太湖水-气界面CO2交换通量观测研究

基于2003-01～2005-06利用静态箱法对太湖水-气界面CO₂交换通量的观测,对太湖水-气界面交换通量的变化特征进行了分析研究.结果表明:太湖水-气界面CO₂交换通量存在明显的日变化,春、夏、秋、冬4季日平均通量分别为-0.79mg/(m²·h)、-4.89 mg/(m²·h)、-4.06 mg/(m²·h)和-2.56 mg/(m²·h),太湖均是CO₂的汇.一般污染越重的区域,CO₂通量值越大.藻型湖区水-气界面CO₂交换通量季节变化不明显,草型湖区水-气界面CO₂交换通量季节变化很明显,夏秋季高,冬春季低.CO₂通量变化的可能相关因子还有天气情况、太阳辐射、风速及水温、pH、TA、Chla、TC、TN和TP等.     

VARIATION FEATURES OF PRECIPITATION IN GUANGXI

VariationfeaturesofprecipitationinGuangxiUnevendistributionofprecipitationinareas　ByreasonofcomplexlandforminGuangxi,theprecipitationvariesindifferentregionsandisgenerallyabundantinthesouthandthenorth,littleinthemiddleregion;abundantintheeastandlittleinthewest;abundantinhillyareasandlittleintherivervalleysandbasins;abundantinwindwardslopesandlittleinleewardslopes;abundantincoastlandandlittleinis lands.Therearemainly 4 pluvialregionsand 2littlerainfallregions.The 4pluvialregionswithprecipitat…     

陕西泾阳4.8级地震前后重力变化与断裂活动

本文对泾阳Ms4．8级地震前后陕西关中地区流动重力观测资料和有关断裂垂直形变资料进行了分析研究。结果表明：①波速比高值区很可能存在地下深部地幔物质的入侵，由此引发地震和重力场的显著下降；②用震源机制解和GPS所作的运动矢量图可以较好地解释泾阳地震前后重力场时空演化特征及有关断裂活动——其变化是北西向剪切应力带作用的结果．     

塔克拉玛干沙漠腹地沙尘暴特征--以塔中地区为例

塔克拉玛干沙漠是中国油气开发的重要区域，沙尘暴是该区域重要的灾害性天气，但以往相关的研究很少。为了了解塔克拉玛干沙漠腹地沙尘暴的发生规律，利用塔中气象站1997-2002年的气象资料，对塔中地区沙尘暴的强度、过程、类型和时间变化等特征进行了分析。研究结果表明：（1）塔中年平均沙尘暴日数为16．83d，较沙漠北缘的轮台和沙漠南缘的民丰、和田为多，体现出沙尘源对沙尘暴发生的影响；（2）沙尘暴发生之前出现明显的风速突然降低和风向转换；（3）同塔里木盆地其它区域一样，塔中沙尘暴也可分为5种类型，其主导类型为冷空气东灌型；（4）沙尘暴时间变化规律明显，且从20世纪90年代至21世纪初，塔中沙尘暴日数与持时明显下降，同全疆的变化趋势一致。     

我国物流产业基本经济活动空间格局分析

基于经济基础理论,对1991～2001年间我国各省区物流产业基本经济活动部分进行了实证分析,从省际差异、东中西部差异两个方面分析了我国区域物流产业基本经济活动的省区差异:在时间维度上区域差异呈逐步扩大趋势,在空间结构上表现出较明显的沿海指向性和交通指向性,并以此分析归纳出我国物流产业基本活动的"四区(物流集聚区)一带(物流集聚带)"空间格局特征,进而得出其基本经济活动强度与区域经济发展水平、物流需求程度、科技水平、区位条件、交通等基础设施、政策及历史发展作用紧密相关的结论.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

THE INFLUENCE OF CLIMATE VARIATION ON THE ESTIMATION OF LOW FLOWS USED TO PROTECT WATER QUALITY: A NATIONWIDE ASSESSMENT1

ABSTRACT: Historical flow records are used to estimate the regulatory low flows that serve a key function in setting discharge permit limits through the National Pollutant Discharge Elimination System, which provides a nationwide mechanism for protecting water quality. Use of historical records creates an implicit connection between water quality protection and climate variability. The longer the record, the more likely the low flow estimate will be based on a broad set of climate conditions, and thus provides adequate water quality protection in the future. Unfortunately, a long record often is not available at a specific location. This analysis examines the connection between climate variability and the variability of biologically based and hydrologically based low flow estimates at 176 sites from the Hydro‐Climatic Data Network, a collection of stream gages identified by the USGS as relatively free of anthropogenic influences. Results show that a record of 10 to 20 years is necessary for satisfactory estimates of regulatory low flows. Although it is possible to estimate a biologically based low flow from a record of less than 10 years, these estimates are highly uncertain and incorporate a bias that undermines water quality protection.     

Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities

A data analysis of three major Korean cities was conducted to assess roadside inhalable particulate matter 10 μm or smaller in aerodynamic diameter (PM₁₀), including temporal and meteorological variations, over a recent period of 4 to 6 years. The yearly roadside PM₁₀ concentrations presented a well-defined increasing trend or no trend depending on the roadside monitoring station. Most mean values exceeded or approximated the Korean standard of 70 μg/m³ per year for PM₁₀. A representative roadside diurnal trend was characterized by a distinct morning maximum. In most cases, the Sunday roadside concentrations were similar to or somewhat lower than the weekday concentrations, and the PM₁₀ concentrations presented a well-defined seasonal variation, with the maximum concentration in March. The monthly maximum concentrations observed in March were most likely attributable to Asian dust storms. In two metropolitan cities (Seoul and Busan), the frequency of days with roadside PM₁₀ concentrations exceeding the standard of 150μg/m³ per 24 h was much lower for the roadside monitoring stations than for the residential monitoring station, whereas in the third city (Daegu), this result was reversed. Interestingly, the average maximum concentrations observed for the roadside sites in Seoul and Busan during March were higher than those for the residential sites, suggesting that the roadside concentrations responded more to the dust storms than the residential areas. The relationship between the pollutant concentrations and five important meteorological parameters (solar radiation, wind speed, air temperature, relative humidity, and precipitation) showed that the number and type of meteorological variables included in the equations varied according to the monitoring station or season. Finally, the current results confirmed that attention should be given to the PM₁₀ exposure of residents living near roadways.     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado