Relating coupled map lattices to integro-difference equations: dispersal-driven instabilities in coupled map lattices

Recently there has been a great deal of interest within the ecological community about the interactions of local populations that are coupled only by dispersal. Models have been developed to consider such scenarios but the theory needed to validate model outcomes has been somewhat lacking. In this paper, we present theory which can be used to understand these types of interaction when population exhibit discrete time dynamics. In particular, we consider a spatial extension to discrete-time models, known as coupled map lattices (CMLs) which are discrete in space. We introduce a general form of the CML and link this to integro-difference equations via a special redistribution kernel. General conditions are then derived for dispersal-driven instabilities. We then apply this theory to two discrete-time models; a predator-prey model and a host-pathogen model.     

Using mechanistic models to understand synchrony in forest insect populations: the North American gypsy moth as a case study

In many forest insects, subpopulations fluctuate concurrently across large geographical areas, a phenomenon known as population synchrony. Because of the large spatial scales involved, empirical tests to identify the causes of synchrony are often impractical. Simple models are, therefore, a useful aid to understanding, but data often seem to contradict model predictions. For instance, chaotic population dynamics and limited dispersal are not uncommon among synchronous forest defoliators, yet both make it difficult to achieve synchrony in simple models. To test whether this discrepancy can be explained by more realistic models, we introduced dispersal and spatially correlated stochasticity into a mechanistic population model for the North American gypsy moth Lymantria dispar. The resulting model shows both chaotic dynamics and spatial synchrony, suggesting that chaos and synchrony can be reconciled by the incorporation of realistic dynamics and spatial structure. By relating alterations in model structure to changes in synchrony levels, we show that the synchrony is due to a combination of spatial covariance in environmental stochasticity and the origins of chaos in our multispecies model.     

Density-dependent birth rate, birth pulses and their population dynamic consequences

 In most models of population dynamics, increases in population due to birth are assumed to be time-independent, but many species reproduce only during a single period of the year. We propose a single-species model with stage structure for the dynamics in a wild animal population for which births occur in a single pulse once per time period. Using the discrete dynamical system determined by the stroboscopic map, we obtain an exact periodic solution of systems which are with Ricker functions or Beverton-Holt functions, and obtain the threshold conditions for their stability. Above this threshold, there is a characteristic sequence of bifurcations, leading to chaotic dynamics, which implies that the dynamical behaviors of the single species model with birth pulses are very complex, including small-amplitude annual oscillations, large-amplitude multi-annual cycles, and chaos. This suggests that birth pulse, in effect, provides a natural period or cyclicity that allows for a period-doubling route to chaos. Received: 13 June 2001 / Revised version: 7 September 2001 / Published online: 8 February 2002     

Allee effects, invasion pinning, and species' borders

All species' ranges are the result of successful past invasions. Thus, models of species' invasions and their failure can provide insight into the formation of a species' geographic range. Here, we study the properties of invasion models when a species cannot persist below a critical population density known as an "Allee threshold." In both spatially continuous reaction-diffusion models and spatially discrete coupled ordinary-differential-equation models, the Allee effect can cause an invasion to fail. In patchy landscapes (with dynamics described by the spatially discrete model), range limits caused by propagation failure (pinning) are stable over a wide range of parameters, whereas, in an uninterrupted habitat (with dynamics described by a spatially continuous model), the zero velocity solution is structurally unstable and thus unlikely to persist in nature. We derive conditions under which invasion waves are pinned in the discrete space model and discuss their implications for spatially complex dynamics, including critical phenomena, in ecological landscapes. Our results suggest caution when interpreting abrupt range limits as stemming either from competition between species or a hard environmental limit that cannot be crossed: under a wide range of plausible ecological conditions, species' ranges may be limited by an Allee effect. Several example systems appear to fit our general model.     

Variability,vagueness and comparison methods for ecological models

A unified approach is presented for the construction and analysis of models for the dynamics of populations and communities in the presence of temporal variability, vague density dependence, chaos or analytical intractability. The approach is based on comparisons involving simpler models which provide ceilings and floors to the densities predicted by the full models. The method is applied to examples of several types of models, including difference equations, ordinary differential equations, non-linear Leslie matrices and reaction-diffusion equations. The models treated describe various ecological phenomena including self-regulation, competition, predator-prey interactions, age structure and spatial structure. Some results needed for the analysis of matrix models and patch models are given in the Appendix. Research partially supported by NSF grant DMS-93-03708.     

Incorporating spatial variation in density enhances the stability of simple population dynamics models

Simple discrete time models of population growth admit a wide variety of dynamic behaviors, including population cycles and chaos. Yet studies of natural and laboratory populations typically reveal their dynamics to be relatively stable. Many explanations for the apparent rarity of unstable or chaotic behavior in real populations have been developed, including the possible stabilizing roles of migration, refugia, abrupt density-dependence, and genetic variation in sensitivity to density. We develop a theoretical framework for incorporating random spatial variation in density into simple models of population growth, and apply this approach to two commonly used models in ecology: the Ricker and Hassell maps. We show that the incorporation of spatial density variation into both these models has a strong stabilizing influence on their dynamic behavior, and leads to their exhibiting stable point equilibria or stable limit cycles over a relatively much larger range of parameter values. We suggest that one reason why chaotic population dynamics are less common than the simple models indicate is, these models typically neglect the potentially stabilizing role of spatial variation in density.     

Demographic noise and resilience in a semi-arid ecosystem model

The scarcity of water characterising drylands forces vegetation to adopt appropriate survival strategies. Some of these generate water–vegetation feedback mechanisms that can lead to spatial self-organisation of vegetation, as it has been shown with models representing plants by a density of biomass, varying continuously in time and space. However, although plants are usually quite plastic they also display discrete qualities and stochastic behaviour. These features may give rise to demographic noise, which in certain cases can influence the qualitative dynamics of ecosystem models. In the present work we explore the effects of demographic noise on the resilience of a model semi-arid ecosystem. We introduce a spatial stochastic eco-hydrological hybrid model in which plants are modelled as discrete entities subject to stochastic dynamical rules, while the dynamics of surface and soil water are described by continuous variables. The model has a deterministic approximation very similar to previous continuous models of arid and semi-arid ecosystems. By means of numerical simulations we show that demographic noise can have important effects on the extinction and recovery dynamics of the system. In particular we find that the stochastic model escapes extinction under a wide range of conditions for which the corresponding deterministic approximation predicts absorption into desert states.     

Periodic forcing of microbial cultures: a model for induction synchrony

Periodic environmental shifts have been used to induce synchrony in many different microbial populations. In this article, the induction synchrony phenomenon is analyzed using an age distribution model in which the age at which the cells divide is subjected to periodic forcing. It is found that synchrony will occur whenever the period of the forcing lies in the interval between the youngest and the oldest division age that occur in the population during the forcing. The analysis also predicts that under certain conditions it should be possible to obtain a multimodal synchrony in which cells in the population are distributed among a set of discrete, synchronized cell lines. The behavior of the age distribution when the conditions for synchrony are not satisfied is briefly explored. It is found that the age distribution model is able to exhibit a very rich spectrum of possible dynamic behavior. Many of the phenomena observed can be thought of in terms that are familiar from nonlinear analysis, such as stable and unstable limit cycles, period doubling, halving, and chaos. The richness of dynamic behavior opens the possibility that environmental shifts or periodic forcing could be used as a powerful tool in discriminating models of microbial kinetics and cell cycle control.     

集合种群空间混沌的模拟研究以及Allee效应、拥挤效应与捕食效应对空间模式的影响

集合种群的空间模式研究是当今生态学的核心问题之一。本研究利用常微分动力系统以及基于网格模型的元胞自动机模型对Allee效应、拥挤效应以及捕食作用集合种群的空间分布模式做了全面的模拟研究。Allee效应描述当种群水平低于某一阈值时会发生由生殖成功几率下降造成的种群负增长率,而拥挤效应是指当种群密度过高时引起的个体性为异常从而达到调节种群增长率的作用。文章组建了3个空间确定性模型：局部作用模型(CIM)、距离敏感模型(DSM)和集合种群捕食模型(MMP)。局部作用模型显示在一维生境中空斑块形成金字塔状,二维模型显示出明显的动态拟周期性以及由空间混沌所形成的异质性。距离敏感模型可导致由迁移个体中密度制约强度决定的集合种群大小复杂动态与种群密度的双峰分布。这些结果说明动态行为的复杂性,不仅可用于表征研究物种的特性,而且可以表明该物种的续存能力与灭绝风险。集合种群捕食模型是概率转换空间模型,利用该模型得出了依赖于模型参数和生境尺度的白组织种群概率空间分布模式。模拟的结果表明,系统的内在机制和这种白组织模式导致捕食者形成集团型不明显的“捕食小组”或“杀手小组”,并具有较高扩散力．但却包括侵占率低、灭绝率高的特点。而使猎物种群形成高集团性、高侵占率、低灭绝率、低扩散力的种群集团。这种特点又使捕食者种群在生境中处于中心地带,而使猎物种群形成在捕食者和生境边缘间的环状分布。这些结果还说明了尺度对于生态学的研究是至关重要的,不同的尺度将产生不同的系统模式。     

Functional response,numerical response,and stability in arthropod predator-prey ecosystems involving age structure

Summary A general model of arthropod predator-prey systems incorporating age structure in the predator is employed to study the role of functional and numerical responses on stability and the paradox of enrichment. The destabilizing effect of age structure leads to both qualitatively and quantitatively new results for an environment which has an infinite prey carrying capacity, including a lower bound to prey density for a stable equilibrium, a feature not present in models without age structure. When applied to an environment with finite prey carrying capacity, the effect of age structure is to reinforce the arguments implicit to the paradox of enrichment originally developed for traditional models lacking age structure.     

Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker-trait associations in sugarcane

Few association mapping studies have simultaneously accounted for population structure, genotype by environment interaction (GEI), and spatial variation. In this sugarcane association mapping study we tested models accounting for these factors and identified the impact that each model component had on the list of markers declared as being significantly associated with traits. About 480 genotypes were evaluated for cane yield and sugar content at three sites and scored with DArT markers. A mixed model was applied in analysis of the data to simultaneously account for the impacts of population structure, GEI, and spatial variation within a trial. Two forms of the DArT marker data were used in the analysis: the standard discrete data (0, 1) and a continuous DArT score, which is related to the marker dosage. A large number of markers were significantly associated with cane yield and sugar content. However, failure to account for population structure, GEI, and (or) spatial variation produced both type I and type II errors, which on the one hand substantially inflated the number of significant markers identified (especially true for failing to account for GEI) and on the other hand resulted in failure to detect markers that could be associated with cane yield or sugar content (especially when failing to account for population structure). We concluded that association mapping based on trials from one site or analysis that failed to account for GEI would produce many trial-specific associated markers that would have low value in breeding programs.     

Continuum or discrete patch landscape models for savanna birds? Towards a pluralistic approach

Conceptualising landscapes as a mosaic of discrete habitat patches is fundamental to landscape ecology, metapopulation theory and conservation biology. An emerging question in ecology is: when is the discrete patch model more appropriate than alternative and conceptually appealing models such as the continuum model? There is limited empirical testing of the utility of alternative landscape models compared to the discrete patch model for a range of species. In this paper, we constructed three alternative sets of models for testing the effect of landscape structure on diversity and abundance of a suite of woodland birds in a savanna landscape of northern Australia: the null model (only site‐scale habitat variables, landscape context not important), the continuum model, and the discrete patch model. We utilised high‐spatial resolution satellite images to quantify spatial gradients in tree cover density (the continuum model), and to then aggregate the fine‐scale heterogeneity in tree cover into discrete patches of trees, with grass cover forming the “matrix” (the discrete patch‐model). We then evaluated the relative importance of the alternative models using generalised linear models and an information theoretic approach. We found that the importance of the models varied among species, with no single model dominant. Species that move between open grassy areas and woody shelter responded well to the continuum model, reflecting the importance of gradients in density of forage (grasses) and cover (trees), while the discrete model performed best for species that forage in all vegetation strata, and nest predominantly in dense woody vegetation. This finding supports a pluralistic approach, highlighting the need for adopting and testing more than one landscape model in savanna landscapes, and in other landscapes that do not have a well defined patch structure.     

Competition for space can drive the evolution of dormancy in a temporally invariant environment

I present a model for the evolution of a seed bank in the absence of externally driven environmental variation. I use Evolutionarily Stable Strategy (ESS) analyses of both analytic and simulation models to assess the conditions under which a dormant genotype can invade and resist invasion. In my models, plant seeds compete through lottery for discrete safe sites holding one individual each. Analyzing the conditions under which a dormant genotype can invade when rare and resist invasion once established, I conclude that dormancy can be an ESS when some fraction of seeds is retained locally, seed bank survival is high, and mortality in the seed bank is low. The advantage of dormancy stems from the ability of dormant seeds to recapture a lost site and the fact that a plant’s offspring are more likely to win the lottery in its own site than in any new site. The advantage of dormancy does not depend on individual fecundity or on low relatedness with the offspring of kin, making this mechanism distinct from earlier models of sib competition.     

A unifying framework for chaos and stochastic stability in discrete population models

 In this paper we propose a general framework for discrete time one-dimensional Markov population models which is based on two fundamental premises in population dynamics. We show that this framework incorporates both earlier population models, like the Ricker and Hassell models, and experimental observations concerning the structure of density dependence. The two fundamental premises of population dynamics are sufficient to guarantee that the model will exhibit chaotic behaviour for high values of the natural growth and the density-dependent feedback, and this observation is independent of the particular structure of the model. We also study these models when the environment of the population varies stochastically and address the question under what conditions we can find an invariant probability distribution for the population under consideration. The sufficient conditions for this stochastic stability that we derive are of some interest, since studying certain statistical characteristics of these stochastic population processes may only be possible if the process converges to such an invariant distribution. Received 15 May 1995; received in revised form 17 April 1996     

A general population-genetic model for the production by population structure of spurious genotype-phenotype associations in discrete, admixed or spatially distributed populations

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle--applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.     

Matrix models and sensitivity analysis of populations classified by age and stage: a vec-permutation matrix approach

Matrix population models in which individuals are classified by both age and stage can be constructed using the vec-permutation matrix. The resulting age-stage models can be used to derive the age-specific consequences of a stage-specific life history or to describe populations in which the vital rates respond to both age and stage. I derive a general formula for the sensitivity of any output (scalar, vector, or matrix-valued) of the model, to any vector of parameters, using matrix calculus. The matrices describing age-stage dynamics are almost always reducible; I present results giving conditions under which population growth is ergodic from any initial condition. As an example, I analyze a published stage-specific model of Scotch broom (Cytisus scoparius), an invasive perennial shrub. Sensitivity analysis of the population growth rate finds that the selection gradients on adult survival do not always decrease with age but may increase over a range of ages. This may have implications for the evolution of senescence in stage-classified populations. I also derive and analyze the joint distribution of age and stage at death and present a sensitivity analysis of this distribution and of the marginal distribution of age at death.     

When individual life history matters: conditions for juvenile-adult stage structure effects on population dynamics

Ecological theory about the dynamics of interacting populations is mainly based on unstructured models that account for species abundances only. In turn, these models constitute the basis for our understanding of the functioning of ecological communities and ecosystems and their responses to environmental change, natural disturbances and human impacts. Structured models that take into account differences between individuals in age, stage or size have been shown to sometimes make predictions that run counter to the predictions of unstructured analogues. It is however unclear which biological mechanisms that are accounted for in the structured models give rise to these contrasting predictions. Focusing on two particular rules-of-thumb that generally hold in unstructured consumer-resource models, one relating to the relationship between mortality and equilibrium density of the consumer and the other relating to the stability of the equilibrium, I investigate the necessary conditions under which accounting for juvenile-adult stage structure can lead to qualitatively different model predictions. In particular, juvenile-adult stage structure is shown to overturn the two rules-of-thumb in case the model also accounts for the energetic requirements for basic metabolic maintenance. Given the fundamental nature of both juvenile-adult stage structure as well as metabolic maintenance requirements, these results call into question the generality of the predictions derived from unstructured models.     

Analysis of periodic growth-disturbance models

In this paper, I present and discuss a potentially useful modeling approach for investigating population dynamics in the presence of disturbance. Using the motivating example of wildfire, I construct and analyze a deterministic model of population dynamics with periodic disturbances independent of spatial effects. Plant population growth is coupled to fire disturbance to create a growth-disturbance model for a fluctuating population. Changes in the disturbance frequency are shown to generate a period-bubbling bifurcation structure and population dynamics that are most variable at intermediate disturbance frequencies. Similar dynamics are observed when the model is extended to include a seed bank. Some general conditions necessary for a rich bifurcation structure in growth-disturbance models are discussed.     

Self-organization, scale and stability in a spatial predator-prey interaction

Simple predator-prey models often predict extreme instability in interactions where the prey are depressed well below their carrying capacity. Although the behaviour of some laboratory systems conforms to this pattern, field and mesocosm studies generally show prolonged co-existence of prey and predator. Prominent among the possible causes of this discrepancy are the effects of spatial heterogeneity. In this paper we show that both discrete and continuous representations of the spatial Rosenzweig-McArthur model with immobile prey can be stabilized by self-organized prey heterogeneity. This concordance of behaviour closely parallels that which we have previously established in the context of invasion waves. We use the continuous model variant to calculate the characteristic spatial scales of the self-organized structures. The discrete variant forms the basis of a simulation study demonstrating the variety of stable structures and elucidating their relation to the history of the system. We note that all stable prey distributions take the form of a network of occupied patches separated by prey-free regions, and liken the process which generates such assemblages to the formation of a landscape mozaic.     

Resolving discrepancies between deterministic population models and individual-based simulations

ABSTRACT This work ties together two distinct modeling frameworks for population dynamics: an individual-based simulation and a set of coupled integrodifferential equations involving population densities. The simulation model represents an idealized predator-prey system formulated at the scale of discrete individuals, explicitly incorporating their mutual interactions, whereas the population-level framework is a generalized version of reaction-diffusion models that incorporate population densities coupled to one another by interaction rates. Here I use various combinations of long-range dispersal for both the offspring and adult stages of both prey and predator species, providing a broad range of spatial and temporal dynamics, to compare and contrast the two model frameworks. Taking the individual-based modeling results as given, two examinations of the reaction-dispersal model are made: linear stability analysis of the deterministic equations and direct numerical solution of the model equations. I also modify the numerical solution in two ways to account for the stochastic nature of individual-based processes, which include independent, local perturbations in population density and a minimum population density within integration cells, below which the population is set to zero. These modifications introduce new parameters into the population-level model, which I adjust to reproduce the individual-based model results. The individual-based model is then modified to minimize the effects of stochasticity, producing a match of the predictions from the numerical integration of the population-level model without stochasticity.