The nearest-plant method is robust and powerful enough for different survey teams to monitor change in mesic grassland species composition

A long-term rangeland monitoring programme needs to employ a field survey technique that is practicable, precise, powerful enough to distinguish change, not prone to worker bias, and able to distinguish real change from operator error arising from staff turnover. These criteria were used to evaluate a widely used grassland sampling technique in South Africa – the nearest-plant (with 200 points) method (NP) – against common alternatives, namely NP excluding forbs (NP-nf), the plant number scale (PNS; a cover-abundance method) and quadrat frequency (QF), using multivariate ordination and permutation tests. Four trained teams surveyed four grasslands using each method. PNS took more than twice as long as the other techniques, which were similarly rapid. Estimates of composition using NP methods were the most precise and PNS was least repeatable, with QF intermediate. Compositional differences between sites were most finely distinguished using NP-nf, followed by NP and QF. PNS was able to detect only marked differences and had the greatest potential for surveyor bias. The NP method, with or without including forbs, is therefore recommended for monitoring the species composition of mesic, dense grassland. Some suggestions for monitoring agencies on how best to use multivariate methods are presented.     

Application of Multivariate Statistics in Early-warning of Corporation Financial Crisis

This paper is focused on early warning of corporation financial crisis for the China's household electric appliance manufacturers in stock market. Firstly, using company's open-disclosed annual statements as data resource, the financial indexes system is constructed. Secondary, adopting the multivariable statistical analysis method, such as cluster, discriminate and principle component analysis, the multivariate models for the empirical study on early warning of financial crisis by making use of SPSS statistical software are set up. The corporation might discover the financial affairs crisis that shall probably arise beforehand by using the financial affairs crisis early warning system. This study and analysis may serve as reference for domestic industries and enterprises.     

杭州市城区热岛效应与景观格局的动态研究

以杭州市城区为研究对象,以1992年、2004年Landsat-5,2015年Landsat-8卫星遥感数据为信息源,利用单窗算法反演三期城区地表温度,通过提取土地利用类型信息来计算景观格局指数,结合多元回归线性模型分析了杭州市城区景观格局对地表温度的影响。结果表明:(1)在研究时间段内,杭州市城区存在着明显的热岛效应,高温区域不断扩张、分散;(2)多元线性回归模型可以很好地刻画景观格局与地表温度之间的定量关系,景观格局指数PLAND,ED,LSI和AI与地表温度的相关性最高,分别达0.753,0.771,0.779,0.772,景观的面积指标、形状指标、边缘指标和聚合指标等共同影响着杭州市城区热岛效应的强度;(3)在城市化建设进程中,应通过增加绿地景观的面积,合理选择植物物种,形成集中成片的绿地,从而对城镇用地进行分割,提高现有绿地景观的立体化程度,建设较为复杂的绿地生态网络系统等方式,来缓解和改善热岛效应,达到改善人居环境的目的。     

Allometric and ontogenetic patterns related to feeding of a neotropical fish, Satanoperca pappaterra (Perciformes, Cichlidae)

Abstract –  This study aims to analyse whether Satanoperca pappaterra changes its feeding habit throughout ontogenetic development, and whether morphological ontogenetic patterns are related to its feeding habit and food capture. We collected 258 individuals in the Cuiabá river basin (Brazil) for analyses. There was a weak relationship between diet and body size, as evidenced by size class and multivariate analyses, and niche breadth did not vary strongly during ontogenetic development. Eight morphometric variables were measured in each individual. We found an isometric relationship for mouth height and width, and for head length. We found positive allometry for snout length and body height in relation to body length, whereas this relationship for intestine length and eye diameter showed negative allometry. These results suggest that morphology and consequently diet vary weakly during ontogenetic development of S. pappaterra .     

冻融土壤Philip入渗模型参数的非线性传输函数模型研究

为满足季节性冻土地区越冬期间储水灌溉管理的需求,基于山西省汾河灌区季节性冻土的冬季大田土壤水分入渗试验,得到了120组Philip入渗模型参数实测样本,借助MATLAB软件,建立了以土壤温度、有机质质量分数、土壤含水率、土壤体积质量、物理性黏粒量为输入因子、以Philip入渗模型参数吸渗率和稳渗率为输出因子的多元非线性传输函数模型,并用实测资料对该模型进行了精度检验。结果表明,预测参数的相对误差均小于11%,预报精度在可接受范围之内。     

基于Bi-LSTM的古籍事件句触发词分类方法研究

[目的/意义]开展面向数字人文的古籍触发动词识别及分类研究,对于古籍文本的深层次挖掘和内容揭示具有重大的意义。本文利用深度学习分类算法,探索依据古籍触发词进行事件句文本多元分类的自动化方法。[方法/过程]在构建了典籍事件触发词分类体系和触发词典的基础上,选取4个不同类别的事件句文本作为实验数据,利用Onehot和Tokenizer对类别标签和句子文本进行分别编码后,输入Bi-LSTM模型中训练分类器,并通过调整参数设置了对比实验,采取通用的评价指标分析了分类器的性能。[结果/结论]经过多次训练和调整之后得到的分类器,在测试集的评估中精确度达到了0.95,证明基于深度学习的实验方法和构建的触发词数据集能够有效的帮助我们实现古籍事件句文本的自动化多元分类。     

中国圆田螺与中华圆田螺形态比较研究

为研究中国圆田螺(Cipangopaludina chinensis)和中华圆田螺(Cipangopalndina cathayensis)两者之间的形态差异.通过单因子方差分析、主成分分析、聚类分析和判别分析对185个中国圆田螺和中华圆田螺个体的11个可量性状及23项性状参数进行了比较研究.单因子方差分析的结果显示,...     

桑树资源概况及其多元化利用

桑树是具有广泛用途的木本植物。就我国桑树种质资源分类以及不同生态类型的分布情况,从养蚕业、生态建设、畜牧饲料、果业开发、庭园观赏、医药保健、食品生产、化工应用等方面对桑树植物资源的多元化利用价值进行了概述,并对桑树植物多元化利用研究作了展望。