单甲脒农药对模型池塘生态系统藻类群落结构的影响

在１．５－５０．０ｍｇ／Ｌ的浓度范围内，单甲脒农药对模型池塘生态系统中的浮游植物群落结构有明显影响。尤其在加药的头４ｄ内，藻类种类、数量、多样性指数、种类数比及增长率明显下降，优势比显著上升，敏感种及清洁种减少甚至消失，高浓度（５０．０ｍｇ／Ｌ）的单甲脒在２ｄ内可把藻类全部杀灭。随试验时间的延长，药物不断降解，６ｄ后藻类种类、数量、多样性指数又不断回升。随加药次数的增多，药物对藻类抑制作用明显减弱，藻类的种类、数量、多样性指数等指标不断上升，尤其是藻类数量增加明显，试验后期，藻类数量高低主要受Ｎ、Ｐ浓度大小的影响。     

工业废液纳滤膜分离模型研究

纳滤膜处理工业废液时，纳滤膜系统可以看做一个封闭体系。实验表明透过液通量Jw与压力差呈直线关系；透过液通量Jw与管过液溶质浓度CR都与浓缩时间呈较好的数学关系。但数学关系形式不同；透过液溶质浓度CR与进液溶质浓度Ci呈指数关系；透过液溶质浓度CR与膜压力差△p的关系为指数关系。     

Regression analysis of forest inventory data with time and space dependencies

In this paper the data of a forest health inventory are analyzed. Since 1983 the degree of defoliation, together with various explanatory variables (covariates) concerning stand, site, soil and weather, are recorded by the second of the two authors, in the forest district of Rothenbuch (Spessart, Bavaria). The focus is on the space and time dependencies of the data. The mutual relationship of space-time functions and the set of covariates is evaluated. For this we use generalized linear models (GLMs) for ordinal response variables and semiparametric estimation approaches. By using goodness-of-fit measures it turns out that (i) the contribution of space-time functions is quantitatively comparable with that of the set of covariates, (ii) the contribution of space-time functions is small compared with the contribution of a set of variables describing the last-year and neighboring response values. By applying appropriate residual methods a detailed analysis of the individual sites in the area can be carried out. This analysis reveals where the predictive power of the covariates fail to explain the observed defoliation.     

Uncertainty, learning, and the optimal management of wildlife

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.     

活性炭吸附水中铅离子的动态研究

本文采用两种煤质活性炭，研究了其对不同浓度二价铅离子溶液的吸附，应用固定床吸附动力学模型，Ｍａｒｑａｄｔ方法非线性回归固定床吸附流出曲线，获得了铅离子在活性炭上的扩散传质系数。结果发现，孔扩散系数Ｄｐ强裂地依赖于铅离子入口浓度，随着入口浓度的升高，孔扩散系数变小，随后用上述扩攻系数理论预测了其它操作条件下的流出曲线，结果表明实验曲线与理论预测曲线能很好地相符，动态法能可靠地获取固吸附过程的吸附及扩     

拓扑指数在定量结构生物降解性关系中的应用

本文采用二氧化碳生成量实验，对训练组有机物，利用逐步回归分析程序，从计算和十四种分子连接性指数中筛选出与生物降解性最为相关的分子结构描述参数，建立定量结构－生物降解性关系模型，其相关系数为０．９３１，利用该模型对预测组质的预测结果表明，此模型对芳香化合物的好氧生物降解性具有良好的预测能力，其正确预测率达８３．３％。     

On the latent state estimation of nonlinear population dynamics using Bayesian and non-Bayesian state-space models

Nonlinear state-space models have been increasingly applied to study population dynamics and data assimilation in environmental sciences. State-space models can account for process error and measurement error simultaneously to correct for the bias in the estimates of system state and model parameters. However, few studies have compared the performance of different nonlinear state-space models for reconstructing the state of population dynamics from noisy time series. This study compared the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF) and Bayesian nonlinear state-space models (BNSSM) through simulations. Synthetic population time series were generated using the theta logistic model with known parameters, and normally distributed process and measurement errors were introduced using the Monte Carlo simulations. At higher levels of nonlinearity, the UKF and BNSSM had lower root mean square error (RMSE) than the EKF. The BNSSM performed reliably across all levels of nonlinearity, whereas increased levels of nonlinearity resulted in higher RMSE of the EKF. The Metropolis–Hastings algorithm within the Gibbs algorithm was used to fit the theta logistic model to synthetic time series to estimate model parameters. The estimated posterior distribution of the parameter θ indicated that the 95% credible intervals included the true values of θ (=0.5 and 1.5), but did not include 1.0 and 0.0. Future studies need to incorporate the adaptive Metropolis algorithm to estimate unknown model parameters for broad applications of Bayesian nonlinear state-space models in ecological studies.     

A distributed-delay model to predict ageing and survival rates of adults of Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in granaries filled with wheat

A time-varying distributed-delay model simulating effects of multifactors was developed. Prediction of the ageing rate and survival distribution of adults of the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in various environments found in wheat-filled granaries was conducted as an example to illustrate the application of this developed model. Published adult mortalities, determined at different temperatures, relative humidities, and food sources, were directly used to find the average ageing rate and family of cumulative function of adult mortality. The developed model could predict the adult survival rate at constant or transient temperatures with different relative humidities. This model could also simulate the effect of adult acclimation to their environment when they experience temperature and moisture fluctuations inside granaries. To validate the developed model, the simulation results were compared with available experimental data from the literature. There was no difference between predicted and measured mortalities in two granaries in which the mortalities were determined in a 4-month experiment.     

Examination of model predictions at different horizontal grid resolutions

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.The U.S. Governments right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.     

The performance of RAMS in representing the convective boundary layer structure in a very steep valley

Data from a comprehensive field study in the Riviera Valley of Southern Switzerland are used to investigate convective boundary layer structure in a steep valley and to evaluate wind and temperature fields, convective boundary layer height, and surface sensible heat fluxes as predicted by the mesoscale model RAMS. Current parameterizations of surface and boundary layer processes in RAMS, as well as in other mesoscale models, are based on scaling laws strictly valid only for flat topography and uniform land cover. Model evaluation is required to investigate whether this limits the applicability of RAMS in steep, inhomogeneous terrain. One clear-sky day with light synoptic winds is selected from the field study. Observed temperature structure across and along the valley is nearly homogeneous while wind structure is complex with a wind speed maximum on one side of the valley. Upvalley flows are not purely thermally driven and mechanical effects near the valley entrance also affect the wind structure. RAMS captured many of the observed boundary layer characteristics within the steep valley. The wind field, temperature structure, and convective boundary layer height in the valley are qualitatively simulated by RAMS, but the horizontal temperature structure across and along the valley is less homogeneous in the model than in the observations. The model reproduced the observed net radiation, except around sunset and sunrise when RAMS does not take into account the shadows cast by the surrounding topography. The observed sensible heat fluxes fall within the range of simulated values at grid points surrounding the measurement sites. Some of the scatter between observed and simulated turbulent sensible heat fluxes are due to sub-grid scale effects related to local topography.