基于植物多样性的生态系统恢复动力学原理

生态系统恢复动力学是生态学的重要问题.本研究利用岛屿生物地理学、植物群落演替、生物多样性维持机制及生态系统功能等有关理论,推导了生态系统恢复动力学模型,并用半湿润常绿阔叶林次生演替阶段数据作了初步验证.基于动力学模型讨论了动力学原理.结果表明,生态系统恢复的动力学过程决定于生态系统恢复力F1、干扰力F2和环境阻力F3的综合作用.植物多样性恢复速度的变率与植物种丰富度呈反比,与生态系统恢复总动力F呈正比.生态系统恢复力F1和环境阻力F3是初始物种丰富度s0、特定地理区域资源环境状况的函数.干扰力是干扰强度系数b和物种丰富度s的函数.当生态系统存在有害干扰的条件下,物种丰富度不能达到生态系统最高物种丰富度sm.动力学模型显示,初始物种丰富度s0越小,生态系统恢复过程越具有逻辑斯蒂性.建立了生态系统恢复力、环境阻力和干扰力的计算模型和植物多样性、干扰对生态系统恢复的作用模型.生态系统恢复动力模型显示,植物多样性能增加生态系统恢复力,促进生态系统稳定性.     

西沙珊瑚礁生态系统完整性评价与动态仿真模拟研究

以中国西沙珊瑚礁生态监控区为例,从生态系统完整性视角出发,结合珊瑚礁功能群组与环境变化的多重反馈效应,运用系统动力学方法构建了西沙珊瑚礁生态系统动态诊断模型,并通过基础情景和典型干扰情景（捕捞活动、陆源沉积、长棘海星（Acanthaster planci）暴发）的模拟过程,分析该生态监控区2010-2050年生态系统完整性的发展趋势及演变机理。结果显示：（1）系统动力学与生态系统完整性评价方法的整合,为珊瑚礁生态系统完整性的定量研究提供了一种可行性的方法;（2）珊瑚礁生态系统各效应指数中累积效应的变化最为明显,2010-2050年指数最大增长17.2,年均增长率约为1.2%,综合完整性指数在波动变化中稳步上升,珊瑚礁受损程度由中受损向中、低受损转变;（3）不同状态的珊瑚礁生态系统完整性,在其演化的不同阶段各有差异性,并且这种差异通常随时间推移才逐渐放大;（4）无论何种情景下,珊瑚礁生态系统都具有一定的恢复能力,尤其处于系统演化的释放重组阶段（2035-2040年）,生态系统的不稳定将创造了一定的可恢复性。研究结果对于分析西沙珊瑚礁生态系统的整体演化过程提供了理论借鉴,也为我国后续的珊瑚礁生态系统适应性修复理论模式研究提供了重要的基础。     

基于管理目标的湖泊生态系统动力学

基于生态系统管理的目标,在对相关研究分析的基础上,依据生态系统生态学、淡水生态学的理论,提出了湖泊生态系统动力学研究的2个理论基础：生态系统管理和生态系统特征.在此基础上,分析得到湖泊生态系统动力学的研究方法体系,主要包括研究内容与技术路线、关键问题识别和动力学模拟、湖泊生态系统的适应性管理决策等部分.其中,湖泊生态系统结构和过程、湖泊中食物网营养动力学研究、生源要素循环、湖泊中关键过程的生态作用以及湖泊生态系统动力学模拟是研究的核心问题.此后,以P为主要的生源要素,将生态系统分为3个子过程：入流、出流和内部反馈,并以此建立了湖泊生态系统动力学的模型框架,以辅助于湖泊的生态系统管理.     

The coupling of biogeochemical cycles of nutrients

For any element which is incorporated into biomass, the biogeochemical cycle of that element in a given ecosystem will be coupled to that of any other element similarly incorporated. The mutual interaction of two such cycles is examined using a simple model in which each cycle is constrained into four compartments. In each cycle the assimilation rate (primary productivity) is related in a non-linear fashion to the two nutrients and to biomass. The interactions are represented by combining a hyperbolic dependence for each nutrient (involving a "Michaelis constant") with a logistic equation governing the dependence of rate on biomass (involving a "carrying capacity"). The response of the model to perturbation (e.g. mobilization of an abiotic reserve) is strongly governed by the values assigned to these constants. The coupled cycles can exhibit positive feed-back with anomalous responses of the steady state and time-dependent solutions may exhibit complex oscillatory behaviour. Both the steady-state sensitivity and the kinetic behaviour of such coupled systems are simplified if the range of atomic ratios permitted by the assimilation process is restricted. It will therefore be of importance to determine under what conditions the assimilation rates for different elements are governed by mass-action effects (Liebig's Law) or by stoichiometric constraints (Redfield ratios).     

Meta-ecosystem dynamics and functioning on finite spatial networks

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory.     

Environmentally‐induced noise dampens and reddens with increasing trophic level in a complex food web

Stochastic variability of key abiotic factors including temperature, precipitation and the availability of light and nutrients greatly influences species’ ecological function and evolutionary fate. Despite such influence, ecologists have typically ignored the effect of abiotic stochasticity on the structure and dynamics of ecological networks. Here we help to fill that gap by advancing the theory of how abiotic stochasticity, in the form of environmental noise, affects the population dynamics of species within food webs. We do this by analysing an allometric trophic network model of Lake Constance subjected to positive (red), negative (blue), and non‐autocorrelated (white) abiotic temporal variability (noise) introduced into the carrying capacity of basal species. We found that, irrespective of the colour of the introduced noise, the temporal variability of the species biomass within the network both reddens (i.e. its positive autocorrelation increases) and dampens (i.e. the magnitude of variation decreases) as the environmental noise is propagated through the food web by its feeding interactions from the bottom to the top. The reddening reflects a buffering of the noise‐induced population variability by complex food web dynamics such that non‐autocorrelated oscillations of noise‐free deterministic dynamics become positively autocorrelated. Our research helps explain frequently observed red variability of natural populations by suggesting that ecological processing of environmental noise through food webs with a range of species’ body sizes reddens population variability in nature.     

Ecological Stability: Reality,Misconceptions, and Implications for Risk Assessment

Over a long time frame, an ecological system may not exhibit constancy due to successional and evolutionary changes in the species composing the system. However, over shorter time frames an ecological system exhibits a certain degree of constancy (i.e., varies within defined bounds). Traditionally, ecologists considered this short-term constancy to reflect a “balance of nature,” which was viewed akin to the simple homeostatic dynamics of physiological systems. This is an appealing perspective because the disruption of the system's “balance” (i.e., its ”health“) can be ascertained by comparing the system's current state after the imposition of a perturbation with the societally desired state (i.e., baseline). Recently, ecologists have started to develop a much more complex, and perhaps more realistic, perspective regarding ecosystem dynamics, which does not depend upon homeostasis with a single baseline state. This new view includes stochastic variation, nonlinear dynamics and alternative states, and poses a challenge for assessing environmental “health” and the risk of creating “unhealthy” ecological systems     

复杂生态系统分形层次结构的统计动力学分析

生态系统具有异质性、非线性、多层次性等复杂特性.针对生态系统的复杂性,从统计动力学的视角出发,从生态组元相互作用的微观动力学角度,对生态系统分形层次结构的起源及其形成过程的动力学机理进行了初步探讨,并分析了生态系统分形维数的影响因素及机理.对理论结果与实际例子进行了比较,并讨论了在实践中的可能应用.     

Ecosystem dynamics through the past 2000 years as revealed by fossil mammals from Lamar cave in Yellowstone National Park,USA

Lamar Cave, a late Holocene paleontological site in Yellowstone National Park, USA, has yielded 36 fossil mammal species from 10 stratigraphic units representing about 2000 years. The fossil fauna is similar to the mammals in the park today and affords a unique opportunity to investigate paleocommunity and ecosystem dynamics through time.

Remains of an extralimital species in Yellowstone today, Microtus ochrogaster are found only in the oldest cave deposits, dated at 1695 ± 60 yr B.P. Disappearance of this species by about 1550 years ago marks evolution into the ecosystem that has persisted into the present and is recognizable by a fossil mammal assemblage that is virtually identical to the modern one. Relative abundance fluctuations in the mammal populations imply community resilience through the past 2000 years. Trends in relative abundances of small mammals, particularly the inverse relationship between Microtus and Spermophilus are interpreted as evidence of declining grass cover near Lamar Cave between approximately 1500 and 1000 years ago. The initiation of this environmental change may well have stimulated the ecosystem change marked by Microtus ochrogaster extirpation. Support for this hypothesis is found in a pollen record from a nearby lake.     

Habitat structure mediates biodiversity effects on ecosystem properties

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised.     

采伐和火烧对森林氮动态的影响

森林是重要的陆地生态系统类型,它通过特有的养分循环机制维持其结构和功能.其中氮素对林木生长和发育十分重要,而且常是森林生产力的限制因素.另一方面,森林氮动态又常受到人类活动干扰的影响.根据国内外研究结果综述了采伐和火烧对森林氮动态的影响.结果表明采伐后环境因素的变化将影响森林N动态,其中最为关注的是采伐后一系列因素引起的N损失,如:N淋溶增加、伴随生物量的N迁移以及因径流或侵蚀增加造成的枯枝落叶层和土壤层N流失.这些N损失又将影响更新林分的生长和生产力.此外,采伐后N吸收速率一般下降,但随着植被快速生长N吸收速率将不断增加.采伐后氨化和硝化过程增强,但因短期内同化作用较弱,生态系统中大部分N将发生损失.火烧对森林N动态的短期影响主要包括:第一,火烧时N直接挥发损失;第二,火烧后N有效性增加,这主要由灰分沉积、根和微生物死亡及有机质N矿化增强等综合造成.随着时间延长,N有效性逐渐降低,这可能与火烧引起的有机质损失、植物N吸收增加、淋溶或侵蚀损失有关.然而,目前关于火烧造成的长期生态影响,如火烧后地上植被恢复与地下生物地球化学过程变化有何联系仍不太清楚.未来研究应着重于探讨氮素对森林采伐和火烧作出的短期响应将如何长期影响森林的结构和功能.此外,建议在实施营林方案时需考虑采伐和火烧对生态系统氮的影响.     

Recovery in aquatic ecosystems: an overview of knowledge and needs

This article summarizes the views of scientists asked to address some of the critical unanswered questions concerning recovery in aquatic systems. Spatial and temporal variability were emphasized because of their implications for our abilities to distinguish between recovered and non-recovered ecosystems and the consequent effects such variability has on the statistical precision of developed recovery metrics. There was also consensus that pre-disturbance ecosystem states may not be re-established in the absence of a disturbance event and that better data sets will be required to separate the influences of natural variability from disturbance event induced fluctuations in many biological measures. Although discussions tended to focus at the population or community level, evidence from physiological-based measures of recovery indicates divergent rates of recovery at varying levels of biological organization, a fact which suggests a role for biomarkers in developing a complete understanding of recovery. Critical questions concerning the determination and understanding of recovery that remain to be answered are identified. This revised version was published online in July 2006 with corrections to the Cover Date.     

Food web complexity and chaotic population dynamics

In mathematical models, very simple communities consisting of three or more species frequently display chaotic dynamics which implies that long‐term predictions of the population trajectories in time are impossible. Communities in the wild tend to be more complex, but evidence for chaotic dynamics from such communities is scarce. We used supercomputing power to test the hypothesis that chaotic dynamics become less frequent in model ecosystems when their complexity increases. We determined the dynamical stability of a universe of mathematical, nonlinear food web models with varying degrees of organizational complexity. We found that the frequency of unpredictable, chaotic dynamics increases with the number of trophic levels in a food web but decreases with the degree of complexity. Our results suggest that natural food webs possess architectural properties that may intrinsically lower the likelihood of chaotic community dynamics.     

水库生态系统特征研究及其在水库水质管理中的应用

水库是一种半人工半自然水体,兴建水库是人类调节自然水资源在时间和空间上分布的主要手段,水库生态系统受人类调节明显,具有独特的生态学特征,对近20a来国际水库生态系统的研究进行总结,概括水库生态系统的主要特征,阐述这些特征在水库中水质管理中的应用与实施方法,强调开展水库生态学研究在我国水资源可持续利用中的重要性和必要性。     

A chronology of plankton dynamics in silico: how computer models have been used to study marine ecosystems

Research on plankton ecology in the oceans has traditionally been conducted via two scientific approaches: in situ (in the field) and in vitro (in the laboratory). There is, however, a third approach: exploring plankton dynamics in silico, or using computer models as tools to study marine ecosystems. Models have been used for this purpose for over 60 years, and the innovations and implementations of historical studies provide a context for how future model applications can continue to advance our understanding. To that end, this paper presents a chronology of the in silico approach to plankton dynamics, beginning with modeling pioneers who worked in the days before computers. During the first 30 years of automated computation, plankton modeling focused on formulations for biological processes and investigations of community structure. The changing technological context and conceptual paradigms of the late-1970s and 1980s resulted in simulations becoming more widespread research tools for biological oceanographers. This period saw rising use of models as hypothesis-testing tools, and means of exploring the effects of circulation on spatial distributions of organisms. Continued computer advances and increased availability of data in the 1990s allowed old approaches to be applied to old and new problems, and led to developments of new approaches. Much of the modeling in the new millennium so far has incorporated these sophistications, and many cutting-edge applications have come from a new generation of plankton scientists who were trained by modeling gurus of previous eras. The future directions for modeling plankton dynamics are rooted in the historical studies.     

Acceleration of climate warming and plant dynamics in Antarctica

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