西双版纳州地震活动特点及与环境因子的关系

本文揭示了西双版纳州东、西两部分地震（以澜沧江为界）的交替活动性、强震的近似原地重复性以及与环境因子的关系，进而指出本世纪90年代中至21世纪初该州的强震危险区主要在勐海县周围。最后，为实现逐年跟踪逼近预测，又提出了一种根据大气降水对地壳的加卸载动态变化具体化判断发震年份的方法。     

内蒙古东部半干旱区旱灾与厄尔尼诺相关性研究

本文利用近４５年的水灾害资料，通过对海—气耦合事件与特定区域的旱灾发生年份的统计分析，发现了在半干旱区（０．６）Ｋ≥０．３）东部，即昭乌达盟、哲里木盟的干旱年与厄尔尼诺年份存在着较好的遥相关，这对研究本区的旱情进行超长期预报有重要意义。     

黔江地区矿产资源开发利用研究

黔江地区蕴藏有可开发利用的矿产资源汞、锰、萤石等３０余种。已开发利用的有１０余种。多数矿产地和矿种勘查程度低，远远满足不了经济发展的需要。本文探讨了本地区矿产开发１０年规划及“八五”、“九五”期间发展重点。     

新疆阿勒泰地区人工增水效果评估

利用1960-2015年新疆阿勒泰地区7个气象观测站的日降水量资料和中国气象数据共享网提供的2014-2015年中国地面时降水0.1°×0.1°格点数据集,初步评估了阿勒泰地区人工增水效果。结果表明,人工增雪使阿勒泰地区冬季平均降雪量增加了20.80 mm,冬季降雪量占全年降水量的比例也由15.50%提高到22.39%。同一时期年平均降水量增加了39.47 mm,有一半以上来自冬季增雪量。人工增雨使阿勒泰地区夏季平均降雨量增加了16.59 mm,增雨率为4%,夏季增雨不如冬季增雪效果明显。     

延边天宝山矿集区新兴铅锌(银)矿床成矿岩体的年代学与地球化学特征

新兴铅锌(银)矿床位于兴蒙造山带东段的天宝山矿集区,主矿体受花岗闪长岩体中的角砾岩筒控制。为确定该矿床的成岩成矿时代、物质源区和构造背景,对与成矿作用关系密切的花岗闪长岩进行了LA_ICP-MS锆石U_Th_Pb同位素测定和岩石地球化学分析。结果表明:花岗闪长岩中锆石U_Pb年龄的加权平均值为264.6±4.4 Ma(n=15),表明该岩体侵位于中二叠世;新兴花岗闪长岩的元素地球化学特征上表现为富钠(Na2O/K2O为1.36~1.85,均1)、准铝质(A/CNK值为0.96~1.04,均值0.99)和中等偏高的Al2O3含量(16.04%~16.34%),属I型花岗岩和高钾钙碱性-钙碱性岩石系列,具有岛弧岩浆岩的地球化学属性;微量元素组成上,富集轻稀土[(La/Yb)N=8.44~16.64],具弱的负Ce异常(δCe=0.72~0.91,均值为0.83)和弱的正Eu异常(δEu=1.00~1.15,均值为1.06),富集大离子亲石元素(LILE)Ba、Rb、K及不相容元素Th、U,相对亏损高场强元素(HFSE)Ta、Nb和Ti等,微量元素比值介于地壳和地幔平均值之间,均表明新兴成矿岩体形成过程中壳源物质的贡献。结合东北地区晚古生代区域构造演化,认为该花岗闪长岩体及相关热液成矿事件是中二叠世古亚洲洋板块俯冲作用的结果。该期岩浆-成矿事件的识别对区内区域成矿作用及成矿规律研究具重要意义。     

府际关系视角下的跨区域经济合作——以江苏对口支援新疆伊犁哈萨克自治州直地区为例

 对口援疆是国家引导下的特殊跨区域经济合作关系,是解决区域发展不平衡、促进少数民族地区经济增长的重要手段。随着2010年新一轮对口支援新疆工作的实施启动,亟需加强该领域的理论研究。基于府际关系的理论视角,以江苏省对口支援伊犁州直为例,分析对口援疆中府际关系网络的形成、利益相关者的作用和利益诉求,进而探讨了对口援疆工作合作方式。研究表明,援疆的府际关系网络是由纵向府际关系促成横向府际关系而建立的复杂网络,在这一网络中,中央政府以协调区域关系为主,江苏省政府、新疆维吾尔自治区政府、伊犁州政府起政策过渡作用,伊犁州直各县市等受援方最关注如何使用援助资金改善民生、完善基础设施,江苏市区县等施援方对建立产业合作最为重视。对口援疆是双方府际关系发展的一个阶段,今后发展的重点将逐渐转向充分利用地缘和资源优势打造产业平台,实现优势互补,变“对口支援”关系为“战略型伙伴”关系。     

新疆阿勒泰地区中低产田及其改造措施

中低产田指农作物产量低下的耕地。中低产田生产潜力大,对其改造的经济和生态效益均大于新垦荒地,在水少地多和生态脆弱的干旱区尤其如此,对其加强研究与改造是十分重要的。阿勒泰地区中低产田分布广,面积大,成因复杂,在新疆有较好的代表性。本文论述阿勒泰地区中低产田的分布、类型,分析中低产田的成因,并提出改造措施。     

黔东南州可持续发展的度量研究——基于BEF与TEF的综合测度

在生态足迹模型的基础上,将生态足迹划分为本底生态足迹和旅游生态足迹,构建了本地生态足迹模型,由饮食、住宿、交通、游乐、购物和废物6个子模块组成的旅游生态足迹模型,以区域可持续发展差量、区域可持续发展指数、区域生态效率指数为指标的可持续发展度量模型,综合评价区域可持续发展状态;以贵州省黔东南苗族侗族自治州为研究区域,进行了西部典型山区可持续发展的度量研究;研究结果表明。黔东南州2005年资源消耗以本地居民消耗为主,游客对生态足迹贡献率较小,旅游生态足迹约为89 660 hm2,仅为本底生态足迹的1/15,且以交通子模块贡献率最大;2 362.97美元/hm2的旅游生态效率指数远高于457.58美元/hm2的非旅游生态效率指数,亦高于1 106美元/hm2的全球生态效率指数;生态承载力供给盈余约为859 859 hm2,区域可持续发展指数为0.61,全州处于"良"的可持续发展状态。     

Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture

Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry. Quantitative assessment of the relative contributions of climate change and human activities, which are considered as the dominant triggers of grassland degradation, to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture. In this paper, the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity (NPP_A) and potential net primary productivity (NPP_P) in the Altay Prefecture from 2000 to 2019. Meanwhile, the difference between potential NPP and actual NPP was employed to reflect the effects of human activities (NPP_H) on the grassland. On this basis, we validated the viability of the simulated NPP using the Pearson correlation coefficient, investigated the spatiotemporal variability of grassland productivity, and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture. The results indicate three main points. (1) The simulated NPP_A was highly consistent with the MOD17A3 dataset in spatial distribution. (2) Regions with an increased NPP_A accounted for 70.53% of the total grassland, whereas 29.47% of the total grassland area experienced a decrease. At the temporal scale, the NPP_A presented a slightly increasing trend (0.83 g C m^?2 yr^?1) over the study period, while the trends of NPP_P and NPP_H were reduced (?1.31 and ?2.15 g C m^?2 yr^?1). (3) Compared with climate change, human activities played a key role in the process of grassland restoration, as 66.98% of restored grassland resulted from it. In contrast, inter-annual climate change is the primary cause of grassland degradation, as it influenced 55.70% of degraded grassland. These results could shed light on the mechanisms of grassland variation caused by climate change and human activities, and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.     

Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine

Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development. In the past 20 years, the ecological environment in Altay Prefecture has changed significantly due to global warming. Meanwhile, with increasing human activities, the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess. Hence, we quantified the vegetation growth by using the Normalized Difference Vegetation Index (NDVI) on the Google Earth Engine (GEE). Then, the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale. Finally, significance threshold segmentation was performed using meteorological data based on the correlation analysis results, and the contributions of climate change and human activities to vegetation variation were quantified. The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north. The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture, respectively. Moreover, spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature, precipitation and sunlight hours accounted for 3.3%, 6.9% and 20.3% of Altay Prefecture, respectively. In the significant restoration area, 18.94% was dominated by multiple factors, while 3.4% was dominated by human activities, and 1.74% was dominated by climate change. Within the significant degradation area, abnormal degradation and climate change controlled 1.07% and 0.17%, respectively. This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture, and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture.