The glacier area changes in the Qangtang Plateau based on the multi-temporal grid method and its sensitivity to climate change

Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melting of glaciers accelerated,only a few of glaciers in an advancing state during 1970-2000 in the whole Qangtang Plateau.However,the glaciers seemed still more stable in the study area than in most areas of western China.We estimate that glacier retreat was likely due to air temperature warming during 1970-2000 in the Qangtang Plateau.Furthermore,the functional model of glacier system is applied to study climate sensitivity of glacier area changes,which indicates that glacier lifespan mainly depends on the heating rate,secondly the precipitation,and precipitation increasing can slow down glacier retreat and make glacier lifespan prolonged.     

广州地区稻田甲烷排放及中国稻田甲烷排放的空间变化

１９９３年在广州地区采用中国科学院大气物理研究所研制的自动采集和分析系统测量了稻田甲烷的排放率，首次获得了占我国２０－２５％左右水稻收获面积的华南地区稻田甲烷排放特征值。从而宏观地使我国五个主要水稻生态区的甲烷排放率都有了实测资料。稻田甲烷排放率的季节变化主要与气温及灌溉水状态的变化的较大关系，日变化规律以下午出现极大为主。本实验田的甲烷排放率低。     

中国火山温泉气体地球化学特征及其在火山监测中的应用

中国火山温泉主要分布在吉林长白山、云南腾冲和黑龙江五大连池等火山区。这些火山虽然处于休眠状态,但大面积的温泉分布指示着岩浆房存在的可能性。本文总结了前人研究成果,分析了中国主要火山区温泉气体地球化学特征,并探讨了温泉气体在火山监测中的应用。长白山、腾冲和五大连池火山区温泉气体地球化学性质类似,都以CO₂为主要气体,含量在80%以上,最高可达99%以上,其它气体组分包括CH₄、N₂、O₂、SO₂、H₂S、He和H₂等。长白山火山温泉气体中氦同位素比值（3He/4He）最高,约为4—6R_A,CO₂中碳同位素比值（δ13C）为-7.9‰—-1.3‰,CH₄中碳同位素为-48.0‰—-28.7‰;腾冲火山温泉气体氦同位素比值为3—5.5R_A,CO₂中的碳同位素为-6.49‰—-2.07‰,CH₄中碳同位素为-23.5‰—-9.3‰;五大连池火山温泉气体氦同位素比值约为3R_A,CO₂中的碳同位素比值为-9.6‰—-3.1‰,CH₄中碳同位素为-47.2‰—-44.4‰。3个火山区的温泉气体均显示地幔来源的岩浆气体特征,并在上升运移过程中受地壳或古俯冲物质的影响。     

Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data

Soil moisture (SM) is a key variable of land surface‐atmosphere interactions. Data‐driven methods have been used to predict SM, but the predictability of SM has not been well evaluated. This study investigated what variables and methods can be used to better predict SM for leading times of 7 days or longer with a global coverage of FLUXNET site data for the first time. Three machine‐learning models, that is, Bayesian linear regression, random forest, and gradient boosting regression tree, are used for the prediction. Variables including atmospheric forcing, surface soil temperature, time variables (year, day of year, and hour), the Fourier transformation of time variables, and lagged SM (7‐ to 14‐day lagged) were sequentially added into models. A framework with five experiments is designed for factorial exploration of SM predictability. A stepwise method was used to build the best models for each site. The performance of regression models became better when adding more explaining variables in most cases. The results showed that from 50 to 95% of variation of the best models can be explained. The important explaining variables are lagged surface SM, followed by day of year, year, soil temperature, and atmospheric forcing. The predictability of SM depends highly on SM memory characteristics and the persistence of seasonality. The effect of SM memory characteristics on SM prediction as an initial condition question has been widely discussed in this paper. Our results also provide an insight that mechanisms of seasonality effects on SM should be also paid more attention to.     

稻田CH4的排放规律

通过对我国长江中下游地区、西南地区及华中地区这三大主要水稻区稻田CH_4排放的多年测量,描述了稻田CH_4排放的一般规律及特征。稻田CH_4排放的日变化有三种型式,即下午最大值型式、夜间最大值型式以及下午、夜间双峰型式,导致这三种型式的主要原因是CH_4排放路径的日变化;不同品种水稻的不同生理特性、天气条件会通过改变CH_4排放路径的日变化来改变CH_4排放日变化的型式;随着水稻生长,CH_4排放日变化幅度也会随着变化。 早稻与晚稻稻田CH_4排放的季节变化型式不一致。早稻的CH_4排放一般出现三个排放峰值,其中第一个与第三个峰值是由土壤中CH_4的产生率增加引起的,第二个峰值则是由于CH_4排放路径的畅通引起的。四川地区单季稻CH_4排放的季节变化与早稻比较一致,但是没有第一个排放峰值的出现。引起早、晚稻不同季节变化的原因是水稻生长季节中气温的季节变化。灌溉水状态也能够较大程度的影响稻田CH_4的排放的季节变化。 含SO_4~(2-)的肥料能够降低CH_4的排放,但其作用的大小取决于土壤中有机物质(肥)的数量;施尿素、KCl也能够使CH_4排放降低,但它的降低效应没有有机肥使CH_4排放增大的正效应大,这说明有机肥对CH_4排放的影响很大,而在空气中堆腐过的沼渣肥使稻田CH_4的排放大大降低。不同的施肥使     

内蒙白云鄂博铁矿床中磁铁矿和赤铁矿的氧同位素组成

白云鄂博矿床分布在内蒙地轴北部边缘的过渡带。含矿岩系为元古代海相沉积碳酸盐、碎屑岩建造,主要由石英岩、白云岩和板岩组成,其中白云岩是矿体围岩。 矿床受东西向向斜构造控制。向斜以北为一大背斜构造,沿轴部被断层破坏,出露有古老的片麻岩和片岩。向斜以南的背斜构造轴部有海西期黑云母花岗岩侵入,使背斜构造轴部遭受破坏。     

发酵浒苔对珍珠龙胆石斑鱼生长、非特异性免疫及消化酶活性的影响

浒苔经发酵后按添加比例（0%、1%、2%、3%、4%、5%）分别加入到珍珠龙胆石斑鱼（Epinephelus lanceolatus♂×Epinephelus fuscoguttatus♀）基础饲料中配制成6种饲料,用以探讨发酵浒苔对珍珠龙胆石斑鱼生长、肠消化酶活性及血清非特异性免疫力的影响。选用初始平均体质量为（19.16±0.25）g的珍珠龙胆石斑鱼为研究材料,试验周期28 d。结果表明:发酵浒苔能显著影响石斑鱼的增重率（WGR）和特定生长率（SGR）（P<0.05）,且随着发酵浒苔添加水平的升高呈现先升高后降低的趋势,在2%组添加量时显著高于对照组。同时,相比于对照组,各添加组饲料系数（FCR）均有下降,在2%组时显著降低（P<0.05）。添加发酵浒苔可以显著提高血清总超氧化物歧化酶（T-SOD）、碱性磷酸酶（AKP）和酸性磷酸酶（ACP）的活性（P<0.05）,但对溶菌酶（LZM）和酚氧化酶（PO）活性影响差异不显著（P>0.05）。在添加组中,淀粉酶、脂肪酶以及胰蛋白酶活性均得到了显著提高（P<0.05）,添加水平在2%~3%时效果最好。综合发酵浒苔对珍珠龙胆石斑鱼的作用效果可以看出,发酵浒苔可以明显促进其生长,提高非特异性免疫力及肠道中消化酶活力,建议发酵浒苔在饲料中添加量为2%左右。     

中国西部冰川对近期气候变暖的响应*

中国冰川主要分布在青藏高原及周边地区,在这一广大的区域内分布有冰川46377条。研究表明,中国西部变暖显著,1950年代以来平均气温上升0.2℃/10a,其中1990年代是近千年中最暖的10年;同时,1950s以来西北各省的降水量增加了约18 ％ 。为认识这一气候变化对中国西部冰川的影响,利用遥感和地理信息系统方法,获取了近50a来5000多条冰川的变化状况。结果表明,中国西部82.2 ％ 的冰川处于退缩状态,冰川面积减少了4.5 ％ ,同时也有一些冰川处于前进状态。此外,近数十年中国西部冰川变化表现出明显的区域差异,青藏高原中部和西北部地区的冰川相对稳定,而高原周边山区的冰川物质亏损严重,处于加速退缩状态。     

Cytological studies on neurosecretory cell of the X-organ in Scylla serrata

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A study on the flora of woody plants of Shanxi and the relationship among the flora of Shanxi and some regions, China

There are 463 species of woody plant, belonging to 166 genera and 70 families in Shanxi, North China. The floristic composition types of genera and species are abundant, in which the compositions distributed in temperate zones (including North Temperate, Old World Temperate and Temperate Asia), having 62 genera, are dominant and account for 38.27% in total genera (except for Cosmopolitan), and they are major constructive or dominant species of vegetation in Shanxi. The floristic compositions of woody plants of Shanxi, Hebei, Beijing, Shandong, Henan, Jiangxi and Inner Mongolia were studied comparatively by using diversity index, principal component analysis (PCA) and group-average clustering, respectively. The floristic composition of Shanxi was considerably similar to that of Hebei, Beijing and Shandong because they shared a lot of genera, specially genera distributed in temperate regions, such as Rosa, Quercus, Populus, Salix, Acer, Ulmus, Pinus etc. and their eco-environment were considerably similar. However, the flora of Shanxi was comparatively different from that of Henan, Jiangxi and Inner Mongolia by reason that there were distinct differences among their eco-geographic conditions, floristic compositions and constructive or dominant species of dominant vegetation types. Supported by Shanxi Returned Oversea Scholar Foundation, China