基于自然资源价值理论的自然岸线价值核算——以辽宁省大连市为例

以自然资源价值理论为指导,构建以使用价值和生态价值为基础的自然岸线资源二元价值结构。结果表明：通过建立自然岸线资源物质量与价值量核算方法,得出大连市自然岸线资源物质总量为766.6 km,全市自然保有率为46.9%。到“十四五”末,大连市海岸线资源价值总量约1 792.88亿元,自然资源岸线价值组成中生态价值占主导地位,价值量占比为99.8%。该核算方法实现了自然岸线资源生态价值的内部化过程,解决了岸线资源的价值以使用价值为主、对生态价值的忽视或考虑不足、导致整体价值被低估的核心问题。过度的资源开发是造成自然岸线资源稀缺的原因,加之资源保护与开发的高质量发展模式,自然岸线资源价值将不断攀高。自然岸线资源价值也将成为沿海地区核心价值的重要组成部分。     

西藏甲玛矿床南坑高分异Ⅰ型花岗斑岩及黑云母矿物学特征

高硅花岗岩对于理解浅部岩浆房的行为具有重要意义.本文对西藏甲玛矿区南坑矿段的花岗斑岩开展了岩相学、岩石地球化学及黑云母矿物学研究.结果显示,该花岗斑岩具有高SiO2(73.39％～77.99％)、高K2O(4.34％～6.45％)和低P2O5(0.03％～0.06％)特征,铝饱和指数为0.97～0.98,富集Rb、Th...     

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基于孔隙率的延安黄土抗剪强度模型

孔隙率对黄土抗剪强度具有非常重要的影响,然而,孔隙率对黄土抗剪强度影响效果的认识并不充分。本文以陕西省延安黄土为研究对象,开展不同孔隙率的黄土直剪试验研究,探讨了孔隙率对粘聚力与内摩擦角的定量变化关系;并以此为基础,构建了基于孔隙率的延安黄土抗剪强度模型,并对其进行了验证。研究结果表明:(1)延安黄土粘聚力与孔隙率间呈幂函数变化关系;(2)延安不同孔隙率黄土内摩擦角取值呈现出两个区间,当孔隙率n≥0.4时,其内摩擦角在25±2.5°的范围内变动,而当孔隙率n<0.4时,其内摩擦角在29.5±2°的范围内变动;(3)通过分析得到了基于孔隙率的延安黄土抗剪强度模型,且该模型得到的黄土抗剪强度理论值与实测值间的误差较小,相对误差均在7%以内,具有较高的精确度。研究成果不仅能为延安黄土抗剪强度研究等提供技术支持,而且还能为该地区的工程建设等方面提供理论参考。     

Spatial distribution characteristics of national protected areas in China

Journal of Geographical Sciences - This paper investigated spatial structures of 3418 national protected areas (NPAs) grouped into 13 types using GIS and quantitative analysis, including point...     

基于线粒体COI和16S rRNA基因的中国沿海相手蟹系统发育研究

相手蟹科的诸多种类因其形态极其相似成为方蟹总科分类中疑问较多的一个类群。通过对中国沿海相手蟹线粒体COI和16S rRNA基因序列进行分子系统发育分析,结果表明14种相手蟹COI和16S rRNA基因序列之间差异分别为5.7%～14.5%和1.5%～12.1%,均达到了种间差异水平。构建的系统发育树显示,14种相手蟹分别为独立有效物种,但分属于拟相手蟹属和近相手蟹属的4种拟相手蟹和3种近相手蟹,没有分别形成2个独立的支系,而是混合聚成一大支系。而属于螳臂相手蟹属的无齿螳臂相手蟹则首先与属于中相手蟹属的中华中相手蟹聚成一支,再与红螯螳臂相手蟹聚为一大支,表现出与形态分类的不一致。错综复杂的分子系统关系预示着相手蟹类为多系起源,也表明它们之间的种间关系乃至于属间关系尚有诸多问题有待进一步厘定。     

基于无人机多源遥感数据海岛植被叶面积指数协同反演研究

无人机多源遥感数据的获取、融合以及应用是当今研究的热点和难点。文中以城洲岛为例,针对海岛特殊的地理生态环境,获取无人机多源遥感数据。结合无人机多光谱遥感数据定量分析各遥感植被指数与植被叶面积指数(Leaf Area Index, LAI)的响应关系,构建单因子遥感反演模型;基于无人机激光LiDAR点云提取海岛植被冠层高度模型(Canopy Height Model,CHM),并将其作为自变量引入到多源统计回归分析中,从而构建多源遥感数据协同反演模型,对区域尺度下海岛叶面积指数(LAI)进行估算,开展验证和精度评价。结果显示,加入植被冠层高度因子的协同反演模型的判定系数R2为0.92,绝对平均误差系数为12.29%,预测精度要优于单因子反演模型(判定次数R2为0.86,绝对平均误差系数19.95%)。研究表明,加入了植被冠层高度因子的协同反演模型能在一定程度上提高乔木植被LAI的预测精度。实践证明,无人机多源遥感技术在生态学定量研究中具有巨大的潜力和广阔的应用前景。     

A comparison of three widely used GPS triple-frequency precise point positioning models

GPS Solutions - The EUREF Permanent Network (EPN) is a network of continuously operating GNSS stations installed throughout the European continent. The EPN Central Bureau (CB) performs the...     

基于多种测绘装备协同工作在白河滑坡灾害中的应用

无人机低空摄影测量技术在应对各类地质灾害方面有着明显优势。本文以安康市白河县茅坪镇山体滑坡灾害为例,介绍了灾害应急中两大无人机系统以及IBIS微形变监测设备所发挥的巨大作用,阐述了无人机飞行设计、现场快速影像处理技术、灾区三维模型构建技术以及潜在危险区域形变量实时监测,并通过获取的数据成果对灾情进行了分析。     

Comparative analysis on microbial community associated with different gastrointestinal regions of wild northern snakehead Channa argus Cantor, 1842

Microbial communities in different gastrointestinal regions(stomach, foregut, midgut, and hindgut) of the northern snakehead C hanna argus(Cantor, 1842) were compared by polymerase chain reaction and partial 16 S r DNA sequencing. A total of 194, 140, 212, and 122 OTUs were detected in the stomach, foregut, midgut, and hindgut, respectively. Significant dif ferences were found in the Sobs, ACE, Shannon, and Simpson indices among samples(P 0.05). The gastrointestinal microbial community of C. argus consisted predominantly of Proteobacteria with either H alomonas, Shewanella, Plesiomonas, or Sphingomonas. Fusobacteria, Firmicutes, and Bacteroidetes also existed in the gastrointestinal tracts. However, significant diff erences were found in the compositions of microbial community among the four regions( P 0.05). Cyanobacteria and Spirochetes were significantly higher in the midgut and hindgut( P 0.05). Fusobacteria and Firmicutes were dominant in the hindgut and foregut, respectively(P 0.05). Proteobacteria was the lowest in the hindgut( P 0.05). At genus level, C etobacterium and Plesiomonas were significantly higher in the hindgut than in the other three samples( P 0.05). Clostridium and Prevotella were the highest in the midgut(P 0.05). Halomonas, Shewanella, and S phingomonas were the highest in the foregut( P 0.05). Paracoccus and Vibrio were the highest in the stomach. Several genera were only detected in certain regions, as follows: stomach, P aracoccus and Vibrio; foregut, Halomonas, Shewanella, and Sphingomonas; midgut, Clostridium and Prevotella; and hindgut, C etobacterium and Plesiomonas( P 0.05). At the species level, A cinetobacter rhizosphaerae was only detected in the stomach. P revotella copri and Clostridium perfring were not detected in the foregut and midgut, respectively, whereas Prevotella copri and Faecalibacterium pra were not detected in the hindgut. These findings provide valuable information on the microbial community in each gastrointestinal region of C. argus. Moreover, this study indicated that microbial community was not only related to rearing environment but also to the physico-chemical characteristics of each gastrointestinal region.