青海省民和县土地利用景观生态格局动态分析

为研究青海省民和县近20年景观分布规律及其土地利用程度问题,在GIS技术的支持下,将青海省民和县作为研究对象,选用2000、2010、2020年的全球地表覆盖数据GlobeLand30,基于GlobeLand30分类系统,构建分类体系,并通过土地类型转移矩阵得到20年来研究区各景观类型面积及其变化情况,最后利用Fragstats4景观分析软件选取9个主要景观指标,对民和县的景观格局进行斑块类型和景观水平的对比分析。结果表明：（1）面积增加最多的是人造地表,耕地面积减少最多,耕地转化为人造地表的趋势尤为明显;（2）草地和耕地的破碎化程度最高,湿地破碎化程度较小;（3）土地利用程度指数整体上升,土地利用效果明显。进行景观生态格局动态分析对区域的土地利用规划有重要的作用,可为其生态环境保护提供参考。     

一种改进深度卷积神经网络的海岛识别方法

受不规律潮汐的影响,现有的海岛地物类别自动识别方法存在精度低和时效性差等问题,通过改进深度卷积神经网络提出了一种基于遥感影像的海岛快速识别方法:(1)在深度卷积神经网络的卷积层中增设1×1的卷积核作为瓶颈单元,对多波段的遥感影像进行降维;(2)在池化层引入了重采样方法,基于灰度值对海量的遥感影像进行特征压缩。以300景Landsat-8遥感影像为源数据,分别采用CNN、RCNN和本文改进的深度卷积神经网络对遥感影像中的海岛进行识别,实验结果表明:(1)改进的深度卷积神经网络降低了海岛识别的计算耗时,其计算耗时仅为CNN的4.56%和RCNN的5.60%;(2)改进的深度卷积神经网络较CNN和RCNN提高了海岛识别的精度,识别精度分别为96.0%、93.3%和95.0%。结果说明,改进的深度卷积神经网络适用于面向遥感影像的海岛自动识别。     

Asterosaponins: Structures,Taxonomic Distribution,Biogenesis and Biological Activities

Asterosaponins are a class of steroid oligoglycosides isolated from starfish with characteristic structures and diverse biological activities. In this review, we have attempted to combine the most important data concerning asterosaponins and give a list of these secondary metabolites with their structural peculiarities. The purpose of this review is to provide a brief but as complete as possible principal information about their chemical structures, taxonomic distribution in the marine environment, distribution in different geographical areas and depths, some properties, biological activities, and functions. Some other rare steroid metabolites from starfish, closely related in structures and probably biogenesis to asterosaponins, are also discussed.     

基于主成分和隶属函数分析的高粱品种耐深播性综合评价

采用盆栽试验,分别设置1、3、5、7 cm播深,对34个高粱品种在不同播深下的出苗率、幼苗形态和幼苗干物质量进行分析,筛选耐深播性鉴定指标,综合评价高粱品种的耐深播性。研究结果表明,随着播种深度的加大,出苗率、苗长、根长、根数和苗重均呈下降趋势,3、5、7 cm与1 cm播深上述指标测定值的比值分别为0.84～0.60、0.96～0.75、0.83～0.53、0.88～0.64和0.95～0.85;中胚轴长、根重和根冠比呈上升趋势,3、5、7 cm与1 cm播深上述指标测定值的比值为1.52～3.30、1.10～1.25和1.17～1.50;胚芽鞘长在播深间差异不显著。主成分分析结果表明,前4个主成分的累积方差贡献率为77.647%,相对根冠比、相对根长、相对中胚轴长和相对出苗率载荷量最大,将其作为高粱耐深播性筛选的主要指标并计算隶属函数值。根据隶属函数值对高粱品种进行聚类分析,结果显示,34个高粱品种可聚为3类,晋粱白2号等11个品种为耐深播品种,红青壳等14个品种为中等耐深播品种,吉品609等9个品种为深播敏感品种。品种间耐深播性差异明显,杂交种较常规种耐深播性强。     

Precipitation forecasting by large-scale climate indices and machine learning techniques

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.     

黄瓜花叶病毒浙江白术分离物全基因组序列测定与分析

正白术(Atractylodes macrocephala Koidz.)为菊科(Compositae)苍术属(Atractylodes)多年生草本植物,其根茎入药具补脾健胃、燥湿利水、止汗安胎等功效,在我国广泛栽培,并以于术(浙江临安于潜)品质最佳[1]。近年来白术生产由于品种单一,长期连作等因素导致病毒病害日趋严重。据报道,黄瓜花叶病毒(Cucumber mosaic virus,CMV)~([2])、蚕豆萎蔫病毒2号(Broad bean wilt virus 2,     

竹花叶病毒浙江麻竹分离物全基因组序列及siRNA分析

正已知有3种病毒可在自然条件下侵染竹类植物,即竹花叶病毒(bamboo mosaic virus,BaMV)~[1]、樱桃坏死锈斑驳病毒(cherry necrotic rusty mottle virus,CNRMV)和苹果茎沟病毒(apple stem grooving virus,ASGV)~[2,3]。其中,BaMV是最早在巴西的金竹(Bambusa vulgaris Cv.)和孝顺竹     

城镇化进程中的粮食安全问题:一个研究综述

研究城镇化进程中的粮食安全问题,本质上是城镇化进程中产业之间的协调问题。中国的城镇化由于规模庞大、人口众多,使得城镇化是否影响粮食安全的研究一直伴随着国家城镇化水平的提升而从未间断过,特别是中国开始进入城镇化快速发展阶段之后。在简单回顾城镇化与粮食安全问题研究历史的基础上,通过着重梳理近十年来中国城镇化对粮食安全的研究文献,从城镇化影响粮食安全的因素和城镇化背景下保障粮食安全的解决方案两个角度的内容出发,指出了研究侧重点的发展变化。在影响因素问题上,研究者们从最初的侧重关注耕地减少,到探索农业生产技术应用提升农业生产力,再到保障劳动力的资源水平和满足粮食消费,越来越全面地认识城镇化对粮食安全的影响。而在解决方案上,从战略政策的演变,到夯实生产能力的策略变化,再到对海外资源依靠方式的转变,体现出不断完善的粮食安全保障体系建立。最后认为未来的研究可以在空间异质性、人力资本和制度要素变化上进一步深入。     

基于大型渔业平台的深远海渔业发展现状与思考

基于渔业产业现状,分析国内外在大型渔业平台、深海网箱和养殖工船方面的发展现状,提出“游弋式”养殖工船及深远海渔业的基本概念。受限于投资成本、技术发展水平等客观因素,中国深远海养殖发展速度缓慢,但近年来取得了一定的发展成效。笔者针对现阶段渔业粗放型生产方式的现状,从国家战略、渔业改革和产业需求等角度分析深远海渔业发展的必要性,认为发展以养殖工船为代表的深远海大型渔业平台是实现渔业强国之路的有效途径之一,走出一条符合中国国情的深远海渔业平台的开发之路势在必行。     

振捣提浆与侧深施肥技术模式对寒地水稻产量性状及肥水效率的影响

为解决北方寒地传统搅浆平地耕作模式造成稻田泡田灌溉水量大和肥料利用效率低等问题,于2018—2019年以稻田水整地环节振捣提浆机与侧深施肥机为材料,采用2种耕整地模式和2种施肥模式的正交试验设计：搅浆平地耕整地模式(WPF)、振捣提浆耕整地模式(VEP)、基肥撒施模式(CFA)和侧深施肥模式(SDF),分析振捣提浆+侧深施肥技术模式对泡田期灌水量、干物质积累量、产量指标、肥料利用率及经济效益的影响。结果表明：与常规搅浆平地耕整地+基肥撒施(WPF+CFA)相比,搅浆平地耕整地+侧深施肥(WPF+SDF)、振捣提浆耕整地+基肥撒施(VEP+CFA)和振捣提浆耕整地+侧深施肥(VEP+SDF)3种技术模式对水稻泡田灌溉量、产量性状、肥料利用效率和经济效益均产生显著的影响,以VEP+SDF增幅最大,WPF+SDF次之,VEP+CFA最小。与WPF+CFA相比,VEP+SDF模式能显著提高肥水效率,节约泡田灌溉水11.4%,减少肥料施用量10%,产量和经济效益分别提高7.3%和1628.7元/hm²。本研究表明,VEP+SDF模式显著改善肥水利用效率,提高植株产量和经济效益,是北方寒地水稻较为理想的机械化整地施肥技术模式。