Effects of evolutionary changes in prey use on the relationship between food web complexity and stability

The relationship between food web complexity and stability has been the subject of a long-standing debate in ecology. Although rapid changes in the food web structure through adaptive foraging behavior can confer stability to complex food webs, as reported by Kondoh (Science 299:1388–1391, 2003), the exact mechanisms behind this adaptation have not been specified in previous studies; thus, the applicability of such predictions to real ecosystems remains unclear. One mechanism of adaptive foraging is evolutionary change in genetically determined prey use. We constructed individual-based models of evolution of prey use by predators assuming explicit population genetics processes, and examined how this evolution affects the stability (i.e., the proportion of species that persist) of the food web and whether the complexity of the food web increased the stability of the prey–predator system. The analysis showed that the stability of food webs decreased with increasing complexity regardless of evolution of prey use by predators. The effects of evolution on stability differed depending on the assumptions made regarding genetic control of prey use. The probabilities of species extinctions were associated with the establishment or loss of trophic interactions via evolution of the predator, indicating a clear link between structural changes in the food web and community stability.     

Strong stability and evolutionarily stable strategies with two types of players

Static ESS conditions are developed for the frequency evolution of a two-species haploid system by analyzing the stability of the corresponding dynamics for two pairs of strategies. A dynamic strong stability concept is introduced and shown to be equivalent to the ESS conditions in all cases where a regularity assumption is satisfied.     

The Effects of Predator Evolution and Genetic Variation on Predator–Prey Population-Level Dynamics

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator–prey systems. We do this by analyzing a general eco-evolutionary predator–prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator–prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator–prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.     

On the Emergence of Biology from Chemistry: A Discontinuist Perspective from the Point of View of Stability and Regulation

In this paper we argue that molecular evolution, and the evolution of prebiotic and early biological systems are qualitatively different processes, in which a crucial role is played respectively by structural stability and by dynamical mechanisms of regulation and integration. These different features entail also distinct modalities of interaction between system and environment that need to be taken into consideration when discussing molecular and biological evolution and selection.     

The paradox of enrichment in an adaptive world

Paradoxically, enrichment can destabilize a predator-prey food web. While adaptive dynamics can greatly influence the stability of interaction systems, few theoretical studies have examined the effect of the adaptive dynamics of interaction-related traits on the possibility of resolution of the paradox of enrichment. We consider the evolution of attack and defence traits of a predator and two prey species in a one predator-two prey system in which the predator practises optimal diet use. The results showed that optimal foraging alone cannot eliminate a pattern of destabilization with enrichment, but trait evolution of the predator or prey can change the pattern to one of stabilization, implying a possible resolution of the paradox of enrichment. Furthermore, trait evolution in all species can broaden the parameter range of stabilization. Importantly, rapid evolution can stabilize this system, but weaken its stability in the face of enrichment.     

Evolutionary stability in Lotka-Volterra systems

The Lotka-Volterra model of population ecology, which assumes all individuals in each species behave identically, is combined with the behavioral evolution model of evolutionary game theory. In the resultant monomorphic situation, conditions for the stability of the resident Lotka-Volterra system, when perturbed by a mutant phenotype in each species, are analysed. We develop an evolutionary ecology stability concept, called a monomorphic evolutionarily stable ecological equilibrium, which contains as a special case the original definition by Maynard Smith of an evolutionarily stable strategy for a single species. Heuristically, the concept asserts that the resident ecological system must be stable as well as the phenotypic evolution on the "stationary density surface". The conditions are also shown to be central to analyse stability issues in the polymorphic model that allows arbitrarily many phenotypes in each species, especially when the number of species is small. The mathematical techniques are from the theory of dynamical systems, including linearization, centre manifolds and Molchanov's Theorem.     

GroEL/ES Buffering and Compensatory Mutations Promote Protein Evolution by Stabilizing Folding Intermediates

Maintaining stability is a major constraint in protein evolution because most mutations are destabilizing. Buffering and/or compensatory mechanisms that counteract this progressive destabilization during functional adaptation are pivotal for protein evolution as well as protein engineering. However, the interplay of these two mechanisms during a full evolutionary trajectory has never been explored. Here, we unravel such dynamics during the laboratory evolution of a phosphotriesterase into an arylesterase. A controllable GroEL/ES chaperone co-expression system enabled us to vary the selection environment between buffering and compensatory, which smoothened the trajectory along the fitness landscape to achieve a > 10⁴ increase in arylesterase activity. Biophysical characterization revealed that, in contrast to prevalent models of protein stability and evolution, the variants' soluble cellular expression did not correlate with in vitro stability, and compensatory mutations were linked to a stabilization of folding intermediates. Thus, folding kinetics in the cell are a key feature of protein evolvability.     

Spontaneous modulation of a dynamic balance between bacterial genomic stability and mutability: roles and molecular mechanisms of the genetic switch

Bacteria need a high degree of genetic stability to maintain their species identities over long evolutionary times while retaining some mutability to adapt to the changing environment.It is a long unanswered question that how bacteria reconcile these seemingly contradictory biological properties.We hypothesized that certain mechanisms must maintain a dynamic balance between genetic stability and mutability for the survival and evolution of bacterial species.To identify such mechanisms,we analyzed bacterial genomes,focusing on the Salmonella mismatch repair(MMR)system.We found that the MMR gene mutL functions as a genetic switch through a slipped-strand mispairing mechanism,modulating and maintaining a dynamic balance between genetic stability and mutability during bacterial evolution.This mechanism allows bacteria to maintain their phylogenetic status,while also adapting to changing environments by acquiring novel traits.In this review,we outline the history of research into this genetic switch,from its discovery to the latest findings,and discuss its potential roles in the genomic evolution of bacteria.     

The occurrence of nitrate on the early earth and its role in the evolution of the prokaryotes

It has been suggested that the evolution of the respiratory system coupled to oxidative phosphorylation occurred under anaerobic conditions in which inorganic compounds, principally nitrate, served as electron acceptors. Such a hypothesis requires that nitrate be produced, consistently and at adequate concentrations for utilization in biological processes, at a time when much of the Earth's surface was still in a relatively reduced state. This paper is directed towards a consideration of the possible sources of nitrate under primeval conditions, its stability, and its concentration in sites favorable to the evolution of the bacteria.     

基于Logistic模型的煤电产业共生系统稳定性分析

煤电产业共生系统中煤炭企业与电力企业之间的关系与生物种群中物种之间的互利共生关系存在一定的相似性,煤电产业共生系统要实现自身的完善与稳定发展,其内部互利共生关系的企业间必须达到利益上的均衡。借鉴自然界生物种群竞争与合作的共生演化理论与思想,用企业产值来反映煤电产业共生系统演化过程的外生变量,建立了企业产值增长的竞争与合作型Logistic模型。在厘清稳定点的条件之后,通过协同演化博弈分析对煤电产业共生系统演化过程进行了模拟。研究结果表明:(1)煤电产业共生系统的稳定不仅取决于煤电企业进入对方造成的分散力与集聚力之间的较量,还取决于各自在系统内外所取得效益的比较;不仅取决于核心企业的决定性作用,还很大程度上取决于相关企业为进入系统所做出的努力和采取的措施,同时,还与企业的初始产值、竞争力、合作性以及产值增长率等有着密切的关系;(2)煤电产业共生系统要实现长期可持续发展,必须保持产业共生系统互补的共生系统结构以及较高的生产活力。     

Adaptation to larval crowding in Drosophila ananassae leads to the evolution of population stability

Density-dependent selection is expected to lead to population stability, especially if r and K tradeoff. Yet, there is no empirical evidence of adaptation to crowding leading to the evolution of stability. We show that populations of Drosophila ananassae selected for adaptation to larval crowding have higher K and lower r, and evolve greater stability than controls. We also show that increased population growth rates at high density can enhance stability, even in the absence of a decrease in r, by ensuring that the crowding adapted populations do not fall to very low sizes. We discuss our results in the context of traits known to have diverged between the selected and control populations, and compare our results with previous work on the evolution of stability in D. melanogaster. Overall, our results suggest that density-dependent selection may be an important factor promoting the evolution of relatively stable dynamics in natural populations.     

Evolutionary origins of human apoptosis and genome-stability gene networks

Apoptosis is essential for complex multicellular organisms and its failure is associated with genome instability and cancer. Interactions between apoptosis and genome-maintenance mechanisms have been extensively documented and include transactivation-independent and -dependent functions, in which the tumor-suppressor protein p53 works as a ‘molecular node’ in the DNA-damage response. Although apoptosis and genome stability have been identified as ancient pathways in eukaryote phylogeny, the biological evolution underlying the emergence of an integrated system remains largely unknown. Here, using computational methods, we reconstruct the evolutionary scenario that linked apoptosis with genome stability pathways in a functional human gene/protein association network. We found that the entanglement of DNA repair, chromosome stability and apoptosis gene networks appears with the caspase gene family and the antiapoptotic gene BCL2. Also, several critical nodes that entangle apoptosis and genome stability are cancer genes (e.g. ATM, BRCA1, BRCA2, MLH1, MSH2, MSH6 and TP53), although their orthologs have arisen in different points of evolution. Our results demonstrate how genome stability and apoptosis were co-opted during evolution recruiting genes that merge both systems. We also provide several examples to exploit this evolutionary platform, where we have judiciously extended information on gene essentiality inferred from model organisms to human.     

Optimal Placement of Unified Power Flow Controllers to Improve Dynamic Voltage Stability Using Power System Variable Based Voltage Stability Indices

This study examines a new approach to selecting the locations of unified power flow controllers (UPFCs) in power system networks based on a dynamic analysis of voltage stability. Power system voltage stability indices (VSIs) including the line stability index (LQP), the voltage collapse proximity indicator (VCPI), and the line stability index (L_mn) are employed to identify the most suitable locations in the system for UPFCs. In this study, the locations of the UPFCs are identified by dynamically varying the loads across all of the load buses to represent actual power system conditions. Simulations were conducted in a power system computer-aided design (PSCAD) software using the IEEE 14-bus and 39- bus benchmark power system models. The simulation results demonstrate the effectiveness of the proposed method. When the UPFCs are placed in the locations obtained with the new approach, the voltage stability improves. A comparison of the steady-state VSIs resulting from the UPFCs placed in the locations obtained with the new approach and with particle swarm optimization (PSO) and differential evolution (DE), which are static methods, is presented. In all cases, the UPFC locations given by the proposed approach result in better voltage stability than those obtained with the other approaches.     

应用系统遗传学与细胞发生的基因调控网络序列标记显示分析

基因型-表现型复杂系统自组织化是基因系统到蛋白质系统、代谢酶系统的遗传信息转换过程。一个协同表达的基因群调控一个相对独立性状的功能模块,基因网络的自组织化建构基因组稳态与遗传适应过程。腺垂体干细胞分化成5种不同的内分泌细胞系,受上丘脑和性腺、胰岛细胞等激素的调控,涉及系列转录因子的诱导表达,成为细胞系发生研究的模型。GH基因的表达受上丘脑激素GRF、GHRP-6刺激以及SMS抑制,经不同受体、G蛋白亚单元和PKA、PKC信号传导路径,转录因子调控细胞再生或GH基因表达、激素分泌。基因表达调控决定于基因序列,如启动子、非翻译RNA区、蛋白质的结构域等,系统生物学包括组学、计算与合成生物技术,序列标志片段显示(STFD),可用于细胞系分化、病理变化等基因表达谱、信号传导网络的系统分析与功能基因克隆。     

Laboratory evolution of population stability in Drosophila: constancy and persistence do not necessarily coevolve

1. Despite considerable theoretical work, the evolution of population stability has rarely been investigated empirically. Moreover, it is not clear whether different stability properties of a population evolve together, or independently. 2. We investigate the evolution of two aspects of population stability using laboratory populations of Drosophila melanogaster selected for faster preadult development and early reproduction, and their matched controls. 3. We show that the constancy stability of the selected populations is significantly higher than their controls, confirming a previous observation that population stability can evolve as a by-product of life-history evolution. This enhanced constancy stability is due to a reduced maximal per capita growth rate, brought about by a reduction in fecundity of the selected populations as a result of the trade-off between developmental rate and fecundity. 4. Persistence stability, as reflected by the probability of extinction, does not differ significantly between selected and control populations. 5. We also show how seemingly trivial experimental details, such as the protocol for restarting extinct populations, can interact with life-history traits to alter the manifestation of the stability properties of a population.     

Pathogen evolution in switching environments: A hybrid dynamical system approach

We propose a hybrid dynamical system approach to model the evolution of a pathogen that experiences different selective pressures according to a stochastic process. In every environment, the evolution of the pathogen is described by a version of the Fisher-Haldane-Wright equation while the switching between environments follows a Markov jump process. We investigate how the qualitative behavior of a simple single-host deterministic system changes when the stochastic switching process is added. In particular, we study the stability in probability of monomorphic equilibria. We prove that in a "constantly" fluctuating environment, the genotype with the highest mean fitness is asymptotically stable in probability while all others are unstable in probability. However, if the probability of host switching depends on the genotype composition of the population, polymorphism can be stably maintained.     

底栖生物影响下的潮滩微地貌演化数值模拟

潮滩是海岸带湿地的主要类型之一,其中分布的底栖生物对生态环境具有重要的调节作用。潮滩底栖微藻、泥沙与水动力之间存在相互作用,影响潮滩微地貌形态,明晰底栖生物对潮滩微地貌的演化机制至关重要。以黄河三角洲潮滩湿地为研究区,通过构建潮滩微地貌动力模型,探究底栖生物对微地貌格局演化的作用机制,分析底栖生物对微地貌系统稳定性的影响。结果表明(1)底栖微藻生长与泥沙扩散、水流再分配过程交互作用驱动下,潮滩上可形成底栖微藻覆盖的高丘与积水洼地交替分布的规则性微地貌斑图;(2)微地貌斑图的形成提高了潮滩生态系统初级生产力和泥沙淤积高度;(3)底栖微藻与泥沙、水流的交互作用使得潮滩微地貌系统对侵蚀扰动呈现非线性响应行为,系统存在临界点,且在一定侵蚀率范围内存在双稳态;(4)黄河口泥螺入侵使得微地貌系统抵抗侵蚀扰动能力减小,且系统稳定性随泥螺生物量的增加而降低。     

Boltzmann Entropy: Generalization and Applications

The object of the paper is to generalize Boltzmann entropy to takeaccount of the subjective nature of a system. The generalized entropyor relative entropy so obtained has been applied to an ecologicalsystem leading to some interesting new results in violation ofexisting physical laws. The entropy was further developed to derive ageneralized macroscopic measure of relative entropy which plays asignificant role in the study of stability and evolution ofecological and chemical reaction systems.     

Emergent Robustness in Competition Between Autocatalytic Chemical Networks

The origin of auto-catalytic networks has been proposed as an initial step in pre-biotic evolution. It is possible to derive simple models where auto-catalytic networks naturally arise from simple chemical mixtures. In order for such a system to develop, there needs to be some degree of stability, what is characterised as `robustness'. We demonstrate that competing systems generate this robustness as they create a distributed network of catalytic pathways.