Fragility assessment of bottom plates in above ground storage tanks during flood events

This study aims to improve the fundamental understanding on the performance of bottom plates in above ground storage tanks (ASTs) during flood events. To this end, fragility models that estimate the probability of material yielding and rupture in the bottom plates were derived. A significant number of ASTs are located in coastal areas and are susceptible to hurricane hazards. Consequently, ASTs have suffered severe damage during past hurricanes resulting in spills with catastrophic environmental and social impacts. Therefore, several failure modes such as flotation, buckling, and sliding have been studied in past research. However, the literature lacks studies that consider the failure of bottom plate due to uplift pressure generated during floods and there are no design guidelines to address this issue. To address this gap, fragility functions that provide the probability of failure as a function of tank geometry, material properties, design parameters, and hazard conditions were developed herein. For this purpose, Latin Hypercube Sampling was performed to span the space of these parameters uniformly. For each parameter combination, maximum stresses in bottom plates were determined using analytical formulations for simply supported and clamped boundary conditions and were compared against two different failure thresholds. The results were used to develop a closed form fragility model using step wise logistic regression. Fragility functions were applied to four case study tanks. Sensitivity analysis were performed to understand the impacts of different probability density functions for various variables on the bottom plates’ fragility. The results provided several insights such as ASTs with larger diameter were vulnerable to bottom plate failure. Comparison with other failure modes revealed that the probability of bottom plate failure was higher than flotation failure for anchored ASTs with clamped boundary condition.     

Impact of maximum sustainable yield on independent populations

We investigate a community of independent logistically growing populations under a common harvesting effort which leads to the total maximum sustainable yield (TMSY). It is surprising that in the case of two populations with approximately equal carrying capacities, TMSY is reached while both populations persist, although their biotic potential may differ substantially. In general, however, TMSY with a common harvesting effort implies suboptimal fishing of some populations, overfishing of others and extinction of the rest of the populations. Since extinction of populations is a rule rather than an exception and since a community of independent populations is more robust than an ecosystem with multiple trophic levels, we call for urgent retraction of all legal documents advocating MSY in ecosystems.     

祁连山北麓生态移民的生计风险与应对策略选择——以武威市为例

生计风险作为移民社会整合的标尺,已成为研究生态移民生计及可持续发展的重要视角。以祁连山北麓的武威市为例,利用Binary Logistic模型分析了移民生计风险对其应对策略的影响机制,以期为制定有效的生计风险防范体系提供科学支撑。结果表明：（1）武威市生态移民的生计类型以非农户为主,纯农户比例不足10%,生计多样化指数仅为1.74且存在显著的区域差异。（2）67.44%的移民面临着多重风险,以经济风险为主,生活开支大、新分棚圈耕地质量差、返贫是主要的风险要素。（3）应对策略主要为向亲朋借钱、银行贷款、外出打工和减少开支,后顾生计则多选择扩大养殖、长期打工和维持现状,不同县区移民的策略选择略有不同。（4）政策、福利和经济风险会显著影响移民对“向银行贷款”“减少开支”及“外出打工”等应对策略的选择,而后顾生计的选择更多受制于生计资本储量,而政策及经济风险的影响较低。移民户的类型对策略选择影响显著,非农型兼业户更倾向于选择“向银行贷款”和“扩大养殖”。     

林窗对岷江冷杉幼苗种群优势度增长与周期性波动的影响

在川西亚高山岷江冷杉原始林中布设样带,开展林窗和林下更新幼苗生长状况调查,采用Logistic模型和谱分析进行种群优势度增长和周期性波动分析。结果表明：Logistic模型能较好地反映出岷江冷杉幼苗种群优势度增长规律,基于基面积和总生物量拟合的种群优势度最大环境容量分别为11.34 mm²/m²和4.64 g/m²,内禀增长率为0.60和0.62,基面积和生物量均能很好地表示岷江冷杉幼苗种群大小。基于基面积拟合和计算的林窗种群的最大环境容纳量、内禀增长率和最大增长速率约为林下种群的4.2倍、1.4倍和5.8倍,最大增长速率出现时间较林下种群早2龄级。谱分析发现岷江冷杉幼苗种群的波动性是多个周期的叠加,大周期内存在着小周期,均以基波振幅最大,林窗种群基波振幅约为林下种群的3倍,谐波对林窗种群影响较林下种群早2龄级。林窗干扰提高了岷江冷杉幼苗种群优势度的环境容纳量和内禀增长率、增强了基波对种群周期性波动的控制,使幼苗种群具有更强的增长优势和相对稳定的生长环境。因此,在岷江冷杉原始林的管理过程中应充分重视林窗的作用。     

表面分子膜降低氨挥发的Logistic模型研究

通过盆钵和田间试验,研究了表面分子膜对水体氨挥发的影响。结果表明,表面分子膜可有效抑制氨的挥发,但抑制效果跟分子膜用量有关。Ｌｏｇｉｓｔｉｃ模型可以很好模拟预测盆钵试验中的氨挥发过程,通过修正氨挥发速率常数ｃ,可较好地模拟田间氨挥发过程。     

The derivation of species response curves with Gaussian logistic regression is sensitive to sampling intensity and curve characteristics

We investigated quantitatively the sensitivity of plant species response curves to sampling characteristics (number of plots, occurrence and frequency of species), along a simulated pH gradient. We defined 54 theoretical unimodal response curves, issued from combinations of six values for optimum (opt = 3, 4, …, 8), three values for tolerance (tol = 0.5, 1.0, and 1.5, sensu ter Braak and Looman [ter Braak, C.J.F., Looman, C.W.N., 1986. Weighted averaging, logistic regression and the Gaussian response model. Vegetatio 65, 3–11]), and three values for maximum probability of presence (p_max = 0.05, 0.20, and 0.50). For each of these 54 theoretical response curves, we built artificial binary data sets (presence/absence) to test the influence of species occurrence, frequency, or number of available plots. With real data extracted from EcoPlant, a phytoecological database for French forests [Gégout, J.-C., Coudun, Ch., Bailly, G., Jabiol, B., 2005. EcoPlant: a forest sites database linking floristic data with soil characteristics and climatic conditions. J. Veg. Sci. 16, 257–260], we compared the ecological response of 50 plant species to soil pH, based first on a small data set (100 randomly sampled plots), and then based on the whole data set available (3810 plots).     

On the use of growth rate parameters for projecting population sizes: Application to aphids

This paper extends the application of the cumulative size based mechanistic model, which has previously been shown to describe diverse aphid population size data well. The mechanistic model is reviewed with a focus on the explanatory role of the birth and death rate formulation. An analysis of two data sets, one on the mustard aphid and the other on the pecan aphid, indicates that multiple linear regression equations based on the estimated birth and death rate parameters alone account for nearly all (R² > 0.95) of the variability in two key population attributes, namely the peak count and the cumulative density. This indicates that population size variables may be projected directly from the growth rate parameters using linear equations. Such linear relationships based on the birth and death rate parameters are shown to hold also for certain generalized mechanistic models for which the analytical solution is not available. The birth and death rate coefficients, therefore, constitute a new succinct set of variables that could be included in the predictive modeling of aphid populations, as well as other insect and animal populations with local collapse which follow similar growth dynamics.     

Logistic回归模型在尘肺发病预测与控制中的应用研究

目的 :探讨 L ogistic回归模型在尘肺发病预测与控制中的应用。方法 :采用多元Logistic回归统计方法建立粉尘作业工人的接尘工龄 (ET)、工龄平均浓度 (AEC)、粉尘毒性 (T)三因素与尘肺发病概率的回归模型。结果 :尘肺发病预测与控制的回归模型为 :P=1/ { 1+ exp[- (- 5.4 70 7+ 0 .0 94 7ET+ 0 .0 0 2 4 AEC+ 1.9784 T) ]} ,接尘工龄等三因素对尘肺发病影响的比数比分别为 :1.0 994 (ET)、1.0 0 2 4 (AEC)和 7.2 310 (T)。结论 :所建立尘肺发病预测与控制的回归模型与所研究人群的符合率较高 ,对今后预防尘肺发生的科学化管理与决策有较好的实用性和应用价值。