Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

Bibliometric analysis of simulated driving research from 1997 to 2016

Objective: The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

Methods: The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

Results: A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

Conclusions: This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.     

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

基于遗传神经网络的除湿机故障诊断与寿命预测

目的识别除湿机的性能状态和预测吸附剂的剩余寿命。方法针对除湿机故障过程缓变的特点,提出一种基于数据驱动的遗传神经网络模型。首先,为解决设备失效程度划分模糊的问题,由5个热力参数组成反映吸附剂劣化程度的特征向量,关联分析得到除湿机的5类故障模式。其次,利用遗传神经网络建立状态参数和故障模式的映射关系。最后,对表征设备吸附能力的主参数进行外推预测。结果训练好的诊断网络可准确地识别出设备的劣化程度及其演变过程,预测网络的预测精度非常高。结论该方法可有效地实现对除湿机的故障诊断与预测。。     

电晕放电辐射信号的特征提取和模式识别方法研究

目的研究电晕放电辐射信号的特征提取和模式识别方法。方法在分析信号特征提取方法的基础上,对实测的电晕放电辐射信号特征提取,利用概率神经网络开展电晕放电辐射信号目标识别,检验特征提取的有效性。结果以奇异值作为输入特征量的PNN在整体上效果更优,稳定性好,对两类不同放电辐射信号的正确识别率均可达到80%以上,并且当输入特征量个数达到10个时,对实测样本的正确识别率均达到了最高值。电晕放电的正确识别率为96.7%,火花放电的正确识别率为93.3%。结论该方法能基本满足实际放电信号的识别应用。     

基于WebGIS的水环境模拟关键技术研究

近年来随着水环境模拟领域的发展出现了较多水环境数学模型,目前日益成熟的WebGIS技术是使模型使用变得简单化和直观化的一大途径.是在通过Flex和ArcGIS Server搭建WebGIS系统平台的基础上,利用PHP进行WebGIS和水环境模拟模型的数据交互,实现系统平台和数值模型的松散耦合.用户在浏览器端进行模型输入条件的设置,模型在远程服务器端进行运行计算,反馈的模拟结果通过RIA在WebGIS中进行多元化动态展示.该方法对一般模型具有适用性,可降低模型使用门槛,提高模拟结果展示和分析能力.     

基于T-S模糊神经网络的大沽河水质变化特征分析研究

基于T-S模糊神经网络,利用大沽河2010年-2015年水质监测数据,选取溶解氧、化学需氧量、高锰酸盐指数、氨氮、总氮、总磷对水质具有重要影响的6项指标,建立适用的水质评价模型,对大沽河水质变化特征进行分析.结果显示:上游水质评价结果明显优于中游、下游水质评价结果,网络评价水质等级变化趋势同真实指标数据变化趋势一致.验证结果充分表明了T-S模糊神经网络用于水质变化特征分析是可行、有效的.     

省级生态保护红线划定实践研究 ——以青岛市为例

在省级及以上禁止开发区、重点生态功能保护区等进行调查分析的基础上,以青岛市为实践区域,与多类规划衔接,划定青岛市省级生态保护红线.青岛市最终划定59处省级生态保护红线区,面积合计1120.65 km2,占国土面积的9.9%.划定的生态保护红线符合确立"三生"空间和落实"多规合一"的要求,有利于改善生态系统服务功能,保障人居环境安全,增强经济社会可持续发展能力,对于青岛市市级生态保护红线的划定和生态安全格局的构建具有非常重要的意义.     

基于熵权的长沙市城市生态安全综合评估与预测

城市是一个社会-经济-自然复合生态系统,区域资源与城市自然系统是城市社会经济发展的重要基础和载体。城市生态安全评估是对未来的安全状态进行预测,以实现城市的可持续发展。文章以长沙市为例,在城市生态安全主要影响因素识别的基础上,应用PSR模型、熵权法等建立城市生态安全评估指标及计算方法,研究了长沙市近11年来生态安全的变化趋势。研究结果表明,1999-2009年间长沙生态安全的趋势由较不安全向较安全状态发展,生态安全值从25.4提高到60.7,人文环境响应是长沙生态安全改善的主导因素,资源环境压力,水土资源保持是限制长沙市生态安全的主要因素。     

基于生态足迹改进模型的生态安全及其预测研究

由William Rees提出的生态足迹模型已经成为近年来生态可持续发展的重要的度量工具,但是该模型仅考虑了土地的基本生产功能,忽视了土地生态系统的服务功能。文章借鉴生态系统服务功能理论改进了传统的生态足迹模型,将生态系统服务功能价值当量因子引入生态足迹模型均衡因子和产量因子的计算中,改进后的模型体现了生态系统功能的完整性;同时,文章以江苏省2010年的统计数据为基础,应用改进模型计算了其2010年生态压力指数,结果表明,江苏省生态压力指数达到1.495,其安全状况已经超过了极不安全边界,处于极不安全状态;最后利用灰色理论GM(1,1)模型对其2011-2015年的生态安全状况进行了预测,发现江苏省未来5年生态压力指数快速增大,年平均增长速度为6.89%,表明江苏省未来5年生态安全状况将继续恶化,这将严重影响其生态可持续发展和经济可持续发展。