Application of a temperature-dependent von Bertalanffy growth model to bullhead (Cottus gobio)

The most studied and commonly applied model of fish growth is the von Bertalanffy model. However, this model does not take water temperature into account, which is one of the most important environmental factors affecting the life cycle of fish, as many physiological processes that determine growth, e.g. metabolic rate and oxygen supply, are directly influenced by temperature. In the present study we propose a version of the von Bertalanffy growth model that includes mean annual water temperatures by correlating the growth coefficient, k, explicitly and the asymptotic length, L_∞, implicitly to water temperature. All relationships include parameters with an obvious biological relevance that makes them easier to identify. The model is used to fit growth data of bullhead (Cottus gobio) at different locations in the Bez River network (Drme, France). We show that temperature explains much of the growth variability at the different sampling sites of the network.     

Multiple structural modifications to dendritic ecological networks produce simple responses

Structural modifications to landscapes affect the ability of organisms to access different habitat patches. There exist, however, very few general methods by which to relate modifications to expectations of effects, and even fewer that enable understanding of how multiple modifications may interact. In the absence of any guiding principles, ecologists have assumed that interactions will result in complex landscape-scale effects. One way of understanding such effects is through rendering a landscape as a graph or network, among the simplest of which are dendritic networks typified by stream systems. Yet even for stream networks, there are no known general principles concerning the nature of interactions between multiple modifications. We developed a model to describe the ability of fish to access and use different habitat patches within dendritic networks. We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications. Rather than showing complex interactions, our analytic and simulation-based results show that the combined effect of multiple modifications approximately equals the sum of individually predicted effects. Dendritic networks thus appear to respond far more simply to multiple modifications than has previously been assumed. These results have implications for stream management planning, and offer a firm foundation from which to better understand population processes within dendritic networks.     

基于人工神经网络法的绿色建筑评价

以实际建筑物为例,介绍了用层次分析法建立绿色建筑评价模型的过程,并分别用层次分析法和人工神经网络法对实际建筑物进行了评价。评价结果显示,人工神经网络法与层次分析法相对误差不到0.5%,表明人工神经网络法作为一种客观科学的评价方法,应用于绿色建筑的评价,能有效降低主观因素带来的影响,会使结果更具有客观性。     

Social capital networks for achieving sustainable development

There have been few empirical studies investigating whether and how social capital (SC) relates to better achievement of sustainability goals and, if so, how. This research investigates the roles three types of SC, namely, bonding, bridging, and bracing SC, play in achieving sustainable development (SD), using a case study of the Japanese region to explore the process of SC accumulation leading to collective action. The research question as to whether SC accumulation makes a difference in the progress towards sustainability is addressed qualitatively and quantitatively using a case study, and network and regression analysis; in particular the impact and functions of bracing SC are closely investigated. The study concludes that SC accumulation can indeed make a difference in achieving sustainability and that bracing SC plays an essential role in expediting the processes of goal sharing and resource flow by connecting various networks across sectors and scales, thereby making collective action possible. These findings suggest that creating an environment in which the generation of all three types of SC is encouraged may help local governments to achieve their desired policy goals for SD.     

Climate change in mountain regions: how local communities adapt to extreme events

This paper examines how local communities adapt to climate change and how governance structures can foster or undermine adaptive capacity. Climate change policies, in general, and disaster risk management in mountain regions, in particular, are characterised by their multi-level and multi-sectoral nature during formulation and implementation. The involvement of numerous state and non-state actors at local to national levels produces a variety of networks of interaction and communication. The paper argues that the structure of these relational patterns is critical for understanding adaptive capacity. It thus proposes an expanded concept of adaptive capacity that incorporates (horizontal and vertical) actor integration and communication flow between these actors. The paper further advocates the use of formal social network analysis to assess these relational patterns. Preliminary results from research on adaptation to climate change in a Swiss mountain region vulnerable to floods and other natural hazards illustrate the conceptual and empirical significance of the main arguments.     

区域生态安全评价的BP神经网络方法

生态安全评价是建立生态安全预警系统及进行环境管理的基础。为确立有效的区域生态安全评价方法,基于压力－状态－响应概念模型,构建了区域生态安全评价指标体系和评价标准;采用BP神经网络的途径,对安徽省17个地级市的生态安全评价问题进行了研究。结果表明：宣城、池州、黄山为Ⅱ级,亳州、宿州、阜阳、滁州、六安、巢湖、安庆为Ⅲ级,合肥、淮北、蚌埠为IV级,淮南、马鞍山、芜湖、铜陵为Ⅴ级。区域生态安全的BP神经网络评价方法涵义明确,计算过程简单,能区分生态安全的等级,可以应用于具有评价标准的其它生态系统综合评价。     

基于改进辐射模型的乡镇人口流动网络研究

乡镇尺度的人口流动联系和空间结构研究对统筹区域城镇体系规划和产业结构调整具有重要意义.本文以复杂网络理论为研究视角,将空间可达性引入传统辐射模型进行参数修正,构建乡镇人口流动网络;从节点和社团结构以及无标度和小世界特征等方面,探讨在地域差异影响下人口流动的空间分布格局和复杂网络特征,并以荆门市55个乡镇为例进行实证研究.结果表明:①荆门市乡镇人口流动网络的节点度分布以高发展水平乡镇为核心,呈现“一横二纵”的空间分异格局,与荆门市城镇体系和产业布局存在极强的耦合关系;②全网包含四个社团,各社团内部联系紧密且空间结构特征各异,社团间联系相对松散.③受空间距离和地理环境影响,网络的无标度特征不够明显;④网络具有一定的小世界特征,整体联通性和局部集聚性较好.本文通过对传统模型进行方法改进,实现了异质空间下乡镇人口流动联系及分布的可视化表达,实例研究结果可为荆门市城镇规划和产业布局提供决策思路.     

基于二分图理论的产业环境资源竞争网络模型研究——以广州开发区为例

采用二分图理论来研究区域内不同产业部门或排污企业之间对于环境容量的竞争关系,建立产业环境资源竞争网络模型,并从点权分布和加权集聚系数等方面加以分析,依据强关联矩阵来确定排污企业对于区域环境容量需求强度的聚类情况.在此基础上,进一步依据2010年广州开发区的排污企业数据进行了实证研究,分析了开发区产业现状,并对未来生态工业园区建设中产业的发展提出了指导性建议.采用复杂网络模型来分析企业环境外部性的方法,不仅较传统的经济度量方式有理论上创新,而且根据区域不同情况来构建模型,从复杂系统视角对环境管理体系进行分析,有利于改进环境管理方式.     

A multiobjective optimization framework for multicontaminant industrial water network design

The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view.     

Weak indirect effects inherent to nitrogen biogeochemical cycling within anthropogenic ecosystems: A network environ analysis

Indirect effects are assumed to be the major causes of the complexity and stability of ecological networks. The complexity of urban-rural complexes (URCs) could also be attributed to the indirect effects associated with human activities. No studies, however, have quantified the strength of indirect effects in relation to urban biogeochemistry. A network environ analysis (NEA) was used for this study to investigate and compare indirect effects in relation to the nitrogen (N) cycling networks of 22 natural ecosystems and five URCs. Results show that indirect effects were proven to be weak for URC N cycling networks (accounting for only ∼2% of the overall effects measured in natural ecosystems). The weak indirect effects found provide a counterexample for the hypothesis that indirect effects are in fact the dominant components of biogeochemical networks. It also implies that human activity in itself does not always raise the complexity of ecological processes as previously suggested. Weak indirect effects also lead to perturbation fragility for URC N cycles (where the decay rate is greater in comparison to natural ecosystems by a factor of 13). In order to improve the robustness and efficiency of URC biogeochemical cycling, a knockout analysis was carried out. By comparing results after removing single interactions between natural ecosystems and URCs it was found that the loss of indirect effects require cooperative strategies to optimize N cycling networks within URCs.