The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

Invasive species impacts on ecosystem structure and function: A comparison of Oneida Lake, New York, USA, before and after zebra mussel invasion

Exotic species invasion is widely considered to affect ecosystem structure and function. Yet, few contemporary approaches can assess the effects of exotic species invasion at such an inclusive level. Our research presents one of the first attempts to examine the effects of an exotic species at the ecosystem level in a quantifiable manner. We used ecological network analysis (ENA) and a social network analysis (SNA) method called cohesion analysis to examine the effect of zebra mussel (Dreissena polymorpha) invasion on the Oneida Lake, New York, USA, food web. We used ENA to quantify ecosystem function through an analysis of food web carbon transfer that explicitly incorporated flow over all food web paths (direct and indirect). The cohesion analysis assessed ecosystem structure through an organization of food web members into subgroups of strongly interacting predators and prey. Our analysis detected effects of zebra mussel invasion throughout the entire Oneida Lake food web, including changes in trophic flow efficiency (i.e., carbon flow among trophic levels) and alterations of food web organization (i.e., paths of carbon flow) and ecosystem activity (i.e., total carbon flow). ENA indicated that zebra mussels altered food web function by shunting carbon from pelagic to benthic pathways, increasing dissipative flow loss, and decreasing ecosystem activity. SNA revealed the strength of zebra mussel perturbation as evidenced by a reorganization of food web subgroup structure, with a decrease in importance of pelagic pathways, a concomitant rise of benthic pathways, and a reorganization of interactions between top predator fish. Together, these analyses allowed for a holistic understanding of the effects of zebra mussel invasion on the Oneida Lake food web.     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.     

Effectiveness of Vegetation Surrogates for Parasitoid Wasps in Reserve Selection

Abstract:  Selecting suitable nature reserves is a continuing challenge in conservation, particularly for target groups that are time-consuming to survey, species rich, and extinction prone. One such group is the parasitoid Hymenoptera, which have been excluded from conservation planning. If basic characteristics of habitats or vegetation could be used as reliable surrogates of specific target taxa, this would greatly facilitate appropriate reserve selection. We identified a range of potential habitat indicators of the species richness of pimpline parasitoid communities (Hymenoptera: Ichneumonidae: Pimplinae, Diacritinae, Poemeniinae) and tested their efficiency at capturing the observed diversity in a group of small woodlands in the agricultural landscape of the Vale of York (United Kingdom). Eight of the 18 vegetation-based reserve-selection strategies were significantly better at parasitoid species inclusion than random selection of areas. The best strategy maximized richness of tree species over the entire reserve network through complementarity. This strategy omitted only 2–3 species more (out of 38 captured in the landscape as a whole) than selections derived from the parasitoid survey data. In general, strategies worked equally well at capturing species richness and rarity. Our results suggest that vegetation data as a surrogate for species richness could prove an informative tool in parasitoid conservation, but further work is needed to test how broadly applicable these indicators may be.     

折线法和滚球法确定避雷针保护范围的安全性分析

概述了如何利用折线法和滚球法确定避雷针保护范围 ,并通过分析对比两者的安全性 ,提出了必须具体问题具体对待才能做到安全防雷     

秦皇岛市生态环境景观生态学研究

运用景观分类与评价、景观结构与功能分析、景观生态安全格局判断等景观生态学原理和方法对秦皇岛市生态环境进行了研究,结果表明:秦皇岛景观类型丰富独特,景观空间格局对主要生态过程有重要影响,对1986～1996年间景观变化定量分析的结查显示由于人工干扰指数的提高,使自然景现类型数量减少,并出现破碎化,从而降低了景观多样性和景观优势度,易导致系统的生产力、稳定性、自维持性趋向于降低。     

我国粮食安全保障中改善农业环境的途径

本文分析了我国粮食安全及粮食持续生产所依托的农业环境状况。从我国粮食生产状况与经济发展水平看,全国粮食生产处于结构性过剩与低水平安全中,区域性粮食安全与不安全并存;耕地资源、水资源以及农民的经济收入状况等均不容乐观,加之自然灾害加重,粮食生产的环境成本将随之增加,这将影响我国未来粮食安全。为此,本文提出了走农业集约化道路是解决我国粮食安全与改善环境的基本途径。     

环境安全：21世纪人类面临的根本问题

本文从人类社会的可持续进步和国家的可持续发展两个层面,深层次地分析了环境安全问题的不可替代的重要性,并从理论和实践两个方面得出：第一,我国应将环境安全的保证能力作为综合国力的重要组成部分;第二,应将环境安全观作为指导我国21世纪两大战略-加入WTO和西部大开发的重要方针。     

基于Zigbee技术的无线辐射监测系统的建立

基于Zigbee技术的无线辐射监测系统可对众多辐射监测仪的监测数据进行实时采集和统计分析,无需布线,组网灵活。该辐射监测系统包括多台辐射监测仪及上位机监测平台。辐射监测仪负责测量辐射信息,并将辐射测量结果通过Zigbee模块发送出来。辐射监测平台负责接收辐射测量结果,并将数据在监测平台上进行显示和存储。对辐射监测仪和辐射监测系统进行测试,测试结果表明:辐射监测仪可对在环境本底的基础上增加0.1 μSv/h的γ辐射给出可靠报警;辐射监测系统可自动进行无线网络连接,整体运行稳定,数据采集准确,可实现对各个辐射监测仪监测数据的实时采集和存储。     

基于节点流量校核的供水管网爆管定位研究

针对目前基于节点压力变化定位供水管网爆管的方法,当供水管网中泵切换时,导致定位爆管位置存在误报的问题,提出了基于节点流量校核的管网爆管定位方法.利用奇异矩阵法推导出节点流量灵敏度矩阵,采取奇异矩阵中的最优搜索向量计算方法找到节点流量变化位置,确定爆管管道.首先,将该方法应用于一个小管网,阐述基于节点流量校核的管网爆管定...