A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

Specific features of the growth of Scots pine vegetative organs in the forest-steppe zone of Cisbaikalia

The dependence of the annual increment of vegetative organs on air temperature and humidity and the amount of precipitation per phenophase, as well as the period of their growth in Scots pine, were studied in the forest-steppe zone of Cisbaikalia. The multiple effect of variation in environmental conditions on the annual increment of organs increased when precipitation in September of the previous year was taken into account. These factors proved to have a stronger effect on variation in the annual increment of needles (R ² = 0.59, p = 0.00005) than that in the annual ring width (R ² = 0.38, p = 0.0002).     

Theoretical and Empirical Analysis on Influence Factors of Modern Agricultural Equipment Level in the Processof Agricultural Sustainable Development

To promote modern agricultural equipment level is one characteristic of constructing and developing modern agriculture in China.This paper makes up stepwise linear regression analysis model of influence factors of modern agricultural equipment level,and chooses rural labor,per capita income of rural residents,rural investment,proportion of people at secondary education level and at higher level in per hundred rural labor force and arable land area as independent variables,and total power of machine as induced variable.The major results show that the relativity of modern agricultural equipment level,rural investment and education level of peasants is remarkable,and they are the major influence factors of modern agricultural equipment level.Raising investment level of rural infrastructure construction as well as and research and development and promotion of advanced and applicable modern agricultural equipment,improving quality and education level of peasants can accelerate the development of China’s modern agricultural equipment effectively in the process of agricultural sustainable development.     

网络化治理视域下的中国区域环境治理研究进展

网络化治理作为一种不同于科层—集中型和市场—分散型的新型治理方式,在环境治理中有其自身的优势。当前,区域环境公共事务的不断增长已超出政府单个主体的能力范围,需要加强政府与企业、社会组织及公众等多元主体的共同治理,构建以多元主体参与为核心的多重、复杂、交叉的网络化环境治理模式。基于网络化治理产生的背景、演变过程和内涵,围绕多元主体相互作用、行动主体的网络关系结构和模式、治理网络的运行逻辑和机制等方面系统梳理其研究进展,为推进我国现代化环境治理体系提供参考。     

H∞ loop-shaping controller design for a grid-connected single-phase photovoltaic system

This paper presents a H_∞ loop-shaping controller for controlling dc-link voltage by regulating the switching signal of the inverter associated with a grid-connected single-phase photovoltaic system. To facilitate a robust control design, state-space realisation of the system model is made with uncertainties represented by linear fractional transformation. The controller is achieved through H_∞ synthesis followed by obtaining desired loop shapes through the choice of the proper weighting functions. The controller order is reduced by Henkel-norm method for facilitating its practical implementation. Controller performance is evaluated through carrying out simulations on MATLAB/Simulink platform under standard and changing atmospheric conditions, and fault condition.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.     

A DYNAMIC MODEL FOR WATER AND RELATED LAND RESOURCE PLANNING1

ABSTRACT. Planning an optimal system of activities for generating economic goods and services within an existing natural resource capacity is a difficult problem to solve. A mathematical programming model with the capacity to check multiple resource demand and supply compatibility over many time periods was developed for the solution to this type of problem. The characteristics of natural resource supply and the demand of activities were utilized to reduce the number of time periods and to minimize the loss of the dynamic reality of the problem. Reduction in the number of time periods extended the capability of the model to the solution of complex resource planning problems without oversimplification.     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.