基于全局灵敏度分析的浒苔生长影响参数研究

近年来,以浒苔为主的绿潮灾害频发。构建了浒苔生长模型,以定量分析浒苔生长过程,探索浒苔爆发机理。参数不确定性是模型不确定性的主要来源,以参数灵敏度分析为基础的参数优化有利于提高模型精度,采用Morris方法对模型涉及的主要参数进行了全局灵敏度分析,以研究浒苔生长的主要影响参数。不同于其他有关大型绿藻的模型模拟,模型同时考虑了幼体浒苔和成熟浒苔的生物量变化,并修正了营养盐限制函数以及温度计算函数。全局性的参数灵敏度分析结果表明,最适温度(T_(opt))、光合作用最适光强(Is)、最大发芽率(G_(max))、浒苔生长所需的氮含量的半饱和系数(kqn)、最大氮摄取率(V_(maxn))这5个参数在浒苔生长模型中具有较大灵敏性。其中,T_(opt)影响最大,Is和V_(maxn)其次,说明浒苔生长主要受温度光照和氮含量限制。相较于局部灵敏度分析仅关注单个参数变化、依赖于初值选取等缺陷,全局灵敏度分析同时从各个参数的取值范围上分析参数对模型结果的影响,能揭示参数之间相互作用的影响。此外,灵敏度较大的参数往往和其他参数之间存在较大相关性。     

生态模型的灵敏度分析

灵敏度分析用于定性或定量地评价模型参数误差对模型结果产生的影响,是模型参数化过程和模型校正过程中的有用工具,具有重要的生态学意义．灵敏度分析包括局部灵敏度分析和全局灵敏度分析．局部灵敏度分析只检验单个参数的变化对模型结果的影响程度;全局灵敏度分析则检验多个参数的变化对模型运行结果总的影响,并分析每一个参数及其参数之间相互作用对模型结果的影响．目前,在对生态模型的灵敏度分析中,越来越倾向于使用全局灵敏度分析的方法．但国内仍多采用局部灵敏度分析方法,很少采用全局灵敏度分析方法．文中详细论述了局部灵敏分析和全局灵敏度分析的主要方法(一次变换法、多元回归法、Morris法、Sobol’法、傅里叶幅度灵敏度检验法和傅里叶幅度灵敏度检验扩展法),希望能为国内生态模型的发展提供一个比较完善的灵敏度分析方法库．结合国内外的灵敏度分析发展现状,指出联合灵敏度研究、灵敏度共性研究及空间直观景观模型的灵敏度分析将为生态模型灵敏度分析研究中的热点和难点．     

SWMM模型参数局部灵敏度分析

利用Morris筛选法,分析了3场不同雨强降雨条件下,城市降雨径流模型SWMM的水文水力模块和水质模块的参数灵敏度。结果表明:对SWMM模型径流总量和径流峰值最敏感的参数依次是不透水面洼蓄量(destore-imperv)、管道曼宁系数(conduit roughness)和汇流区宽度(width-K),最大灵敏度分别为-0.329、-0.144、0.133和-0.294、0.171和0.143;对污染物总量敏感性较高的是路面和屋面的最大积累量(max buildup)、冲刷系数(coefficient)和冲刷指数(exponent)参数。雨强对于SWMM模型水文水力参数中的下渗参数的敏感性有较大影响,而对水质参数的敏感性影响较小;研究区的土地利用状况对参数敏感性也有较大的影响。水质参数总体的稳定性要高于水文水力参数。     

一类带有阈的神经网络模型的全局稳定性

利用分析技巧,获得了一类带有阈的神经网络模型全局稳定性的判据,去掉了文「１」相应结果的一个较强条件∫＾∞０ｓｋ（ｓ）ｄｓ〈＋∞。     

稻田甲烷排放模型研究——模型灵敏度分析

模型方法对区域稻田甲烷排放估计的不确定性主要源于模型参数在区域范围内的误差,这种误差导致的估计不确定性由模型灵敏度决定.采用一种动力学分析与统计分析相结合的方法对稻田甲烷模型CH4MOD进行了参数灵敏度分析,结果表明,稻田水管理方式的灵敏度最高,灵敏度指数为O.64,其次为稻田土壤的砂粒含量参数,灵敏度指数0.50,灵敏度最低的参数是水稻移栽期地上生物量.以模型灵敏度指数为基础,建立了模型估计值不确定性与模型参数区域化误差间的数量关系,利用这一量化关系得出我国2000年稻田甲烷排放的不确定性范围为3.09～10.61Tg.此外,模型灵敏度参数的大小也反映了模型要素对稻田甲烷排放影响的大小,因而分析的结果对于采取合理措施减少稻田甲烷排放具有指导意义.     

具有时滞的Schoener模型的全局稳定性

研究了具有时滞的Schoener竞争模型,通过构造一个合理的lyapunov函数,在一定条件下得到了该系统正解的全局稳定性．     

基于BIOME-BGC模型的长白落叶松林净初级生产力模拟参数敏感性

基于植被生理生态过程的模型包含较多参数,合理的参数取值能够极大地提高模型的模拟能力.参数敏感性分析可以全面分析模型参数对模拟结果的影响程度,在筛选模型敏感参数过程中起到重要作用.本研究以模拟吉林省汪清林业局长白落叶松林净初级生产力（NPP）为例,分析了BIOME-BGC模型的参数敏感性.首先利用样地实测NPP数据与模拟值进行对比分析,检验模型对长白落叶松林NPP的模拟能力;然后利用Morris法和EFAST法筛选出BIOME-BGC模型中对长白落叶松林NPP影响较大的敏感参数.在此基础上,通过EFAST法对所有筛选出的参数进行定量的敏感性分析,计算了敏感参数的全局敏感性指数、一阶敏感性指数和二阶敏感性指数.结果表明： BIOME-BGC模型能够较好地模拟研究区内长白落叶松林NPP的变化趋势;Morris法可以在样本量较少的情况下实现对BIOME-BGC模型敏感参数的筛选,而EFAST法可以定量分析BIOME-BGC模型中单个参数以及不同参数之间交互作用对模拟结果的影响程度;BIOME-BGC模型中对长白落叶松林NPP影响较大的敏感参数为新生茎与叶片的碳分配比和叶片碳氮比,且二者之间的交互作用明显大于其他参数之间的交互作用.     

城市生态系统的模拟方法：灵敏度模型及其改进

评估城市生态系统的持续发展能力,探讨其持续发展对策是一个复杂的动态问题,需要运用动态的模拟方法进行。由德国著名生态控制论专家Ｆ．Ｖｅｓｔｅｒ和Ａ．Ｖ．Ｈｅｓｌｅｒ教授提出的“灵敏度模型”方法,将系统科学思想、生态控制论方法及城市规划融为一体,解释、模拟、评价和规划城市复杂的系统关系,是模拟城市生态系统很好的方法。本文对该方法进行了改进。改进后的“灵敏度模型”为评价城市持续发展能力、探讨其持续发展对策提供了新的思路。     

城市生态系统灵敏度模型评述

系统复杂性是困扰城市生态系统研究和管理的因素之一,成熟的系统分析模型可以帮助研究者及管理者应对这种挑战。德国系统思想大师Vester教授开发的灵敏度模型就是致力于解决城市规划管理中的复杂性问题,并在一系列的实践应用中取得了显著成效。网状思维(Networked Thinking)与生物控制论观点是Vester教授的核心思想,也是灵敏度模型的思想基础。模型主要分为三大层次:最底层是以数据的收集与筛选过程为代表的信息组织层次;随后是系统解释层次,主要是对系统关系网进行控制论解释;最后是系统综合评价层次,采用生物控制论观点对系统结构、行为等进行检验与评价。为方便用户使用,模型被分解为9个标准步骤,每一部分都包含数个实用的数学分析工具。模型还明确提出了4个等级的系统控制论指标(或特征)体系,以帮助使用者更好地进行系统思考。灵敏度模型本身具有众多的原创性贡献,但同时也有一定的局限性。这些经验与教训为未来的城市生态系统建模工作提供了宝贵启示。     

Watkinson时滞差分方程模型的全局渐近稳定性

考虑差分方程ｘｎ＋１＝λｘｎ／（１＋ａｘｎ－ｋ）＾ｐ＋ｂλｘｎ－ｍ,ｎ＝０,１,２,…,其中ａ,ｂ,ｐ＞０,λ＞１,ｋ,ｍ∈｛０,１,２,…｝,当ｋ＝ｍ＝０时,Ｗａｔｋｉｎｓｏｎ用此方程来描述热带地区季蜀黍属作物的生长规律,当Ｐ＝１时,此方程就是著名的含多个滞量的Ｌｏｇｉｓｔｉｃ微分方程的离散模拟,本文主要目的是研究该方程唯一正平衡解的全局渐近稳定性。     

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low‐quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision‐making framework will result in better‐informed, more robust decisions.     

胶州湾生物-物理耦合模型参数灵敏度分析

参数灵敏度分析旨在评价模型中各参数对模拟结果的影响程度,是参数优化和模型校正的基础步骤,也是认识模型行为的重要工具。所建的胶州湾生物-物理耦合模型包括浮游植物、浮游动物、营养盐、碎屑和溶解氧5类状态变量,对其涉及的50个参数进行灵敏度分析,得到3个非常灵敏性参数、2个灵敏性参数、11个比较灵敏性参数和34个不太灵敏性参数。非常灵敏及灵敏性参数包括浮游植物生长速率(μPRPC)、暗反应修正因子(FAC)、光饱和强度(α)、浮游植物死亡率(μDEPC)和水体消光系数(bla),主要影响浮游植物生长和死亡过程,反映了浮游植物在生态系统中的基础性和重要性作用。这5个参数显著地影响碳和营养盐循环,是整个胶州湾生态系统最主要的影响参数,应优先进行优化。比较灵敏性参数的影响主要表现在营养盐对浮游植物生长或死亡的限制以及温度对光饱和量的限制,浮游动物生长、牧食和死亡过程以及浮游植物生物量对牧食的限制,叶绿素a的生产,缺氧条件下沉积物释放磷以及浮游植物对磷的摄取等过程,这些参数对于各状态变量的灵敏性存在不同程度的差异,从而表征不同的特点。与不太灵敏性参数相关的过程主要为叶绿素a和碎屑消光作用,温度对浮游植物生长、浮游动物牧食、碎屑和沉积物矿化的限制,碎屑和沉积物矿化与沉降,与无机氮相关的大部分过程,溶解氧浓度变化等,这些过程除了受模型内部参数影响外,还在很大程度上受水深、海水温度和陆源污染等外部因素影响。比较灵敏及不太灵敏性参数影响模型局部过程,是模型校正的重要依据,除了非常灵敏及灵敏性参数以外,叶绿素a、浮游动物、碎屑和无机磷四种状态变量可分别根据叶绿素a最大生产系数(K CHmax)、浮游动物一级死亡率(μDEZC1)、有机碎屑矿化率(μREDC)和浮游植物磷摄取的半饱和常数(h UPPP)进行校正。与营养盐相关参数的灵敏度分析表明,胶州湾浮游植物处于磷限制,无机氮主要受陆源排污影响。因此,对无机氮的校正主要通过合理设置沿岸河流径流量或陆源污染物浓度与比例以及无机氮初始场。溶解氧对各参数均不太灵敏。     

Sensitivity analysis of the tree distribution model Phenofit to climatic input characteristics: implications for climate impact assessment

Species distributions are already affected by climate change. Forecasting their long‐term evolution requires models with thoroughly assessed validation. Our aim here is to demonstrate that the sensitivity of such models to climate input characteristics may complicate their validation and introduce uncertainties in their predictions. In this study, we conducted a sensitivity analysis of a process‐based tree distribution model Phenofit to climate input characteristics. This analysis was conducted for two North American trees which differ greatly in their distribution and eight different types of climate input for the historic period which differ in their spatial (local or gridded data) and temporal (daily vs. monthly) resolution as well as their type (locally recorded, extrapolated or simulated by General Circulation Models). We show that the climate data resolution (spatial and temporal) and their type, highly affect the model predictions. The sensitivity analysis also revealed, the importance, for global climate change impact assessment, of (i) the daily variability of temperatures in modeling the biological processes shaping species distribution, (ii) climate data at high latitudes and elevations and (iii) climate data with high spatial resolution.     

Parametric sensitivity analysis and reduction of a detailed nutritional model of plant cell cultures

A kinetic model of plant nutrition described by Cloutier et al. (Cloutier et al., 2008. Biotechnol Bioeng 99:189-200) is progressively simplified so as to obtain a predictive model that describes the evolution of the biomass and the extracellular and intracellular concentrations of three determining nutrients, that is, free intracellular nitrogen, phosphate, and carbohydrate compounds. Three techniques of global sensitivity analysis are successively applied to assess the model parameter influence and potential correlation. The resulting dynamic model is able to predict plant growth for the two most encountered plant bioprocesses, namely suspension cells and hairy roots.     

Development of a physiologically based toxicokinetic model for butadiene and four major metabolites in humans: global sensitivity analysis for experimental design issues

1,3-Butadiene (BD) is metabolized in humans and rodents to mutagenic and carcinogenic species. Our previous work has focused on developing a physiologically based toxicokinetic (PBTK) model for BD to estimate its metabolic rate to 1,2-epoxy-3-butene (EB), using exhaled breath BD concentrations in human volunteers exposed by inhalation. In this paper, we extend our BD model to describe the kinetics of its four major metabolites EB, 1,2:3,4-diepoxybutane (DEB), 3-butene-1,2-diol (BDD), and 3,4-epoxy-1,2-butanediol (EBD), and to test whether the extended model and experimental data (to be collected for BD and metabolites in humans) are together adequate to estimate the metabolic rate constants of each of the above chemicals. Global sensitivity analyses (GSA) were conducted to evaluate the relative importance of the model parameters on model outputs during the 20min of exposure and the 40min after exposure ended. All model parameters were studied together with various potentially measurable model outputs: concentrations of BD and EB in exhaled air, concentrations of BD and all metabolites in venous blood, and cumulated amounts of urinary metabolites excreted within 24h. Our results show that pulmonary absorption of BD and subsequent distribution and metabolism in the well-perfused tissues compartment are the critical processes in the toxicokinetics of BD and metabolites. In particular, three parameters influence numerous outputs: the blood:air partition coefficient for BD, the metabolic rate of BD to EB, and the volume of the well-perfused tissues. Other influential parameters include other metabolic rates, some partition coefficients, and parameters driving the gas exchanges (in particular, for BD outputs). GSA shows that the impact of the metabolic rate of BD to EB on the BD concentrations in exhaled air is greatly increased if a few of the model's important parameters (such as the blood:air partition coefficient for BD) are measured experimentally. GSA also shows that all the transformation pathways described in the PBTK model may not be estimable if only data on the studied outputs are collected, and that data on a specific output for a chemical may not inform all the transformations involving that chemical.     

Ranking bioprocess variables using global sensitivity analysis: a case study in centrifugation

The selection of appropriate operating conditions for bioprocessing is complex due to the large number of interacting stages and variables. Bioprocesses also operate under tight regulation and therefore tools to assist bioprocess design are of significant utility. Conventional approaches for the analysis of variable sensitivities are inadequate. We propose the use of global sensitivity analysis to determine the level of importance of each variable and their interactions. Once key variables have been determined, the designer may focus on the most significant subset. Two case studies are used to demonstrate the applicability of the approach. Each is based on centrifugation and determines the impact of flow-rate, feed viscosity, density difference and particle size, while performance is assessed by supernatant clarification. Significant differences in sensitivities were found between the two studies due to the different feed material properties. Variable sensitivities were found to be system-specific and provide insight for potential operating strategies.     

Mechanical performance of endodontic restorations with prefabricated posts: sensitivity analysis of parameters with a 3D finite element model

Many studies have investigated the effect of different parameters of the endodontically restored tooth on its final strength, using in vitro tests and model simulations. However, the differences in the experimental set-up or modelling conditions and the limited number of parameters studied in each case prevent us from obtaining clear conclusions about the relative importance of each parameter. In this study, a validated 3D biomechanical model of the restored tooth was used for an exhaustive sensitivity analysis. The individual influence of 20 different parameters on the mechanical performance of an endodontic restoration with prefabricated posts was studied. The results bring up the remarkable importance of the loading angle on the final restoration strength. Flexural loads are more critical than compressive or tensile loads. Young's modulus of the post and its length and diameter are the most influential parameters for strength, whereas other parameters such as ferrule geometry or core and crown characteristics are less significant.