植物群落动态的模型分析

植物群落的动态是植物群落学的中心问题之一,包括更新、波动、演替、进化等主要内容。空间格局对种群和群落的动态起着至关重要的作用,种群空间格局和群落空间结构是群落中各种过程相互作用的产物。模型是描述群落动态、认识植物群落组建和维持机理的有效工具。本文阐述和比较了描述群落动态的四种具有代表性的经验模型,即镶嵌循环模型、随意游走模型、同资源种团比例模型、空间抢先占有模型及其机理。四种经验模型的空间性及缺陷分别是:(1)“镶嵌循环模型”考虑到了相邻斑块之间的植被空间结合在群落动态中的作用,而另外三种模型没有考虑到这一点;(2)在一定程度上,四种植物群落动态模型对各自针对的植物群落可能是适合的,但要作为描述群落动态发展的一般性模型还需要不断完善和发展;因为四种模型均没有考虑到自然干扰和人类干扰对植物群落动态的影响。作者对将来植物群落动态的研究及实践意义做出以下展望:(1)在不同空间尺度上,更加有效地评价控制群落动态变化的各种过程的相对重要性,并进一步将它们之间的复杂相互作用整合到群落动态模型中;(2)充分认识植物群落中存在的各种自然环境条件和生物群体的结构配置对植物群落动态发展的重要性;(3)重视植物群落动态发展中自然干扰过程和人类干扰过程的整合以     

Sensitivity analysis of transient population dynamics

Short-term, transient population dynamics can differ in important ways from long-term asymptotic dynamics. Just as perturbation analysis (sensitivity and elasticity) of the asymptotic growth rate reveals the effects of the vital rates on long-term growth, the perturbation analysis of transient dynamics can reveal the determinants of short-term patterns. In this article, I present a completely new approach to transient sensitivity and elasticity analysis, using methods from matrix calculus. Unlike previous methods, this approach applies not only to linear time-invariant models but also to time-varying, subsidized, stochastic, nonlinear and spatial models. It is computationally simple, and does not require calculation of eigenvalues or eigenvectors. The method is presented along with applications to plant and animal populations.     

Variation in plant quality and the population dynamics of herbivores: there is nothing average about aphids

In the attempt to use results from small-scale studies to make large-scale predictions, it is critical that we take into account the greater spatial heterogeneity encountered at larger spatial scales. An important component of this heterogeneity is variation in plant quality, which can have a profound influence on herbivore population dynamics. This influence is particularly relevant when we consider that the strength of density dependence can vary among host plants and that the strength of density dependence determines the difference between exponential and density- dependent growth. Here, we present some simple models and analyses designed to examine the impact of variable plant quality on the dynamics of insect herbivore populations, and specifically the consequences of variation in the strength of density dependence among host plants. We show that average values of herbivore population growth parameters, calculated from plants that vary in quality, do not predict overall population growth. Furthermore, we illustrate that the quality of a few individual plants within a larger plant population can dominate herbivore population growth. Our results demonstrate that ignoring spatial heterogeneity that exists in herbivore population growth on plants that differ in quality can lead to a misunderstanding of the mechanisms that underlie population dynamics.     

Demographic response of plant populations to habitat fragmentation and temporal environmental variability

Many plant species currently exist in fragmented populations of different sizes, while they also experience unpredictable climatic fluctuation over time. However, we still understand little about how plant demography responds to such spatial and temporal environmental variability. We studied population dynamics of an understory perennial herb Trillium camschatcense in the Tokachi plain of Hokkaido, Japan, where a significant effect of forest fragmentation on seedling recruitment was previously reported. Four populations across a range of fragment sizes were studied for 6 years, and the data were analyzed using matrix population models. Per capita fecundity (the number of recruits per plant) varied greatly among populations, but the variation in population growth rates (λ) was mainly driven by the variation in stasis and growth rates, suggesting that the general trend of reduced fecundity in fragmented populations may not be readily translated into subsequent dynamics. Temporal variation in λ among years was more than 2 times larger than spatial variation among populations, and this result was likely attributable to the contrasting response of correlation structures among demographic rates. The among-population variation in λ was dampened by negative covariation between matrix elements possibly due to density-dependent regulation as well as an inherent constraint that some elements are not independent, whereas positive covariation between matrix elements resulted in large temporal variation in λ. Our results show that population dynamics responded differently to habitat fragmentation and temporal variability of the environment, emphasizing the need to discriminate these spatial and temporal variations in demographic models. Although no populations were projected to be declining in stochastic simulations, correlation between current habitat size and plant density implies historical λ is positively related to habitat size.     

Functional–structural plant models: a growing paradigm for plant studies

A number of research groups in various areas of plant biology as well as computer science and applied mathematics have addressed modelling the spatiotemporal dynamics of growth and development of plants. This has resulted in development of functional–structural plant models (FSPMs). In FSPMs, the plant structure is always explicitly represented in terms of a network of elementary units. In this respect, FSPMs are different from more abstract models in which a simplified representation of the plant structure is frequently used (e.g. spatial density of leaves, total biomass, etc.). This key feature makes it possible to build modular models and creates avenues for efficient exchange of model components and experimental data. They are being used to deal with the complex 3-D structure of plants and to simulate growth and development occurring at spatial scales from cells to forest areas, and temporal scales from seconds to decades and many plant generations. The plant types studied also cover a broad spectrum, from algae to trees. This special issue of Annals of Botany features selected papers on FSPM topics such as models of morphological development, models of physical and biological processes, integrated models predicting dynamics of plants and plant communities, modelling platforms, methods for acquiring the 3-D structures of plants using automated measurements, and practical applications for agronomic purposes.     

Spatio-temporal development of forests – current trends in field methods and models

We present a critical review of current trends in research of spatio-temporal development of forests. The paper addresses (1) field methods for the development of spatially-explicit models of forest dynamics and their integration in models of forest dynamics, (2) strengths and limitations of traditional patch models versus spatially-explicit, individual-based models, and (3) the potential for moment-based methods in the analysis of forest dynamics. These topics are discussed with reference to their potential for solving open questions in the studies of forest dynamics. The study of spatio-temporal processes provides a link between pattern and process in plant communities, and plays a crucial role in understanding ecosystem dynamics. In the last decade, the development of spatially-explicit, individual-based models shifted the focus of forest dynamics modelling from the dynamics of discrete patches to the interactions among individual organisms, thus encapsulating the theory of “neighbourhood” dynamics. In turn, the stochastic properties and the complexity of spatially-explicit, individual-based models gave rise to the development of a new suite of so-called moment-based models. These new models describe the dynamics of individuals and of pairs of individuals in terms of their densities, thus directly capturing second-order information on spatial structure. So far, this approach has not been applied to forests; we indicate extensions needed for such applications. Moment-based models may be an important complement to spatially explicit individual-based models in developing a general spatial theory of forest dynamics. However, both kinds of models currently focus on fine scales, whereas a critical issue in forest dynamics is to understand the interaction of fine-scale processes with coarser-scale disturbances. To obtain a more complete picture of forest dynamics, the relevant links and interactions between fine-, intermediate-, and coarse-scale processes ought to be identified. Intensive links between modelling work and field studies designed across different scales are a promising means to create a new perspective on forest dynamics.     

Urbanization alters the spatiotemporal dynamics of plant–pollinator networks in a tropical megacity

Urbanization is a major driver of biodiversity change but how it interacts with spatial and temporal gradients to influence the dynamics of plant–pollinator networks is poorly understood, especially in tropical urbanization hotspots. Here, we analysed the drivers of environmental, spatial and temporal turnover of plant–pollinator interactions (interaction β-diversity) along an urbanization gradient in Bengaluru, a South Indian megacity. The compositional turnover of plant–pollinator interactions differed more between seasons and with local urbanization intensity than with spatial distance, suggesting that seasonality and environmental filtering were more important than dispersal limitation for explaining plant–pollinator interaction β-diversity. Furthermore, urbanization amplified the seasonal dynamics of plant–pollinator interactions, with stronger temporal turnover in urban compared to rural sites, driven by greater turnover of native non-crop plant species (not managed by people). Our study demonstrates that environmental, spatial and temporal gradients interact to shape the dynamics of plant–pollinator networks and urbanization can strongly amplify these dynamics.     

Accounting for spatial pattern when modeling organism-environment interactions

Statistical models of environment-abundance relationships may be influenced by spatial autocorrelation in abundance, environmental variables, or both. Failure to account for spatial autocorrelation can lead to incorrect conclusions regarding both the absolute and relative importance of environmental variables as determinants of abundance. We consider several classes of statistical models that are appropriate for modeling environment-abundance relationships in the presence of spatial autocorrelation, and apply these to three case studies: 1) abundance of voles in relation to habitat characteristics; 2) a plant competition experiment; and 3) abundance of Orbatid mites along environmental gradients. We find that when spatial pattern is accounted for in the modeling process, conclusions about environmental control over abundance can change dramatically. We conclude with five lessons: 1) spatial models are easy to calculate with several of the most common statistical packages; 2) results from spatially-structured models may point to conclusions radically different from those suggested by a spatially independent model; 3) not all spatial autocorrelation in abundances results from spatial population dynamics; it may also result from abundance associations with environmental variables not included in the model; 4) the different spatial models do have different mechanistic interpretations in terms of ecological processes – thus ecological model selection should take primacy over statistical model selection; 5) the conclusions of the different spatial models are typically fairly similar – making any correction is more important than quibbling about which correction to make.     

Host plant quality,spatial heterogeneity,and the stability of mite predator–prey dynamics

Population dynamics models suggest that both the over-all level of resource productivity and spatial variability in productivity can play important roles in community dynamics. Higher productivity environments are predicted to destabilize consumer–resource dynamics. Conversely, greater heterogeneity in resource productivity is expected to contribute to stability. Yet the importance of these two factors for the dynamics of arthropod communities has been largely overlooked. I manipulated nutrient availability for strawberry plants in a multi-patch experiment, and measured effects of overall plant quality and heterogeneity in plant quality on the stability of interactions between the phytophagous mite Tetranychus urticae and its predator Phytoseiulus persimilis. Plant size, leaf N content and T. urticae population growth increased monotonically with increasing soil nitrogen availability. This gradient in plant quality affected two correlates of mite population stability, population variability over time (i.e., coefficient of variation) and population persistence (i.e., proportion of plant patches colonized). However, the highest level of plant quality did not produce the least stable dynamics, which is inconsistent with the “paradox of enrichment”. Heterogeneity in plant productivity had modest effects on stability, with the only significant difference being less variable T. urticae densities in the heterogeneous compared to the corresponding homogeneous treatment. These results are generally congruent with metapopulation theory and other models for spatially segregated populations, which predict that stability should be governed largely by relative movement rates of predators and prey—rather than patch quality.     

病原菌与自然植物种群Ⅱ病原菌与植物种群生物学

病原菌在自然植物种群中普遍存在,其对寄主植物的生长发育,对寄主植物种群的大小、结构、动态、遗传和进化等都有重要影响。本文着重论述：１）病原菌对寄主植物个体的影响;２）病原菌对寄主植物种群生物学的影响;３）菌病发生的空间格局;４）病原菌感染的种群模型。     

Population consequences of constitutive and inducible plant resistance: herbivore spatial spread

Abstract Little attention has been paid to the impact that constitutive and inducible plant resistance traits will have on herbivore spatial dynamics. We investigate mathematical models in which herbivore demographic rates and movement rates respond to host plant quality, which in turn is determined by constitutive and inducible resistance. Models with and without induced resistance yield the same analytic expression for the asymptotic speed at which a herbivore population will spread through an initially uninduced plant population, suggesting that induced resistance will have no effect on the rate of invasion of herbivores that respond to plant resistance on small spatial scales. In contrast, constitutive resistance will influence the speed of an invasion. If herbivore movement is quite sensitive to plant quality, an increase in constitutive resistance can actually accelerate the rate of herbivore spread even while it reduces the herbivore's intrinsic rate of increase. In other scenarios, the rate of invasion attains a maximum at intermediate levels of constitutive resistance. These results argue that our view of plant resistance should be broadened to include herbivore movement if we are to understand fully the implications of differences in resistance for the dynamics of herbivore populations in natural and managed settings.     

入侵杂草化感作用的细胞自动机模拟研究

细胞自动机模型(Cellular Automata Model,简称CA模型)是一种能够表现系统复杂行为的模拟方法,适于研究植物群落时空动态过程.本文利用CA模型,模拟具有化感作用的外来种入侵原有物种所构成植被的过程.模型由产生化感物质的外来种和两个对化感物质敏感性不同的本地种组合成不同类型的群落,利用化感物质作用下受体物种生物活性响应模型及种子扩散负指数分布模型,模拟外来杂草和本地种分布格局的时空动态变化.结果表明,外来种可成功地完全入侵由两个对化感物质敏感的本地种构成的群落空间,但对于由对化感物质敏感的一个本地种及对化感物质具有抗性的另一个本地种构成的群落,外来种只能够与本地种共存.     

Variation in and correlation between intrinsic rate of increase and carrying capacity

Intrinsic population growth rate and density dependence are fundamental components of population dynamics. Theory suggests that variation in and correlations between these parameters among patches within a population can influence overall population size, but data on the degree of variation and correlation are rare. Replicate populations of a specialist aphid (Chaetosiphon fragaefolii) were followed on 11 genotypes of host plant (Fragaria chiloensis) in the greenhouse. Population models fit to these census data provide estimates of intrinsic growth rate and carrying capacity for aphid populations on each plant genotype. Growth rate and carrying capacity varied substantially among plant genotypes, and these two parameters were not significantly correlated. These results support the existence of spatial variation in population dynamic parameters; data on frequency distributions and correlations of these parameters in natural populations are needed for evaluation of the importance of variation in growth rate and density dependence for population dynamics in the field.     

Parasite–grass–forb interactions and rock–paper– scissor dynamics: predicting the effects of the parasitic plant Rhinanthus minor on host plant communities

1.  Parasitic plants affect the growth, reproduction and metabolism of their hosts and may also influence the outcome of competitive interactions between host species and, consequently, the structure of entire host communities.
2.  We investigate the effect of the root hemiparasitic plant Rhinanthus minor on plant community dynamics using a spatial theoretical model. The model is parameterized with data from pairwise interaction experiments under two nutrient levels between the hemiparasite and three grass species ( Cynosurus cristatus , Festuca rubra and Phleum bertolonii ) and three forb species ( Leucanthemum vulgare , Plantago lanceolata and Ranunculus acris ).
3.  Relative interaction coefficients were intransitive, with the dynamics of the system conforming to a rock–paper–scissors game. Stable deterministic dynamics emerge from parameters obtained under low-nutrient conditions. Under high-nutrient conditions, the dynamics are unstable, but are stabilized in spatially explicit models. The outcomes are sensitive to initial spatial pattern and frequency.
4.   Synthesis . This study supports the idea that hemiparasite populations may form 'shifting clouds' in natural populations and explains seemingly unpredictable shifts in host community structure following introduction of hemiparasites. Management of plant communities using hemiparasites needs to take these complex dynamics into account.     

集合种群动态对生境毁坏空间异质性的响应

首次将分形几何(Fractal geometry)与元胞自动机(Cellular automata)相结合,研究了破碎化生境中集合种群的空间分布格局动态,以及集合种群动态对生境毁坏空间异质性的响应。研究发现:(1)各个物种种群在生境中的分布具有很好的分形特征,物种的计盒维数(Box dimension)不仅可以很好地反映种群的空间分布结构,也能很好地反映种群动态。(2)如果将空间因素考虑进来的话,生境毁坏的灭绝债务(Time debt)将大于空间隐含模式所模拟的结果。(3)物种灭绝同时存在强物种灭绝和弱物种灭绝。并且只有在生境随机毁坏下,才与空间隐含的模拟结果比较接近,即强物种中将是最强物种率先灭绝。而在边缘毁坏这种比较集中成块的开发方式下,将是较强的物种灭绝。(4)边缘毁坏相对随机毁坏有利于物种,尤其是弱物种的长期续存。     

Spatial models of virus-immune dynamics

To date, the majority of theoretical models describing the dynamics of infectious diseases in vivo are based on the assumption of well-mixed virus and cell populations. Because many infections take place in solid tissues, spatially structured models represent an important step forward in understanding what happens when the assumption of well-mixed populations is relaxed. Here, we explore models of virus and virus-immune dynamics where dispersal of virus and immune effector cells was constrained to occur locally. The stability properties of our spatial virus-immune dynamics models remained robust under almost all biologically plausible dispersal schemes, regardless of their complexity. The various spatial dynamics were compared to the basic non-spatial dynamics and important differences were identified: When space was assumed to be homogeneous, the dynamics generated by non-spatial and spatially structured models differed substantially at the peak of the infection. Thus, non-spatial models may lead to systematic errors in the estimates of parameters underlying acute infection dynamics. When space was assumed to be heterogeneous, spatial coupling not only changed the equilibrium properties of the uncoupled populations but also equalized the dynamics and thereby reduced the likelihood of dynamic elimination of the infection. In line with experimental and clinical observations, long-lasting oscillation periods were virtually absent. When source-sink dynamics were considered, the long-term outcome of the infection depended critically on the degree of spatial coupling. The infection collapsed when emigration from source sites became too large. Finally, we discuss the implications of spatially structured models on medical treatment of infectious diseases, and note that a huge gap exists in data accurately describing infection dynamics in solid tissues.     

Inferring the dynamics of a spatial epidemic from time-series data

Spatial interactions are key determinants in the dynamics of many epidemiological and ecological systems; therefore it is important to use spatio-temporal models to estimate essential parameters. However, spatially-explicit data sets are rarely available; moreover, fitting spatially-explicit models to such data can be technically demanding and computationally intensive. Thus non-spatial models are often used to estimate parameters from temporal data. We introduce a method for fitting models to temporal data in order to estimate parameters which characterise spatial epidemics. The method uses semi-spatial models and pair approximation to take explicit account of spatial clustering of disease without requiring spatial data. The approach is demonstrated for data from experiments with plant populations invaded by a common soilborne fungus, Rhizoctonia solani. Model inferences concerning the number of sources of disease and primary and secondary infections are tested against independent measures from spatio-temporal data. The applicability of the method to a wide range of host-pathogen systems is discussed.     

植物群落中物种小尺度空间结构研究

植物群落中, 物种小尺度空间结构影响着种群或群落的动态及有关的生态学过程。植物主要是和它同种或异种的邻近个体相互作用,植物个体周围的局部环境和大空间尺度下群落的平均水平是完全不同的。群落中的许多过程都影响小尺度空间结构的形成和动态,同样,局部空间结构反过来影响着植物的生长、更新和凋亡等重要过程。鉴于目前对小尺度空间结构进行的大量研究以及其重要性,有必要对其研究进展进行适当的总结,以期明确将来进一步的研究方向。该文以此为出发点,首先介绍了植物群落中物种小尺度空间结构产生的6个原因:1)生境的空间异质性;2)植物繁殖体的传播;3)植物之间的相互作用;4)生物环境(动物和微生物)的作用;5)外界干扰的作用;6)多因子综合作用。然后阐述了小尺度空间结构意义及对生物多样性、植物种群遗传学和恢复生态学研究的影响。最后对目前物种小尺度空间结构研究存在的几点问题及将来的研究方向作以下归纳:1)大尺度植被动态的研究应该整合小尺度空间结构的信息;2)不论从生物学还是生态学上来讲, 植被小尺度空间结构的研究应该把植物作为中心,确定适当的尺度和采取合理的空间统计方法;3)充分重视小尺度空间结构在退化生态系统恢复中的应用意义;4)注重从小尺度的局部格局研究入手对群落总体特征进行整合;5)植物群落动态研究中,物种小尺度空间结构与平均场假说相结合的必要性。     

Dispersal evolution in temporally variable environments: implications for plant range dynamics

Dispersal—the movement of an individual from the site of birth to a different site for reproduction—is an ecological and evolutionary driver of species ranges that shapes patterns of colonization, connectivity, gene flow, and adaptation. In plants, the traits that influence dispersal often vary within and among species, are heritable, and evolve in response to the fitness consequences of moving through heterogeneous landscapes. Spatial and temporal variation in the quality and quantity of habitat are important sources of selection on dispersal strategies across species ranges. While recent reviews have evaluated the interactions between spatial variation in habitat and dispersal dynamics, the extent to which geographic variation in temporal variability can also shape range-wide patterns in dispersal traits has not been synthesized. In this paper, we summarize key predictions from metapopulation models that evaluate how dispersal evolves in response to spatial and temporal habitat variability. Next, we compile empirical data that quantify temporal variability in plant demography and patterns of dispersal trait variation across species ranges to evaluate the hypothesis that higher temporal variability favors increased dispersal at plant range limits. We found some suggestive evidence supporting this hypothesis while more generally identifying a major gap in empirical work evaluating plant metapopulation dynamics across species ranges and geographic variation in dispersal traits. To address this gap, we propose several future research directions that would advance our understanding of the interplay between spatiotemporal variability and dispersal trait variation in shaping the dynamics of current and future species ranges.