Statistical Estimation and Model Selection of Species-Accumulation Functions

Abstract:  Soberón and Llorente (1993) proposed pure-birth stochastic processes as theoretical models for species-accumulation curves, and these processes have frequently been used to describe the progress of biological inventories. We describe, in algorithmic form, an alternative statistical analysis based on a likelihood approach ( Díaz-Francés & Gorostiza 2002 ) that provides mathematical rigor to the ideas in Soberón and Llorente (1993) and improves the estimation of the models by incorporating the facts that the variance of the error is not constant and that the observations are correlated. Additionally, we used the likelihood ratios between candidate models as an objective procedure for model selection, allowing comparison between the goodness of fit of various models. The software for these statistical methods can now be downloaded off the Internet. We used two examples of butterfly data sets to illustrate the use of the methods and the software.     

加快石油企业清洁发展的思路探索

实施清洁生产是石油企业实现"节能、降耗、减污、增效"和赢得市场的最佳选择。文章分析了清洁生产发展历程、石油企业清洁生产发展现状、发展清洁生产的保障措施、列举了长庆油田清洁生产典型案例。得出以下结论:石油企业实施的清洁生产治污观念必须由以前的末端治理变为源头和全过程控制;清洁生产纳入常规化管理,并与企业环境管理有机结合,完善奖惩激励机制,激发中低层环保管理者工作动力;转变认识、营造氛围、投入资金、创新技术、完善机制是促进清洁生产可持续发展的保障。     

基于MODIS植被指数的浑善达克沙地植被物候变化

基于近20a MODIS的2种植被指数数据,利用Logistic曲线曲率极值法和动态阈值法,对浑善达克沙地植被物候进行了提取,分析其时空变化,并利用研究结果数据,分析植被物候对高程和气象因子的响应.结果表明,2000~2019年间研究区的植被物候呈微弱波动趋势,浑善达克沙地植被返青期（SOS）主要集中在110~140d,枯黄期（EOS）主要集中在250~280d,整体呈微弱推迟趋向（0.28d/a）,生长季长度（LOS）主要集中在120~170d,整体呈微弱延长趋向（0.23d/a）.在空间分布上,占研究区51.51%的区域植被SOS呈提前趋势;占研究区67.02%的区域植被EOS呈提前趋势,并且占研究区32.98%的区域植被EOS呈推迟趋势.占研究区62.71%的区域植被LOS呈延长趋势.在海拔900~1500m区间,随着海拔升高,SOS显著推迟,EOS不显著提前,LOS显著缩短.前一年11、12月和当年1、2、4月降水量对SOS有提前作用.6、7、8、9月份气温和降水都对EOS推迟有明显的作用.总的来说,浑善达克沙地植被物候与气候因子的相应规律比较复杂,表现出季节性的差别及地形的差异性.     

基于环境监测的矿井通风三维仿真辅助决策系统设计

为优化金属矿山矿井通风系统及辅助决策设计,弥补常用矿井通风仿真解算软件在环境监测、实时解算和辅助决策方面的不足,基于矿井通风理论、环境监测、计算机与通信技术开发矿井通风三维仿真辅助决策系统。提出通过利用实时监测到的井下通风环境参数（风量、风速等）和已存储在系统数据库里的巷道参数,实现对矿井通风网络实时解算,并将其应用到山金阿尔哈达矿井通风系统中。结果表明:矿井通风三维仿真辅助决策系统同步实现了山金阿尔哈达矿井通风系统的环境监测、风网实时解算和三维仿真模拟,提高了其矿井通风管理水平,为矿井通风系统改造优化设计和矿井向深部中段延伸时的通风系统设计提供辅助决策依据。     

自适应神经网络在确定落煤残存瓦斯量中的应用

落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节，它直接影响着采掘工作面瓦斯涌出量预测的精度，并与煤的变质程度、落煤粒度，原始瓦斯含量、暴露时间等影响因素呈非线性关系，人工神经网络具有表示任意非线性关系和学习的能力，是解决复杂非线性，不确定性和时变性问题的新思想和新方法，基于此，作提出自适应神经网络的落煤残丰瓦斯量预测模型，并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究，结果表明，自适应调整权值的变步长BP神经网络模型预测精度高，收敛速度快，该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据，为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。     

Numerical simulation study of dust concentration distribution regularity in cavern stope

Based on the theory of gas-solid two-phase flow and the characteristics of cavern stope a model of dust migration was established. The dust concentration changing of cavern stope by ventilation in 20 min after blasting and the dust trajectory in different wind speed were simulated by Fluent Software. The results show that distribution of dust concentration is significantly affected by flow field of airway in cavern, and the dust concentration of inlet is higher than that of outlet and the highest one on the corner of inlet’s side. In the stope, the smaller the wind speed of inlet is, the shorter of dust can be captured, settled and discharged, the more obviously affected by the trajectory of gas flow field. It goes into the stage of clean cycle emissions after 60 s, the speed of dust concentration dropped is the biggest between 0 s and 70 s, the main dust in stope is respirable dust after 70 s, it needs much time to settlement.According to the measured data of metal mining, approximately 87% of dust was generated during the drilling and blasting in the mine (Wang, 1979). A lot of dust with high concentrations was produced during the cavern stope blasting and it was difficult to be discharged. It can help choose the right speed to rule out the dust quickly which produced during cavern blasting, if the dust concentration distribution and the dust migration law of different inlet velocity in the cavern can be verified, what’s more, the labor productivity can be increased. It has great significance for choosing reasonable ventilation parameters, reducing dust hazards of stope to researching the dust concentration distribution regularity in the stope.     

R/S法的土石坝施工期沉降规律及预警标准研究

为提高施工期土石坝沉降安全性,研究其具有复杂非线性特征的施工期沉降规律和相应的预警标准。基于国内某在建高土石坝的沉降数据,采用R/S法分析坝体不同高程测点、同高程测点和同测点不同时期沉降数据的Hurst指数及分形维数,提出评价坝体施工期沉降安全性的预警标准。结果表明:各测点的Hurst指数最小值为0.763,坝内各处沉降仍处于快速增长阶段;坝体下部比上部、中部比下游堆石区沉降能更快趋于稳定,且坝体下部的沉降速率已经渐趋平缓。