization. In this study, Pseudomonas K22-D and Terribacillus goriness CS3 were isolated from bamboo forest soil with plant growth-promoting properties. Biofertilizers were prepared by inoculating bacteria into BBPW, and the effects of their application in a bamboo forest were evaluated. The chemical oxygen demand, TOC, TN, and NH4-N contents decreased after inoculation, indicating that the bacteria were able to degrade macromolecules in BBPW. The BBPW biofertilizer produced by mixed bacteria (CS3 + K22-D) significantly improved the soil organic carbon and mineral-associated organic carbon content and reduced the pH, alkali-hydrolysable nitrogen, available phosphorus, and available potassium content of the soils in the bamboo forest, which might be attributed to the high C:N ratio and microbial synergism in the biofertilizer and the fast growth period of bamboo shoots. Notably, the CS3 biofertilizer significantly increased soil-available phosphorus (90.25%), and the K22-D biofertilizer significantly decreased soil-available phosphorus (70.33%) compared with CK, suggesting that the presence of inorganic phosphorus-solubilizing bacteria can promote soil P. We believe that the return of inoculated bamboo shoot processing wastewater to bamboo plantations can be an eco-friendly, sustainable practice for bamboo forest management.

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    Forests
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    Authors: Jinhai Yu; Qinghe Zhao; Zaihui Yu; Yi Liu; +1 Authors

    Forest roads are a common land use feature with a significant impact on sediment yield and the water sediment transport processes within a watershed, seriously disrupting the safety and stability of the watershed. Previous studies have focused on the sediment production processes within the road prism. However, there has been limited attention given to the transport processes of road-eroded sediment at various scales, which is crucial for understanding the off-site effects of road erosion. This paper reviews research conducted on forest road erosion over the past two decades. It summarizes the mechanisms of sediment production from road erosion and provides a detailed analysis of the transport mechanisms of eroded sediments from roads to streams at the watershed scale. The paper also examines the ecological and hydrological effects, research methods, and control measures related to sediment transport caused by forest road erosion. It identifies current research limitations and outlines future research directions. The findings of this review highlight several key points: (1) Most research on forest road erosion tends to be specific and unilateral, often neglecting the broader interaction between roads and the watershed in terms of water–sediment dynamics. (2) Various research methods are employed in the study of forest road erosion, including field monitoring, artificial simulation experiments, and road erosion prediction models. Each method has its advantages and disadvantages, but the integration of emerging technologies like laser scanning and fingerprint recognition remains underutilized, hindering the simultaneous achievement of convenience and accuracy. (3) The transport processes of forest road-eroded sediment, particularly on road–stream slopes, are influenced by numerous factors, including terrain, soil, and vegetation. These processes exhibit significant spatial and temporal variability, and the precise quantification of sediment transport efficiency to the stream remains challenging due to a lack of long-term and stable investigation and monitoring methods. The establishment and operation of runoff plots and sedimentation basins may help offer a solution to this challenge. (4) Both biological and engineering measures have proven effective in reducing and limiting sediment erosion and transport. However, the costs and economic benefits associated with these regulation measures require further investigation. This review provides a comprehensive summary of relevant research on sediment erosion and transport processes on unpaved forest roads, enhancing our understanding of sediment yield in watersheds and offering valuable insights for reducing sediment production and transport to streams.

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    Forests
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    Authors: Jiafeng Yang; Shutong Zhang; Yun Qian; Haili Chen; +2 Authors

    The utilization of wood as a construction material offers inherent advantages, including its renewability, good process property, wide availability, and carbon sequestration. However, its susceptibility to combustion and limited mechanical properties also constrain its applications. In this work, calcium phosphate was in situ deposited in dignified Chinese fir wood, followed by hot-pressed densification. Thermogravimetric analysis (TG) reveals that mineralization and densification alleviate the thermal decomposition and combustion behavior of wood, which greatly promotes the formation of the dense char layer during wood combustion. Therefore, the maximum heat release rate (HRR), total heat release rate (THR), and total smoke production rate (TSP) of the as-prepared mineralized dense wood were significantly reduced by 37%, 32%, and 56% compared with the control one. Further, the mineralized dense wood showed a remarkable enhancement in flexural strength and flexural modulus of elasticity, 203% and 220% higher than the natural wood, respectively. This study demonstrated a straightforward and eco-friendly approach to fabricating structural wood possessing exceptional flame retardancy and mechanical characterization, which holds immense potential for application in energy-efficient green buildings.

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    Forests
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      Forests
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    Authors: Sol-E Choi; Sunjeoung Lee; Jeongmook Park; Suyeon Lee; +2 Authors

    This study provides the methodology for the development of sustainable forest management activities and systematic strategies using national spatial data, satellite imagery, and a random forest machine learning classifier. This study conducts a regional province-scale approach that can be used to analyze forest clear-cutting in South Korea; we focused on the Chungcheongnam-do region. Based on spatial information from digital forestry data, Sentinel-2 satellite imagery, random forest (RF) classifier, and digital forest-type maps (DFTMs), we detected and analyzed the characteristics of clear-cut areas. We identified forest clear-cut areas (accounting for 2.48% of the total forest area). The methodology integrates various vegetation indices and the RF classifier to ensure the effective detection of clear-cut areas at the provincial level with an accuracy of 92.8%. Specific leaf area vegetation index (SLAVI) was determined as the most important factor for accurately detecting clear-cut areas. Moreover, using a DFTM, we analyzed clear-cutting characteristics in different forest types (including private, national, natural, and planted forests), along with age class and diameter-at-breast-height class. Our method can serve as a basis for forest management and monitoring by analyzing tree-cutting trends in countries with forest areas, such as Republic of Korea.

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    Authors: Mingqian Liu; Yihong Zhu; Rongrong Pang; Lushuang Gao;

    Large trees dominate stand-level biomass but their growth suffers more from droughts, while sheltering small trees during droughts. Under a warmer and drier climate, whether the growth decline of large trees could be compensated by prompted small trees’ growth remains unknown. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) series, drought characteristics were determined, and two drought events were selected. We reconstructed historical diameters at breast height (DBH) and the aboveground biomass of Larix gmelinii through tree ring data allometric equations. To clarify the difference in the responses of tree size to drought, we calculated resistance, recovery, and resilience in each diameter class. We used a growth dominance coefficient (GDC) to exhibit the contributions of different-sized individuals to stand growth and demonstrated the growth dynamics of both the individual and stand level. The results proved that large trees were more vulnerable to local droughts, the resilience of larch had a negative relationship with the DBH (p < 0.05), and small trees could recover to even exceed their pre-drought growth level. Most plots had a negative GDC and small trees contributed more to stand growth compared with their size, but their AGB growth was far less than that of large trees, which made it difficult to compensate for stand growth decline. Our results indicate that tree resilience has a negative relationship with their pre-drought sizes, as large trees in the stand fail to regain their growth level before drought. Even with a larger relative contribution and higher resilience, small trees cannot cover deficits in large trees’ growth. Under more frequent droughts, the total aboveground biomass growth of larches would decline.

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