核筒悬挂结构三道抗震防线时程分析设计方法

提出了高层建筑核筒式悬挂结构三道抗震防线的时程分析设计计算方法,并编制了相应的计算程序Hangsys。计算结果与核筒悬挂结构模拟地震振动台试验的结果符合较好。因此,核筒悬挂结构完全可以通过精心设计使该类结构具有多道抗震防线,使悬挂结构既具有安全性又具有适用性。     

重庆地区重复地震识别及在数字地震台网定位评价中的应用

利用重庆数字地震台网2010年1月至2017年12月的地震波形资料和观测报告,选出5个研究区1 251个ML≥1.5地震进行波形互相关计算,识别出358对同时被2个地震台站记录且各台波形互相关系数(cc)不小于0.8的重复地震对,涉及342个地震事件,约占地震总数的27%。将筛选出的重复地震对用于定量判断地震目录中震相拾取误差及评估台网定位精度,结果显示:重庆数字地震台网的垂直定位误差约为3 km,水平定位误差约为5 km,Pg、Sg震相拾取误差分别为0.5 s和0.7 s;其中武隆区地震定位和震相拾取精度最高,綦江区最低。     

车载自组网可信节点与可信路由分析及实现

将可信赖平台模块(TPM)芯片引入车载自组织网VANET,提出了一种有效保护地理位置信息路由协议GPSR(贪婪周边无状态路由协议)的可信安全机制,从而能够防止恶意篡改路由协议和邻居位置信息表的行为。在NS2.30下对网络真实场景进行了模拟,证实此可信安全路由协议模型是正确的、有效的和合理的。     

附加GIM约束的全球电离层建模

针对目前地基GNSS台站在全球分布不均匀,导致南半球海洋和中高纬地区出现与实际不符的VTEC为负值的问题,利用IGS前1 d的最终GIM作为虚拟观测值对TEC可能为负值的地区进行约束,结合GNSS数据建立全球电离层模型(称为SGG模型),并用2014年200多个IGS台站数据对模型进行验证。结果表明,各台站VTEC的RMS优于3 TECu(赤道异常区域RMS在5~7 TECu)。同时SGG能有效消除南半球海洋(40°~90°S)VTEC为负的情况,且对原有非负VTEC几乎没有影响(其变化小于2 TECu)。SGG的卫星DCB与CODE 相比,RMS和MEAN分别优于0.2 ns和0.04 ns,不同纬度带SGG与CODE的接收机DCB估值变化基本一致,两者之差基本在1 ns以内。     

Influencing factors of seed long-distance dispersal on a fragmented forest landscape on Changbai Mountains,China

Seed long-distance dispersal(LDD) events are typically rare, but are important in the population processes that determine large-scale forest changes and the persistence of species in fragmented landscapes. However, previous studies focused on species dispersed via animal-mediated LDD, and ignored those dispersed by wind. The aim of this study was to assess the effects of canopy openness, edge, seed source, and patch tree density on the LDD of seeds by wind in forest. We collected birch seeds, a typical wind-dispersed species, throughout a larch plantation. We then assessed the relationship between birch LDD and each factor that may influence LDD of seeds by wind including distance to edge, canopy openness size, distance to mature forest, and the tree density of the larch plantation. We used univariate linear regression analysis to assess the influence of those factors on birch LDD, and partial correlations to calculate the contribution of each factor to LDD. The results showed that both canopy openness and edge had significant influences on birch LDD. Specifically, a negative relationship was observed between distance to edge and birch LDD, whereas there was a positive correlation between canopy openness size and LDD. In contrast, the distance to the mature forest was not correlated with birch LDD. Our results suggest that patch tree density could potently affect the probability of LDD by wind vectors, which provides novel and revealing insights regarding the effect of fragmentation on wind dynamics. The data also provide compelling evidence for the previously undocumented effect of habitat fragmentation on wind-dispersed organisms. As such, these observations will facilitate reasonable conservation planning, which requires a detailed understanding of the mechanisms by which patch properties hamper the delivery of seeds of wind-dispersed plants to fragmented areas.     

Human settlement evaluation in mountain areas based on remote sensing, GIS and ecological niche modeling

The Qinghai-Tibet Plateau is the world’s highest and largest plateau. Due to increasing demands for environment exploration and tourism, a large transitional area is required for altitude adaptation. Hehuang valley, which locates in the transition zone between the Loess Plateau and the Qinghai-Tibet Plateau, has convenient transportation and relatively low elevation. Our question is whether the geographic conditions here are appropriate for adapted stay before going into the Qinghai-Tibet Plateau. Therefore, in this study, we examined the potential use of ecological niche modeling (ENM) for mapping current and potential distribution patterns of human settlements. We chose the Maximum Entropy Method (Maxent), an ENM which integrates climate, remote sensing and geographical data, to model distributions and assess land suitability for transition areas. After preprocessing and selection, the correlation between variables and spatial autocorrelation input data were removed and 106 occurrence points and 9 environmental layers were determined as the model inputs. The threshold-independent model performance was reasonable according to 10 times model running, with the area under the curve (AUC) values being 0.917 ± 0.01, and 0.923 ± 0.002 for test data. Cohen’s kappa coefficient of model performance was 0.848. Results showed that 82.22% of the study extent was not suitable for human settlement. Of the remaining areas, highly suitable areas accounted for 1.19%, moderately for 5.3% and marginally for 11.28%. These suitable areas totaled 418.79 km², and 86.25% of the sample data was identified in the different gradient of suitable area. The decisive environmental factors were slope and two climate variables: mean diurnal temperature range and temperature seasonality. Our model showed a good performance in mapping and assessing human settlements. This study provides the first predicted potential habitat distribution map for human settlement in Ledu County, which could also help in land use management.     

Rebirth after death: forest succession dynamics in response to climate change on Gongga Mountain,Southwest China

Global climate change is having long-term impacts on the geographic distribution of forest species. However, the response of vertical belts of mountain forests to climate change is still little known. The vertical distribution of forest vegetation(vertical vegetation belt) on Gongga Mountain in Southwest China has been monitored for 30 years. The forest alternation of the vertical vegetation belt under different climate conditions was simulated by using a mathematical model GFSM(the Gongga Forest Succession Model). Three possible Intergovernmental Panel on Climate Change(IPCC) climate scenarios(increase of air temperature and precipitation by 1.8℃/5%, 2.8℃/10% and 3.4℃/15% for B_1, A_1B and A_2 scenarios, respectively) were chosen to reflect lower, medium and higher changes of global climate. The vertical belts of mountainous vegetation will shift upward by approximately 300 m, 500 m and 600 m in the B_1, A_1B and A_2 scenarios, respectively, according to the simulated results. Thus, the alpine tree-line will move to a higher altitude. The simulation also demonstrated that, in a changing climate, the shift in the vegetation community will be a slow and extended process characterized by two main phases. During the initial phase, trees of the forest community degrade or die, owing to an inability to adapt to a warmer climate. This results in modest environment for the introduction of opportunistic species, consequently, the vegetation with new dominant tree species becomes predominant in the space vacated by the dead trees at the expense of previously dominated original trees as the succession succeed and climate change advance. Hence, the global climate change would dramatically change forest communities and tree species in mountainous regions because that the new forest community can grow only through the death of the original tree. Results indicated that climate change will cause the change of distribution and composition of forest communities on Gongga Mountain, and this change may enhance as the intensity of climate change increases. As a result, the alternation of death and rebirth would finally result in intensive landscape changes, and may strongly affect the eco-environment of mountainous regions.     

Organic carbon deposition flux on the North Chukchi Sea shelf based on 210pb radioactivity dating

Deposition of organic carbon forms the final net effect of the ocean carbon sink at a certain time scale. Organic carbon deposition on the Arctic shelves plays a particularly important role in the global carbon cycle because of the broad shelf area and rich nutrient concentration. To determine the organic carbon deposition flux at the northern margin of the Chukchi Sea shelf, the 210pb dating method was used to analyze the age and deposition rate of sediment samples from station R17 of the third Chinese National Arctic Research Expedition. The results showed that the deposition rate was 0.6 mm＇aI, the apparent deposition mass flux was 0.72 kg.m2a1, and the organic carbon deposition flux was 517 mmol C.m2.al. It was estimated that at least 16% of the export organic carbon flux out of the euphoric zone was transferred and chronically buried into the sediment, a value which was much higher than the average ratio （-10%） for low- to mid-latitude regions, indicating a highly effective carbon sink at the northern mar- gin of the Chukchi Sea shelf. With the decrease of sea ice coverage caused by warming in the Arctic Ocean, it could be inferred that the Arctic shelves will play an increasingly important role in the global carbon cycle.     

Estimating aboveground biomass using Pléiades satellite image in a karst watershed of Guizhou Province,Southwestern China

Biomass in karst terrain has rarely been measured because the steep mountainous limestone terrain has limited the ability to sample woody plants.Satellite observation, especially at high spatial resolution, is an important surrogate for the quantification of the biomass of karst forests and shrublands. In this study, an artificial neural network(ANN) model was built using Pléiades satellite imagery and field biomass measurements to estimate the aboveground biomass(AGB) in the Houzhai River Watershed, which is a typical plateau karst basin in Central Guizhou Province, Southwestern China. A back-propagation ANN model was also developed.Seven vegetation indices, two spectral bands of Pléiades imagery, one geomorphological parameter,and land use/land cover were selected as model inputs. AGB was chosen as an output. The AGB estimated by the allometric functions in 78 quadrats was utilized as training data(54 quadrats, 70%),validation data(12 quadrats, 15%), and testing data(12 quadrats, 15%). Data-model comparison showed that the ANN model performed well with an absolute root mean square error of 11.85 t/ha, which was 9.88%of the average AGB. Based on the newly developed ANN model, an AGB map of the Houzhai River Watershed was produced. The average predicted AGB of the secondary evergreen and deciduous broadleaved mixed forest, which is the dominant forest type in the watershed, was 120.57 t/ha. The average AGBs of the large distributed shrubland,tussock, and farmland were 38.27, 9.76, and 11.69 t/ha, respectively. The spatial distribution pattern ofthe AGB estimated by the new ANN model in the karst basin was consistent with that of the field investigation. The model can be used to estimate the regional AGB of karst landscapes that are distributed widely over the Yun-Gui Plateau.     

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