一类离散捕食-食饵模型的混沌跟踪控制

针对一类离散捕食食饵系统,采用Lyapunov指数方法、绘制系统分岔图和混沌吸引子等方式验证了混沌现象的存在.为了消除系统的混沌现象,根据控制理论的轨迹跟踪控制原理,设计混沌跟踪控制器将系统控制到任意给定的期望周期轨道上,达到了稳定种群的目的.仿真分析表明了所设计控制器的有效性.     

离散广义Logistic模型的混沌控制

利用Lyapunov指数方法,验证了一类离散广义Logistic模型存在混沌现象,并采用混沌控制中OGY方法的基本思想,研究了这类模型的混沌控制问题,得出了消除混沌,保持种群稳定到不动点和2-周期轨道的充分条件．     

自然种群中混沌的检测及其在种群动态研究中的意义

混沌现象广泛地存在于自然界,20世纪70年代以来,通过大量的生物模型模拟说明混沌也存在于生物系统中。几十年来生态学家一直在努力寻找混沌在自然生态系统存在的证据,但所获不多,这是源于自然的现实还是由于检测方法的不当和数据的局限?一直困扰着生态学家,自然界中对混沌的检测成为一个要点,也是一个难点。在概述混沌概念和性质的基础上,着重介绍目前在自然生态系统检测混沌的方法,对各种方法的应用条件和范围进行了概述。这些方法包括功率谱法、时间序列的自相关函数分析、模型参数估计、庞加莱截面法、全局和局域李雅普若夫特征指数的估计、吸引子关联维的确定、非线性预测。大量研究结果显示,虽然在自然界检测到的混沌的例子还不多,但其存在却是不容怀疑的。问题是什么样的系统在什么样的条件下会出现混沌?研究表明食物链的结构、种群的迁入和迁出、环境噪音都会对种群的复杂性动态特征产生影响。混沌动态可能对产生系统的多样性和适应性有利,它比随机系统对外界干扰的抵抗能力更强。自然界的变化和系统的维持是持续性和混沌相互矛盾统一的结果。害虫种群复杂性动态的研究为害虫的管理提供了更多的理论依据。混沌控制的理论和方法有可能为害虫管理提供新的思路和途径。在孤立的种群中,混沌会增加种群的灭绝概率,而在集合种群中,混沌动态降低了各局域种群的同步性和同时灭绝的倾向,所以混沌虽然能增加局域种群灭绝的概率,但却能减少整个集合种群灭绝的概率。系统结构及其时空动态与混沌及种群灭绝之间的关系,是保护生物学及生物多样性保护研究的一个重要方面。今后的研究应更多地从种群、群落、生态系统及景观不同层次上的时空动态入手,利用3S等信息技术和空间动态分析方法,研究复杂性动态产生的条件及其在系统调控中的作用机制。     

基于生态位构建的2-物种集合种群关系动力学分析

结合生态位构建对两局域种群的生存竞争关系的影响,建立了基于生态位构建的2-物种集合种群关系模型,得到了共存平衡点的唯一性和全局稳定性条件,分析了两种群共存过程中空间混沌现象的存在性,并作了实例仿真加以验证．     

马尾松毛虫种群动态的时间序列分析及复杂性动态研究

自从May(1974)指出即使是简单的种群模型也能揭示混沌动态以来,自然种群是否存在混沌一直具有争论,如何检测自然种群的混沌行为也成为种群动态研究的一个难点,通过时间序列分析和反应面模型建模的8方法分析了马尾松毛虫的复杂性动态,用自相关函数对马尾松毛虫发生的时间动态分析的结果认为动态是平衡的,其周期性不显著,而具有一定的复杂性,这种类型可以是减幅波动,有限周期或弱混沌,波动主要由系统内因引起,进一步采用反应面模型估计全局李雅普若夫指数和局域李雅普若夫指数结果均为负,显示马尾松毛虫种群动态不存在混沌现象,但是在增加一个小的噪音以后,局域李雅普若夫指数变为在0以上的波动,说明系统对噪音非常敏感,噪音对松毛虫种群动态具有很大的影响,可以将其从非混沌状态变为混沌,研究结果认为全局郴雅普若夫指数λ是一定时间内两个变动轨迹的总平均偏差,而随着种群动态的波动,指数也是波动的,所以对于检测自然种群的混沌来说不是一个好的指标,局域李雅普若夫指数λM能更好地表示自然种群混沌的存在和产生混沌的条件,对害虫管理来说对种群暴发初期的预测是尤其重要的,而此时又最难于预测,所以对种群动态的监测就尤为重要,由于马尾松毛虫的代间种群动态为第一级密度相关,前一代的虫口密度与下一代的虫口密度相关性最强,所以前一代预测下一代是最可靠的。     

宿主-寄生物相互作用种群模型中的混沌与分形现象

自然界具有离散世代的宿主-寄生物相互作用的种群模型都以差分方程组来描述,由于宿主-寄生物相互关系具有不同的类型,模型的功能反应函数也具有多种形式.通过数值模拟试验,分析研究了聚集效应模型随参数变化时表现出的混沌动态行为以及吸引域的自相似分形属性.结果显示虽然在一定参数范围内种群数量显示严格的周期,但混沌动态是不可避免的,共存的多吸引子初值区域显示出自相似分形属性.说明混沌动态行为和分形属性是离散的种群互作用种群模型中必然出现的现象.     

昆虫种群动态非线性建模理论与应用

本文以非线性动力学为基础,对自然界中昆虫种群动态的复杂性、不确定性进行了建模方法的探讨,在讨论了昆虫种群动态的混沌与非线性时间序列预测方法的前提下,以山东省玉米螟等种群动态资料进行了实例分析。     

混沌与生物系统的研究

介绍了混沌理论的基本思想,研究方法,评述了混沌在生物系统研究中意义,讨论了目前研究中存在的问题和发展的方向。     

取整对Logistic种群模型动态的影响

不考虑环境嗓音,Logistic取整模型的种群动态是非混沌的,只会出现稳态和周期;在1＜r＜3和0＜r＜1区间,取整模型较原始模型能较快收敛到定态或者灭绝;增大K不能消除取整效应;取整模型周期长度受初值、K值和r值的影响;取整是混沌控制的一条新途径,它可能是自然种群中很少能检测到混沌的重要原因之一．     

银鱼的产量能预报吗

将离散Ｌogistic模型应用于银鱼种群数量变动研究,通过对滇池等４个典型湖泊或水库的银鱼年产量变动的初步分析和模拟,发现现的有的湖泊或水库银鱼产量的参数值都落入了混沌区间,在自然生态系统中找到了混沌行为的证据。同时指出：（１）混沌行为使银鱼产量长期预报不可能实现,只有短期预报才能保证必要的精度。（２）严格控制捕劳对尚未繁殖的亲鱼的影响,保留足够的繁殖亲鱼,才能保证资源的持续利用。另一方面,如谷获得相对稳定的产量,可能控制捕捞死亡率Ｆ来改变增增长率参数μ,防止银鱼产量剧烈波动。（３）水域污染和其他破坏水域饵料生物种群结构的因素能导致银鱼的内禀自然增长率γ值和最大种群数量Ｎmax发生变化,从而引起种群的数量变动。     

混沌理论及其在建立神经网络模型中的应用

随着许多学科的相互紧密交叉以及混沌理论的日益深入的研究,人们从生物现象中提出了许多与混沌有关的神经网络模型,本文对混沌理论的基本原理做了简要概述,并着重介绍了四种有代表性的混沌神经网络模型及其应用．同时指出这一研究方向无论在理论还是在应用方面都具有十分诱人的前景．     

Chaotic Signatures of Heart Rate Variability and Its Power Spectrum in Health,Aging and Heart Failure

A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a ‘litmus test’ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative ‘HF chaos’ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF.     

Bifurcations and chaos in a predator-prey system with the Allee effect

It is known from many theoretical studies that ecological chaos may have numerous significant impacts on the population and community dynamics. Therefore, identification of the factors potentially enhancing or suppressing chaos is a challenging problem. In this paper, we show that chaos can be enhanced by the Allee effect. More specifically, we show by means of computer simulations that in a time-continuous predator-prey system with the Allee effect the temporal population oscillations can become chaotic even when the spatial distribution of the species remains regular. By contrast, in a similar system without the Allee effect, regular species distribution corresponds to periodic/quasi-periodic oscillations. We investigate the routes to chaos and show that in the spatially regular predator-prey system with the Allee effect, chaos appears as a result of series of period-doubling bifurcations. We also show that this system exhibits period-locking behaviour: a small variation of parameters can lead to alternating regular and chaotic dynamics.     

Explosive route to chaos through a fractal torus in a generalized Lotka-Volterra model

The behavior of a model that generalizes the Lotka-Volterra problem into three dimensions is presented. The results show the analytic derivation of stability diagrams that describe the system's qualitative features. In particular, we show that for a certain value of the bifurcation parameter the system instantly jumps out of a steady state solution into a chaotic solution that portrays a fractal torus in the three-dimensional phase space. This scenario, is referred to as the explosive route to chaos and is attributed to the non-transversal saddle connection type bifurcation. The stability diagrams also present a region in which the Hopf type bifurcation leads to periodic and chaotic solutions. In addition, the bifurcation diagrams reveal a qualitative similarity to the data obtained in the Texas and Bordeaux experiments on the Belousov-Zhabotinskii chemical reaction. The paper is concluded by showing that the model can be useful for representing dynamics associated with biological and chemical phenomena.     

Time-dependent regimes of a tourism-based social–ecological system: Period-doubling route to chaos

The period-doubling route to chaos has occupied a prominent position and it is still object of great interest among the different complex phenomena observed in nonlinear dynamical systems. The reason of such interest is that such route to chaos has been observed in many physical, chemical and ecological models when they change over from simple periodic to complex aperiodic motion. In interlinked social–ecological systems (SESs) there might be an apparent great ability to cope with change and adapt if analysed only in their social dimension. However, such an adaptation may be at the expense of changes in the capacity of ecosystems to sustain the adaptation and it could affect the quality of ecosystem goods and services since it could degrade natural renewable and non-renewable resources and generate traps and breakpoints in the whole SES eventually leading to chaotic behaviour. This paper is rooted in previous results on modelling tourism-based SESs, only recently object of theoretical investigations, focusing on the dynamics of the coexistence between mass-tourists and eco-tourists. Here we describe a finer scale analysis of time-dependent regimes in the ranges of the degradation coefficient (bifurcation parameter), for which the system can exhibit coexistence. This bifurcation parameter is determined by objective changes in the real world in the quality of ecosystem goods and services together with whether and how such changes are perceived by different tourist typologies. Varying the bifurcation parameter, the dynamical system may in fact evolve toward an aperiodical dynamical state in many ways, showing that there could be different scenarios for the transition to chaos. This paper provides a further evidence for the period-doubling route to chaos with reference to tourism-based socio-ecological models, and for a period locking behaviour, where a small variation in the bifurcation parameter can lead to alternating regular and chaotic dynamics. Moreover, for many models undergoing chaos via period-doubling, it has been showed that structural perturbations with real ecological justification, may break and reverse the expected period-doublings, hence inhibiting chaos. This feature may be of a certain relevance also in the context of adaptive management of tourism-based SESs: these period-doubling reversals might in fact be used to control chaos, since they potentially act in way to suppress possibly dangerous fluctuations.     

Can noise induce chaos?

An important component of the mathematical definition of chaos is sensitivity to initial conditions. Sensitivity to initial conditions is usually measured in a deterministic model by the dominant Lyapunov exponent (LE), with chaos indicated by a positive LE. The sensitivity measure has been extended to stochastic models; however, it is possible for the stochastic Lyapunov exponent (SLE) to be positive when the LE of the underlying deterministic model is negative, and vice versa. This occurs because the LE is a long-term average over the deterministic attractor while the SLE is the long-term average over the stationary probability distribution. The property of sensitivity to initial conditions, uniquely associated with chaotic dynamics in deterministic systems, is widespread in stochastic systems because of time spent near repelling invariant sets (such as unstable equilibria and unstable cycles). Such sensitivity is due to a mechanism fundamentally different from deterministic chaos. Positive SLE's should therefore not be viewed as a hallmark of chaos. We develop examples of ecological population models in which contradictory LE and SLE values lead to confusion about whether or not the population fluctuations are primarily the result of chaotic dynamics. We suggest that "chaos" should retain its deterministic definition in light of the origins and spirit of the topic in ecology. While a stochastic system cannot then strictly be chaotic, chaotic dynamics can be revealed in stochastic systems through the strong influence of underlying deterministic chaotic invariant sets.     

When can noise induce chaos and why does it matter: a critique

Noise‐induced chaos illustrates how small amounts of exogenous noise can have disproportionate qualitative impacts on the long term dynamics of a nonlinear system. This property is particularly clear in chaotic systems but is also important for the majority of ecological systems which are nonchaotic, and has direct implications for analyzing ecological time series and testing models against field data. Dennis et al. point out that a definition of chaos which we advocated allows a noise‐dominated system to be classified as chaotic when its Lyapunov exponent λ is positive, which misses what is really going on. As a solution, they propose to eliminate the concept of noise‐induced chaos: chaos “should retain its strictly deterministic definition”, hence “ecological populations cannot be strictly chaotic”. Instead, they suggest that ecologists ask whether ecological systems are strongly influenced by “underlying skeletons with chaotic dynamics or whatever other dynamics”– the skeleton being the hypothetical system that would result if all external and internal noise sources were eliminated. We agree with Dennis et al. about the problem – noise‐dominated systems should not be called chaotic – but not the solution. Even when an estimated skeleton predicts a system's short term dynamics with extremely high accuracy, the skeleton's long term dynamics and attractor may be very different from those of the actual noisy system. Using theoretical models and empirical data on microtine rodent cycles and laboratory populations of Tribolium, we illustrate how data analyses focusing on attributes of the skeleton and its attractor – such as the “deterministic Lyapunov exponent”λ₀ that Dennis et al. have used as their primary indicator of chaos – will frequently give misleading results. In contrast, quantitative measures of the actual noisy system, such as λ, provide useful information for characterizing observed dynamics and for testing proposed mechanistic explanations.     

Biological Experimental Observations of an Unnoticed Chaos as Simulated by the Hindmarsh-Rose Model

An unnoticed chaotic firing pattern, lying between period-1 and period-2 firing patterns, has received little attention over the past 20 years since it was first simulated in the Hindmarsh-Rose (HR) model. In the present study, the rat sciatic nerve model of chronic constriction injury (CCI) was used as an experimental neural pacemaker to investigate the transition regularities of spontaneous firing patterns. Chaotic firing lying between period-1 and period-2 firings was observed located in four bifurcation scenarios in different, isolated neural pacemakers. These bifurcation scenarios were induced by decreasing extracellular calcium concentrations. The behaviors after period-2 firing pattern in the four scenarios were period-doubling bifurcation not to chaos, period-doubling bifurcation to chaos, period-adding sequences with chaotic firings, and period-adding sequences with stochastic firings. The deterministic structure of the chaotic firing pattern was identified by the first return map of interspike intervals and a short-term prediction using nonlinear prediction. The experimental observations closely match those simulated in a two-dimensional parameter space using the HR model, providing strong evidences of the existence of chaotic firing lying between period-1 and period-2 firing patterns in the actual nervous system. The results also present relationships in the parameter space between this chaotic firing and other firing patterns, such as the chaotic firings that appear after period-2 firing pattern located within the well-known comb-shaped region, periodic firing patterns and stochastic firing patterns, as predicted by the HR model. We hope that this study can focus attention on and help to further the understanding of the unnoticed chaotic neural firing pattern.     

Uncovering chaotic structure in mechanomyography signals of fatigue biceps brachii muscle

The mechanomyography (MMG) signal reflects mechanical properties of limb muscles that undergo complex phenomena in different functional states. We undertook the study of the chaotic nature of MMG signals by referring to recent developments in the field of nonlinear dynamics. MMG signals were measured from the biceps brachii muscle of 5 subjects during fatigue of isometric contraction at 80% maximal voluntary contraction (MVC) level. Deterministic chaotic character was detected in all data by using the Volterra–Wiener–Korenberg model and noise titration approach. The noise limit, a power indicator of the chaos of fatigue MMG signals, was 22.20±8.73. Furthermore, we studied the nonlinear dynamic features of MMG signals by computing their correlation dimension D₂, which was 3.35±0.36 across subjects. These results indicate that MMG is a high-dimensional chaotic signal and support the use of the theory of nonlinear dynamics for analysis and modeling of fatigue MMG signals.