土地利用和土地覆盖变化研究模型综述

本文综述了全球变化研究中土地利用和土地覆盖变化（ＬＵＣＣ）的主要模型,重点介绍了植被模型和引入社会驱动力的ＬＵＣＣ模型,并归纳出ＬＵＣＣ模型的以下发展趋势：①新一代的ＬＵＣＣ模型应该能够模拟ＬＵＣＣ的主要社会经济和自然驱动力,包括从ＬＵＣＣ到驱动力和全球变化的主要反馈关系；②具有明确的空间关系,能够以适当的空间分辨率,比较好地预测长期的（５０～１００ａ）土地利用和覆盖变化及有关的生物物理参数,如植被特征、资源的积聚和退化等；③能够更好地认识ＬＵＣＣ与其主要驱动力之间的关系在局地、区域和全球尺度上的动态和后果；充分考虑土地利用和覆盖变化对政策、技术进步、人口增长、经济发展、市场变化等社会变量的灵敏性,此外,还应注意意识、信仰等文化因素的影响；④发展新的ＬＵＣＣ建模方法,使ＬＵＣＣ模型能够与其它类型的全球变化模型,特别是气候模型建立联系。     

Flooding in Texas: Examination of Temporal Changes and Impacts of Tropical Cyclones

Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann‐Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.     

干旱区城市昌吉降雪及积雪中PGEs含量分布及其影响因素

选择干旱区中小城市昌吉市,对其降雪及积雪中铂族元素(PGEs)含量分布及影响因素进行研究.运用ICP-MS对样品进行分析测定.结果表明,降雪中Rh、Pd、Pt平均含量分别为0.43 ng·L-1(未检出～2.24 ng·L-1)、60.07 ng·L-1(46.66～84.25 ng·L-1)和4.54 ng·L-1(3.02～6.38 ng·L-1).不同场次降雪中PGEs含量存在差异,随雪前干燥期天数加长,降雪中PGEs含量趋于增大;降雪量对PGEs含量也有一定影响,降雪量越小,雪中PGEs含量越高.积雪中Rh、Pd、Pt的平均含量分别为6.65 ng·L-1(2.50～18.80 ng·L-1)、83.45 ng·L-1(46.83～199.20 ng·L-1)和8.17 ng·L-1(4.27～13.78 ng·L-1).积雪中PGEs含量远高于降雪,降雪中PGEs仅来自于单场次降雪对大气PGEs的淋洗,而积雪中PGEs不仅来自于多场次降雪中PGEs的累积,且由于积雪长时间暴露,还源源不断接受了大气干沉降带来的PGEs.各采样点积雪PGEs含量表现出交通区>居民文教区>公园广场区>郊区农田,随功能区不同,积雪中PGEs输入途径与输入量有显著差异,这是造成各功能区积雪PGEs含量不同且具有一定规律性的主要原因.     

Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore,Maryland1

Smith, Monica Lipscomb, Weiqi Zhou, Mary Cadenasso, Morgan Grove, and Lawrence E. Band, 2010. Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland. Journal of the American Water Resources Association (JAWRA) 46(2):429-442. DOI: 10.1111/j.1752-1688.2009.00412.x Abstract: We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km², 9 km², and gauged watershed scales within the Baltimore Ecosystem Study to determine the usefulness and limitations of the NLCD in heterogeneous urban to exurban environments for the determination of land-cover information for hydrological applications. Although the NLCD canopy and impervious data are significantly correlated with the high-resolution land-cover dataset, both layers exhibit bias at <10 and >70% cover. The ratio of total impervious area and connected impervious area differs along the range of percent imperviousness – at low percent imperviousness, the NLCD is a better predictor of pavement alone, whereas at higher percent imperviousness, buildings and pavement together more resemble NLCD impervious estimates. The land-cover composition and range for each NLCD urban land category (developed open space, low-intensity, medium-intensity, and high-intensity developed) is more variable in areas of low-intensity development. Fine-vegetation land-cover/lawn area is incorporated in a large number of land use categories with no ability to extract this land cover from the NLCD. These findings reveal that the NLCD may yield important biases in urban, suburban, and exurban hydrologic analyses where land cover is characterized by fine-scale spatial heterogeneity.     

Photoinduced reduction of divalent mercury in ice by organic matter

Reduction of divalent mercury and subsequent emission to the atmosphere has been identified as loss process from surface snow, but its mechanism and importance are still unclear. The amount of mercury that stays in the snow pack until spring is of significance, because during snow melt it may be released to the aquatic environment and enter the food web. Better knowledge of its fate in snow might further assist the interpretation of ice core data as paleo-archive. Experiments were performed under well-controlled laboratory conditions in a coated wall flow tube at atmospheric pressure and irradiated with light between 300 nm and 420 nm. Our results show that the presence of benzophenone and of oxalic acid significantly enhances the release of mercury from the ice film during irradiation, whereas humic acid is less potent to promote the reduction. Further it was found that oxygen or chloride, and acidic conditions lowered the photolytically induced mercury release in the presence of benzophenone, while the release got larger with increasing temperatures.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.     

A regression tree-based method for integrating land-cover and land-use data collected at multiple scales

As data sets of multiple types and scales proliferate, it will be increasingly important to be able to flexibly combine them in ways that retain relevant information. A case in point is Amazonia, a large, data-poor region where most whole-basin data sets are limited to understanding land cover interpreted through a variety of remote sensing techniques and sensors. A growing body of work, however, indicates that the future state of much of Amazonia depends on the land use to which converted areas are put, but land use in the tropics is difficult to assess from remotely sensed data alone. An earlier paper developed new snapshots of agricultural land use in this region using a statistical fusion of satellite data and agricultural census data, an underutilized ancillary data source available across Amazonia. The creation of these land-use maps, which have the spatial detail of a satellite image and the attribute information of an agricultural census, required the development of a new statistical technique for merging data sets at different scales and of fundamentally different data types. Here we describe and assess this nonlinear technique, which reinterprets existing land cover classifications by determining what categories are most highly related to the polygon land-use data across the study area. Although developed for this region, the technique appears to hold broad promise for the systematic fusion of multiple data sets that are closely related but of different origins. The figures in the printed version of this article appear in black and white. Color figures are available from the author upon request.     

青藏高原冰川雪冰微生物研究进展

微生物作为青藏高原冰川研究的一个参数,不仅能提供丰富的物种和嗜冷基因资源作用于冰川的能量和化学物质平衡,而且还与气候和环境相关联.近年来,青藏高原冰川雪藻的研究主要在南部的Yala冰川开展,细菌的研究集中在北部冰川.这些研究主要针对冰川雪冰微生物与环境的关系.未来除在研究方法上加以改进外,还应该在微生物多样性、生态意义、嗜冷机制及其与气候和环境的关系等方面进一步深入研究.参36     

季节性雪被对青藏高原东缘高寒草甸土壤氮矿化的影响

依据自然雪被分布的差异,在青藏高原东缘高寒草甸中设置3条样带(即深雪、中等厚度雪被和浅雪),于2008年的秋冬过渡期,连续监测各样带中的雪被厚度和土壤温度,并采用原位培养法测定每月的土壤氮素氨化、硝化和矿化速率,以研究不同厚度雪被对高寒草甸土壤氮矿化的影响.结果表明,月均土温、每月日最高土温均值分别与雪被厚度极显著相关,二次函数关系拟合较好(R2=0.576,0.685),且根据每月日最高土温均值与雪被厚度的二次函数关系方程可知,25 cm厚的雪被可以起到较好的隔绝效果;土壤含水量受雪被厚度和土壤温差两个因素的显著影响.在秋冬过渡期末,浅雪梯度下土壤硝态氮含量显著降低,且雪被下的净氮矿化速率与月均土温、每月日最高土温均值、每月日最低土温均值都分别呈极显著相关,二次函数关系拟合较好(R2=0.589,0.541,0.601).研究表明,不同厚度的雪被对土壤温度和含水量影响显著,从而显著地影响着土壤氮的矿化,深雪更有利于氨化、硝化和氮矿化.图7表2参36     

Pressure cookers or pressure valves: Do roads lead to deforestation in China?

The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1 km² (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation.