中国植被分类系统修订方案

为了推动《中国植被志》研编工作, 该文回顾了中国植被分类系统的发展过程和主要阶段性成果, 提出了作为《中国植被志》研编技术框架组成部分的中国植被分类系统修订方案, 对各植被型组及各植被型进行了简单定义和描述, 并针对中国植被分类系统若干问题, 特别就中国植被分类系统总体框架、混交林的界定以及土壤在植被分类中的重要性等问题进行了讨论。1960年侯学煜在《中国的植被》中首次提出了中国植被分类的原则和系统, 1980年出版的《中国植被》制定了分类等级和划分依据等更加完善的系统, 之后《中国植被及其地理格局——中华人民共和国1:1 000 000植被图说明书》和《中国植物区系与植被地理》以及很多省区的植被专著对该系统进行过修订。2017年宋永昌在《植被生态学》中提出了一个分类等级单位调整的方案。本次提出的中国植被分类系统修订方案基本沿用《中国植被》的植被分类原则、分类单位及系统, 采用“植物群落学-生态学”分类原则, 主要以植物群落特征及其与环境的关系作为分类依据, 包含三级主要分类单位, 即植被型(高级单位)、群系(中级单位)和群丛(低级单位); 在三个主要分类单位之上分别增加辅助单位植被型组、群系组和群丛组, 在植被型和群系之下主要根据群落的生态差异和实际需要可再增加植被亚型或亚群系。修订方案包含了森林、灌丛、草本植被(草地)、荒漠、高山冻原与稀疏植被、沼泽与水生植被(湿地)、农业植被、城市植被和无植被地段9个植被型组, 划分为48个植被型(含30个自然植被型、12个农业植被型、5个城市植被型和无植被地段)。自然植被中有23个植被型进一步划分出了81个植被亚型。     

On computation of semiparametric maximum likelihood estimators with shape constraints

Large sample theory of semiparametric models based on maximum likelihood estimation (MLE) with shape constraint on the nonparametric component is well studied. Relatively less attention has been paid to the computational aspect of semiparametric MLE. The computation of semiparametric MLE based on existing approaches such as the expectation‐maximization (EM) algorithm can be computationally prohibitive when the missing rate is high. In this paper, we propose a computational framework for semiparametric MLE based on an inexact block coordinate ascent (BCA) algorithm. We show theoretically that the proposed algorithm converges. This computational framework can be applied to a wide range of data with different structures, such as panel count data, interval‐censored data, and degradation data, among others. Simulation studies demonstrate favorable performance compared with existing algorithms in terms of accuracy and speed. Two data sets are used to illustrate the proposed computational method. We further implement the proposed computational method in R package BCA1SG , available at CRAN.     

福州市生态系统生产总值核算

开展生态系统生产总值(GEP)核算是推进生态文明制度建设的必要措施,也是将生态效益纳入经济社会发展评价体系的重要举措。本研究以福州市为研究对象,通过构建具有“山、海、城”特色的生态系统价值核算体系,对2015和2018年福州市GEP进行核算,从时空变化角度对福州市GEP进行对比。结果表明: 2015、2018年福州市GEP分别为9205.92、10472.42亿元,人均GEP分别为13.02、14.39万元,生态产品供给服务价值分别为941.81、1102.61亿元,生态调节服务价值分别为6364.20、5988.51亿元,生态文化服务价值分别为1899.91、3381.3亿元。与2015年相比,2018年福州市GEP增加1266.50亿元,增幅为13.8%,主要得益于生态产品供给服务价值和生态文化服务价值的增加。然而,生态调节服务价值减少375.69亿元,降幅为5.9%,主要源于气候调节、水流动调节和水质净化服务价值的减少。福州率先探索建立一套具有山、海、城特色的核算体系,可以为福建省其他城市及我国其他地区的核算工作提供“福州样板”,同时助推建立生态价值实现的长效机制。     

黄河首曲玛曲县高寒湿地景观格局演变

高寒湿地是青藏高原地区最重要的生态水源涵养区之一, 也是局部气候的有效调节者, 其动态变化与成因亟待深入研究。该研究基于遥感图像分析、地理信息系统空间分析和景观生态指数分析结合的方法, 以黄河首曲玛曲县高寒湿地为研究对象, 对1995-2018年6期湿地的动态变化进行研究。结果表明, 研究区湿地在1995-2010年间不断退化, 1995-2010年湿地面积总共减少了18 680.31 hm²。在2010-2018年间黄河首曲高寒湿地面积有所增加, 但与20世纪90年代相比, 21世纪初开始湿地的面积普遍呈现下降趋势; 1995-2010年湿地斑块数不断增加, 斑块密度不断增大, 平均斑块面积下降, 景观的破碎度升高; 2010-2015年湿地斑块数和斑块密度减少, 2015-2018年湿地斑块数和斑块密度增加, 平均斑块面积先增大后减小, 景观的破碎度先降低后升高。1995-2010年研究区高寒湿地景观Shannon多样性指数和Shannon均匀度指数均呈现下降的趋势, 湿地的景观结构趋于简单, 景观类型分布更加集中。2010-2018年湿地景观Shannon多样性指数和Shannon均匀度指数均呈现上升趋势, 湿地的景观结构趋于复杂, 景观类型增加且分布更加分散。进一步的驱动力分析表明, 引起黄河首曲高寒湿地景观格局演变的主要因素是蒸发量和降水量, 其次是人口数量和大牲畜数量等人类活动影响。气候因子是影响黄河首曲高寒湿地面积变化的主要原因, 过度的人类经济活动在一定程度上加剧了湿地的变化。     

Ageing Effect Evaluation on HD-sEMG Signals Using CCA Approach

ObjectivesThe objective of the proposed study is to exploit the technology of high-density surface electromyography (HD-sEMG), in order to evaluate the muscle activation in young and elderly subjects during a daily life gesture, namely, Sit To Stand (STS), using wireless connected ambulatory equipment (TMSi©) and Blind Source Separation (BSS) approach with Canonical Correlation Analysis (CCA).Materials and methodsSixteen subjects participated (50% females) divided into two categories (‘H1’: young (30.62 yrs ±5.92, 23.95 kg/m² ±3.08), versus ‘H2’: old (61.87 yrs ±7.98, 23.4 kg/m² ±3.38)), in the recording of HD-sEMG signals, using 32-electrodes square grids (4×8), during Sit To Stand (STS) motion, three times at spontaneous speed. The studied muscle is the Rectus Femoris (RF) muscle. The recorded HD-sEMG signals were analyzed with CCA approach to extract correlation coefficient sets according to two age categories (young versus old), in order to evaluate its discriminating power with ageing. Statistical tests (t-test) were used to evaluate the discrimination for these two categories.ResultsThe calculation of CCA correlation coefficients showed a significant difference between young and old category concerning the mean CCA correlation coefficient (P<0.001***) and also the standard deviation of the CCA correlation coefficients (P<0.0001****).ConclusionThe obtained results are promising and indicate a clear difference between the obtained source variability using CCA method between the young and the old tested subjects during daily life motion. Furthermore, these estimated sources seem to be impacted by both anatomical and functional modifications with ageing.     

Cluster analysis of pressure pain threshold maps from the trapezius muscle

The aim of this study was to investigate and present a new mapping method to describe muscle pain sensitivity based on the assessment of pressure pain threshold (PPT) over the trapezius muscle. PPT data were recorded from 36 points in 20 healthy males using a standardised grid. Points were clustered using the K-means algorithm with a fixed initialisation procedure. The total number of clusters was determined on the basis of (1) R ² evaluation of the clustering outcome compared against a desired 95% reduction in variance criterion and (2) the number of empty clusters. A minimum of three clusters were found which fulfilled the criteria. The proposed method enables the identification of a relation between the muscle subdivisions and pressure pain sensitivity within the trapezius. Further, the cluster analysis will enable the study of differences in pain sensitivity distributions between patients and controls and quantify the effect of intervention (physical or pharmacological treatments).     

Pattern classification of kinematic and kinetic running data to distinguish gender,shod/barefoot and injury groups with feature ranking

The identification of differences between groups is often important in biomechanics. This paper presents group classification tasks using kinetic and kinematic data from a prospective running injury study. Groups composed of gender, of shod/barefoot running and of runners who developed patellofemoral pain syndrome (PFPS) during the study, and asymptotic runners were classified.

The features computed from the biomechanical data were deliberately chosen to be generic. Therefore, they were suited for different biomechanical measurements and classification tasks without adaptation to the input signals. Feature ranking was applied to reveal the relevance of each feature to the classification task.

Data from 80 runners were analysed for gender and shod/barefoot classification, while 12 runners were investigated in the injury classification task. Gender groups could be differentiated with 84.7%, shod/barefoot running with 98.3%, and PFPS with 100% classification rate. For the latter group, one single variable could be identified that alone allowed discrimination.     

PARma: identification of microRNA target sites in AGO-PAR-CLIP data

PARma is a complete data analysis software for AGO-PAR-CLIP experiments to identify target sites of microRNAs as well as the microRNA binding to these sites. It integrates specific characteristics of the experiments into a generative model. The model and a novel pattern discovery tool are iteratively applied to data to estimate seed activity probabilities, cluster confidence scores and to assign the most probable microRNA. Based on differential PAR-CLIP analysis and comparison to RIP-Chip data, we show that PARma is more accurate than existing approaches. PARma is available from http://www.bio.ifi.lmu.de/PARma     

Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.