Evaluation of discrete host–parasitoid models for diamondback moth and Diadegma semiclausum field time population density series

The performance of discrete mathematical models to describe the population dynamics of diamondback moth (DBM) (Plutella xylostella L.) and its parasitoid Diadegma semiclausum was investigated. The parameter values for several well-known models (Nicholson–Bailey, Hassell and Varley, Beddington, Free and Lawton, May, Holling type 2, 3 and Getz and Mills functional responses) were estimated. The models were tested on 20 consecutive sets of time series data collected at 14 days interval for pest and parasitoid populations obtained from a highland cabbage growing area in eastern Kenya. Model parameters were estimated from minimized squared difference between the numerical solution of the model equations and the empirical data using Powell's method. Maximum calculated DBM growth rates varied between 0.02 and 0.07. The carrying capacity determined at 16.5 DBM/plant by the Beddington et al. model was within the range of field data. However, all the estimated parameter values relating to the parasitoid, including the instantaneous searching rate (0.07–0.28), per capita searching efficiency (0.20–0.27), search time (5.20–5.33), handling time (0.77–0.90), and parasitism aggregation index (0.33), were well outside the range encountered empirically. All models evaluated for DBM under Durbin–Watson criteria, except the May model, were not autocorrelated with respect to residuals. In contrast, the criteria applied to the parasitoid residuals showed strong autocorrelations. Thus, these models failed to estimate parasitoid dynamics. We conclude that the interactions of the DBM with its parasitoid cannot be explained by any of the models tested. Two factors may be associated with this failure. First, the parasitoid in this integrated biological control system may not be playing a major role in regulating DBM population. Second, and perhaps more likely, poor correlations reflect gross inadequacies in the theoretical assumptions that underlie the existing models.     

工业废水排放量和治理投资费用的预测

利用1996—2005年相关统计数据以及专项调查数据,对重点排放行业工业废水的产生、排放特征以及治理费用函数进行分析,建立了分行业的宏观工业废水排放和治理费用预测模型,并预测了2006—2020年工业废水排放趋势、投资需求以及减排重点. 结果表明:到2010年,工业废水和COD_Cr产生量分别为646×108～658×108和1 575×104～2 031×104 t,二者的排放量将分别介于234×108～301×108和441.1×104～609.2×104 t;“十一五"期间工业废水治理投资和治理费用如不能达到8 000×108元,将面临COD_Cr减排目标不能完成的风险.      

系统安全预测的本质与组合预测

详细分析了系统安全预测的内在规律性、有效时间长度及有效性等方面的问题 ,提出了安全预测的本质就是建立系统安全可预测的思想。并针对目前的安全预测方法 ,提出了组合预测法 ,以提高安全预测的精度和准确性     

CHAOTIC FORECASTING OF DISCHARGE TIME SERIES: A CASE STUDY1

ABSTRACT: This paper considers the problem of forecasting the discharge time series of a river by means of a chaotic approach. To this aim, we first check for some evidence of chaotic behavior in the dynamic by considering a set of different procedures, namely, the phase portrait of the attractor, the correlation dimension, and the largest Lyapunov exponent. Their joint application seems to confirm the presence of a nonlinear deterministic dynamic of chaotic type. Second, we consider the so‐called nearest neighbors predictor and we compare it with a classical linear model. By comparing these two predictors, it seems that nonlinear river flow modeling, and in particular chaotic modeling, is an effective method to improve predictions.     

环渤海地区空气质量时空变化特征及动态预测

基于环渤海地区2017—2021年各城市空气质量指数(AQI)、污染物浓度与社会经济数据,利用数理统计、克里金插值法对环渤海地区AQI与污染物浓度的时空变化特征进行分析,运用皮尔逊相关性分析方法探讨AQI与污染物浓度、社会经济因素的相关关系,采用时间序列预测模型对2022年6月—2023年12月空气质量及污染物浓度进行预测。结果表明:环渤海地区AQI及污染物浓度大致呈逐年降低的趋势。AQI的逐月变化呈"W"形,O₃浓度的年内变化呈倒"V"形,其余污染物则呈现与O₃相反的变化趋势。AQI大致呈现西南高、东北低的空间分布特点,而污染物浓度分布具有明显的空间差异。环渤海地区5个代表性城市的AQI类别以良好为主,冬季首要污染物主要为PM_2.5、PM₁₀,夏季首要污染物以O₃为主。人口数量是影响AQI的主要因素,城市园林绿地面积对AQI具有一定影响。预测结果显示,未来环渤海地区AQI、主要污染物浓度(O₃除外)均呈现出随时间的推移逐渐下降的变化趋势。     

地下水环境智慧监管技术集成与平台应用研究

针对"双源"地下水(地下水污染源和集中式地下水型饮用水源)环境监管需求,研发了一套集地下水污染在线监测预警、评价溯源、预测应急于一体的可视化技术集成与应用平台。该平台将物联网、地下水数值模拟、大数据、云计算等技术集成应用于环境监管,实现了工业园区地下水环境实时动态监测评价及预警、地下水污染路径溯源计算、地下水事故污染预测及应急支撑等网络服务与计算功能,并通过地下空间三维数字化处理,构建了"所见即所得"的三维虚拟现实界面,实现了对地下水环境的便捷、高效监管与决策。该平台兼容手机、平板电脑、台式计算机等固定和移动设备,可为"双源"地下水污染监控、管理和应急提供实时、高效的科技支撑。     

Population as an oscillating system

In this paper we present a new approach describing population dynamics based on the view of a population as an oscillating system. To develop a mathematical model of an oscillating population, we applied a third-order differential equation. Our model describes population dynamics within a parametric-temporal continuum, formed by the relative values of population growth and decrease over time. In this paper we also illustrate how our oscillative model effectively compliments the existing suite of models in population dynamics.     

A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

The spread of invasive species is a long studied subject that garners much interest in the ecological research community. Historically the phenomenon has been approached using a purely deterministic mathematical framework (usually involving differential equations of some form). These methods, while scientifically meaningful, are generally highly simplified and fail to account for uncertainty in the data and process, of which our knowledge could not possibly exist without error. We propose a hierarchical Bayesian model for population spread that accommodates data sources with errors, dependence structures between population dynamics parameters, and takes into account prior scientific understanding via non-linear relationships between model parameters and space-time response variables. We model the process (i.e., the bird population in this case) as a Poisson response with spatially varying diffusion coefficients as well as a logistic population growth term using a common reaction-diffusion equation that realistically mimics the ecological process. We focus the application on the ongoing invasion of the Eurasian Collared-Dove.     

焦作市工业燃煤量与大号SO2污染关系模型研究

研究了焦作市工业燃煤量与大气SO2污染的关系,建立了适合于焦作市城区大气SO2污染的解析模型.在模型中尝试性地将面源污染产生的浓度贡献转化到背景值中计算,简化了解析模型.利用该模式计算了1996～2000年焦作市城区大气中的SO2浓度,并与监测数据进行对比分析,结果表明该模型适合研究区的实际情况,基于该模型实现了焦作市城区大气SO2浓度的动态预测.     

HCl emission characteristics and BP neural networks prediction in MSW/coal co-fired fluidized beds

IntroductionWiththedepletionofspaceforlandfillingofmunicipalsolidwasteandtherisingpricesforrawmaterials ,moreandmorefluidizedbedincineratorshavebeenusedtotreatMSWduetotheprimaryadvantagesofhygieniccontrol,volumereductionandenergyrecovery .BecausetheMSWhas…