The effects of urban remnant natural evergreen broad-leaved forest (EBLF) on the restoration of artificial pine forests surrounding it were studied with reference to species composition,biodiversity,dominant species a...The effects of urban remnant natural evergreen broad-leaved forest (EBLF) on the restoration of artificial pine forests surrounding it were studied with reference to species composition,biodiversity,dominant species and stand structure on Mt. Tieshanping in Chongqing metropolis,Southwest China. The seeds from the remnant EBLF naturally facilitate the restoration process of artificial Pinus massoniana forests near it. The similarity of species composition between the artificial Pinus massoniana forests and the remnant EBLF and biodiversity index of the artificial Pinus massoniana forests decrease as the distance from the remnant EBLF increases. Castanopsis carlesii var. spinusa is the dominant species in the ground vegetation,shrub layer and sub-tree layer of the Pinus massoniana forests near the remnant EBLF. However,the natural restoration processes of those farther away from the remnant EBLF are restricted for the absence of seed source of the inherent components of the remnant EBLF,and the anthropogenic measures should be taken to facilitate the restoration process.展开更多
CO 2 is the key gas of the greenhouse ones, the effect of its radiation on temperature ascent is 60% of the total greenhouse gases. The elevating CO 2 concentration influences to a great extent the future climate warm...CO 2 is the key gas of the greenhouse ones, the effect of its radiation on temperature ascent is 60% of the total greenhouse gases. The elevating CO 2 concentration influences to a great extent the future climate warming in a regional or global scale. Forest is the main part of carbon cycling in the land ecosystem.. Monitoring CO 2 absorption and emission in the forest ecosystem play a non\| fungible role in study on the global change. Gongga Mountain is located in the southeast margin of the Tibetan Plateau, and there exist intact vertical vegetation zonality, which is advantageous for measuring soil CO\-2 emission on each vertical forest zonality and researching the ecological factors of soil respiration.The east slope of Gongga Mountain develops 5 natural forest vertical zones from lower to higher altitudes: secondary forest, ever\|greened and deciduous broad\|leaved mixed forest, broad\|leaved and coniferous mixed forest, coniferous forest and alpine shrubs. Based on the two\|year’s measurement, the soil respiration of each forest averaged: 5 488, 6 344, 5 912, 4 176 and 3 864μmol CO 2/(m 2·s); the flux of soil CO 2 emission was arranged: 208 628, 241 169, 224 746, 158 752 and 146 891kg CO 2/(hm 2·d), respectively.展开更多
[Objective]Both fire and insect outbreaks are considered as important natural disturbance factors in many forest ecosystems,yet few studies have addressed the effects of fires on subsequent insect outbreaks.[Method]In...[Objective]Both fire and insect outbreaks are considered as important natural disturbance factors in many forest ecosystems,yet few studies have addressed the effects of fires on subsequent insect outbreaks.[Method]In this paper,tree mortality,larval density and vertical distribution were measured through field investigation and sampling method to evaluate the short-term response of Japanese pine sawyer beetle,Monochamus alternatus Hope to Masson pine,Pinus massoniana Lamb.in the second year after the fire in Jiangxi Province,China.[Results]compared with unburned Masson pine forest,burned Masson pine forest suffered from higher tree mortality and more pine trees were attacked by M.alternatus.Burned Masson pine tended to harbor much higher larval density further up along the trunk than unburned pine trees,and most individuals distributed in the middle section and middle-lower section of the trunk.[Significance]The results confirmed that Masson pine forest after being damaged by non-lethal fires were more susceptible to attacks by Japanese pine sawyer beetles,displaying higher population density and higher vertical distribution position.The study will provide an important guideline for the managers of Masson pine forests suffering from fires and pest invaded areas.展开更多
A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,wh...A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.展开更多
居民的自然保护态度对自然旅游地的自然保护与旅游可持续发展至关重要,自然旅游地居民自然保护态度的影响因子及影响方式,已经成为自然旅游地管理的重要内容,但相关研究薄弱。以中国九寨沟和英国新森林国家公园(New Forest National Par...居民的自然保护态度对自然旅游地的自然保护与旅游可持续发展至关重要,自然旅游地居民自然保护态度的影响因子及影响方式,已经成为自然旅游地管理的重要内容,但相关研究薄弱。以中国九寨沟和英国新森林国家公园(New Forest National Park,NF)为例,根据实地问卷调查数据,从两地居民的人口属性、旅游环保期望、旅游环境影响感知及旅游环境伦理观与其自然保护态度关系的角度,进行定量比较研究。研究发现:(1)两地居民的自然保护态度受不同因子的影响,存在明显的中外差异;(2)人口属性特征如性别、年龄、居住年限、教育水平及旅游业参与情况对新森林国家公园社区居民的自然保护态度没有影响;但性别、旅游业参与情况却影响九寨沟居民的自然保护态度,女性及旅游业参与者更支持对九寨沟进行自然保护;(3)新森林国家公园居民的自然保护态度受其旅游环保期望及旅游环境伦理观的影响:旅游环保期望较高、持保护主义环境伦理观的新森林国家公园居民,更有可能支持对新森林国家公园进行自然保护;(4)九寨沟居民的自然保护态度不受其旅游环保期望及旅游环境伦理的影响,但受其旅游环境影响感知的影响;居民的旅游环境影响感知越消极,越支持对九寨沟进行自然保护。展开更多
基金Project(30700094) supported by the National Natural Science Foundation of ChinaProject (CSTC, 2008BB7187) supported by the Natural Science Foundation of CQ CSTC, China+2 种基金Project (20092x07104-003-02)supported by the National Science and Technology MinistrySubsidy from the Pro Natural Fund of Japan for 2007Research project for a sustainable development of economic and social structure dependent on the environment of the eastern coast of Asia from Tokyo University of Information
文摘The effects of urban remnant natural evergreen broad-leaved forest (EBLF) on the restoration of artificial pine forests surrounding it were studied with reference to species composition,biodiversity,dominant species and stand structure on Mt. Tieshanping in Chongqing metropolis,Southwest China. The seeds from the remnant EBLF naturally facilitate the restoration process of artificial Pinus massoniana forests near it. The similarity of species composition between the artificial Pinus massoniana forests and the remnant EBLF and biodiversity index of the artificial Pinus massoniana forests decrease as the distance from the remnant EBLF increases. Castanopsis carlesii var. spinusa is the dominant species in the ground vegetation,shrub layer and sub-tree layer of the Pinus massoniana forests near the remnant EBLF. However,the natural restoration processes of those farther away from the remnant EBLF are restricted for the absence of seed source of the inherent components of the remnant EBLF,and the anthropogenic measures should be taken to facilitate the restoration process.
文摘CO 2 is the key gas of the greenhouse ones, the effect of its radiation on temperature ascent is 60% of the total greenhouse gases. The elevating CO 2 concentration influences to a great extent the future climate warming in a regional or global scale. Forest is the main part of carbon cycling in the land ecosystem.. Monitoring CO 2 absorption and emission in the forest ecosystem play a non\| fungible role in study on the global change. Gongga Mountain is located in the southeast margin of the Tibetan Plateau, and there exist intact vertical vegetation zonality, which is advantageous for measuring soil CO\-2 emission on each vertical forest zonality and researching the ecological factors of soil respiration.The east slope of Gongga Mountain develops 5 natural forest vertical zones from lower to higher altitudes: secondary forest, ever\|greened and deciduous broad\|leaved mixed forest, broad\|leaved and coniferous mixed forest, coniferous forest and alpine shrubs. Based on the two\|year’s measurement, the soil respiration of each forest averaged: 5 488, 6 344, 5 912, 4 176 and 3 864μmol CO 2/(m 2·s); the flux of soil CO 2 emission was arranged: 208 628, 241 169, 224 746, 158 752 and 146 891kg CO 2/(hm 2·d), respectively.
基金supported by Research Project of Jiangxi Forestry Bureau(No.201910)National Natural Science Foundation of China(No.31760106)。
文摘[Objective]Both fire and insect outbreaks are considered as important natural disturbance factors in many forest ecosystems,yet few studies have addressed the effects of fires on subsequent insect outbreaks.[Method]In this paper,tree mortality,larval density and vertical distribution were measured through field investigation and sampling method to evaluate the short-term response of Japanese pine sawyer beetle,Monochamus alternatus Hope to Masson pine,Pinus massoniana Lamb.in the second year after the fire in Jiangxi Province,China.[Results]compared with unburned Masson pine forest,burned Masson pine forest suffered from higher tree mortality and more pine trees were attacked by M.alternatus.Burned Masson pine tended to harbor much higher larval density further up along the trunk than unburned pine trees,and most individuals distributed in the middle section and middle-lower section of the trunk.[Significance]The results confirmed that Masson pine forest after being damaged by non-lethal fires were more susceptible to attacks by Japanese pine sawyer beetles,displaying higher population density and higher vertical distribution position.The study will provide an important guideline for the managers of Masson pine forests suffering from fires and pest invaded areas.
基金supported by National Natural Science Foundation of China(Grant No.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002).
文摘A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.
文摘居民的自然保护态度对自然旅游地的自然保护与旅游可持续发展至关重要,自然旅游地居民自然保护态度的影响因子及影响方式,已经成为自然旅游地管理的重要内容,但相关研究薄弱。以中国九寨沟和英国新森林国家公园(New Forest National Park,NF)为例,根据实地问卷调查数据,从两地居民的人口属性、旅游环保期望、旅游环境影响感知及旅游环境伦理观与其自然保护态度关系的角度,进行定量比较研究。研究发现:(1)两地居民的自然保护态度受不同因子的影响,存在明显的中外差异;(2)人口属性特征如性别、年龄、居住年限、教育水平及旅游业参与情况对新森林国家公园社区居民的自然保护态度没有影响;但性别、旅游业参与情况却影响九寨沟居民的自然保护态度,女性及旅游业参与者更支持对九寨沟进行自然保护;(3)新森林国家公园居民的自然保护态度受其旅游环保期望及旅游环境伦理观的影响:旅游环保期望较高、持保护主义环境伦理观的新森林国家公园居民,更有可能支持对新森林国家公园进行自然保护;(4)九寨沟居民的自然保护态度不受其旅游环保期望及旅游环境伦理的影响,但受其旅游环境影响感知的影响;居民的旅游环境影响感知越消极,越支持对九寨沟进行自然保护。
