The evolutionary dynamics of self-incompatibility systems

Self-incompatible flowering plants reject pollen that expresses the same mating specificity as the pistil (female reproductive tract). In most plant families, pollen and pistil mating specificities segregate as a single locus, the S locus. In at least two self-incompatibility systems, distinct pollen and pistil specificity genes are embedded in an extensive nonrecombining tract. To facilitate consideration of how new S locus specificities arise in systems with distinct pollen and pistil genes, we present a graphical model for the generation of hypotheses. It incorporates the evolutionary principle that nonreciprocal siring success (cross-pollinations between two plants produce seeds in only one direction) tends to favor the rejecting partner. This model suggests that selection within S-allele specificity classes could accelerate the rate of nonsynonymous (amino acid-changing) substitutions, with periodic selective sweeps removing segregating variation within classes. Accelerated substitution within specificity classes could also promote the origin of new S-allele specificities.     

Transient dynamics and persistence of ecological systems

Using spatially coupled predator–prey systems as an example of a cyclic ecological system where coexistence depends on oscillations, transient dynamics of models where there are no stable persistent solutions are shown to be a reasonable explanation of persistence over ecological time scales. The parameter values leading to transients within the context of a particular model may be far from parameter values that lead to stable solutions, so transients will need to be explicitly considered in model analysis. Since natural systems with many coupled oscillating species are common, and natural communities are often reset by disturbances or seasonality, transients should play a central role in understanding natural systems.     

Cross-scale ecological dynamics and microbial size spectra in marine ecosystems

Evaluating the component features of 'scaling' planktonic size spectra, commonly observed in marine ecosystems, is crucial for understanding the ecological and evolutionary processes from which they emerge. Here, we develop a theoretical framework that describes such spectra in terms of the size distributions of individual species, and test it against actual datasets of microbial size spectra from the Atlantic Ocean. We describe characteristics of size probability distributions of component species that are sufficient to support the observational evidence and infer that, when a power law describes the community size spectrum (thus suggesting critical self-organization of microbial ecosystem structure and function), a related power law links the total number of individuals of a given species to its mean size.     

Mechanical sensitivity reveals evolutionary dynamics of mechanical systems

A classic question in evolutionary biology is how form–function relationships promote or limit diversification. Mechanical metrics, such as kinematic transmission (KT) in linkage systems, are useful tools for examining the evolution of form and function in a comparative context. The convergence of disparate systems on equivalent metric values (mechanical equivalence) has been highlighted as a source of potential morphological diversity under the assumption that morphology can evolve with minimal impact on function. However, this assumption does not account for mechanical sensitivity—the sensitivity of the metric to morphological changes in individual components of a structure. We examined the diversification of a four-bar linkage system in mantis shrimp (Stomatopoda), and found evidence for both mechanical equivalence and differential mechanical sensitivity. KT exhibited variable correlations with individual linkage components, highlighting the components that influence KT evolution, and the components that are free to evolve independently from KT and thereby contribute to the observed pattern of mechanical equivalence. Determining the mechanical sensitivity in a system leads to a deeper understanding of both functional convergence and morphological diversification. This study illustrates the importance of multi-level analyses in delineating the factors that limit and promote diversification in form–function systems.     

Evolutionary dynamics of predator-prey systems: an ecological perspective

 Evolution takes place in an ecological setting that typically involves interactions with other organisms. To describe such evolution, a structure is needed which incorporates the simultaneous evolution of interacting species. Here a formal framework for this purpose is suggested, extending from the microscopic interactions between individuals – the immediate cause of natural selection, through the mesoscopic population dynamics responsible for driving the replacement of one mutant phenotype by another, to the macroscopic process of phenotypic evolution arising from many such substitutions. The process of coevolution that results from this is illustrated in the context of predator–prey systems. With no more than qualitative information about the evolutionary dynamics, some basic properties of predator–prey coevolution become evident. More detailed understanding requires specification of an evolutionary dynamic; two models for this purpose are outlined, one from our own research on a stochastic process of mutation and selection and the other from quantitative genetics. Much of the interest in coevolution has been to characterize the properties of fixed points at which there is no further phenotypic evolution. Stability analysis of the fixed points of evolutionary dynamical systems is reviewed and leads to conclusions about the asymptotic states of evolution rather different from those of game-theoretic methods. These differences become especially important when evolution involves more than one species. Received 10 November 1993; received in revised form 25 July 1994     

Measuring complexity to infer changes in the dynamics of ecological systems under stress

Despite advances in our mechanistic understanding of ecological processes, the inherent complexity of real-world ecosystems still limits our ability in predicting ecological dynamics especially in the face of on-going environmental stress. Developing a model is frequently challenged by structure uncertainty, unknown parameters, and limited data for exploring out-of-sample predictions. One way to address this challenge is to look for patterns in the data themselves in order to infer the underlying processes of an ecological system rather than to build system-specific models. For example, it has been recently suggested that statistical changes in ecological dynamics can be used to infer changes in the stability of ecosystems as they approach tipping points. For computer scientists such inference is similar to the notion of a Turing machine: a computational device that could execute a program (the process) to produce the observed data (the pattern). Here, we make use of such basic computational ideas introduced by Alan Turing to recognize changing patterns in ecological dynamics in ecosystems under stress. To do this, we use the concept of Kolmogorov algorithmic complexity that is a measure of randomness. In particular, we estimate an approximation to Kolmogorov complexity based on the Block Decomposition Method (BDM). We apply BDM to identify changes in complexity in simulated time-series and spatial datasets from ecosystems that experience different types of ecological transitions. We find that in all cases, K_BDM complexity decreased before all ecological transitions both in time-series and spatial datasets. These trends indicate that loss of stability in the ecological models we explored is characterized by loss of complexity and the emergence of a regular and computable underlying structure. Our results suggest that Kolmogorov complexity may serve as tool for revealing changes in the dynamics of ecosystems close to ecological transitions.     

Bacteriocins: ecological and evolutionary significance

Bacteriocins are compounds that are produced by bacteria and are antagonistic to other bacteria. Although they have been known for many years, recent interest in these compounds has increased because of their potential use as natural food preservatives. Although most of this research has been directed at the molecular level, a clearer picture of the ecological role played by bacteriocins in natural environments is beginning to emerge. In addition, the importance and practical implications of evolutionary aspects of bacteriocins and bacteriocin resistance are now being assessed.     

Multi-species evolutionary dynamics

Dynamical attainability of an evolutionarily stable strategy (ESS) through the process of mutations and natural selection has mostly been addressed through the use of the continuously stable strategy (CSS) concept for species evolutionary games in which strategies are drawn from a continuum, and by the adaptive trait dynamics method. We address the issue of dynamical attainability of an ESS in coevolving species through the use of the concept of an ESNIS. It is shown that the definition of an ESNIS coalition for coevolving species is not in general equivalent to other definitions for CSS given in the literature. We show under some additional conditions that, in a dynamic system which involves the strategies of a dimorphic ESNIS coalition and at most two strategies that are not members of ESNIS coalition, the ESNIS coalition will emerge as the winner. In addition an ESNIS will be approached because of the invasion structure of strategies in its neighborhood. This proves that under the above conditions an ESNIS has a better chance of being attained than a strategy coalition which is a CSS. The theory developed is applied to a class of coevolutionary game models with Lotka–Volterra type interactions and we show that for such models, an ESS coalition will be dynamically attainable through mutations and natural selection if the ESS coalition is also an ESNIS coalition.Co-ordinating editor: Metz     

Molecular evolutionary signatures reveal the role of host ecological dynamics in viral disease emergence and spread

RNA viruses account for numerous emerging and perennial infectious diseases, and are characterized by rapid rates of molecular evolution. The ecological dynamics of most emerging RNA viruses are still poorly understood and difficult to ascertain. The availability of genome sequence data for many RNA viruses, in principle, could be used to infer ecological dynamics if changes in population numbers produced a lasting signature within the pattern of genome evolution. As a result, the rapidly emerging phylogeographic structure of a pathogen, shaped by the rise and fall in the number of infections and their spatial distribution, could be used as a surrogate for direct ecological assessments. Based on rabies virus as our example, we use a model combining ecological and evolutionary processes to test whether variation in the rate of host movement results in predictive diagnostic patterns of pathogen genetic structure. We identify several linearizable relationships between host dispersal rate and measures of phylogenetic structure suggesting genetic information can be used to directly infer ecological process. We also find phylogenetic structure may be more revealing than demography for certain ecological processes. Our approach extends the reach of current analytic frameworks for infectious disease dynamics by linking phylogeography back to underlying ecological processes.     

Key evolutionary innovations and their ecological mechanisms

Explanations for taxonomic diversity in a particular clade often implicate evolutionary innovations, possessed by members of the clade, that are thought to have favoured diversification. We review such “key innovation”; hypotheses, the ecological mechanisms involved, and potential tests of such hypotheses.

Key innovation hypotheses can be supported by evidence of ecological mechanism and by comparative tests. We argue that both are necessary for convincing support. In fact, few key innovation hypotheses are currently backed by either one.

We group ecological mechanisms of diversification in three major classes. Diversification may be spurred by innovations that: I) allow invasion of new adaptive zones; II) increase fitness, allowing one clade to replace another; or III) increase the propensity for reproductive or ecological specialization. Key innovations in different classes are likely to produce different evolutionary patterns, and therefore may be supported by different kinds of ecological evidence.     

Cooperation: integrating evolutionary and ecological perspectives

Putting a competitive squeeze on a cooperative group has long been considered to encourage cheats. Now we learn that competition, by driving diversification among cooperators, can create groups that are both more productive and more resistant to defection.     

Species borders: ecological and evolutionary perspectives

Recent ecological studies on species borders have used a number of approaches to establish causation for specific environmental factors and to identify the traits involved. These include interspecific comparisons, detailed investigations of marginal populations, and experimental manipulation. Species borders continue to be largely ignored in evolutionary biology, although some work suggests that marginal populations may often be relatively better-adapted to unfavourable conditions but perform poorly under most other conditions.     

Single species evolutionary dynamics

Not long after the introduction of evolutionary stable strategy (ESS) concept, it was noticed that dynamic selection did not always lead to the establishment of the ESS. The concept of continuously stable strategy (CSS) was thereafter developed. It was generally accepted that dynamic selection leads to the establishment of an ESS if it is a CSS. Examination of an evolutionary stability concept which is called neighborhood invader strategy (NIS) shows that it may be impossible for an ESS to be established through dynamic selection even if it is a CSS and no polymorphisms occur. We will examine the NIS concept and its implications for two evolutionary game models: root-shoot allocation in plant competition and Lotka–Volterra competition. In the root-shoot model we show that an ESS will be attained through dynamic selection if it is a NIS. Similarly for the Lotka–Volterra model, we show that an ESS will be attained through dynamic selection even if protected dimorphisms occur during the evolutionary process if it is an NIS.