Valery Bondur, T. Chimitdorzhiev, I. Kirbizhekova, Aleksey Dmitriev
Nowadays, global remote sensing studies of tropical forest parameters are relevant for assessing carbon sequestration, whereas boreal forests receive little attention. This is due to the current idea that forests with greater aboveground biomass absorb more carbon. However, new research indicates that rapidly growing young forests take up more carbon than mature ones. Therefore, it is necessary to develop universal methods of remote reforestation/afforestation monitoring. The existing reforestation methods rely on the separate analysis of multispectral optical images and radar data. Here, we propose a method for analyzing the joint dynamics of NDVI (or the Normalized Burn Ratio, NBR) and the radar vegetation index (RVI) on a 2D plot for a test reforestation site. NDVI and NBR time series were derived from Landsat-5,8 data, and the RVI was derived from ALOS-1,2 and PALSAR-1,2 for 2007–2020 using the resources of Google Earth Engine. The quantitative parameters to evaluate the degree of reforestation and changes in the species composition of young trees have been suggested. The suggested method enables a more thorough evaluation of reforestation by measuring the coupled dynamics of the projective cover of young trees and aboveground biomass.
{"title":"A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data","authors":"Valery Bondur, T. Chimitdorzhiev, I. Kirbizhekova, Aleksey Dmitriev","doi":"10.3390/f15010132","DOIUrl":"https://doi.org/10.3390/f15010132","url":null,"abstract":"Nowadays, global remote sensing studies of tropical forest parameters are relevant for assessing carbon sequestration, whereas boreal forests receive little attention. This is due to the current idea that forests with greater aboveground biomass absorb more carbon. However, new research indicates that rapidly growing young forests take up more carbon than mature ones. Therefore, it is necessary to develop universal methods of remote reforestation/afforestation monitoring. The existing reforestation methods rely on the separate analysis of multispectral optical images and radar data. Here, we propose a method for analyzing the joint dynamics of NDVI (or the Normalized Burn Ratio, NBR) and the radar vegetation index (RVI) on a 2D plot for a test reforestation site. NDVI and NBR time series were derived from Landsat-5,8 data, and the RVI was derived from ALOS-1,2 and PALSAR-1,2 for 2007–2020 using the resources of Google Earth Engine. The quantitative parameters to evaluate the degree of reforestation and changes in the species composition of young trees have been suggested. The suggested method enables a more thorough evaluation of reforestation by measuring the coupled dynamics of the projective cover of young trees and aboveground biomass.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"38 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139446217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Roszyk, Radosław Kropaczewski, P. Mania, M. Broda
Bamboo is a plant with various applications. As a natural, renewable material that exhibits good mechanical performance, it seems to be an interesting alternative to wood, which has become a scarce and expensive commodity. However, comprehensive knowledge of its properties is necessary to maximise its potential for various industrial purposes. The swelling behaviour of bamboo is one of the features that has not yet been sufficiently investigated. Therefore, in this research, we aimed to measure and analyse the swelling pressure and kinetics of bamboo blocks. The results show that similar to wood, the swelling kinetics of bamboo depend on its density: the denser the tissue, the higher the maximum swelling value recorded. The maximum tangential swelling measured was about 5%–6%, which is lower than the value for the most commonly used wood species. Swelling pressure ranged from 1.16 MPa to 1.39 MPa, depending on the bamboo density: the denser the sample, the shorter the time required to reach maximum swelling pressure. Like in wood, the smallest linear increase in size due to swelling was observed in the longitudinal direction (0.71%). However, opposite to wood, more pronounced swelling was recorded in the radial direction (over 7%) than in the tangential direction (nearly 6%). The results show that bamboo’s swelling behaviour makes it a good material for use in variable humidity conditions, being more favourable than the unmodified wood of many species.
{"title":"Swelling Behaviour of Bamboo (Phyllostachys pubescens)","authors":"E. Roszyk, Radosław Kropaczewski, P. Mania, M. Broda","doi":"10.3390/f15010118","DOIUrl":"https://doi.org/10.3390/f15010118","url":null,"abstract":"Bamboo is a plant with various applications. As a natural, renewable material that exhibits good mechanical performance, it seems to be an interesting alternative to wood, which has become a scarce and expensive commodity. However, comprehensive knowledge of its properties is necessary to maximise its potential for various industrial purposes. The swelling behaviour of bamboo is one of the features that has not yet been sufficiently investigated. Therefore, in this research, we aimed to measure and analyse the swelling pressure and kinetics of bamboo blocks. The results show that similar to wood, the swelling kinetics of bamboo depend on its density: the denser the tissue, the higher the maximum swelling value recorded. The maximum tangential swelling measured was about 5%–6%, which is lower than the value for the most commonly used wood species. Swelling pressure ranged from 1.16 MPa to 1.39 MPa, depending on the bamboo density: the denser the sample, the shorter the time required to reach maximum swelling pressure. Like in wood, the smallest linear increase in size due to swelling was observed in the longitudinal direction (0.71%). However, opposite to wood, more pronounced swelling was recorded in the radial direction (over 7%) than in the tangential direction (nearly 6%). The results show that bamboo’s swelling behaviour makes it a good material for use in variable humidity conditions, being more favourable than the unmodified wood of many species.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"33 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vaccinium corymbosum L., commonly known as blueberry, is a valuable small fruit tree in terms of its economic significance and is primarily found in China within the regions of Heilongjiang and Jilin provinces. Additionally, it thrives in the areas spanning the middle and lower reaches of the Yangtze River. Beyond their economic value, blueberries play a crucial role within forest ecosystems, serving as a significant energy source and source of nutrients. Their presence contributes significantly to fostering stability, enhancing biodiversity, and acting as an indicator of environmental quality within forest ecosystems. Since August 2022, an unknown leaf disease has been found on a large scale in blueberry fields in Nanjing, Jiangsu Province, China. The disease causes leaf curling, wilting, and even early defoliation, severely reducing the yield and production value of blueberries. The pathogenicity test confirmed the virulence of the isolates (NG5-1, NG5-2, NG5-3, NG5-4, N2-1, and N2-2) against V. corymbosum. The two pathogens were identified as Colletotrichum fructicola and C. aenigma by observing the morphological characteristics of the isolates and combined with multilocus phylogenetic analyses (ITS, CAL, ACT, TUB2, ApMat, and GAPDH). Blueberry anthracnose, caused by C. aenigma, is the first report of this disease in China. The biological characteristics of C. aenigma were investigated under different conditions, including temperature, pH, light conditions, culture medium, and carbon and nitrogen sources. The optimal temperature for growth was determined to be within the range of 25–30 °C; C. aenigma exhibits optimal growth at a pH of 7–8. Mycelial growth is favored under conditions of partial light, whereas complete darkness promotes spore production. It was found that PDA medium was the most favorable medium for C. aenigma mycelial growth, and MM medium was the best medium for spore production; the most suitable carbon sources for colony growth and spore production were sorbitol and glucose, respectively, and the most suitable nitrogen source was peptone. This study furnishes a theoretical foundation for a more scientifically informed approach to the prevention and control of anthracnose on V. corymbosum.
俗称蓝莓的越橘（Vaccinium corymbosum L.）是一种珍贵的小型果树，主要分布在中国的黑龙江省和吉林省。此外，它还生长在长江中下游地区。除经济价值外，蓝莓还在森林生态系统中发挥着至关重要的作用，是重要的能源和养分来源。蓝莓的存在对促进森林生态系统的稳定、提高生物多样性以及作为环境质量的指标做出了重要贡献。自 2022 年 8 月以来，在中国江苏省南京市的蓝莓田里大面积发现了一种未知的叶病。该病害导致蓝莓叶片卷曲、枯萎，甚至提前落叶，严重降低了蓝莓的产量和产值。致病性试验证实了分离物（NG5-1、NG5-2、NG5-3、NG5-4、N2-1 和 N2-2）对 V. corymbosum 的毒力。通过观察分离株的形态特征并结合多焦点系统发育分析（ITS、CAL、ACT、TUB2、ApMat 和 GAPDH），确定这两种病原菌分别为 Colletotrichum fructicola 和 C. aenigma。由 C. aenigma 引起的蓝莓炭疽病在中国尚属首次报道。研究了 C. aenigma 在温度、pH 值、光照条件、培养基、碳源和氮源等不同条件下的生物学特性。经测定，最适宜的生长温度为 25-30 °C；C. aenigma 在 pH 值为 7-8 时生长最理想。偏光条件下有利于菌丝生长，而完全黑暗则会促进孢子的产生。研究发现，PDA 培养基对 C. aenigma 菌丝生长最有利，而 MM 培养基则是孢子产生的最佳培养基；最适合菌落生长和孢子产生的碳源分别是山梨醇和葡萄糖，最适合的氮源是蛋白胨。这项研究为更科学地防治鸡矢藤炭疽病提供了理论依据。
{"title":"Identifying the Biological Characteristics of Anthracnose Pathogens of Blueberries (Vaccinium corymbosum L.) in China","authors":"Wei-Kun Feng, Chong-He Wang, Yun-Wei Ju, Zeng-Xin Chen, Xue Wu, Dong-Lu Fang","doi":"10.3390/f15010117","DOIUrl":"https://doi.org/10.3390/f15010117","url":null,"abstract":"Vaccinium corymbosum L., commonly known as blueberry, is a valuable small fruit tree in terms of its economic significance and is primarily found in China within the regions of Heilongjiang and Jilin provinces. Additionally, it thrives in the areas spanning the middle and lower reaches of the Yangtze River. Beyond their economic value, blueberries play a crucial role within forest ecosystems, serving as a significant energy source and source of nutrients. Their presence contributes significantly to fostering stability, enhancing biodiversity, and acting as an indicator of environmental quality within forest ecosystems. Since August 2022, an unknown leaf disease has been found on a large scale in blueberry fields in Nanjing, Jiangsu Province, China. The disease causes leaf curling, wilting, and even early defoliation, severely reducing the yield and production value of blueberries. The pathogenicity test confirmed the virulence of the isolates (NG5-1, NG5-2, NG5-3, NG5-4, N2-1, and N2-2) against V. corymbosum. The two pathogens were identified as Colletotrichum fructicola and C. aenigma by observing the morphological characteristics of the isolates and combined with multilocus phylogenetic analyses (ITS, CAL, ACT, TUB2, ApMat, and GAPDH). Blueberry anthracnose, caused by C. aenigma, is the first report of this disease in China. The biological characteristics of C. aenigma were investigated under different conditions, including temperature, pH, light conditions, culture medium, and carbon and nitrogen sources. The optimal temperature for growth was determined to be within the range of 25–30 °C; C. aenigma exhibits optimal growth at a pH of 7–8. Mycelial growth is favored under conditions of partial light, whereas complete darkness promotes spore production. It was found that PDA medium was the most favorable medium for C. aenigma mycelial growth, and MM medium was the best medium for spore production; the most suitable carbon sources for colony growth and spore production were sorbitol and glucose, respectively, and the most suitable nitrogen source was peptone. This study furnishes a theoretical foundation for a more scientifically informed approach to the prevention and control of anthracnose on V. corymbosum.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"16 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dachuan Dai, Hongling Hu, Jing Wen, Hong Chen, Gang Chen, Xinglei Cui
Cadmium (Cd) is one of the most common toxic heavy metal elements in soil pollution, which can be continuously enriched in the food chain and eventually threaten human health. Phytoremediation, which is using plants to transfer heavy metal elements from soils, is a promising solution for the remediation of heavy metal-contaminated soils. In this study, we evaluated whether Cunninghamia lanceolata (Lambert) Hooker (Chinese fir), a widely planted timber tree worldwide, had the potential to remediate Cd-contaminated soils through 90 days pot of experiments with different Cd concentration soils (0, 5, 10, 20, 50, 100 mg kg−1). C. lanceolata did not show obvious toxic symptoms in Cd-contaminated soils, although Cd inhibited plant growth and decreased net photosynthetic rate slightly. The activities of antioxidant enzymes increased significantly under Cd stress, indicating that C. lanceolata had a strong self-regulation ability and can tolerate Cd stress. The Cd bioconcentration factor (Cd concentration in plant divided by Cd concentration in soil) of C. lanceolata were greater than 1 at all Cd concentrations, indicating that C. lanceolata had a strong ability to absorb Cd, although Cd was mainly accumulated in roots. Our results indicated that C. lanceolata had a strong tolerance and phytostabilization ability of Cd. Considering the wide distribution worldwide, large biomass, and rapid growth of C. lanceolata, it could be a promising candidate for phytoremediation of Cd-contaminated soils.
{"title":"Cunninghamia lanceolata (Lambert) Hooker: A Promising Candidate for Phytoremediation of Cd-Contaminated Soils","authors":"Dachuan Dai, Hongling Hu, Jing Wen, Hong Chen, Gang Chen, Xinglei Cui","doi":"10.3390/f15010115","DOIUrl":"https://doi.org/10.3390/f15010115","url":null,"abstract":"Cadmium (Cd) is one of the most common toxic heavy metal elements in soil pollution, which can be continuously enriched in the food chain and eventually threaten human health. Phytoremediation, which is using plants to transfer heavy metal elements from soils, is a promising solution for the remediation of heavy metal-contaminated soils. In this study, we evaluated whether Cunninghamia lanceolata (Lambert) Hooker (Chinese fir), a widely planted timber tree worldwide, had the potential to remediate Cd-contaminated soils through 90 days pot of experiments with different Cd concentration soils (0, 5, 10, 20, 50, 100 mg kg−1). C. lanceolata did not show obvious toxic symptoms in Cd-contaminated soils, although Cd inhibited plant growth and decreased net photosynthetic rate slightly. The activities of antioxidant enzymes increased significantly under Cd stress, indicating that C. lanceolata had a strong self-regulation ability and can tolerate Cd stress. The Cd bioconcentration factor (Cd concentration in plant divided by Cd concentration in soil) of C. lanceolata were greater than 1 at all Cd concentrations, indicating that C. lanceolata had a strong ability to absorb Cd, although Cd was mainly accumulated in roots. Our results indicated that C. lanceolata had a strong tolerance and phytostabilization ability of Cd. Considering the wide distribution worldwide, large biomass, and rapid growth of C. lanceolata, it could be a promising candidate for phytoremediation of Cd-contaminated soils.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"10 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingjing Kong, Mei Zan, Zhizhong Chen, Cong Xue, Shunfa Yang
Ecosystem water use efficiency (WUE) is an important measure of the degree of water–hydrogen coupling and an important indicator for assessing ecosystem responses to climate change. Drought adversely affects ecosystem security, particularly in irrigated agricultural areas; therefore, understanding the relationship between WUE and drought is important. This study revealed the spatial and temporal characteristics of drought in the Manas River Basin, Xinjiang, China, from 2001 to 2020 through multi-source data using standardised anomaly indices and mutation detection. It also quantitatively analysed the hysteresis effect and resilience characteristics of drought for different vegetation types in the study area. The results showed that droughts at a severe level occurred less frequently in most of the study area on average from 2001 to 2020, and that droughts in the vegetation growing season occurred more frequently, particularly in grasslands; the frequency of droughts in woodlands was low. Furthermore, the lag in WUE to drought occurred on a 3-month scale and accounted for 64.0% of the total watershed area. Finally, 38.16% of the regional vegetation ecosystems in the Manas River Basin exhibited drought resistance. In conclusion, our results provide novel insights into the water-use strategies of plants in the study area and will help facilitate WUE optimisation.
{"title":"Study on the Response of Vegetation Water Use Efficiency to Drought in the Manas River Basin, Xinjiang, China","authors":"Jingjing Kong, Mei Zan, Zhizhong Chen, Cong Xue, Shunfa Yang","doi":"10.3390/f15010114","DOIUrl":"https://doi.org/10.3390/f15010114","url":null,"abstract":"Ecosystem water use efficiency (WUE) is an important measure of the degree of water–hydrogen coupling and an important indicator for assessing ecosystem responses to climate change. Drought adversely affects ecosystem security, particularly in irrigated agricultural areas; therefore, understanding the relationship between WUE and drought is important. This study revealed the spatial and temporal characteristics of drought in the Manas River Basin, Xinjiang, China, from 2001 to 2020 through multi-source data using standardised anomaly indices and mutation detection. It also quantitatively analysed the hysteresis effect and resilience characteristics of drought for different vegetation types in the study area. The results showed that droughts at a severe level occurred less frequently in most of the study area on average from 2001 to 2020, and that droughts in the vegetation growing season occurred more frequently, particularly in grasslands; the frequency of droughts in woodlands was low. Furthermore, the lag in WUE to drought occurred on a 3-month scale and accounted for 64.0% of the total watershed area. Finally, 38.16% of the regional vegetation ecosystems in the Manas River Basin exhibited drought resistance. In conclusion, our results provide novel insights into the water-use strategies of plants in the study area and will help facilitate WUE optimisation.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"25 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tree species transitioning between different developmental phases requires homeostatic adjustments in order to maintain the integrity of the tree hydraulic system. Hence, adjustments related to hydraulic traits (e.g., xylem conduit diameter) are of key functional significance. However, critical information on the differences between different developmental stages is rare. Using sapwood samples from 36 black locust trees with different growth stages (actively growing and declining stages) and a soil water gradient along a hillslope, xylem conduits at stem apexes and breast height (1.3 m above ground) stems were measured. The results showed marked differences in vascular traits between actively growing and declining trees. In contrast to actively growing trees, declining trees exhibited a reduction in conduit diameters accompanied by increased frequency with a positively skewed distribution and a subsequent decline in cumulative theoretical hydraulic conductivity. Across all sampled trees, the hydraulically weighted mean conduit diameter tapered acropetally from breast height to the stem apex. The extent of conduit tapering in actively growing trees (0.244, 95% CI 0.201–0.287) aligned with predictions from the hydraulic optimality model. Conversely, trees in a declining status displayed significantly reduced conduit tapering (0.175, 95% CI 0.146–0.198), indicating an elevation in hydraulic resistance with increasing tree height. Variations in hydraulic properties predominantly resulted from differences in tree height rather than variations in stem diameter or soil water content. The correlation between conduit diameter and soil water content in both actively growing and declining trees stemmed indirectly from variations in tree height rather than presenting a direct response to drought stress.
在不同发育阶段之间过渡的树种需要进行平衡调节，以保持树木水力系统的完整性。因此，与水力特征（如木质部导管直径）相关的调整具有重要的功能意义。然而，有关不同发育阶段之间差异的关键信息却很少见。利用 36 棵不同生长阶段（旺盛生长期和衰退期）的黑刺槐树的边材样本和山坡上的土壤水分梯度，测量了茎顶和胸高（离地面 1.3 米）茎的木质部导管。结果表明，生长旺盛期和衰退期树木的维管束特征存在明显差异。与生长旺盛的树木相反，衰退期树木的导管直径减小，频率增加，分布呈正偏斜，累积理论水导率随之下降。在所有采样树木中，水力加权平均导管直径从胸高到茎顶逐渐向下变细。生长旺盛的树木导管变细的程度（0.244，95% CI 0.201-0.287）与水力优化模型的预测一致。相反，处于衰退期的树木的导管锥度明显减小（0.175，95% CI 0.146-0.198），这表明随着树高的增加，水力阻力也在增加。水力特性的变化主要源于树高的不同，而不是茎干直径或土壤含水量的变化。无论是生长旺盛的树木还是衰退的树木，其导管直径与土壤含水量之间的相关性都间接源于树高的变化，而不是对干旱压力的直接反应。
{"title":"Comparison of Xylem Anatomy and Hydraulic Properties in Black Locust Trees at Two Growth Stages in Semiarid China","authors":"Changkun Ma, Xi Zhang, Qian Yao, Beibei Zhou, Q. Wang, Mingan Shao","doi":"10.3390/f15010116","DOIUrl":"https://doi.org/10.3390/f15010116","url":null,"abstract":"Tree species transitioning between different developmental phases requires homeostatic adjustments in order to maintain the integrity of the tree hydraulic system. Hence, adjustments related to hydraulic traits (e.g., xylem conduit diameter) are of key functional significance. However, critical information on the differences between different developmental stages is rare. Using sapwood samples from 36 black locust trees with different growth stages (actively growing and declining stages) and a soil water gradient along a hillslope, xylem conduits at stem apexes and breast height (1.3 m above ground) stems were measured. The results showed marked differences in vascular traits between actively growing and declining trees. In contrast to actively growing trees, declining trees exhibited a reduction in conduit diameters accompanied by increased frequency with a positively skewed distribution and a subsequent decline in cumulative theoretical hydraulic conductivity. Across all sampled trees, the hydraulically weighted mean conduit diameter tapered acropetally from breast height to the stem apex. The extent of conduit tapering in actively growing trees (0.244, 95% CI 0.201–0.287) aligned with predictions from the hydraulic optimality model. Conversely, trees in a declining status displayed significantly reduced conduit tapering (0.175, 95% CI 0.146–0.198), indicating an elevation in hydraulic resistance with increasing tree height. Variations in hydraulic properties predominantly resulted from differences in tree height rather than variations in stem diameter or soil water content. The correlation between conduit diameter and soil water content in both actively growing and declining trees stemmed indirectly from variations in tree height rather than presenting a direct response to drought stress.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"3 7","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Quantifying the emotional impact of street greening during the full-leaf seasons in spring, summer, and fall is important for well-being-focused urban construction. Current emotional perception models usually focus on the influence of objects identified through semantic segmentation of street view images and lack explanation. Therefore, interpretability models that quantify street greening’s emotional effects are needed. This study aims to measure and explain the influence of street greening on emotions to help urban planners make decisions. This would improve the living environment, foster positive emotions, and help residents recover from negative emotions. In Hangzhou, China, we used the Baidu Map API to obtain street view images when plants were in the full-leaf state. Semantic segmentation was used to separate plant parts from street view images, enabling the calculation of the Green View Index, Plant Level Diversity, Plant Color Richness, and Tree–Sky View Factor. We created a dataset specifically designed for the purpose of emotional perception, including four distinct categories: pleasure, relaxation, boredom, and anxiety. This dataset was generated through a combination of machine learning algorithms and human evaluation. Scores range from 1 to 5, with higher values indicating stronger emotions and lower values indicating less intense ones. The random forest model and Shapley Additive Explanation (SHAP) algorithm were employed to identify the key indicators that affect emotions. Emotions were most affected by the Plant Level Diversity and Green View Index. These indicators and emotions have an intricate non-linear relationship. Specifically, a higher Green View Index (often indicating the presence of 20–35 fully grown trees within a 200 m range in street view images) and a greater Plant Level Diversity significantly promoted positive emotional responses. Our study provided local planning departments with support for well-being-focused urban planning and renewal decisions. Based on our research, we recommend the following actions: (1) increase the amount of visible green in areas with a low Green View Index; (2) plant seasonal and flowering plants like camellia, ginkgo, and goldenrain trees to enhance the diversity and colors; (3) trim plants in areas with low safety perception to improve visibility; (4) introduce evergreen plants like cinnamomum camphor, osmanthus, and pine.
{"title":"Quantifying the Impact of Street Greening during Full-Leaf Seasons on Emotional Perception: Guidelines for Resident Well-Being","authors":"Nayi Hao, Xinzhou Li, Danping Han, Wenbin Nie","doi":"10.3390/f15010119","DOIUrl":"https://doi.org/10.3390/f15010119","url":null,"abstract":"Quantifying the emotional impact of street greening during the full-leaf seasons in spring, summer, and fall is important for well-being-focused urban construction. Current emotional perception models usually focus on the influence of objects identified through semantic segmentation of street view images and lack explanation. Therefore, interpretability models that quantify street greening’s emotional effects are needed. This study aims to measure and explain the influence of street greening on emotions to help urban planners make decisions. This would improve the living environment, foster positive emotions, and help residents recover from negative emotions. In Hangzhou, China, we used the Baidu Map API to obtain street view images when plants were in the full-leaf state. Semantic segmentation was used to separate plant parts from street view images, enabling the calculation of the Green View Index, Plant Level Diversity, Plant Color Richness, and Tree–Sky View Factor. We created a dataset specifically designed for the purpose of emotional perception, including four distinct categories: pleasure, relaxation, boredom, and anxiety. This dataset was generated through a combination of machine learning algorithms and human evaluation. Scores range from 1 to 5, with higher values indicating stronger emotions and lower values indicating less intense ones. The random forest model and Shapley Additive Explanation (SHAP) algorithm were employed to identify the key indicators that affect emotions. Emotions were most affected by the Plant Level Diversity and Green View Index. These indicators and emotions have an intricate non-linear relationship. Specifically, a higher Green View Index (often indicating the presence of 20–35 fully grown trees within a 200 m range in street view images) and a greater Plant Level Diversity significantly promoted positive emotional responses. Our study provided local planning departments with support for well-being-focused urban planning and renewal decisions. Based on our research, we recommend the following actions: (1) increase the amount of visible green in areas with a low Green View Index; (2) plant seasonal and flowering plants like camellia, ginkgo, and goldenrain trees to enhance the diversity and colors; (3) trim plants in areas with low safety perception to improve visibility; (4) introduce evergreen plants like cinnamomum camphor, osmanthus, and pine.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"65 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Francisco García-Saucedo, F. A. García-Morote, Marta Picazo, C. Wic, Eva Rubio, F. López-Serrano, M. Andrés‐Abellán
This research analyzes how enzymatic and microbiological soil properties relate to site index (SI) and forest maturity (stand age) in Pinus nigra (P. nigra) even-aged forests. The soil parameters selected for multivariate analysis were four enzymatic activities (β-glucosidase, urease, dehydrogenase, and alkaline phosphatase), two microbiological properties (microbial biomass C and basal respiration), and five physicochemical parameters (TOC, N, P, pH, and soil water content). We used LiDAR, the digital elevation model, and the terrain model to obtain a result for the dominant height in each plot. The soil parameters were analyzed in the function of five site index classes (8, 11, 14, 17, and 20) and six age classes (50, 70, 90, 110, 170, and 210 years). Our findings emphasize that the dehydrogenase enzyme exhibited variations in response to both the site index and stand age. The activity of dehydrogenase positively correlated with sites characterized by a higher nutrient demand, particularly on young and poor-quality sites (lower SI), indicating activation. Therefore, dehydrogenase could serve as an index to elucidate both site quality and stand development in P. nigra stands, making it a potential indicator of forest ecosystem development.
{"title":"Responses of Enzymatic and Microbiological Soil Properties to the Site Index and Age Gradients in Spanish Black Pine (Pinus nigra Arn ssp. salzmannii) Mediterranean Forests","authors":"Francisco García-Saucedo, F. A. García-Morote, Marta Picazo, C. Wic, Eva Rubio, F. López-Serrano, M. Andrés‐Abellán","doi":"10.3390/f15010113","DOIUrl":"https://doi.org/10.3390/f15010113","url":null,"abstract":"This research analyzes how enzymatic and microbiological soil properties relate to site index (SI) and forest maturity (stand age) in Pinus nigra (P. nigra) even-aged forests. The soil parameters selected for multivariate analysis were four enzymatic activities (β-glucosidase, urease, dehydrogenase, and alkaline phosphatase), two microbiological properties (microbial biomass C and basal respiration), and five physicochemical parameters (TOC, N, P, pH, and soil water content). We used LiDAR, the digital elevation model, and the terrain model to obtain a result for the dominant height in each plot. The soil parameters were analyzed in the function of five site index classes (8, 11, 14, 17, and 20) and six age classes (50, 70, 90, 110, 170, and 210 years). Our findings emphasize that the dehydrogenase enzyme exhibited variations in response to both the site index and stand age. The activity of dehydrogenase positively correlated with sites characterized by a higher nutrient demand, particularly on young and poor-quality sites (lower SI), indicating activation. Therefore, dehydrogenase could serve as an index to elucidate both site quality and stand development in P. nigra stands, making it a potential indicator of forest ecosystem development.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"51 22","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingxu Wang, Qinan Lin, Shengwang Meng, Huaguo Huang, Yangyang Liu
The infestation of pine shoot beetles (Tomicus spp.) in the forests of Southwestern China has inflicted serious ecological damages to the environment, causing significant economic losses. Therefore, accurate and practical approaches to detect pest infestation have become an urgent necessity to mitigate these harmful consequences. In this study, we explored the efficiency of thermal infrared (TIR) technology in capturing changes in canopy surface temperature (CST) and monitoring forest health at the scale of individual tree crowns. We combined data collected from TIR imagery and light detection and ranging (LiDAR) using unmanned airborne vehicles (UAVs) to estimate the shoot damage ratio (SDR), which is a representative parameter of the damage degree caused by forest infestation. We compared multiple machine learning methods for data analysis, including random forest (RF), partial least squares regression (PLSR), and support vector machine (SVM), to determine the optimal regression model for assessing SDR at the crown scale. Our findings showed that a combination of LiDAR metrics and CST presents the highest accuracy in estimating SDR using the RF model (R2 = 0.7914, RMSE = 15.5685). Our method enables the accurate remote monitoring of forest health and is expected to provide a novel approach for controlling pest infestation, minimizing the associated damages caused.
{"title":"Individual Tree-Level Monitoring of Pest Infestation Combining Airborne Thermal Imagery and Light Detection and Ranging","authors":"Jingxu Wang, Qinan Lin, Shengwang Meng, Huaguo Huang, Yangyang Liu","doi":"10.3390/f15010112","DOIUrl":"https://doi.org/10.3390/f15010112","url":null,"abstract":"The infestation of pine shoot beetles (Tomicus spp.) in the forests of Southwestern China has inflicted serious ecological damages to the environment, causing significant economic losses. Therefore, accurate and practical approaches to detect pest infestation have become an urgent necessity to mitigate these harmful consequences. In this study, we explored the efficiency of thermal infrared (TIR) technology in capturing changes in canopy surface temperature (CST) and monitoring forest health at the scale of individual tree crowns. We combined data collected from TIR imagery and light detection and ranging (LiDAR) using unmanned airborne vehicles (UAVs) to estimate the shoot damage ratio (SDR), which is a representative parameter of the damage degree caused by forest infestation. We compared multiple machine learning methods for data analysis, including random forest (RF), partial least squares regression (PLSR), and support vector machine (SVM), to determine the optimal regression model for assessing SDR at the crown scale. Our findings showed that a combination of LiDAR metrics and CST presents the highest accuracy in estimating SDR using the RF model (R2 = 0.7914, RMSE = 15.5685). Our method enables the accurate remote monitoring of forest health and is expected to provide a novel approach for controlling pest infestation, minimizing the associated damages caused.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"48 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Controlling and extinguishing spreading forest fires is a challenging task that often leads to irreversible losses. Moreover, large-scale forest fires generate smoke and dust, causing environmental pollution and posing potential threats to human life. In this study, we introduce a modified deep convolutional neural network model (MDCNN) designed for the recognition and localization of fire in video imagery, employing a deep learning-based recognition approach. We apply transfer learning to refine the model and adapt it for the specific task of fire image recognition. To combat the issue of imprecise detection of flame characteristics, which are prone to misidentification, we integrate a deep CNN with an original feature fusion algorithm. We compile a diverse set of fire and non-fire scenarios to construct a training dataset of flame images, which is then employed to calibrate the model for enhanced flame detection accuracy. The proposed MDCNN model demonstrates a low false alarm rate of 0.563%, a false positive rate of 12.7%, a false negative rate of 5.3%, and a recall rate of 95.4%, and achieves an overall accuracy of 95.8%. The experimental results demonstrate that this method significantly improves the accuracy of flame recognition. The achieved recognition results indicate the model’s strong generalization ability.
{"title":"A Forest Fire Recognition Method Based on Modified Deep CNN Model","authors":"Shaoxiong Zheng, Xiangjun Zou, Peng Gao, Qin Zhang, Fei Hu, Yufei Zhou, Zepeng Wu, Weixing Wang, Shihong Chen","doi":"10.3390/f15010111","DOIUrl":"https://doi.org/10.3390/f15010111","url":null,"abstract":"Controlling and extinguishing spreading forest fires is a challenging task that often leads to irreversible losses. Moreover, large-scale forest fires generate smoke and dust, causing environmental pollution and posing potential threats to human life. In this study, we introduce a modified deep convolutional neural network model (MDCNN) designed for the recognition and localization of fire in video imagery, employing a deep learning-based recognition approach. We apply transfer learning to refine the model and adapt it for the specific task of fire image recognition. To combat the issue of imprecise detection of flame characteristics, which are prone to misidentification, we integrate a deep CNN with an original feature fusion algorithm. We compile a diverse set of fire and non-fire scenarios to construct a training dataset of flame images, which is then employed to calibrate the model for enhanced flame detection accuracy. The proposed MDCNN model demonstrates a low false alarm rate of 0.563%, a false positive rate of 12.7%, a false negative rate of 5.3%, and a recall rate of 95.4%, and achieves an overall accuracy of 95.8%. The experimental results demonstrate that this method significantly improves the accuracy of flame recognition. The achieved recognition results indicate the model’s strong generalization ability.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"66 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139450065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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