From interesting details to dynamical relevance: toward more effective use of empirical insights in theory construction

A perennial challenge in ecology is to develop dynamical systems models that appropriately abstract and characterize the dynamics of natural systems. Deriving an appropriate model of system dynamics can be a long and iterative process whose outcome depends critically on the quality of empirical data describing the long‐term behavior of a natural system. Most ecological time series are insufficient to offer insight into the way organizational hierarchies and spatial scales are causally linked to natural system dynamics. Moreover, the classic tradition of hypothesis testing in ecology is not likely to lead to those key insights. This because empirical research is geared almost exclusively toward testing model predictions based on underlying causal relationships assumed by theorists. So, empirical research relies heavily on theory for guidance on what is or is not dynamically relevant. I argue here that it is entirely possible to reduce much of this guesswork involved with deciding on causal structure by giving empirical research a new role in theory development. In this role, natural history and field observations are used to develop stochastic, individual‐based and spatially explicit computational models or IBMs that can explore the range of contingency and complexity inherent in real‐world systems.
IBMs can be used to run simulations allowing deductions to be made about the causal linkages between organizational hierarchies, spatial scales, and dynamics. These deductions can be tested under field conditions using experiments that manipulate the putative causal structure and evaluate the dynamical consequences. The emerging insights from this stage can then be used to inspire an analytical construct that embodies the dynamically relevant scales and mechanisms. In essence, computational modeling serves as an intermediate step in theory development in that a wide range of possibly important biological details are considered and then reduced to a subset that is dynamically relevant.     

The role of seasonal timing and phenological shifts for species coexistence

Shifts in the phenologies of coexistence species are altering the temporal structure of natural communities worldwide. However, predicting how these changes affect the structure and long‐term dynamics of natural communities is challenging because phenology and coexistence theory have largely proceeded independently. Here, I propose a conceptual framework that incorporates seasonal timing of species interactions into a well‐studied competition model to examine how changes in phenologies influence long‐term dynamics of natural communities. Using this framework I demonstrate that persistence and coexistence conditions strongly depend on the difference in species’ mean phenologies and how this difference varies across years. Consequently, shifts in mean and interannual variation in relative phenologies of species can fundamentally alter the outcome of interactions and the potential for persistence and coexistence of competing species. These effects can be predicted by how per‐capita effects scale with differences in species’ phenologies. I outline how this approach can be parameterized with empirical systems and discuss how it fits within the context of current coexistence theory. Overall, this synthesis reveals that phenology of species interactions can play a crucial yet currently understudied role in driving coexistence and biodiversity patterns in natural systems and determine how species will respond to future climate change.     

Are natural microcosms useful model systems for ecology?

Several recent, high-impact ecological studies feature natural microcosms as tools for testing effects of fragmentation, metacommunity theory or links between biodiversity and ecosystem processes. These studies combine the microcosm advantages of small size, short generation times, contained structure and hierarchical spatial arrangement with advantages of field studies: natural environmental variance, 'openness' and realistic species combinations with shared evolutionary histories. This enables tests of theory pertaining to spatial and temporal dynamics, for example, the effects of neighboring communities on local diversity, or the effects of biodiversity on ecosystem function. Using examples, we comment on the position of natural microcosms in the roster of ecological research strategies and tools. We conclude that natural microcosms are as versatile as artificial microcosms, but as complex and biologically realistic as other natural systems. Research to date combined with inherent attributes of natural microcosms make them strong candidate model systems for ecology.     

海南霸王岭热带山地雨林森林循环与树种多样性动态

通过对海南岛霸王岭热带山地雨林的调查 ,研究了热带山地雨林树种多样性特征随森林循环的动态变化规律。结果表明 :( 1 )热带山地雨林森林循环不同阶段斑块在森林景观中所占的面积比例分别是 :林隙阶段 ( G)占 38.5 0 % ,建立阶段 ( B)占 2 8.5 0 % ,成熟阶段 ( M)占 2 7.0 0 % ,衰退阶段 ( D)占 6 .0 0 %。 ( 2 )热带山地雨林中乔木树种的密度随森林循环的变化趋势是由 G→B→M呈现出逐渐增加的趋势 ,以成熟阶段达到最大 ,而到衰退阶段又趋于下降。灌木树种则表现出 G阶段斑块的密度最大 ,B阶段的最小 ,从 B到 M有所增加 ,到 D又稍有下降。 ( 3)热带山地雨林中不同高度级和不同径级的树木的密度在森林循环的不同阶段表现出不同的增减趋势 ,其随森林循环过程呈现出的动态变化可能与不同阶段斑块内的空间、环境及物种生物学特性有关。 ( 4 )热带山地雨林中树木的平均胸径、平均高、平均胸高断面积、平均单株材积随森林循环过程呈现出不断增加的趋势 ,其中平均胸径和平均高随森林循环的变化较为平缓 ,而平均胸高断面积和平均单株材积之变化较为陡急。 ( 5 )热带山地雨林森林循环不同阶段的物种多样性指数不同 ,其中 G和 B阶段的物种丰富度和多样性指数值较接近 ,M阶段的物种丰富度达到最大 ,D阶段则最小。     

Global dynamics of biological systems from time-resolved omics experiments

The emergent properties of biological systems, organized around complex networks of irregularly connected elements, limit the applications of the direct scientific method to their study. The current lack of knowledge opens new perspectives to the inverse scientific paradigm where observations are accumulated and analysed by advanced data-mining techniques to enable a better understanding and the formulation of testable hypotheses about the structure and functioning of these systems. The current technology allows for the wide application of omics analytical methods in the determination of time-resolved molecular profiles of biological samples. Here it is proposed that the theory of dynamical systems could be the natural framework for the proper analysis and interpretation of such experiments. A new method is described, based on the techniques of non-linear time series analysis, which is providing a global view on the dynamics of biological systems probed with time-resolved omics experiments.     

Natural selection and self-organization

The Darwinian concept of natural selection was conceived within a set of Newtonian background assumptions about systems dynamics. Mendelian genetics at first did not sit well with the gradualist assumptions of the Darwinian theory. Eventually, however, Mendelism and Darwinism were fused by reformulating natural selection in statistical terms. This reflected a shift to a more probabilistic set of background assumptions based upon Boltzmannian systems dynamics. Recent developments in molecular genetics and paleontology have put pressure on Darwinism once again. Current work on self-organizing systems may provide a stimulus not only for increased problem solving within the Darwinian tradition, especially with respect to origins of life, developmental genetics, phylogenetic pattern, and energy-flow ecology, but for deeper understanding of the very phenomenon of natural selection itself. Since self-organizational phenomena depend deeply on stochastic processes, self-organizational systems dynamics advance the probability revolution. In our view, natural selection is an emergent phenomenon of physical and chemical selection. These developments suggest that natural selection may be grounded in physical law more deeply than is allowed by advocates of the autonomy of biology, while still making it possible to deny, with autonomists, that evolutionary explanations can be modeled in terms of a deductive relationship between laws and cases. We explore the relationship between, chance, self-organization, and selection as sources of order in biological systems in order to make these points.     

Extending and expanding the Darwinian synthesis: the role of complex systems dynamics

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself.     

Nonequilibrium thermodynamics and different axioms of evolution

Proponents of two axioms of biological evolutionary theory have attempted to find justification by reference to nonequilibrium thermodynamics. One states that biological systems and their evolutionary diversification are physically improbable states and transitions, resulting from a selective process; the other asserts that there is an historically constrained inherent directionality in evolutionary dynamics, independent of natural selection, which exerts a self-organizing influence. The first, the Axiom of Improbability, is shown to be nonhistorical and thus, for a theory of change through time, acausal. Its perception of the improbability of living states is at least partially an artifact of closed system thinking. The second, the Axiom of Historically Determined Inherent Directionality, is supported evidentially and has an explicit historical component. Historically constrained dynamic populations are inherently nonequilibrium systems. It is argued that living, evolving systems, when considered to be historically constrained nonequilibrium systems, do not appear improbable at all. Thus, the two axioms are not compatible. Instead, the Axiom of Improbability is considered to result from an unjustified attempt to extend the contingent proximal actions of natural selection into the area of historical, causal explanations. It is thus denied axiomatic status, and the effects of natural selection are subsumed as an additional level of constraint in an evolutionary theory derived from the Axiom of Historically Determined Inherent Directionality.     

Plant Community Recovery following Restoration in Temporally Variable Riparian Wetlands

Wetlands historically provided many ecosystem services but most have been lost or degraded through land conversion. Recent appreciation for wetland values and increasing ecotourism in the Central Platte River Valley (U.S.A.) has promoted restoration of wet meadow systems, although recovery patterns are not well known. We quantified plant community structure in sloughs (deeper habitats) and adjacent margins (slightly higher elevation) of six wetland sites, restored for 1–7 years at the onset of a 3-year study, and three natural wetlands to assess recovery dynamics. Plant community metrics recovered differentially between habitats. Within restored margins, richness and diversity showed a weak quadratic response with time since restoration, indicating that both indexes overshoot natural levels shortly following restoration. Within sloughs, richness and diversity showed no change with time, suggesting that recovery occurs more quickly in these deeper, moister habitats. Percent similarity of plant communities in restorations and natural wetlands increased linearly over time. However, ordinations of plant community composition showed that recovery was strongly influenced by site-specific hydrology and that recovery may not be a linear trajectory toward natural systems. The analysis and interpretation of plant community dynamics revealed several challenges to restoration assessment, including the role of interannual variability in precipitation, limitations to hydrologic recovery, and temporal variability in plant community structure in natural systems that resulted in "moving targets" for recovery comparisons. Temporal variability in climate must be considered when assessing restoration success in systems where plant community structure is responsive to variable moisture regimes.     

Three mechanisms of Red Queen dynamics

Models describing systems of coevolving populations often have asymptotically non-equilibrium dynamics (Red Queen dynamics (RQD)). We claim that if evolution is much slower than ecological changes, RQD arises due to either fast ecological processes, slow genetical processes, or to their interaction. The three corresponding generic types of RQD can be studied using singular perturbation theory and have very different properties and biological implications. We present simple examples of ecological, genetical, and ecogenetical RQD and describe how they may be recognized in natural populations. In particular, ecogenetical RQD often involve alternations of long epochs with radically different dynamics.     

Phenotypic variability promotes diversity and stability in competitive communities

Intraspecific variation is at the core of evolutionary theory, and yet, from an ecological perspective, we have few robust expectations for how this variation should affect the dynamics of large communities. Here, by adapting an approach from evolutionary game theory, we show that the incorporation of phenotypic variability into competitive networks dramatically alters the dynamics across ecological timescales, stabilising the systems and buffering the communities against demographic perturbations. The beneficial effects of phenotypic variability are strongest when there are substantial differences among phenotypes and when phenotypes are inherited with moderately high fidelity; yet even low levels of variation lead to significant increases in diversity, stability, and robustness. By identifying a simple and ubiquitous stabilising force in competitive communities, this work contributes to our core understanding of how biological diversity is maintained in natural systems.     

森林景观变化的地理环境因素整合分析——以伊洛河流域洛宁县为例

运用景观生态学的基本原理,借助于地理信息系统技术,整合分析了地理环境因素对伊洛河流域洛宁县森林景观动态变化的影响。结果显示,应用地理环境因素影响指数可以很好地从整体上分析地理环境因素,如高程、坡度、距离居民点中心的距离、与森林边缘距离等地理环境因子对区域森林景观动态变化的影响。1983和1999年,伊洛河流域洛宁县森林景观在地理环境因素影响指数上的优势分布区间(Pie1)分别为1230和1030,即在中高地理环境因素影响指数分布区间内,且有向低地理环境因素影响指数分布区间略为移动的趋势。森林景观类型保持不变部分、森林景观转化为非森林景观类型部分和非森林景观转化为森林景观类型部分所对应的在地理环境因素影响指数上的优势分布区间(Pie1)分别为1130、18和613。通过建立森林景观动态变化与地理环境因素影响指数的相互关系,表明森林景观动态变化与地理环境因素影响指数(特别是在地理环境因素影响指数的优势分布区间内)有显著相关关系。     

On the Emergence of Living Systems

If the problem of the origin of life is conceptualized as a process of emergence of biochemistry from proto-biochemistry, which in turn emerged from the organic chemistry and geochemistry of primitive earth, then the resources of the new sciences of complex systems dynamics can provide a more robust conceptual framework within which to explore the possible pathways of chemical complexification leading to living systems and biosemiosis. In such a view the emergence of life, and concomitantly of natural selection and biosemiosis, is the result of deep natural laws (the outlines of which we are only beginning to perceive) and reflects a degree of holism in those systems that led to life. Further, such an approach may lead to the development of a more general theory of biology and of natural organization, one informed by semiotic concepts.     

Critical-like self-organization and natural selection: Two facets of a single evolutionary process?

We argue that critical-like dynamics self-organize relatively easily in non-equilibrium systems, and that in biological systems such dynamics serve as templates upon which natural selection builds further elaborations. These critical-like states can be modified by natural selection in two fundamental ways, reflecting the selective advantage (if any) of heritable variations either among avalanche participants or among whole systems. First, reproducing (avalanching) units can differentiate, as units adopt systematic behavioural variations. Second, whole systems that are exposed to natural selection can become increasingly or decreasingly critical. We suggest that these interactions between SOC-like dynamics and natural selection have profound consequences for biological systems because they could have facilitated the evolution of division of labour, compartmentalization and computation, key features of biological systems. The logical conclusion of these ideas is that the fractal geometry of nature is anything but coincidental, and that natural selection is itself a fractal process, occurring on many temporal and spatial scales.     

An uncertain life: demography in random environments

This paper concisely reviews the demography of populations with random vital rates, highlights examples and techniques which yield insight into population dynamics, summarizes the state of significant applications of the theory, and points to open problems. The central picture in this theory is of a time-varying but statistically stationary equilibrium for population, sharply distinct from the notions of classical demography. The deepest biological insights from the theory reveal the temporal structure of life histories to be a rich arena for natural selection.     

Plant–floral visitor network structure in a smallholder <Emphasis Type="Italic">Cucurbitaceae</Emphasis> agricultural system in the tropics: implications for the extinction of main floral visitors

Animal pollination is responsible for the majority of the human food supply. Understanding pollination dynamics in agricultural systems is thus essential to help maintain this ecosystem service in the face of human disturbances. Surprisingly, our understanding of plant–pollinator interactions in widely distributed smallholder agricultural systems is still limited. Knowledge of pollination dynamics in these agricultural systems is necessary to fully assess how human disturbances may affect pollination services worldwide. In this study, we describe the structure of a plant–floral visitor network in a smallholder Cucurbitaceae agricultural system. We further identify the main floral visitors of these crops and tested their importance by simulating how their extinction affected network structure and robustness. The observed network was highly connected and generalized but it was neither nested nor compartmentalized. Our results suggest that the structure of agricultural plant–pollinator networks could be inherently different from those in natural communities. These differences in network structure may reflect differences in spatial distribution of floral resources between agricultural and natural systems. We identified Augochlora nigrocyanea and Peponapis limitaris as the two most frequent floral visitors. However, removal of these species did not affect network structure or its robustness, suggesting high levels of interaction rewiring. To our knowledge, this is one of the first studies to describe the structure of a plant–floral visitor network in diverse agricultural systems in the tropics. We emphasize the need for more studies that evaluate network structure in agricultural systems if we want to fully elucidate the impact of human disturbances on this key ecosystem service.     

Mesoscopic biochemical basis of isogenetic inheritance and canalization: stochasticity, nonlinearity, and emergent landscape

Biochemical reaction systems in mesoscopic volume, under sustained environmental chemical gradient(s), can have multiple stochastic attractors. Two distinct mechanisms are known for their origins: (a) Stochastic single-molecule events, such as gene expression, with slow gene on-off dynamics; and (b) nonlinear networks with feedbacks. These two mechanisms yield different volume dependence for the sojourn time of an attractor. As in the classic Arrhenius theory for temperature dependent transition rates, a landscape perspective provides a natural framework for the system's behavior. However, due to the nonequilibrium nature of the open chemical systems, the landscape, and the attractors it represents, are all themselves emergent properties of complex, mesoscopic dynamics. In terms of the landscape, we show a generalization of Kramers' approach is possible to provide a rate theory. The emergence of attractors is a form of self-organization in the mesoscopic system; stochastic attractors in biochemical systems such as gene regulation and cellular signaling are naturally inheritable via cell division. Delbrück-Gillespie's mesoscopic reaction system theory, therefore, provides a biochemical basis for spontaneous isogenetic switching and canalization.     

Hysteresis Dynamics,Bursting Oscillations and Evolution to Chaotic Regimes

This article describes new aspects of hysteresis dynamics which have been uncovered through computer experiments. There are several motivations to be interested in fast-slow dynamics. For instance, many physiological or biological systems display different time scales. The bursting oscillations which can be observed in neurons, beta-cells of the pancreas and population dynamics are essentially studied via bifurcation theory and analysis of fast-slow systems (Keener and Sneyd, 1998; Rinzel, 1987). Hysteresis is a possible mechanism to generate bursting oscillations. A first part of this article presents the computer techniques (the dotted-phase portrait, the bifurcation of the fast dynamics and the wave form) we have used to represent several patterns specific to hysteresis dynamics. This framework yields a natural generalization to the notion of bursting oscillations where, for instance, the active phase is chaotic and alternates with a quiescent phase. In a second part of the article, we emphasize the evolution to chaos which is often associated with bursting oscillations on the specific example of the Hindmarsh-Rose system. This evolution to chaos has already been studied with classical tools of dynamical systems but we give here numerical evidence on hysteresis dynamics and on some aspects of the wave form. The analytical proofs will be given elsewhere.     

植物-土壤反馈理论及其在自然和农田生态系统中的应用研究进展

植物-土壤反馈理论最早源于农业生产,近年来已成为生态学上研究植被动态变化、群落组成和功能,以及生态系统响应人为干扰、气候变化等众多热点问题的重要理论和方法支撑。总结了植物-土壤反馈定义和类型,分析了反馈机制,在此基础上综述了该理论在自然生态系统中的应用,包括物种入侵、群落演替、植物共存及多样性形成、植物多样性-生产力关系、多营养级交互作用以及响应气候变化等关键生态学命题。探讨了植物-土壤反馈理论在农田生态系统中的应用,介绍了该理论在提高多样化种植体系生产力、土壤污染修复、种植体系设计等方面的进展和潜在应用价值。提出了植物-土壤反馈理论在未来发展中进一步研究的方向,对应用该理论提高生态系统服务功能,促进可持续发展等方面进行了展望。     

Fuzzy systems vegetation theory

Fuzzy systems vegetation theory is a comprehensive framework for the expression of vegetation theory and conceptual models, as well as the development of vegetation analyses. It is applicable to vegetation/environment relations, vegetation dynamics, and the effects of environmental dynamics on vegetation composition. Fuzzy systems vegetation theory is a fuzzy set generalization of dynamical systems theory and incorporates a formal logic and mathematics. This paper presents the elements of fuzzy systems vegetation theory and discusses the relationship of the fuzzy systems theory to the geometric concepts generally employed in vegetation theory.