Ecosystem spatial self-organization: Free order for nothing?

Ecosystems are complex adaptive systems (CAS) by nature, which means that macroscopic patterns and properties emerge from, and feed back to affect, the interactions among adaptive individual ecological agents. These agents then further adapt (genetically) to the outcomes of those interactions. The concept of self-organization has become increasingly important for understanding ecosystem spatial heterogeneity and its consequences. It is well accepted that ecosystems can self-organize, and that resulting spatial structures carry functional consequences. Feedbacks from the outcome of spatial pattern to the individual agents from which patterns emerge, are an essential component of the definition of CAS but have been rarely examined for ecosystems. We explore whether spatial self-organization provides a mechanism for such feedback for ecosystems as CAS, that is, whether ecosystem-level outcomes of self-organized patterning could feed back to affect or even reinforce local pattern-forming processes at the agent level. Diffuse feedbacks of ecological and evolutionary significance ensue as a result of spatial heterogeneity and regular patterning, whether this spatial heterogeneity results from an underlying template effect or from self-organization. However, feedbacks directed specifically at pattern-forming agents to enhance pattern formation—reinforcing feedback—depend upon the level of organization of agents. Reinforcing evolutionary feedbacks occur at the individual level or below. At the ecosystem level, evidence for mechanisms of feedback from outcomes to patterning to agents forming the patterning remain tenuous. Spatial self-organization is a powerful dynamic in ecosystem and landscape science but feedbacks have been only loosely integrated so far. Self-organized patterns influencing dynamics at the ecosystem level represent “order for free”. Whether or not this free order generated at the ecosystem level carries evolutionary function or is merely epiphenomenal is a fundamental question that we address here.     

Alternative states and positive feedbacks in restoration ecology

There is increasing interest in developing better predictive tools and a broader conceptual framework to guide the restoration of degraded land. Traditionally, restoration efforts have focused on re-establishing historical disturbance regimes or abiotic conditions, relying on successional processes to guide the recovery of biotic communities. However, strong feedbacks between biotic factors and the physical environment can alter the efficacy of these successional-based management efforts. Recent experimental work indicates that some degraded systems are resilient to traditional restoration efforts owing to constraints such as changes in landscape connectivity and organization, loss of native species pools, shifts in species dominance, trophic interactions and/or invasion by exotics, and concomitant effects on biogeochemical processes. Models of alternative ecosystem states that incorporate system thresholds and feedbacks are now being applied to the dynamics of recovery in degraded systems and are suggesting ways in which restoration can identify, prioritize and address these constraints.     

森林-农业景观格局变化的社会-生态系统模拟模型方法进展

社会-生态系统（SES）模拟模型是景观格局分析和决策的有效工具,能表征景观格局变化的社会-生态效应及景观决策的复杂反馈机制。文献综述了森林-农业景观格局的SES模型方法进展发现：（1）多数模型对景观过程与社会经济决策的反馈关系分析不足;（2）应集成多种情景模拟和景观效应分析方法,完善现有SES模型的理论方法基础;（3）通过集成格局优化模型和自主体模型会有效改进SES模型功能,具体途径包括：集成情景-生态效应的景观格局模拟方法、完善景观决策的理论基础、加强集成模型的不确定性分析、降低模型复杂性和综合定性-定量数据等。研究结果有助于理解多尺度森林-农业景观格局在社会-生态系统中的重要作用,能更好地支持跨学科集成模型开发与应用。     

Cells in the system of multicelular organism from positions of non-linear dynamics

The organism physiological systems forming a hierarchic network with mutual dependence and subordination can be considered as systems with non-linear dynamics including positive and negative feedbacks. In the course of evolution there occurred selection of robust, flexible, modular systems capable for adaptive self-organization by non-linear interaction of components, which leads to formation of the ordered in space and time robust and plastic organization of the whole. Cells of multicellular organisms are capable for coordinated “social” behavior with formation of ordered cell assemblies, which provides a possibility of morphological and functional variability correlating with manifestations of the large spectrum of adaptive reactions. The multicellular organism is the multilevel system with hierarchy of numerous subsystems capable for adaptive self-organization; disturbance of their homeostasis can lead to pathological changes. The healthy organism regulates homeostasis, self-renewal, differentiation, and apoptosis of cells serving its parts and construction blocks by preserving its integrity and controlling behavior of cells. The systemic approach taking into account biological regularities of the appearance and development of functions in evolution of multicellular organisms opens new possibilities for diagnostics and treatment of many diseases.     

Quantifying the Adaptive Cycle

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.     

Marine Ecosystems as Complex Adaptive Systems: Emergent Patterns,Critical Transitions,and Public Goods

Complex adaptive systems provide a unified framework for explaining ecosystem phenomena. In the past 20 years, complex adaptive systems have been sharpened from an abstract concept into a series of tools that can be used to solve concrete problems. These advances have been led by the development of new techniques for coupling ecological and evolutionary dynamics, for integrating dynamics across multiple scales of organization, and for using data to infer the complex interactions among different components of ecological systems. Focusing on the development and usage of these new methods, we discuss how they have led to an improved understanding of three universal features of complex adaptive systems, emergent patterns; tipping points and critical phenomena; and cooperative behavior. We restrict our attention primarily to marine ecosystems, which provide numerous successful examples of the application of complex adaptive systems. Many of these are currently undergoing dramatic changes due to anthropogenic perturbations, and we take the opportunity to discuss how complex adaptive systems can be used to improve the management of public goods and to better preserve critical ecosystem services.     

Scaling biodiversity responses to hydrological regimes

Of all ecosystems, freshwaters support the most dynamic and highly concentrated biodiversity on Earth. These attributes of freshwater biodiversity along with increasing demand for water mean that these systems serve as significant models to understand drivers of global biodiversity change. Freshwater biodiversity changes are often attributed to hydrological alteration by water‐resource development and climate change owing to the role of the hydrological regime of rivers, wetlands and floodplains affecting patterns of biodiversity. However, a major gap remains in conceptualising how the hydrological regime determines patterns in biodiversity's multiple spatial components and facets (taxonomic, functional and phylogenetic). We synthesised primary evidence of freshwater biodiversity responses to natural hydrological regimes to determine how distinct ecohydrological mechanisms affect freshwater biodiversity at local, landscape and regional spatial scales. Hydrological connectivity influences local and landscape biodiversity, yet responses vary depending on spatial scale. Biodiversity at local scales is generally positively associated with increasing connectivity whereas landscape‐scale biodiversity is greater with increasing fragmentation among locations. The effects of hydrological disturbance on freshwater biodiversity are variable at separate spatial scales and depend on disturbance frequency and history and organism characteristics. The role of hydrology in determining habitat for freshwater biodiversity also depends on spatial scaling. At local scales, persistence, stability and size of habitat each contribute to patterns of freshwater biodiversity yet the responses are variable across the organism groups that constitute overall freshwater biodiversity. We present a conceptual model to unite the effects of different ecohydrological mechanisms on freshwater biodiversity across spatial scales, and develop four principles for applying a multi‐scaled understanding of freshwater biodiversity responses to hydrological regimes. The protection and restoration of freshwater biodiversity is both a fundamental justification and a central goal of environmental water allocation worldwide. Clearer integration of concepts of spatial scaling in the context of understanding impacts of hydrological regimes on biodiversity will increase uptake of evidence into environmental flow implementation, identify suitable biodiversity targets responsive to hydrological change or restoration, and identify and manage risks of environmental flows contributing to biodiversity decline.     

Patterns of biotic community organization and reorganization: A conceptual framework and a case study

Reorganization is an important concept for confronting complex adaptive systems (CAS) theory with ecological reality. However, little work has been done to translate the reorganization idea into a practical conceptual framework. This paper focuses on community-level reorganization, the process of re-forming patterns in relation to the distribution of species density (abundance) and their frequency of occurrence in space (incidence). We assert that changes in species positions in the incidence–abundance (IA) phase plane depict community reorganization in response to environmental changes. This is because species positions in the IA plane represent the most prominent organizational features of a biotic community.We identified four sequential levels of species reorganization in the IA phase plane: reshuffling of species, species appearance, species disappearance and whole-assemblage shift. We propose that the sequential levels represent an increase in reorganization intensity depending on the extent of environmental change.We formulate the Environmental Change and Re-Organization (ECRO) hypothesis specifying that ecosystems respond predictably in terms of community reorganization in the IA phase plane to external drivers. The predictable reorganization follows the four sequential levels of organization in response to intensity of environmental change. We suggest that the response of a species assemblage to external drivers in sequential levels of reorganization is independent of ecosystem properties, type of environmental variables, taxa, and spatio-temporal scales.We tested the predictability of reorganization according to the ECRO hypothesis, using annual plant assemblages of a semiarid shrubland. These assemblages exhibit CAS properties as suggested by Levin: high species diversity, high numbers of individuals, local interactions among individuals in relation to water consumption, and annually selected species subsets for replication.We investigated annual plant assemblage organization and reorganization for 12 years in response to disturbance and resource input, using the IA phase plane. The field study supports our assertion that reorganization of species assemblages in response to environmental change can be represented by species repositioning in the IA phase plane, and that community reorganization follows the four sequential levels of reorganization in response to the intensity of environmental change.Our conceptual framework and experimental studies demonstrate that hypotheses related to core CAS concepts of organization and reorganization can be tested by linking them with community ecology concepts of species patterns in the IA phase plane. We also discuss the relationship between reorganization in the IA phase plane and resilience, regime shift and ecosystem functioning as affected by species response and effects traits.     

The influence of biotic interactions on soil biodiversity

Belowground communities usually support a much greater diversity of organisms than do corresponding aboveground ones, and while the factors that regulate their diversity are far less well understood, a growing number of recent studies have presented data relevant to understanding how these factors operate. This review considers how biotic factors influence community diversity within major groups of soil organisms across a broad spectrum of spatial scales, and addresses the mechanisms involved. At the most local scale, soil biodiversity may potentially be affected by interactions within trophic levels or by direct trophic interactions. Within the soil, larger bodied invertebrates can also influence diversity of smaller sized organisms by promoting dispersal and through modification of the soil habitat. At larger scales, individual plant species effects, vegetation composition, plant species diversity, mixing of plant litter types, and aboveground trophic interactions, all impact on soil biodiversity. Further, at the landscape scale, soil diversity also responds to vegetation change and succession. This review also considers how a conceptual understanding of the biotic drivers of soil biodiversity may assist our knowledge of key topics in community and ecosystem ecology, such as aboveground–belowground interactions, and the relationship between biodiversity and ecosystem functioning. It is concluded that an improved understanding of what drives the diversity of life in the soil, incorporated within appropriate conceptual frameworks, should significantly aid our understanding of the structure and functioning of terrestrial communities.     

Simulation modelling of ecological hierarchies in constructive dynamical systems

Organized complexity is a characteristic feature of ecological systems with heterogeneous components interacting at several spatio-temporal scales. The hierarchy theory is a powerful epistemological framework to describe such systems by decomposing them vertically into levels and horizontally into holons. It was at first developed in a temporal and functional perspective and then, in the context of landscape ecology, extended to a spatial and structural approach. So far, most ecological applications of this theory were restricted to observational purposes, using multi-scale analysis to describe hierarchies. In spite of an increasing attention to dynamics of hierarchically structured ecological systems, current simulation models are still very limited in their representation of self-organization in complex adaptive systems. An ontological conceptualization of the hierarchy theory is outlined, focusing on key concepts, such as levels of organization and the compound and component faces of the holons. Various existing formalisms are currently used in simulation modelling, such as system dynamics, discrete event and agent based paradigms. Their ability to express the hierarchical organization of dynamical ecological systems is discussed. It turns out that a multi-modelling approach linking all these formalisms and oriented toward the specification of a constructive dynamical system would be able to express the dynamical structure of the hierarchy (creation, destruction and change of holons) and the functional and structural links between levels of organization.     

N‐dimensional hypervolumes to study stability of complex ecosystems

Although our knowledge on the stabilising role of biodiversity and on how it is affected by perturbations has greatly improved, we still lack a comprehensive view on ecosystem stability that is transversal to different habitats and perturbations. Hence, we propose a framework that takes advantage of the multiplicity of components of an ecosystem and their contribution to stability. Ecosystem components can range from species or functional groups, to different functional traits, or even the cover of different habitats in a landscape mosaic. We make use of n‐dimensional hypervolumes to define ecosystem states and assess how much they shift after environmental changes have occurred. We demonstrate the value of this framework with a study case on the effects of environmental change on Alpine ecosystems. Our results highlight the importance of a multidimensional approach when studying ecosystem stability and show that our framework is flexible enough to be applied to different types of ecosystem components, which can have important implications for the study of ecosystem stability and transient dynamics.     

From proteomics toward systems biology: integration of different types of proteomics data into network models

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.     

Exotic Grass Invasions: Applying a Conceptual Framework to the Dynamics of Degradation and Restoration in Australia’s Tropical Savannas

Plant invasions can cause severe degradation of natural areas. The ability of an ecosystem to recover autogenically from degradation following weed control is in part determined by the type and magnitude of changes to both biotic and abiotic processes caused by the invasion and how these interact with structural and functional components of the ecosystem. Recently, a number of conceptual frameworks have been proposed to describe the dynamics of degradation and regeneration in degraded ecosystems. We assessed the utility of one of these frameworks in describing the degradation and restoration potential of Australia’s tropical savannas following exotic grass invasion. First, we identified easily measured structural characteristics of putative states. We found that a continuous cover of the exotic grasses Gamba grass (Andropogon gayanus Kunth.) and Perennial mission grass (Pennisetum polystachion (L.) Schult.) under an intact tree canopy was a common state with an understorey characterized by reduced species richness and abundance and a change in the relative contribution of functional groups. Further degradation led to a state where the canopy was severely reduced and the impacts on the understorey were more severe. In both states, the seed bank was substantially less degraded than the understorey vegetation. Guided by the framework, we combined our study with other studies to construct a conceptual model for degradation in exotic grass‐invaded savannas.     

Linking saturation,stability and sustainability in food webs with observed equilibrium structure

Stability of a dynamic equilibrium in a predator-prey system depends both on the type of functional response and on the point of equilibrium on the response curve. Saturation effects from Holling type II responses are known to destabilise prey populations, while a type III (sigmoid) response curve has been shown to provide stability at lower levels of saturation. These effects have also been shown in multi-trophic model systems. However, stability analyses of observed equilibria in real complex ecosystems have as yet not assumed non-linear functional responses. Here, we evaluate the implications of saturation in observed balanced material-flow structures, for system stability and sustainability. We first make the effects of the non-linear functional responses on the interaction strengths in a food web transparent by expressing the elements of Jacobian ‘community’ matrices for type II and III systems as simple functions of their linear (type I) counterparts. We then determine the stability of the systems and distinguish two critical saturation levels: (1) a level where the system is just as stable as a type I system and (2) a level above which the system cannot be stable unless it is subsidised, separating a stable materially sustainable regime from an unsustainable one. We explain the stabilising and destabilising effects in terms of the feedbacks in the systems. The results shed light on the robustness of observed patterns of interaction strengths in complex food webs and suggest the implausibility of saturation playing a significant role in the equilibrium dynamics of sustainable ecosystems.     

流域径流泥沙对多尺度植被变化响应研究进展

植被变化与流域水文过程构成一个反馈调节系统,是目前生态水文学研究的重点对象.由于植被自身的生长发育以及受自然因素和人为干扰的作用,植被变化具有多尺度性;由于受流域水文环境的异质性和水文通量的变化性的影响,流域水文过程也同样具有多尺度性.因此,只有通过对不同尺度生态水文过程分析,才能揭示流域径流泥沙对植被变化的响应机理.从不同时空尺度回顾了植被生长、植被演替、植被分布格局变化、造林以及森林经营措施等对流域径流泥沙影响的主要研究成果;概括了目前研究采用的3种主要方法,即植被变化对坡面水流动力学影响的实验室模拟、坡面尺度和流域尺度野外对比观测实验以及水文生态模型模拟方法;分析了植被变化与径流泥沙响应研究要考虑的尺度问题,从小区尺度上推至流域尺度或区域尺度时应考虑不同的生物物理控制过程.研究认为,要确切理解植被与径流泥沙在不同时空尺度的相互作用,必须以等级生态系统的观点为基础,有效结合生态水文与景观生态的理论,从地质-生态-水文构成的反馈调节入手,系统地理解植被变化与径流泥沙等水分养分之间的联系及反馈机制,建立尺度转换的基础.同时,作为有效的研究工具,今后水文模型的发展应更加注重耦合植被生理生态过程以及景观生态过程,从流域径流泥沙对多尺度植被变化水文响应的过程与机制入手,为植被恢复与重建、改善流域水资源状况和流域生态环境奠定基础.     

An explanatory framework for adaptive personality differences

We develop a conceptual framework for the understanding of animal personalities in terms of adaptive evolution. We focus on two basic questions. First, why do behavioural types exhibit limited behavioural plasticity, that is, behavioural correlations both across contexts and over time? Second, how can multiple behavioural types coexist within a single population? We emphasize differences in 'state' among individuals in combination with state-dependent behaviour. Some states are inherently stable and individual differences in such states can explain stable differences in suites of behaviour if it is adaptive to make behaviour in various contexts dependent on such states. Behavioural stability and cross-context correlations in behaviour are more difficult to explain if individual states are potentially more variable. In such cases stable personalities can result from state-dependent behaviour if state and behaviour mutually reinforce each other by feedback mechanisms. We discuss various evolutionary mechanisms for the maintenance of variation (in states and/or behaviour), including frequency-dependent selection, spatial variation with incomplete matching between habitat and phenotype, bet-hedging in a temporally fluctuating environment, and non-equilibrium dynamics. Although state differences are important, we also discuss how social conventions and social signalling can give rise to adaptive personality differences in the absence of state differences.     

河流景观生态服务供给与需求/消费的互馈机制

河流景观系统孕育了人类文明,为人类社会提供类型多样的生态系统服务。其本身是一个自然景观过程和社会经济过程高度耦合的社会-生态系统,具有极高的空间异质性、时间动态和鲜明的组织尺度等级结构。当前,对河流景观系统这种特点所决定的生态系统服务供给与需求/消费互馈的机制研究不够深入,普遍缺乏从过程角度刻画生态服务供给与需求/消费互馈关系及其时空异质性和尺度特征。生态服务供给、需求和消费产生于社会-生态系统,是社会-生态耦合的纽带。阐述了河流景观生态服务供给和需求/消费的时空异质性,阐释了它们时空耦合机制和尺度特征,梳理了当前对生态服务供给、需求/消费互馈机理研究的不足。认为未来需要在社会-生态系统的框架下,从景观结构和生态过程出发,融合景观生态过程和社会过程来深入认识河流景观系统的生态服务供给与区内人类对生态服务的需求/消费之间的互馈机制。未来应重点关注：（1）河流景观结构和过程决定的生态服务供给和消费的空间分异及驱动机制;（2）河流生态服务传输的自然和人文载体及其耦合格局;（3）将生态服务需求/消费通过景观结构和生态过程对生态服务供给的反馈融入生态服务评估的方法框架,研发基于生态服务供给和需求/消费的社会-生态互馈过程模型。     

Studying the Logone floodplain,Cameroon, as a coupled human and natural system§

African floodplains are an excellent example of coupled human–natural systems because they exhibit strong interactions among multiple social, ecological, and hydrological systems. The intra-annual and interannual variations in seasonal flooding have direct and indirect impacts on ecosystems and human lives and livelihoods. Coupled human and natural system (CHANS) is a broad conceptual framework that is used to study systems in which human and natural components interact. While there are other conceptual frameworks to study social-ecological systems, the CHANS framework offers a clear way of studying the interactions, called couplings, between human and natural systems. Core features of the framework are the following: human and natural systems are analytically separated; focus is on processes within and couplings between systems; and the goal is to build an integrative, quantitative model of the coupled system. This paper explains the conceptual framework of coupled systems, using the case study of the Logone floodplain in Cameroon. We compare the CHANS framework with other frameworks that have been used to study the same floodplain, and argue for its usefulness in the study of African floodplains.