不同地形条件地面同步光谱定标场对比研究

利用美国ASD公司的FieldSpec Pro FR地面波谱仪,选择5°视场角探头和135cm探头距测试地物高度,开展0°、5°、10°、15°、20°等五种不同地形坡度明、暗地物自然定标场地面波谱测试。通过对比研究不同地形坡度具代表性、能真实反映被测试目标平均自然性的各波谱测试点波谱曲线特征,得出0°、5°地形坡度获取的波谱曲线连续、平滑,信噪比高,没有混入大气水气吸收、仪器噪声等因素导致的剧烈波动、跳跃现象或尖锐锯齿状噪声,波谱特征明显,吸收峰最小值位置清晰可辨,各波谱测试点波谱曲线变化幅度小,整体反射率值变化小,Fe~(2+)、Fe~(3+)、Al-OH、Mg-OH、CO_3~(2-)等分子基团与离子波谱的诊断性波谱特征位置清晰可辨。因此0°和5°坡度地形条件获取的地面同步自然场光谱定标波谱曲线,可以满足航空高光谱遥感数据的大气校正、光谱重建和空、地回归分析等所需的地面波谱数据要求。     

金川铜镍矿床中新生代抬升冷却过程：来自裂变径迹的证据

本文基于热年代学理论,利用锆石和磷灰石裂变径迹测年数据及对磷灰石热史的模拟,分析探讨金川铜镍矿床在中新生代的抬升冷却过程,认为金川超基性岩体自中生代以来一直处于持续的冷却抬升阶段,且在中侏罗世和晚白垩世早期经历了两期快速的抬升冷却事件,推断此事件与青藏高原后期活动时间相对应,证明金川岩体受到该事件的远程效应波及,致使该矿床遭受了一定的改造。     

钟姑地区典型矿床的重磁找矿模式

钟姑地区位于宁芜中生代火山岩盆地南段,已发现有白象山铁矿等多个大型铁矿,是长江中下游成矿带以玢岩型铁矿为主的矿集区。本文以钟姑地区实测岩石物性参数为桥梁,以实测重磁数据为基础,分析了该区白象山铁矿、钟九铁矿和云楼铁矿的重磁场分布特征,并根据典型矿区已知地质条件,运用成熟的2.5D重磁联合反演技术进行计算,从定量角度认识铁矿体深部发育形态、位置与重磁异常之间对应关系,建立钟姑地区白象山铁矿等典型矿床的重磁找矿模式,为该区进一步找矿突破提供地球物理场信息。     

基于18S和ITS-5.8S rDNA基因序列的白色霞水母(Cyanea nozakii)的分子鉴定与检测

采用通用引物PCR扩增法,测定了辽东湾海域的白色霞水母(Cyanea nozakii)螅状体、碟状体及水母体的18S以及ITS-5.8S r DNA序列,同时利用Gene Bank数据库中已有同源序列对其进行序列分析及系统分析。结果显示,白色霞水母3个个体的18S和ITS-5.8S r DNA序列完全一致。白色霞水母样品的ITS-5.8S r DNA序列与Gen Bank中未知真核生物的序列高度相似(≥99%),推测该物种可能是早期发育阶段(卵、浮浪幼虫或碟状体)的白色霞水母样品。霞水母属不同种间18S r DNA序列经比对后同源序列长度为1709bp,多态位点数33个;比对后ITS1同源序列长度为368bp,其中变异位点203个,简约信息位点数178个,单变异位点21个。基于18S r DNA基因序列的霞水母属种内和种间平均遗传距离分别为0、0.008,而基于ITS1序列的霞水母属种内和种间平均遗传距离分别为0.019、0.284。基于ITS1的种间遗传距离是种内遗传距离的15倍,适合于进行物种鉴定。NJ系统树的结果也表明同种的不同个体各自聚枝,其聚类结果大致与形态分类吻合。研究表明,ITS基因片段在霞水母不同种间变异较大,更适于大型水母种类鉴定、检测及属内种间水平的系统进化研究。     

不同饵料种类、投喂方式及环境条件对凡纳滨对虾相对摄食量的影响

为提高对虾养殖过程中的饵料利用率并减少养殖废水的排放,作者以凡纳滨对虾(Litopenaeus vannamei)为实验对象,研究了不同饵料种类、投喂方式、体质量、充气量、光照强度、水温及盐度对其相对摄食量的影响。结果表明:配合饲料组对虾的相对摄食量显著高于冰鲜虾肉组;连续单颗投喂时对虾的相对摄食量较高;相对摄食量随对对虾体重升高而显著(P0.01)下降,而且不同规格的对虾在竞争条件下平均相对摄食量会降低;充气量6 L/min组对虾的相对摄食量明显高于另外两组;弱光环境下对虾的相对摄食量较高;水温和盐度对相对摄食量的影响极显著(P0.01),在32℃时对虾获得最大相对摄食量,在盐度为5时相对摄食量最小,高盐度下组间差异不显著(P0.05)。因此,在实际生产中应采取少量多次的投饵策略,并根据环境条件的变化合理的调整投饵量。     

我国海岛管理信息化建设问题与对策研究

海岛管理信息化建设是《中华人民共和国海岛保护法》赋予海洋行政主管部门的主要职责之一。文章分析研究我国海岛管理信息化建设的背景和现状,指出面临的一系列问题,从总体规划、数据应用、完善机制、统筹管理、加强配套、保障安全等方面提出相应对策,为我国海岛管理信息化建设提供参考。     

Livelihood changes and evolution of upland ethnic communities driven by tourism: a case study in Guizhou Province,southwest China

As an effective livelihood approach to alleviate poverty without rural population migration, ethnic tourism has become the primary choice of economic development in ethnic areas worldwide in addition to traditional livelihood approaches. This article applies the theories of livelihood to study the community evolution driven by tourism livelihood and examine three mountainous tourism communities in different stages of tourist area life cycle. Drawing on the methods of GIS spatial analysis, semi-structured interviews and questionnaires, this article proposes a sustainable livelihood framework for ethnic tourism to explore the evolution of ethnic tourism communities by identifying changes in livelihood assets (natural, financial, social, cultural and human capitals) in the process of tourism development. The results show that the development of ethnic tourism has led to changes in the increase of building land, and the diversification of land use functions with a trend of shifting from meeting local villagers' living needs to satisfying tourists, income composition and uneven distribution of tourism income spatially. Ethnic tourism also led to the deterioration of traditional social management structure, collapse of neighboring relationship, the over- commercialization and staged authenticity of ethnic culture, as well as the gradual vanish of agricultural knowledge with a trend of increasing modern business knowledge and higher education. In addition, these changes, involving livelihood assets from natural, economic, human, social and cultural aspects are interrelated and interactive, which form new evolution characters of ethnic community. This study reveals the conflicts over livelihood approaches which have formed new vulnerabilities to impact on sustainable evolution of ethnic communities. This research provides implications for achieving the sustainable development of ethnic communities with the driving force of tourism livelihood.     

Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC(Environmental Policy Integrated Climate) model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was 0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.     

Advanced glycation endproducts in 35 types of seafood products consumed in eastern China

Advanced glycation endproducts(AGEs) have been recognized as hazards in processed foods that can induce chronic diseases such as cardiovascular disease, diabetes, and diabetic nephropathy. In this study, we investigated the AGEs contents of 35 types of industrial seafood products that are consumed frequently in eastern China. Total fluorescent AGEs level and Nε-carboxymethyl-lysine(CML) content were evaluated by fluorescence spectrophotometry and gas chromatography-mass spectrometry(GC-MS), respectively. The level of total fluorescent AGEs in seafood samples ranged from 39.37 to 1178.3 AU, and was higher in canned and packaged instant aquatic products that were processed at high temperatures. The CML content in seafood samples ranged from 44.8 to 439.1 mg per kg dried sample, and was higher in roasted seafood samples. The total fluorescent AGEs and CML content increased when seafood underwent high-temperature processing, but did not show an obvious correlation. The present study suggested that commonly consumed seafood contains different levels of AGEs, and the seafood processed at high temperatures always displays a high level of either AGEs or CML.     

Local Spatiotemporal Modeling of House Prices: A Mixed Model Approach

The real estate market has long provided an active application area for spatial–temporal modeling and analysis and it is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics, but house prices tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be based on property values from previous years and in the spatial–temporal dimension, the properties on which current prices are based tend to be in close spatial proximity. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using ten years of house price data in Fife, Scotland (2003–2012), this research applies a mixed model approach, semiparametric geographically weighted regression (GWR), to explore, model, and analyze the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates that the mixed modeling technique provides better results than standard approaches to predicting house prices by accounting for spatiotemporal relationships at both global and local scales.