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}
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}
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}
Wenfang Li, Hui Xu, Yong Wu, Xiaoli Zhang, Chunxiao Liu, Chi Lu, Zhibo Yu, Guanglong Ou
Using various biomass factors, such as biomass expansion factor (BEF) and biomass conversion and expansion factor (BCEF), yields different results for estimating forest biomass. Therefore, ensuring compatibility between total biomass and its components when employing different biomass factors is crucial for developing a set of rapid and efficient models for large-scale biomass calculation. In this study, allometric equations were utilized to construct independent models and the proportional values (root-to-shoot ratio (Rra), crown-to-stem ratio (Rcs), bark-to-wood ratio (Rbw), foliage-to-bark ratio (Rfb), and wood biomass-to-wood volume (ρ)) by using the mean height (Hm) and the mean diameter at breast height (Dg) of 98 Pinus densata plots in Shangri-La, Yunnan province, China. The compatible methods were applied to reveal the compatibility between the total biomass and each component’s biomass. The results showed the following: (1) Both the independent model and compatible model had a higher accuracy. The values were greater than 0.7 overall, but the foliage biomass accuracy was only 0.2. The total biomass and the component biomass showed compatibility. (2) The accuracy of BEF and BCEF exceeded 0.87 and the total error was less than 0.1 for most components. (3) The mean BEF (1.6) was greater than that of the Intergovernmental Panel on Climate Change (IPCC) (M = 1.3), and the mean BCEF was smaller than that of the IPCC; the values were 0.6 and 0.7, respectively. The range of BEF (1.4–2.1) and BCEF (0.44–0.89) were all within the range of the IPCC (1.15–3.2, 0.4–1.0). This study provides a more convenient and accurate method for calculating conversion coefficients (BEF and BCEF), especially when only Rcs data is available.
{"title":"A Compatible Estimation Method for Biomass Factors Based on Allometric Relationship: A Case Study on Pinus densata Natural Forest in Yunnan Province of Southwest China","authors":"Wenfang Li, Hui Xu, Yong Wu, Xiaoli Zhang, Chunxiao Liu, Chi Lu, Zhibo Yu, Guanglong Ou","doi":"10.3390/f15010026","DOIUrl":"https://doi.org/10.3390/f15010026","url":null,"abstract":"Using various biomass factors, such as biomass expansion factor (BEF) and biomass conversion and expansion factor (BCEF), yields different results for estimating forest biomass. Therefore, ensuring compatibility between total biomass and its components when employing different biomass factors is crucial for developing a set of rapid and efficient models for large-scale biomass calculation. In this study, allometric equations were utilized to construct independent models and the proportional values (root-to-shoot ratio (Rra), crown-to-stem ratio (Rcs), bark-to-wood ratio (Rbw), foliage-to-bark ratio (Rfb), and wood biomass-to-wood volume (ρ)) by using the mean height (Hm) and the mean diameter at breast height (Dg) of 98 Pinus densata plots in Shangri-La, Yunnan province, China. The compatible methods were applied to reveal the compatibility between the total biomass and each component’s biomass. The results showed the following: (1) Both the independent model and compatible model had a higher accuracy. The values were greater than 0.7 overall, but the foliage biomass accuracy was only 0.2. The total biomass and the component biomass showed compatibility. (2) The accuracy of BEF and BCEF exceeded 0.87 and the total error was less than 0.1 for most components. (3) The mean BEF (1.6) was greater than that of the Intergovernmental Panel on Climate Change (IPCC) (M = 1.3), and the mean BCEF was smaller than that of the IPCC; the values were 0.6 and 0.7, respectively. The range of BEF (1.4–2.1) and BCEF (0.44–0.89) were all within the range of the IPCC (1.15–3.2, 0.4–1.0). This study provides a more convenient and accurate method for calculating conversion coefficients (BEF and BCEF), especially when only Rcs data is available.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"8 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944905","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}
Michael S. Watt, Dilshana De Silva, H. Estarija, Warren Yorston, P. Massam
Despite the utility of thermal imagery for characterising the impacts of water stress on plant physiology, few studies have been undertaken on plantation-grown conifers, including the most widely planted exotic species, radiata pine. Using data collected from a pot trial, where water was withheld from radiata pine over a nine-day period, the objectives of this study were to (i) determine how rapidly key physiological traits change in response to water stress and (ii) assess the utility of normalised canopy temperature, defined as canopy temperature–air temperature (Tc–Ta), for detecting these physiological changes. Volumetric water content remained high in the well-watered control treatment over the course of the experiment (0.47–0.48 m3 m−3) but declined rapidly in the water stress treatment from 0.47 m3 m−3 at 0 days after treatment (DAT) to 0.04 m3 m−3 at 9 DAT. There were no significant treatment differences in measurements taken at 0 DAT for Tc–Ta, stomatal conductance (gs), transpiration rate (E) or assimilation rate (A). However, by 1 DAT, differences between treatments in tree physiological traits were highly significant, and these differences continued diverging with values in the control treatment exceeding those of trees in the water stress treatment at 9 DAT by 42, 43 and 61%, respectively, for gs, E and A. The relationships between Tc–Ta and the three physiological traits were not significant at 0 DAT, but all three relationships were highly significant from as early as 1 DAT onwards. The strength of the relationships between Tc–Ta and the three physiological traits increased markedly over the duration of the water stress treatment, reaching a maximum coefficient of determination (R2) at 7 DAT when values were, respectively, 0.87, 0.86 and 0.67 for gs, E and A. The early detection of changes in tree physiology from 1 DAT onwards suggests that thermal imagery may be useful for a range of applications in field-grown radiata pine.
尽管热图像可用于描述水分胁迫对植物生理的影响，但针对种植园栽培的针叶树（包括种植最广泛的外来物种辐射松）的研究却很少。本研究利用从盆栽试验中收集到的数据，在为期九天的时间内不给辐射松浇水，其目的是：(i) 确定关键生理特征在应对水分胁迫时的变化速度；(ii) 评估归一化冠层温度（定义为冠层温度-空气温度 (Tc-Ta)）在检测这些生理变化方面的效用。在实验过程中，水分充足的对照处理的体积含水量仍然很高（0.47-0.48 立方米/立方米），但在水分胁迫处理中，体积含水量迅速下降，从处理后 0 天（DAT）的 0.47 立方米/立方米降至处理后 9 天（DAT）的 0.04 立方米/立方米。在 0 DAT 时测量的 Tc-Ta、气孔导度（gs）、蒸腾速率（E）或同化速率（A）没有明显的处理差异。然而，到 1 日龄时，各处理之间的树木生理性状差异非常显著，而且这些差异还在继续扩大，到 9 日龄时，对照处理的 gs、E 和 A 值分别比水胁迫处理的树木值高出 42%、43% 和 61%。随着水分胁迫处理持续时间的延长，Tc-Ta 与三种生理性状之间的关系强度明显增加，在 7 DAT 时达到最大决定系数 (R2)，此时 gs、E 和 A 的值分别为 0.87、0.86 和 0.67。
{"title":"Detecting the Short-Term Effects of Water Stress on Radiata Pine Physiology Using Thermal Imagery","authors":"Michael S. Watt, Dilshana De Silva, H. Estarija, Warren Yorston, P. Massam","doi":"10.3390/f15010028","DOIUrl":"https://doi.org/10.3390/f15010028","url":null,"abstract":"Despite the utility of thermal imagery for characterising the impacts of water stress on plant physiology, few studies have been undertaken on plantation-grown conifers, including the most widely planted exotic species, radiata pine. Using data collected from a pot trial, where water was withheld from radiata pine over a nine-day period, the objectives of this study were to (i) determine how rapidly key physiological traits change in response to water stress and (ii) assess the utility of normalised canopy temperature, defined as canopy temperature–air temperature (Tc–Ta), for detecting these physiological changes. Volumetric water content remained high in the well-watered control treatment over the course of the experiment (0.47–0.48 m3 m−3) but declined rapidly in the water stress treatment from 0.47 m3 m−3 at 0 days after treatment (DAT) to 0.04 m3 m−3 at 9 DAT. There were no significant treatment differences in measurements taken at 0 DAT for Tc–Ta, stomatal conductance (gs), transpiration rate (E) or assimilation rate (A). However, by 1 DAT, differences between treatments in tree physiological traits were highly significant, and these differences continued diverging with values in the control treatment exceeding those of trees in the water stress treatment at 9 DAT by 42, 43 and 61%, respectively, for gs, E and A. The relationships between Tc–Ta and the three physiological traits were not significant at 0 DAT, but all three relationships were highly significant from as early as 1 DAT onwards. The strength of the relationships between Tc–Ta and the three physiological traits increased markedly over the duration of the water stress treatment, reaching a maximum coefficient of determination (R2) at 7 DAT when values were, respectively, 0.87, 0.86 and 0.67 for gs, E and A. The early detection of changes in tree physiology from 1 DAT onwards suggests that thermal imagery may be useful for a range of applications in field-grown radiata pine.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"22 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947448","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}
Small scattered plots of a few hundred square meters well reflect structural variability at stand level, but not at small spatial scales as the data between plots is missing. Information about structural similarities between managed and unmanaged stands, especially based on large sample plots, is still scarce. Our first objective was to quantify and illustrate structural variability of a selection-managed stand and a corresponding old-growth (OG) stand at small spatial scales. The second goal was to find out if there is a positive autocorrelation among neighboring patches in these stands regarding tree density (N) and basal area (BA). Tree positions and their diameters were recorded in 1.5 ha plots. Structural variation was examined at scales from 0.01 ha to 0.36 ha. Spatial correlation of N and BA was examined by applying experimental semivariograms. The variability of N was similar in both stands, whereas it significantly differed regarding BA (α = 0.05). Semivariance did not detect positive spatial autocorrelation of BA, while adjacent plots appeared to be more similar (autocorrelated) regarding N in both stands. Despite statistical difference regarding BA variability, the selection-managed stand exhibited many structural similarities to the OG stand, which makes it potentially suitable for modulating, if needed, to bring it step closer to an old-growth structure.
几百平方米的零星小块能很好地反映林分层面的结构变化，但由于缺少小块之间的数据，因此不能反映小空间尺度上的结构变化。关于有管理和无管理林分之间结构相似性的信息，尤其是基于大样地的信息，仍然非常稀缺。我们的第一个目标是在小空间尺度上量化和说明选择管理林分和相应的老林地（OG）的结构变异性。第二个目标是找出这些林分中相邻斑块之间在树木密度（N）和基部面积（BA）方面是否存在正的自相关性。在 1.5 公顷的地块上记录了树木的位置和直径。在 0.01 公顷到 0.36 公顷的范围内对结构变化进行了研究。应用实验半变量图检验了 N 和 BA 的空间相关性。氮的变异在两个林分中相似，而在 BA 方面则有显著差异（α = 0.05）。半方差没有检测到 BA 的正空间自相关性，而在两个林分中，相邻地块的氮似乎更相似（自相关）。尽管在 BA 变异性方面存在统计差异，但选择管理的林分在结构上与 OG 林分有许多相似之处，这使其可能适合在必要时进行调节，使其更接近于老生林分结构。
{"title":"Fine-Scale Spatial Variability of Stand Structural Features under Selection Management and Strict Protection: An Example from the Dinaric Mountains","authors":"Srdjan Keren, Wojciech Ochał, V. Dukić","doi":"10.3390/f15010032","DOIUrl":"https://doi.org/10.3390/f15010032","url":null,"abstract":"Small scattered plots of a few hundred square meters well reflect structural variability at stand level, but not at small spatial scales as the data between plots is missing. Information about structural similarities between managed and unmanaged stands, especially based on large sample plots, is still scarce. Our first objective was to quantify and illustrate structural variability of a selection-managed stand and a corresponding old-growth (OG) stand at small spatial scales. The second goal was to find out if there is a positive autocorrelation among neighboring patches in these stands regarding tree density (N) and basal area (BA). Tree positions and their diameters were recorded in 1.5 ha plots. Structural variation was examined at scales from 0.01 ha to 0.36 ha. Spatial correlation of N and BA was examined by applying experimental semivariograms. The variability of N was similar in both stands, whereas it significantly differed regarding BA (α = 0.05). Semivariance did not detect positive spatial autocorrelation of BA, while adjacent plots appeared to be more similar (autocorrelated) regarding N in both stands. Despite statistical difference regarding BA variability, the selection-managed stand exhibited many structural similarities to the OG stand, which makes it potentially suitable for modulating, if needed, to bring it step closer to an old-growth structure.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"10 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947759","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}
In this study, carbon and nitrogen contents in the undisturbed terrestrial ecosystems in the northern taiga zone of Russia’s Murmansk region were estimated. The goal of this study was to examine the carbon and nitrogen dynamics in atmospheric precipitation, assimilating organs of coniferous trees (Picea obovata and Pinus sylvestris), needle litter, soils, and soil water. The objects of our research were the most common dwarf shrub-green moss spruce forests and lichen-dwarf shrub pine forests of the boreal zone. The study was carried out on permanent plots between 1999 and 2020. The long-term dynamics of carbon concentrations in snow demonstrated a trend towards increasing carbon concentrations in forested and treeless areas of the Murmansk region. It was shown that in representative spruce and pine forests, the concentrations and atmospheric precipitation of carbon compounds and carbon leaching with soil water were higher below the tree crowns, compared to between the crowns. In soil water, a decrease was found in carbon concentration with the soil profile depth. For soils, the highest carbon concentrations were found in the organic and illuvial soil horizons. The main soil sinks of carbon and nitrogen in northern taiga forests were found to be located in the organic soil horizon below the crowns. In northern taiga forests, the carbon content of living Picea obovata and Pinus sylvestris needles and Pinus sylvestris needle litter had minor variability; no significant interbiogeocoenotic and age differences were found. We found that the nitrogen content in brown needles and needle litter was significantly lower compared to photosynthetically active needles, probably due to retranslocation processes (withdrawal before needle abscission), corroborating the literature in the results session. The largest stocks of carbon and nitrogen in northern taiga forests are concentrated in the soil organic horizon, and the removal of these elements with soil water is insignificant. Carbon and nitrogen stocks in living and fallen needles are lower than in soil. The least amount of carbon and nitrogen is contained in atmospheric precipitation.
{"title":"Estimation of Carbon and Nitrogen Contents in Forest Ecosystems in the Background Areas of the Russian Arctic (Murmansk Region)","authors":"Vyacheslav Ershov, Tatyana Sukhareva, Nickolay Ryabov, Ekaterina Ivanova, Irina Shtabrovskaya","doi":"10.3390/f15010029","DOIUrl":"https://doi.org/10.3390/f15010029","url":null,"abstract":"In this study, carbon and nitrogen contents in the undisturbed terrestrial ecosystems in the northern taiga zone of Russia’s Murmansk region were estimated. The goal of this study was to examine the carbon and nitrogen dynamics in atmospheric precipitation, assimilating organs of coniferous trees (Picea obovata and Pinus sylvestris), needle litter, soils, and soil water. The objects of our research were the most common dwarf shrub-green moss spruce forests and lichen-dwarf shrub pine forests of the boreal zone. The study was carried out on permanent plots between 1999 and 2020. The long-term dynamics of carbon concentrations in snow demonstrated a trend towards increasing carbon concentrations in forested and treeless areas of the Murmansk region. It was shown that in representative spruce and pine forests, the concentrations and atmospheric precipitation of carbon compounds and carbon leaching with soil water were higher below the tree crowns, compared to between the crowns. In soil water, a decrease was found in carbon concentration with the soil profile depth. For soils, the highest carbon concentrations were found in the organic and illuvial soil horizons. The main soil sinks of carbon and nitrogen in northern taiga forests were found to be located in the organic soil horizon below the crowns. In northern taiga forests, the carbon content of living Picea obovata and Pinus sylvestris needles and Pinus sylvestris needle litter had minor variability; no significant interbiogeocoenotic and age differences were found. We found that the nitrogen content in brown needles and needle litter was significantly lower compared to photosynthetically active needles, probably due to retranslocation processes (withdrawal before needle abscission), corroborating the literature in the results session. The largest stocks of carbon and nitrogen in northern taiga forests are concentrated in the soil organic horizon, and the removal of these elements with soil water is insignificant. Carbon and nitrogen stocks in living and fallen needles are lower than in soil. The least amount of carbon and nitrogen is contained in atmospheric precipitation.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"22 11","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947446","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：