Comparison of ecophysiological characteristics between introduced and indigenous mangrove species in China

Due to its rapid growth, the introduced mangrove species Sonneratia apetala from Bangladesh has been widely used in mangrove restoration in southeastern China since 1985. As an indigenous mangrove species in Hainan, China, Sonneratia caseolaris was also planted in Guangdong Province for afforestation purposes. Both species have developed well in their new habitats, but their ecophysiological differences with the native mangrove species have not been studied. In this study, leaf gas exchange, water and nitrogen use efficiencies of two Sonneratia species were compared with those of selected native mangrove species (Avicennia marina, Aegiceras corniculatum, Kandelia candel, and Excoecaria agallocha) in Hainan and Shenzhen. The introduced S. apetala maintained lower carbon assimilation rate (A) and photosynthetic nitrogen use efficiency (PNUE) than the indigenous S. caseolaris. In Shenzhen, the two introduced Sonneratia had comparable photosynthetic rates and water use efficiency (WUE) with the native mangrove species, except that PNUE in S. caseolaris was significantly higher than in the native mangrove species. The two Sonneratia species showed significant overlap in PNUE and long-term WUE. Photosynthetic parameters derived from leaf photosynthetic light–response curves and A–C_i curves also suggested lower carbon assimilation capacities for the introduced Sonneratia than for the native mangrove species in both study sites. The lower light compensation point (LCP) of two introduced Sonneratia in both study sites also indicated a better adaptation to a low light regime than the native mangrove species. The results of photosynthetic capacities indicated that the introduced mangrove species have little competitive advantage over local native mangrove species in their respective new habitats.     

城市导线测量一体化程序设计

主要阐述利用QBASIC语言开发城市导线测量一体化程序设计的编程思想和实现过程(含程序主模块).     

黑河上游山地土壤容重分布特征及影响因素

土壤容重不仅可用作计算土壤持水力和导水性,也是估算土壤养分和碳储量的重要变量。野外测定土壤容重一般费时费力,特别是在地形复杂的山区,因此山地土壤容重在国内外大多数清查数据库中缺失。本文以黑河上游山地为例,基于野外调查的124个土壤剖面,研究了山地土壤容重的空间分布特征及影响因素。结果表明:黑河上游山地0~10 cm和0~60 cm土壤容重分别为0.91±0.02 g·cm^-3 和1.04±0.01 g·cm^-3;不同植被类型下,高山寒漠容重最大,山地森林最小。随着土壤深度的增加,容重呈幂函数递增;随着土壤有机质含量的增加,容重呈指数递减。区域上,黑河上游从西北到东南,容重呈递减趋势,从高海拔到低海拔,容重呈先减小后增大趋势。主成分分析(PCA)和一般线性模型(GLM)表明,与土壤容重相关的环境因子中,海拔是影响土壤表层容重的第一主成分,土壤有机质含量是第二主成分,黏粒含量和大于2.0 mm砾石含量分别为第三、四主成分。第一、二、三、四主成分分别解释土壤容重空间变异的24.00%、29.40%、0.01%、6.20%。     

国土空间规划中水源涵养功能生态保护红线备选区的识别

水源涵养功能重要性是生态保护红线划分工作中重要的评价指标之一。通过对以往生态系统水源涵养功能区划分的指标及其区域导向的系统梳理,在进一步明晰国土空间规划中水源涵养功能生态保护红线区域指向的基础上,按照国土空间规划关于“三区三线”自下而上试划的要求,探讨了水源涵养重要性生态保护红线划分及其评价的改进方法。选取中国典型喀斯特区域六盘水市作为研究案例区,分别用环保部2015版与2017版《生态保护红线划定技术指南》中的模型法、NPP法以及本研究提出的改进方法,对六盘水市水源涵养功能生态保护红线进行了试划。对比三种方法的划定结果可以看出,改进方法因评价数据精度的提高减少了《生态保护红线划定技术指南》方法的区域损失,提高了区域判别的精准性,可望为国土空间规划中生态保护红线的划定提供科学依据。     

Recognition of Significant Surface Soil Geochemical Anomalies Via Weighted 3D Shortest-Distance Field of Subsurface Orebodies: A Case Study in the Hongtoushan Copper Mine,NE China

Natural Resources Research - Quantitative prediction of concealed mineralization is always confronted with difficulties in comprehensive analysis between 2D and 3D data and between qualitative and...     

基于Cesium的WebGIS倾斜三维平台的实现

由于传统的二维GIS平台日渐式微,地理信息技术发展的速度越来越快,需要精度更高、表现力更好的三维GIS平台以及相应的解决方案。本文阐述了以Cesium开源前端库为依托,通过倾斜三维模型作为基础数据,实现三维WebGIS平台建设的解决方案,同时通过实例对三维平台的功能进行说明。     

基于PS-InSAR技术的地表沉降分析

由于传统测量手段对于地表沉降监测不足,PS-InSAR技术具有高空间分辨率和一定程度能克服时间、空间以及大气的影响等优势,因而逐渐成为一种大范围地表沉降监测的主要方法。本文利用PS-InSAR技术,通过SARscape软件对收集到的34幅覆盖日本千叶市地区的ENVISAT ASAR遥感影像进行沉降监测实验。实验结果表明:日本千叶市地区最大累计沉降量为58.965 mm,主要集中在城市地区,并且该地区的沉降和地下矿藏开发有关。     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.