Evolution of spatially structured host–parasite interactions

Spatial structure has dramatic effects on the demography and the evolution of species. A large variety of theoretical models have attempted to understand how local dispersal may shape the coevolution of interacting species such as host–parasite interactions. The lack of a unifying framework is a serious impediment for anyone willing to understand current theory. Here, we review previous theoretical studies in the light of a single epidemiological model that allows us to explore the effects of both host and parasite migration rates on the evolution and coevolution of various life‐history traits. We discuss the impact of local dispersal on parasite virulence, various host defence strategies and local adaptation. Our analysis shows that evolutionary and coevolutionary outcomes crucially depend on the details of the host–parasite life cycle and on which life‐history trait is involved in the interaction. We also discuss experimental studies that support the effects of spatial structure on the evolution of host–parasite interactions. This review highlights major similarities between some theoretical results, but it also reveals an important gap between evolutionary and coevolutionary models. We discuss possible ways to bridge this gap within a more unified framework that would reconcile spatial epidemiology, evolution and coevolution.     

John Maynard Smith and the natural philosophy of␣adaptation

One of the most remarkable aspects of John Maynard Smith’s work was the fact that he devoted time both to doing science and to reflecting philosophically upon its methods and concepts. In this paper I offer a philosophical analysis of Maynard Smith’s approach to modelling phenotypic evolution in relation to three main themes. The first concerns the type of scientific understanding that ESS and optimality models give us. The second concerns the causal–historical aspect of stability analyses of adaptation. The third concerns the concept of evolutionary stability itself. Taken together, these three themes comprise what I call the natural philosophy of adaptation.     

Bet‐hedging as a complex interaction among developmental instability,environmental heterogeneity,dispersal, and life‐history strategy

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet‐hedging. I used an individual‐based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life‐history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life‐history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet‐hedging, but not in a simple linear fashion. I found higher‐order interactions between life‐history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.     

Application of network methods for understanding evolutionary dynamics in discrete habitats

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene‐flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population‐genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene‐flow patterns. In the last decades, network theory – a branch of discrete mathematics concerned with complex interactions between discrete elements – has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population‐genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology.     

The eco‐evolutionary consequences of interspecific phenological asynchrony – a theoretical perspective

The timing of biological events (phenology) is an important aspect of both a species’ life cycle and how it interacts with other species and its environment. Patterns of phenological change have been given much scientific attention, particularly recently in relation to climate change. For pairs of interacting species, if their rates of phenological change differ, then this may lead to asynchrony between them and disruption of their ecological interactions. However it is often difficult to interpret differential rates of phenological change and to predict their ecological and evolutionary consequences. We review theoretical results regarding this topic, with special emphasis on those arising from life history theory, evolutionary game theory and population dynamic models. Much ecological research on phenological change builds upon the concept of match/mismatch, so we start by putting forward a simple but general model that captures essential elements of this concept. We then systematically compare the predictions of this baseline model with expectations from theory in which additional ecological mechanisms and features of species life cycles are taken into account. We discuss the ways in which the fitness consequences of interspecific phenological asynchrony may be weak, strong, or idiosyncratic. We discuss theory showing that synchrony is not necessarily an expected evolutionary outcome, and how population densities are not necessarily maximized by adaptation, and the implications of these findings. By bringing together theoretical developments regarding the eco‐evolutionary consequences of phenological asynchrony, we provide an overview of available alternative hypotheses for interpreting empirical patterns as well as the starting point for the next generation of theory in this field.     

Microbial laboratory evolution in the era of genome‐scale science

Laboratory evolution studies provide fundamental biological insight through direct observation of the evolution process. They not only enable testing of evolutionary theory and principles, but also have applications to metabolic engineering and human health. Genome‐scale tools are revolutionizing studies of laboratory evolution by providing complete determination of the genetic basis of adaptation and the changes in the organism's gene expression state. Here, we review studies centered on four central themes of laboratory evolution studies: (1) the genetic basis of adaptation; (2) the importance of mutations to genes that encode regulatory hubs; (3) the view of adaptive evolution as an optimization process; and (4) the dynamics with which laboratory populations evolve.     

Striking convergence in the mouthpart evolution of stream-living algae grazers

This scanning-electron microscopic study demonstrates the convergent evolution of the mouthparts of various herbivorous stream animals (insects from different orders, an isopod, snails, fish, and a tadpole) feeding on epilithic algal pastures. This food source is rich but is often difficult to harvest. Nevertheless, a large number of species can live on it because they have evolved highly specialized mouthparts. There are four functional problems that an algae grazer has to solve: the algae must be removed from the stone, they have to be collected and crushed, and a current shield is needed to prevent the water flow sweeping away the food. Among the 30 algae grazers examined in this study, a limited number of morphological solutions have been found for each of these adaptational problems. There are multiple evolutionary pathways for mouthpart adaptation and even closely related species have often evolved different types of tools for the same function. This refects the existence of a certain amount of evolutionary scope. Such freedom of evolution is present, however, only at the beginning of the adaptiogenesis of an algae grazer. Once one of the evolutionary pathways is taken, further improvement of the mouthparts is possible only by the refinement of the ‘chosen’ type of tools. The consequence of this is that a large number of astonishing convergences have occurred in algae grazers that have independently trodden the same evolutionary pathway.     

Geostatistical modelling on stream networks: developing valid covariance matrices based on hydrologic distance and stream flow

1. Geostatistical models based on Euclidean distance fail to represent the spatial configuration, connectivity, and directionality of sites in a stream network and may not be ecologically relevant for many chemical, physical and biological studies of freshwater streams. Functional distance measures, such as symmetric and asymmetric hydrologic distance, more accurately represent the transfer of organisms, material and energy through stream networks. However, calculating the hydrologic distances for a large study area remains challenging and substituting hydrologic distance for Euclidean distance may violate geostatistical modelling assumptions. 2. We provide a review of geostatistical modelling assumptions and discuss the statistical and ecological consequences of substituting hydrologic distance measures for Euclidean distance. We also describe a new family of autocovariance models that we developed for stream networks, which are based on hydrologic distance measures. 3. We describe the geographical information system (GIS) methodology used to generate spatial data necessary for geostatistical modelling in stream networks. We also provide an example that illustrates the methodology used to create a valid covariance matrix based on asymmetric hydrologic distance and weighted by discharge volume, which can be incorporated into common geostatistical models. 4. The methodology and tools described supply ecologically meaningful and statistically valid geostatistical models for stream networks. They also provide stream ecologists with the opportunity to develop their own functional measures of distance and connectivity, which will improve geostatistical models developed for stream networks in the future. 5. The GIS tools presented here are being made available in order to facilitate the application of valid geostatistical modelling in freshwater ecology.     

Looking for middle ground in cultural attraction theory

In their article, Thom Scott‐Phillips, Stefaan Blancke, and Christophe Heintz do a commendable job summarizing the position and misunderstandings of “cultural attraction theory” (CAT). However, they do not address a longstanding problem for the CAT framework; that while it has an encompassing theory and some well‐worked out case studies, it lacks tools for generating models or empirical hypotheses of intermediate generality. I suggest that what the authors diagnose as misunderstandings are instead superficial interpretive errors, resulting from researchers who have attempted to extract generalizable hypotheses from CAT and bring them into contact with the analytical and inferential models of contemporary cultural evolutionary research.     

Predicting trait values and measuring selection in complex life histories: reproductive allocation decisions in Soay sheep

Accurate prediction of life history phenomena and characterisation of selection in free-living animal populations are fundamental goals in evolutionary ecology. In density regulated, structured populations, where individual state influences fate, simple and widely used approaches based on individual lifetime measures of fitness are difficult to justify. We combine recently developed structured population modelling tools with ideas from modern evolutionary game theory (adaptive dynamics) to understand selection on allocation of female reproductive effort to singletons or twins in a size-structured population of feral sheep. In marked contrast to the classical selection analyses, our model-based approach predicts that the female allocation strategy is under negligible directional selection. These differences arise because classical selection analysis ignores components of offspring fitness and fails to consider selection over the complete life cycle.     

MetaPopGen: an r package to simulate population genetics in large size metapopulations

Population genetics simulation models are useful tools to study the effects of demography and environmental factors on genetic variation and genetic differentiation. They allow for studying species and populations with complex life histories, spatial distribution and many other complicating factors that make analytical treatment impracticable. Most simulation models are individual‐based: this poses a limitation to simulation of very large populations because of the limits in computer memory and long computation times. To overcome these limitations, we propose an intermediate approach that allows modelling of very complex demographic scenarios, which would be intractable with analytical models, and removes the limitations imposed by large population size, which affect individual‐based simulation models. We implement this approach in a software package for the r environment, MetaPopGen. The innovative concept of this approach with respect to the other population genetic simulators is that it focuses on genotype numbers rather than on individuals. Genotype numbers are iterated through time by using random number generators for appropriate probabilistic distributions to reproduce the stochasticity inherent to Mendelian segregation, survival, dispersal and reproduction. Features included in the model are age structure, monoecious and dioecious (or separate sexes) life cycles, mutation, dispersal and selection. The model simulates only one locus at a time. All demographic parameters can be genotype‐, sex‐, age‐, deme‐ and time‐dependent. MetaPopGen is therefore indicated to study large populations and very complex demographic scenarios. We illustrate the capabilities of MetaPopGen by applying it to the case of a marine fish metapopulation in the Mediterranean Sea.     

EVOLUTIONARY RESCUE OF SEXUAL AND ASEXUAL POPULATIONS IN A DETERIORATING ENVIRONMENT

The environmental change experienced by many contemporary populations of organisms poses a serious risk to their survival. From the theory of evolutionary rescue, we predict that the combination of sex and genetic diversity should increase the probability of survival by increasing variation and thereby the probability of generating a type that can tolerate the stressful environment. We tested this prediction by comparing experimental populations of Chlamydomonas reinhardtii that differ in sexuality and in the initial amount of genetic diversity. The lines were serially propagated in an environment where the level of stress caused by salt increased over time from fresh water to the limits of marine conditions. In the long term, the combination of high diversity and obligate sexuality was most effective in supporting evolutionary rescue. Most of the adaptation to high‐salt environments in the obligate sexual‐high diversity lines had occurred by midway through the experiment, indicating that positive genetic correlations of adaptation to lethal stress with adaptation to sublethal stress greatly increased the probability of evolutionary rescue. The evolutionary rescue events observed in this study provide evidence that major shifts in ways of life can arise within short time frames through the action of natural selection in sexual populations.     

Genomic approaches with natural fish populations

Natural populations v. inbred stocks provide a much richer resource for identifying the effects of nucleotide substitutions because natural populations have greater polymorphism. Additionally, natural populations offer an advantage over most common research organisms because they are subject to natural selection, and analyses of these adaptations can be used to identify biologically important changes. Among fishes, these analyses are enhanced by having a wide diversity of species (>28 000 species, more than any other group of vertebrates) living in a huge range of environments (from below freezing to > 46° C, in fresh water to salinities >40 ppt.). Moreover, fishes exhibit many different life‐history and reproductive strategies and have many different phenotypes and social structures. Although fishes provide numerous advantages over other vertebrate models, there is still a dearth of available genomic tools for fishes. Fishes make up approximately half of all known vertebrate species, yet <0·2% of fish species have significant genomic resources. Nonetheless, genomic approaches with fishes have provided some of the first measures of individual variation in gene expression and insights into environmental and ecological adaptations. Thus, genomic approaches with natural fish populations have the potential to revolutionize fundamental studies of diverse fish species that offer myriad ecological and evolutionary questions.     

Modelling whole-plant allocation in relation to carbon and nitrogen supply: Coordination versus optimization: Opinion

One of the few integrating theories related to allocation is the hypothesis of optimization. While optimization theory has great heuristic appeal and has been used to describe a range of physiological and ecological phenomena, it has major limitations. Optimization is necessarily based on a definite time integral and an optimal control strategy must be specific to the same patterns exhibited by the driving variables over this same period of time. Optimization tends to employ the use of oversimplifications in order to facilitate analytical solutions to the optimal control strategy, i.e. the mechanism governing the response of plants, which is the critical issue of interest. It is difficult to define objective criteria that can account for the natural variability in plants and testing the quantitative predictions of optimality models is also difficult. Thus, we suggest that optimization theory is too limited for practical use in modelling whole plant allocation. In this paper, we introduce the use of coordination theory as a practical alternative. We develop a simple plant growth allocation model using both coordination and optimization approaches and show that coordination theory is easily applied, produces results that are quantitatively similar to optimization, and overcomes the inherent limitations of optimization theory.     

Maynard Smith,optimization, and evolution

Maynard Smith’s defenses of adaptationism and of the value of optimization theory in evolutionary biology are both criticized. His defense does not adequately respond to the criticism of adaptationism by Gould and Lewontin. It is also argued here that natural selection cannot be interpreted as an optimization process if the objective function to be optimized is either (i) interpretable as a fitness, or (ii) correlated with the mean population fitness. This result holds even if fitnesses are frequency-independent; the problem is further exacerbated in the frequency-dependent context modeled by evolutionary game theory. However, Eshel and Feldman’s new results on “long-term” evolution may provide some hope for the continuing relevance of the game-theoretic framework. These arguments also demonstrate the irrelevance of attempts by Intelligent Design creationists to use computational limits on optimization algorithms as evidence against evolutionary theory. It is pointed out that adaptation, natural selection, and optimization are not equivalent processes in the context of biological evolution. It is a pleasure to dedicate this paper to the memory of John Maynard Smith. Thanks are due to James Justus and Samir Okasha for comments on an earlier draft.     

Matching research and policy tools to scales of climate-change adaptation in the Murray-Darling, a large Australian river basin: a review

Climate change is likely to cause deleterious hydrological and ecological impacts in many of the world’s major river basins. Using the Murray-Darling Basin, Australia, as a case study, we present an adaptation framework which addresses the hydrological impacts of climate change at three spatial scales: the high-conservation value asset, the water management unit and the entire basin. At each scale, the appropriate scientific, policy and operational tools differ, though should be applied in concert. At the scale of the asset, hydrodynamic modelling has improved the capacity of site managers to anticipate the effects of management interventions. These models have also contributed to improve hydrological modelling of the water management unit. When combined with ecosystem response models, hydrological models can compare ecological outcomes over a range of timescales, leading to improvements in the representation of environmental requirements in water sharing plans. At the scale of the basin, the Australian government has used a legislative mechanism to set overarching ecological and diversion objectives. In addition, the purchase of water-use entitlements has created a flexible mechanism to use the water market as a climate-change adaptation mechanism, responding to the changing water availability and conservation priorities that emerge over the coming decades.     

Antarctic ecology from genes to ecosystems: the impact of climate change and the importance of scale

Antarctica offers a unique natural laboratory for undertaking fundamental research on the relationship between climate, evolutionary processes and molecular adaptation. The fragmentation of Gondwana and the development of wide-scale glaciation have resulted in major episodes of extinction and vicariance, as well as driving adaptation to an extreme environment. On shorter time-scales, glacial cycles have resulted in shifts in distribution, range fragmentation and allopatric speciation, and the Antarctic Peninsula is currently experiencing among the most rapid climatic warming on the planet. The recent revolution in molecular techniques has provided a suite of innovative and powerful tools to explore the consequences of these changes, and these are now providing novel insights into evolutionary and ecological processes in Antarctica. In addition, the increasing use of remotely sensed data is providing a large-scale view of the system that allows these processes to be set in a wider spatial context. In these two volumes, we collect a wide range of papers exploring these themes, concentrating on recent advances and emphasizing the importance of spatial and temporal scale in understanding ecological and evolutionary processes in Antarctica.     

Fish distribution predictions from different points of view: comparing associative neural networks,geostatistics and regression models

Accurate prediction of species distributions based on sampling and environmental data is essential for further scientific analysis, such as stock assessment, detection of abundance fluctuation due to climate change or overexploitation, and to underpin management and legislation processes. The evolution of computer science and statistics has allowed the development of sophisticated and well-established modelling techniques as well as a variety of promising innovative approaches for modelling species distribution. The appropriate selection of modelling approach is crucial to the quality of predictions about species distribution. In this study, modelling techniques based on different approaches are compared and evaluated in relation to their predictive performance, utilizing fish density acoustic data. Generalized additive models and mixed models amongst the regression models, associative neural networks (ANNs) and artificial neural networks ensemble amongst the artificial neural networks and ordinary kriging amongst the geostatistical techniques are applied and evaluated. A verification dataset is used for estimating the predictive performance of these models. A combination of outputs from the different models is applied for prediction optimization to exploit the ability of each model to explain certain aspects of variation in species acoustic density. Neural networks and especially ANNs appear to provide more accurate results in fitting the training dataset while generalized additive models appear more flexible in predicting the verification dataset. The efficiency of each technique in relation to certain sampling and output strategies is also discussed.     

Spatial predictability of juvenile fish species richness and abundance in a coral reef environment

Juvenile reef fish communities represent an essential component of coral reef ecosystems in the current focus of fish population dynamics and coral reef resilience. Juvenile fish survival depends on habitat characteristics and is, following settlement, the first determinant of the number of individuals within adult populations. The goal of this study was to provide methods for mapping juvenile fish species richness and abundance into spatial domains suitable for micro and meso-scale analysis and management decisions. Generalized Linear Models predicting juvenile fish species richness and abundance were developed according to spatial and temporal environmental variables measured from 10 m up to 10 km in the southwest lagoon of New Caledonia. The statistical model was further spatially generalized using a 1.5-m resolution, independently created, remotely sensed, habitat map. This procedure revealed that : (1) spatial factors at 10 to 100-m scale explained up to 71% of variability in juvenile species richness, (2) a small improvement (75%) was gained when a combination of environmental variables at different spatial and temporal scales was used and (3) the coupling of remotely sensed data, geographical information system tools and point-based ecological data showed that the highest species richness and abundance were predicted along a narrow margin overlapping the coral reef flat and adjacent seagrass beds. Spatially explicit models of species distribution may be relevant for the management of reef communities when strong relationships exist between faunistic and environmental variables and when models are built at appropriate scales.