Phylogenetic analysis of snow sheep (Ovis nivicola) and closely related taxa

Based on mitochondrial cytochrome b gene sequence analysis, the history of true sheep ( Ovis) began approximately 3.12 million years ago ( MYA). The evolution of Ovis resulted in three generally accepted genetic groups: Argaliforms, Moufloniforms, and Pac

Group Size and Composition of Black．and．White Snub．nosedMonkey(rhinopithecus)Estimated by Faecesof Sleeping Sites at Baima Snow Mountain

介绍了应用过夜地粪便来估计白马雪山黑白仰鼻猴群大小和组成的一种方法。该物种以单雄多雌单 元和全雄组的形式在树上过夜。粪粒根据其大小可分为3种类型：成年雄性的(最大)、成年雌性的(中等大小)和 未成年个体的(最小)。2000一2001年，搜集了滇西北白马雪山国家级自然保护区北部南任村(99。04 7E，28。34 7N) 附近黑白仰鼻猴群每个季节2个过夜地的粪粒。根据2001年11月猴群通过开阔地的数据来确定猴群组成。每个 季节，由于单雄多雌单元的成年个体数与其粪粒数正相关，所以二者回归直线的斜率可以看作是每个个体每晚 的平均排便量。由于该物种的栖息地主要为高山峡谷，而且能见度较低，因此，利用过夜地粪便比以前通过猴群 活动痕迹来估计猴群大小和组成相对准确、可靠。从估计成年雌性个体数的角度看，利用粪粒来估计种群大约有 9．4％的偏差。导致偏差的可能原因有杂草和灌丛对粪粒准确计数的影响、个体排粪率的差异以及成年雄性最小 粪粒与成年雌性最大粪粒的混淆等。该方法适应于栖息地和主要食物与本文研究种群相似的其他种群。

Sleeping sites of black-and-white snub-nosed monkeys (Rhinopithecus bieti) at Baima Snow Mountain, China

Data on sleeping sites of a group of black-and-white snub-nosed monkeys Rhinopithecus bieti (Colobinae, Primates) were collected between April-July and September-December 2001 to try to determine the factors affecting site selection at Nanren (99 degrees

Role of snow depth in spring of Tibetan Plateau in onset of South China Sea summer monsoon

The role of snow depth of Tibetan Plateau in the onset of South China Sea summer monsoon and the influence of ENSO on snow depth of Tibetan Plateau are investigated with use of data from ECMWF reanalysis and NCEP/NCAR reanalysis. The results are as follows: (1) The snow depth data from ECMWF reanalysis are tested and reliable, and can be used to study the influence of snow depth of Tibetan Plateau on the onset of South China Sea summer monsoon; (2) Anomaly of snow depth of Tibetan Plateau causes anomaly in air temperature and its contrast between the Indian Ocean and the continent resulting in easterly wind anomaly over 500 hPa and hence as well as in the atmospheric circulation in the lower layer. For the year of negative anomaly of snow depth a westerly wind anomaly with a cyclone pair takes place, while for positive anomaly of snow depth an easterly anomaly occurs with an anticyclone pair; (3) While positive anomaly of SST occurs in the eastern Pacific Ocean, positive anomaly of air pressure also takes place over the eastern Indian Ocean and the South China Sea, causing stronger meridional pressure gradient between the ocean and continent and then westerly wind anomaly. At the same time, the atmospheric pressure increases in the northern Tibetan Plateau, northerly wind gets stronger, and subtropical front strengthens. All of these are favorable for snowfall over Tibetan Plateau.

Assessing the potential of VEGETATION sensor data for mapping snow and ice cover: a Normalized Difference Snow and Ice Index

The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSIITM =(TM3 -TM5)/(TM3 +TM5); for VGT data, NDSII is calculated as NDSIIVGT =(B2- MIR)/(B2 + MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSIIVGT.