Factors affecting the distribution and abundance of Macrobrachium petersi (Hilgendorf) in the Keiskamma River and estuary,South Africa

A dry (1979–1980) and a wet (1980–1981) season had a marked effect on the freshwater inflow into the Keiskamma estuary. Under low inflow conditions, which results in elevated salinities in the upper reaches, an upstream migration of adult Macrobrachium petersi (Hilgendorf) to freshwater takes place. During periods of increased river inflow adult M. petersi move downstream to the more saline reaches of the estuary. These two migratory responses have been interpreted as (a) a breeding migration under high inflow conditions which ensures that larvae are in close proximity to salinities that favour growth and development, and (b) an adult upstream migration back to freshwater to escape elevated estuarine salinities as a result of the low freshwater inflow.     

Sensitivity analysis of a deterministic water temperature model to forest canopy and soil temperature in Catamaran Brook (New Brunswick,Canada)

A coupled deterministic hydrological and water temperature model, CEQUEAU, was modified to include soil temperature and crown closure in its calculation of local advective terms in the heat budget. The modified model was than tested to verify its sensitivity to these modifications. An analysis of the heat budget of a small forested catchment in eastern Canada revealed that the advective term related to interflow plays a significant role in the daily water heat budget, providing on average 28% of the local advective budget (which also includes advective heat terms from surface runoff and groundwater) and nearly 14% of the total heat budget (which includes all radiative terms at the water surface, convection and evaporation, as well as the local advective terms). Relative sensitivity indices (RSIs) were used to verify the impact of the newly introduced parameters and variables. Among them, parameters related to the forest cover (crown closure and leaf area index) have a maximum RSI of ?0·6; i.e. a 100% increase in value produces a 60% decrease in the local advective term. Parameters with the greatest influence are the volume of water contributing to interflow and the amplitude of the net radiative flux at the soil surface, which, if doubled, would double the contribution of the local interflow advective term to the heat budget. Copyright © 2003 John Wiley & Sons, Ltd.     

Establishment of apparent quantum yield and maximum ecosystem assimilation on Tibetan Plateau alpine meadow ecosystem

The alpine meadow is widely distributed on the Tibetan Plateau with an area of about 1.2×106kn2. Damxung County, located in the hinterland of the Tibetan Plateau, is the place covered with this typical vegetation. An open-path eddy covariance system was set up in Damxung rangeland station to measure the carbon flux of alpine meadow from July to October,2003. The continuous carbon flux data were used to analyze the relationship between net ecosystem carbon dioxide exchange (NEE) and photosynthetically active radiation (PAR), as well as the seasonal patterns of apparent quantum yield (α) and maximum ecosystem assimilation (Pmax).Results showed that the daytime NEE fitted fairly well with the PAR in a rectangular hyperbola function, with α declining in the order of peak growth period (0.0244 μmolCO2 · μmol-1pAR) ＞early growth period ＞ seed maturing period ＞ withering period (0.0098 μmolCO2 · μmol-1pAR).The Pmax did not change greatly during the first three periods, with an average of 0.433mgCO2· m-2· s-1, i.e. 9.829 μmolCO2· m-2· s-1. However, during the withering period, Pmax was only 0.35 mgCO2 · m-2 · s-1, i.e. 7.945 μmolCO2 · m-2 · s-1. Compared with other grassland ecosystems, the α of the Tibetan Plateau alpine meadow ecosystem was much lower.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

地温示踪地表暖化过程中的气候变化和城市热岛效应

对日本熊本平原城区和郊区28口观测井温度进行测量,利用一维非稳定水－热流运移方程解析解反演地表温度变化率,同时与研究区域7个气象站气温数据进行对比验证。结果表明：1987－2012年研究区域城区地表温度增加1.51°C,近地表气温增加1.13°C;郊区地表温度增加0.81°C,近地表气温增加0.59°C。研究区域气候变化和城市热岛效应对地表暖化过程的贡献率基本一致,通过对城区和郊区地温进行测量分析,能有效量化区分两者对地表暖化过程的影响。     

Grey relational analysis on the relation between marine environmental factors and oxidation-reduction potential

The effects of marine environmental factors-temperature(T),dissolved oxygen(DO),salinity(S) and pH-on the oxidation-reduction potential(ORP) of natural seawater were studied in laboratory.The results show an indistinct relationship between these four factors and the ORP,but they did impact the ORP.Common mathematical methods were not applicable for describing the relationship.Therefore,a grey relational analysis(GRA) method was developed.The degrees of correlation were calculated according to GRA and the va...     

改进的DisTrad模型在地形起伏区地表温度空间分辨率提升的应用

DisTrad（Disaggregation procedure for radiometric surface temperature）模型是常用于遥感地表温度空间分辨率提升的主要模型之一。DisTrad模型常面向空间范围有限、地形相对平坦的研究区域,且常选用植被参数（如植被指数或植被覆盖度等）作为关键参数。然而在空间范围较大、地形起伏地区,地表温度的空间变异可能无法完全通过植被参数解释。本研究选取四川盆地及毗邻地区为研究区,通过模拟数据研究DisTrad模型在地形起伏区地表温度空间分辨率提升中的适用性。数字高程模型（Digital Elevation Model,DEM）、归一化差值植被指数（Normalized Difference Vegetation Index,NDVI）等参数,采用滑动窗口逐步回归,将空间分辨率为6km的地表温度提升至空间分辨率为1km。研究结果表明,改进的模型在平原及海拔较低的高原地区提升获得的地表温度空间分辨率具有较高精度,均方根误差（Root Mean Square Error,RMSE）为0.5K左右;在地形起伏较大的地区,RMSE为4K,验证了改进的模型提升的可行性。     

一种基于PPI的高光谱数据矿物信息自动提取方法

本文通过分析PPI算法后续处理存在的问题,引入最大距离法(MD)实现基于PPI的端元自动分类,并将获得的未知端元在波谱库中遍历以匹配最佳地类,最终完成基于PPI端元的矿物信息的自动提取。实验采用美国内华达州Cuprite地区的机载AVIRIS和我国东天山地区的星载Hyperion高光谱遥感数据,利用IDL编程实现矿物信息的自动提取,通过对实验结果的比较分析,验证了本文方法的有效性和实用性。     

��б������������ı�ʾ

??????????????????????????????????????α????????????о??У????????????????????????????α???????????????????????б???б????????Ω???????????μ??????е??????????????????????涨?????????????????????????????α?????????б????????????????????????б?????????о????й???б?????????????????????????????????о????