Spatial and seasonal variation of major ions in Himalayan snow and ice: A source consideration

The spatial and temporal variation of major ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, , , and Cl⁻) in Himalayan snow and ice is investigated by using two snow pits from the East Rongbuk glacier (28°01′N, 86°58′E, 6500 m a.s.l.), one snow pit from the Nangpai Gosum glacier (28°03′N, 86°39′E, 5700 m a.s.l.), one snow pit from the Gyabrag glacier (28°11′N, 86°38′E, 6303 m a.s.l.), and three ice cores from the Sentik (35°59′N, 75°58′E, 4908 m a.s.l.), Dasuopu (28°33′N, 85°44′E, 7000 m a.s.l.), and East Rongbuk (27°59′N, 86°55′E, 6450 m a.s.l.) glaciers, respectively. In general, the major ions show a significant seasonal variation, with high concentrations during the non-monsoon (pre-monsoon and post-monsoon) season and relatively low concentrations during the monsoon season. Monsoon precipitation with high local/regional dust loading related to summer circulation is possibly responsible for the high concentrations occurring sporadically during the monsoon season. The crest of the Himalayas is an effective barrier to the spatial distribution of Na⁺, Cl⁻ and concentrations, but not to the major ions associated with dust influx (e.g. Ca²⁺ and Mg²⁺). Atmospheric backward trajectories from the HYSPLIT_4 model used in identifying chemical species sourcing suggest that the major ions in the Himalayan snow and ice come mainly from the Thar Desert located in the North India, as well as West Asia, or even the distant Sahara Desert in the North Africa during the winter and spring seasons. This is different from the conventionally assumed arid and semi-arid regions of the central Asia. Factors, such as different vapor sources due to atmospheric circulation patterns and geographical features (e.g. altitude, topography), may contribute to the differences in major ionic concentrations between the western and eastern Himalayas.     

Biodiversity and invasibility: Distribution patterns of invasive plant species in the Himalayas,Nepal

Invasive plant species are exerting a serious threat to biological diversity in many regions of the world. To understand plant invasions this study aims to test which of the two plant invasiveness hypotheses; ‘low native diversity' vs. ‘high native diversity', is supported by the regional distribution patterns of invasive plant species in the Himalayas,Nepal. This study is based on data retrieved from published literatures and herbarium specimens. The relationship between invasive plant species distribution patterns and that of native plant species is elucidated by scatter plots, as well as by generalized linear models. The native plant species and invasive plant species have similar distribution patterns and the maximum number of invasive plant species is found in the same altitudinal range where the highest richness for native tree species is found. There is a clear trend of higher invasive plant richness in regions where native tree species richness is relatively high.Consequently, the native plant richness is highest in the central phytogeographic region, followed by the eastern and the western regions, respectively. The invasive plant species also follows a similar trend.Additionally, the invasive plant species richness was positively correlated with anthropogenic factors such as human population density and the number of visiting tourists. This study supports the hypothesis that ‘high native diversity' supports or facilitates invasive plant species. Further, it indicates that nativeand invasive plant species may require similar natural conditions, but that the invasive plant species seem more dependent and influenced by anthropogenic disturbance factors.     

南海温度锋的分布特征及季节变化

利用50a(1950—2007年)的SODA(Simple Ocean Data Assimilation)数据分析了南海上层温度锋分布特征以及季节变化规律。结果表明:受季风、太阳辐照以及诸多因素影响,温度锋季节变化明显,锋面结构复杂。冬季,温度锋基本沿陆架分布,存在于南海北部海区,从台湾海峡一直延伸到北部湾,发育比较显著;春季,主要出现在南海北部海区、北部湾、越南东部海岸,分布比较广泛;夏季温度锋出现概率增加,出现区域扩大,越南东部出现大面积温度锋;秋季南海中西部海域存在大面积的温度锋。     

南海大眼金枪鱼和黄鳍金枪鱼生物学特性及其分布

利用2010年3月—2013年2月南海金枪鱼延绳钓探捕与渔业生产监测取得的生物学数据和生产数据,对南海的大眼金枪鱼(Thunnus obesus)和黄鳍金枪鱼(Thunnus albacres)的生物学特性和渔场分布进行了研究。结果表明:(1)南海大眼金枪鱼叉长范围50—169cm,平均为111.8cm,体重范围2.45—87kg,平均为33.2kg,叉长(FL)体重(W)关系:W=1.74×10–5FL3.01,性腺成熟度Ⅱ期居多,占总尾数的45.27%。绝对怀卵量109.46—456.95万粒,摄食强度以0—2级为主。大眼金枪鱼延绳钓渔场春夏季分布于南沙西北部和南沙中西部海域;秋冬季分布于西、中沙和南沙西北部海域。渔获水深90%集中在150—400m。(2)南海黄鳍金枪鱼叉长范围41—180cm,平均为107.9cm,体重范围1.2—77.5kg,平均为27.9kg,叉长体重关系:W=2.19×10–5FL2.94,性腺成熟度以Ⅱ—Ⅳ期居多,占总尾数的89.01%,绝对怀卵量15—154万粒,摄食强度以1—2级为主。黄鳍金枪鱼延绳钓渔场春夏季分布于南沙西北部和南沙中西部海域;秋冬季分布于西、中沙、南沙西北部、南沙中西部海域。渔获水深93.75%集中在50—350m。西沙西部和南沙西北部海域是灯光围网和灯光罩网捕捞金枪鱼的重要渔场。研究认为:(1)在南海可发展小型冷海水延绳钓船,在每年10月末—次年5月初在西沙东北海域开展浅水延绳钓作业;(2)在南海的岛礁附近设置PAYAO群,开展金枪鱼灯光罩网或围网捕捞。(3)目前取得的资料仍然有限,未来仍需进一步调查,以掌握南海金枪鱼种群动态,为渔业开发和养护提供建议。     

经验模态分解和独立分量分解在航磁数据处理中的应用

以东天山1∶20万航磁数据为例,利用经验模态分解(EMD)方法对航磁数据进行分解,然后利用独立分量分析(ICA)方法对分解出的固有模态函数(IMF)数据进行重构。分解出来的从高频到低频IMF与地质体的分布具有一定的相关性,不同频率的IMF代表了一定的地质意义。经过ICA重构后的独立分量(IC)能够对异常IMF函数从盲源分离的角度进行有效的重构,其结果可以在一定程度上解释不同的地质事件对磁异常的贡献,并对构造识别和构造区域划分具有一定的指示意义。     

Chemical and physical properties affecting strontium distribution coefficients of surficial-sediment samples at the Idaho National Engineering and Environmental Laboratory, Idaho

 The U.S. Geological Survey and Idaho State University, in cooperation with the U.S. Department of Energy, conducted a study to determine strontium distribution coefficients (K_ds) of surficial sediments at the Idaho National Engineering and Environmental Laboratory (INEEL). Batch experiments using synthesized aqueous solutions were used to determine K_ds, which describe the distribution of a solute between the solution and solid phase, of 20 surficial-sediment samples from the INEEL. The K_ds for the 20 surficial-sediment samples ranged from 36 to 275 ml/g. Many properties of both the synthesized aqueous solutions and sediments used in the experiments also were determined. Solution properties determined were initial and equilibrium concentrations of calcium, magnesium, and strontium, pH and specific conductance, and initial concentrations of potassium and sodium. Sediment properties determined were grain-size distribution, bulk mineralogy, whole-rock major-oxide and strontium and barium concentrations, and Brunauer-Emmett-Teller (BET) surface area. Solution and sediment properties were correlated with strontium K_ds of the 20 surficial sediments using Pearson correlation coefficients. Solution properties with the strongest correlations with strontium K_ds were equilibrium pH and equilibrium calcium concentration correlation coefficients, 0.6598 and –0.6518, respectively. Sediment properties with the strongest correlations with strontium K_ds were manganese oxide (MnO), BET surface area, and the >4.75-mm-grain-size fraction correlation coefficients, 0.7054, 0.7022, and –0.6660, respectively. Effects of solution properties on strontium K_ds were interpreted as being due to competition among similarly charged and sized cations in solution for strontium-sorption sites; effects of sediment properties on strontium K_ds were interpreted as being surface-area related. Multivariate analyses of these solution and sediment properties resulted in r² values of 0.8071 when all five properties were used and 0.8043 when three properties, equilibrium pH, MnO, and BET surface area, were used. Received: 30 November 1998 · Accepted: 16 February 1999     

全球海洋人为碳储量估算及时空分布研究进展

海洋是全球最大的碳汇,确定海洋中人为碳含量及其时空变化是一件具有挑战性的工作。就当前海洋人为碳含量确定方法、人为碳储量及其随时间变化进行综述总结。研究表明海洋仍然可以吸收并储藏大量的人为碳,但未来对于海洋吸收储藏人为碳的研究仍具有诸多不确定性。已有证据表明稳态海洋的概念不完全正确,需要在非稳态条件下重新定义人为碳并开展研究。同时需要积累更多的观测数据,采用包括观测和模式模拟等手段来研究不同时间尺度的人为碳的吸收和储藏过程。     

Modelling spatial distribution of critically endangered Asian elephant and Hoolock gibbon in Bangladesh forest ecosystems under a changing climate

The Asian elephant (Elephas maximus) and Hoolock gibbon (Hoolock hoolock) are two globally endangered wildlife species limited to only tropical Asian forests. In Bangladesh both species are critically endangered and distributed mainly in the northeast and southeast hilly regions bordering neighboring India and Myanmar. Using existing distribution data, land-use/land cover, elevation and bio-climatic variables, we modeled the likely distribution of Asian elephant and Hoolock gibbon in Bangladesh for 2050 and 2070. We used the IPCC's Representative Concentration Pathways (RCPs) – RCP6.0 and RCP8.5 and Maximum Entropy algorithm for our modelling. Our study indicated that the Asian elephant will be more resilient to climate change compared with the Hoolock gibbon. Habitat loss for the Asian elephant is also expected to remain constant (i.e. 38%) throughout the period, whilst Hoolock gibbon habitat will be more sensitive to climatic variations, with the species predicted to be extirpated from the country by 2070. Being highly exposed to climate change with ever increasing land use pressures, we believe our study in Bangladesh can be used to enhance our understanding of future vulnerabilities of wildlife in a rapidly changing climate. A trans-boundary conservation program with greater attention to the species that are less resilient to climate change is also essential.     

Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy

Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS – Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R² of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R² of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.