Parameterizing,evaluating and comparing metapopulation models with data from individual-based simulations

Due to the lack of sufficient data and appropriate ecological information parameterizing predictive population dynamical models usually is a difficult task. The approach proposed in this study is meant to overcome this problem by using detailed individual-based simulations to generate artificial data. With short-term data samples, the models to be investigated can be parameterized and their predictions be compared. The flexibility of individual-based simulations as experimental tools also facilitates the evaluation and comparison of different (aggregated) model types. The presented approach is a step towards unifying models of different complexity. As an example we applied it to two metapopulation models of insect species in a highly fragmented landscape: the well-known incidence function model with a patch-based representation of space and a grid-based analogue. The models are tested with respect to their data requirement and recommendations for a better data sampling are derived.     

The models of niche and their application

Having studied the definitions of niche proposed by different ecologists, I have proposed a quantitative method of niche which can be applied to plants. Accordingly, the niche of an operational taxonomic unit (OTU) has been described by a mapping from its environmental set to the unit interval [0, 1], which enables a model of niche to be mathematically operational. The concepts of fundamental niche, realized niche, time niche, etc., may be described by using mathematical models related to each other, and the geometrical relationships between them can be revealed by a multi-dimensional surface. The uni-factor models are built upon the condition that the other factors are optimal for OTU, which are particular cases of the multi-factor models. The establishment of the quantitative relationship between these two kinds of models makes it possible to find out the plants' fundamental niche by doing uni-factor experiments. This may simplify the experiments in which the parameters in a practically applied model are to be estimated. The niche index introduced in this paper is related to average level and aftereffect of plant responses to the effects of its environment (i.e. “inertia”), thus it should be the basis of the simulation of plant seed yield and of its environmental evaluation. Accordingly, models of niche index, of plant seed yield, of plant growth and of environmental evaluation have been built which can be applied to the environmental evaluation or the prediction and management of plant (crop) production, etc.As an example of application, the models of wheat yield and its environmental assessment have been established and practically tested. The results of testing the model of wheat yield showed that the relative errors are 8% and 7.2%, respectively, in 1984 and 1986. The results of the environmental assessment of wheat reveal the fact that the insufficiency of the soil moisture at the 2th and 3th stages is the main restriction of the production of the wheat in Dinxi, Gansu Province, China.     

Leaching of atrazine, metolachlor and diuron in the field in relation to their injection depth into a silt loam soil

A field experiment was conducted on a Calcaric Cambisol soil to study the consequences of the penetration depth and properties of pesticides on the risk of subsequent leaching. Three pesticides with different mobility characteristics and bromide were injected at 30 cm (where soil organic matter (OM) was 2%) and 80 cm (soil OM 0.5%) on irrigated plots without a crop. The migration of injected solutes was assessed for two years by sampling the soil solution using six porous cups installed at 50 and 150 cm depth and by relating solute contents to drainage water flux estimated by the STICS model (Simulateur mulTIdisciplinaire pour les Cultures Standard). Pesticides injected at 30 cm were strongly retained so that no metolachlor or diuron was detected at 50 and 150 cm. The ratio of atrazine peak concentration in the soil solution to concentration in the injected solution (C/C₀) was 1 × 10⁻³ and 0.2 × 10⁻³, respectively, at 50 and 150 cm. When injected at 80 cm, (C/C₀) of atrazine, metolachlor and diuron were 10 × 10⁻³, 1 × 10⁻³ and 0.3 × 10⁻³ at 150 cm, respectively; 1/(C/C₀) was correlated with K_oc values reported from databases. The ratio of drainage volume to the amount of water at field capacity in the soil layer between the injection point at 30 cm and the water sampling level (V/V₀) at 50 and 150 cm was 0.6 and 0.9, respectively, for bromide and 1.6 and 1.0 for atrazine. V/V₀ of the injected solutes at 80 cm was for bromide, atrazine, metolachlor and diuron 0.6, 0.9, 1.2 and 1.7, respectively; pesticide V/V₀ was correlated with K_oc. The retardation factor was a good indicator of migration risk, but tended to overestimate retardation of molecules with high K_oc. Atrazine desorption represented an additional leaching risk as a source of prolonged low contamination. The large variability in soil solution of bromide and pesticide concentrations in the horizontal plane was attributed to flow paths and clods in the tilled soil layer. This heterogeneity was assumed to channel water fluxes into restricted areas and thereby increase the risk of groundwater contamination. The methodology used in the field proves to provide consistent results.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

中国北方沙漠化地区生态重建的环境政策研究——基于Bioe-conomic Model

论文以内蒙古沙漠化地区为例,运用Bioe-conom ic M odel,比较自由放牧与耕垦、禁牧与禁垦、控制放牧规模与禁垦的土地利用政策情景下,引进舍饲养牛技术与信贷服务和增加非农就业机会对农户土地利用决策及其家庭收入的影响,据此探讨中国北方地区沙漠化发展的人文驱动机制以及生态重建的环境政策。结果表明:实施控制放牧规模与禁垦的环境政策,同时引进舍饲养牛技术能够有效地促进生态重建并提高农户收入;引进舍饲养牛技术需要启动基金,提供信贷服务和增加非农就业机会是贫困农户引进该技术的前提。因此,迫切需要调整宏观环境政策,提高农业集约化经营水平和城乡联系力度,从而提高农户家庭收入、减轻农民对环境的依赖性和促进农村的可持续发展。     

生命线工程网络抗震可靠性分析方法的比较研究

生命线工程网络抗震可靠性分析是进行生命线工程系统规划、设计、改造与优化的基础。因此 ,寻找一种高效的适应性强的系统可靠性分析方法对实际工程应用具有重要的意义。本文主要介绍两种高效的网络系统两终端连通可靠性分析方法———递推分解算法和有序二分决策图算法。首先 ,分别对两种算法的原理及实现过程进行了详细的论述和说明 ,并且用c语言编制了二分决策图算法的计算程序。然后 ,利用这两种方法及随机模拟算法对 2 0个以往研究中的经典算例和两个实际工程网络———河南省电力网和上海市浦西供水管网 ,进行了网络系统抗震连通可靠性分析。通过对实例分析结果的比较研究 ,得到了一些经验性的结论 ,以期为优化设计工程网络时选择系统可靠性的分析工具提供参考。研究表明 ,由于递推分解算法具有适应性强和能够求得问题近似解的优点 ,因此有良好的实际工程应用前景。     

高层学生公寓防火体系构建

归纳总结学生高层公寓火灾伤亡事故致因因素,利用事故树分析法对其进行定性分析,得出最小径集,找出控制事故发生的途径,并利用“瑟利模型”建立防火体系,得到此类火灾事故防控措施,即一要通过培训和教育的手段,提高人感觉火灾危险的敏感性,使人处于安全状态并能够迅速、敏捷、正确地做出行为响应;二要保证物处于安全状态,确保电气设备、建筑物本质处于安全状态,并使建筑物能发挥性能化灭火作用,能在一定程度上控制火势,为疏散争取时间.本文能为高校高层学生公寓预防和控制火灾伤亡事故工作提供一定的借鉴作用.     

数据挖掘在预测组织事故防控效果中的应用*

为进一步探索数据挖据技术在组织事故预防工作中的融入性与适用性，基于24Model构建事故预控基础模型,通过预测准确率数值及接受者操作特性曲线（ROC曲线）对比分析随机森林（RF）、支持向量机(SVM)、决策树（DT）与神经网络（NN）4种方法对组织事故防控效果的预测性能。结果表明:针对事故率控制（Y1）、职业危害预防（Y2）、财产损失3类预测目标（Y3），RF方法均能达到较高的准确率及稳定性，具有较优的预测性能。根据特征重要度（FI）排序，明确对组织事故水平影响最显著的因素为安全实践活动认知（SC5）及安全管理程序文件（SMS3），FI值均大于0.150 0。研究结果可为有效预测组织事故防控效果提供方法依据，同时为企业安全工作的规划设计提供思路。     

Assessing wetland changes in the venice lagoon by means of satellite remote sensing data

Not only does lagoon ecology represent a transitional zone between the sea and the continent but it also expresses the equilibrium belt between erosion and sedimentation processes. Within the framework of a coastal management scheme, a precise and timely mapping of morphological changes in this environment is important. This paper illustrates the possible contribution of multi-temporal satellite observations in the monitoring of the erosion/sedimentation processes of coastal zones, where landscape features are subjected to highly morphodynamical modifications. In particular, an improved mapping accuracy was obtained by the successive application of the Maximum Likelihood (MLH) classifier and the Linear Mixture Model (LMM) techniques to the satellite image classification procedure. In fact, by estimating the amount of shallow water and wetland within each satellite pixel, the LMM technique allows for an accurate mapping of the transitional zones in the lagoon environment, thus permitting an optimal separation between land and water. The study concerns the Venice lagoon (Italy) which has been sinking slowly since the beginning of this century. This has led to widespread loss of wetlands. In order to monitor the development of the land cover, four Landsat Thematic Mapper scenes were examined, during the period 1984 to 1993. The results obtained proved that the digital analysis method of multitemporal satellite imagery, applied over a selected test area, enables the evolution of an estuarine environment landscape, with its different sequences of erosion and periods of accretion, to be monitored. The significant influence of tidal stages is discussed in the data analysis.