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The mechanism of evolutionary change can be studied directly through selection experiments in laboratory microcosms. This chapter begins by describing the experimental approach to evolution, and goes on to analyse adaptation over different time scales. The first section in this chapter is about microcosmologica. Subsections here concern Dallinger's experiment; the laboratory microcosm; the inhabitants of the microcosm; the selection experiment; fitness and adaptedness; and microcosm genealogy. The second section is all about sorting (in other words selection of pre-existing variation) and includes subsection on a single episode of selection; the sorting of a single type; the mixture of discrete types; the Fundamental Theorem of Natural Selection; the sorting in finite populations; drift and selection; and fluctuating population size. The third section is on purifying selection (defined as maintaining adaptedness despite genetic deterioration) and this section discusses the following: mutation-drift balance; mutation-selection equilibrium; and Muller's Ratchet. The fourth section is about directional selection (this is restoring adaptedness despite environmental deterioration) and details the probability that a beneficial mutation will be fixed; periodic selection; Fisher's geometrical analogy; the variable-mutation model; the extreme-value mode; clonal interference; the distribution of fitness effects; genetic interference; and the genetic basis of adaptation. The fifth section is about successive substitution and includes detail on phenotypic evolution towards the optimum; adaptive walks; transitivity; and clonal interference. The sixth section, Cumulative adaptation, includes the following: the protein matrix; connectance; synthetic beneficial mutations; functional interaction in a protein structure; the evolution of RNA sequences; reversibility; cumulation; cumulative construction of novel amidases; diminishing returns; and contingency. The last section called Successive substitution at several loci explains genetic interactions; the adaptive landscape; the allele matrix; compensatory mutations; compound structures; processing chains; the effect of mutation in a simple processing chain; the pattern of adaptation; the evolution of metabolic pathways; in vitro selection; genetic changes during adaptation; and repeated adaptation.

This chapter outlines three basic ways in which humans can alter evolution on adaptive landscapes: through changes in topography, changes in dimensionality, and phenotypic excursions. Changes in topography involve the numbers, positions, gradients, and elevations of surface features on the landscape, such as peaks and valleys. Changes in dimensionality involve the number of at least partially independent traits under selection. Excursions typically involve more or less abrupt changes in the phenotypic position of populations on existing adaptive landscapes, such as through plasticity, hybridization, or genetic manipulation. These different types of change can generate predictions for changes in selection and alterations in evolution — assuming the population can persist through the disturbance. Invasive species can have all of these classes of effects, either for the invasive species or for native species. Climate change will most obviously involve a shift in peak position, such as breeding times under warmer temperatures. Hunting/harvesting will also often involve a shift in peak position, particularly toward smaller and slower growing individuals, and might also decrease phenotypic variance. Habitat loss and fragmentation will influence numbers and positions of adaptive peaks, and can also influence excursions by altering patterns of gene flow in meta-populations. Finally, a decrease in habitat quality can decrease the heights of fitness peaks and cause adaptive landscapes to become smoother. It can also change dimensionality, such as through the introduction of a new contaminant. In conclusion, viewing human-induced environmental change in the framework of changes to adaptive landscapes offers new insights and new perspectives for research.

Sewall Wright’s classic Adaptive Landscape has been a highly successful metaphor and scientific concept in evolutionary biology. It has influenced many different research subdisciplines in evolutionary biology and inspired generations of researchers, even though it has also sparked deep scientific and philosophical controversies. Among such subdisciplines are population genetics, evolutionary ecology, quantitative genetics, experimental evolution, conservation biology, speciation and macroevolutionary dynamics, mimicry, saltational evolution, behavioural ecology, molecular biology, protein networks, and theoretical studies on development.

This chapter traces the origins and conceptual lineages of the adaptive landscape concept and its representations. While Armand Janet's 1895 concept arguably marks the origin of the adaptive landscape concept and even its graphic representation, Janet's concept had very limited impact when compared to Sewall Wright's concept from 1932. As part of his effort to reconcile Mendelian genetics and Darwinian evolution in his shifting balance theory, Wright offered the metaphor of the adaptive landscape and its topographic representation as a way of depicting the effect of variations in population size, migration, and the strength of selection. Wright's genetic version of the adaptive landscape inspired other versions of the adaptive landscape based on phenotypic changes and on molecular changes. As a result, the history of the adaptive landscape is described in terms of three lineages based on the material basis of the adaptive landscape: the genetic landscape, the phenotypic landscape, and the molecular landscape.

Sewall Wright's 1932 adaptive landscape diagram is the most influential visual heuristic in evolutionary biology. Yet, the diagram has met with criticism from biologists and philosophers since its origination. This chapter states that the diagram is a valuable evaluation heuristic for assessing the dynamical behaviour of population genetics models. Although Wright's particular use of it is of dubious value, other biologists have established the diagram's positive heuristic value for evaluating dynamical behaviour. This chapter surveys some of the most influential biological and philosophical work considering the role of the adaptive landscape in evolutionary biology. The chapter builds on a distinction between models, metaphors, and diagrams to make a case for why adaptive landscapes as diagrams have heuristic value for evolutionary biologists.

The adaptive landscape has had a major role in shaping and motivating many experimental evolution studies. In return, these studies have made important contributions to our understanding of the nature of adaptive landscapes. The simplest findings come from studies that have examined the similarity of evolutionary outcomes from initially identical replicate populations. Comparison of resulting evolutionary trajectories has allowed experimenters to examine the repeatability of evolution, a reflection of the relative influence of chance and selection on the outcome of evolution. Other experiments have addressed the evolution of diversity within (usually) initially homogeneous populations — an outcome determined by the availability of distinct adaptive peaks and the existence of ecological conditions that allow the maintenance of subpopulations at different peaks. Experiments can be carefully designed and controlled to assess the effect of environment — e.g. spatial structure, resource complexity — on the likelihood that distinct peaks will be reached. This chapter discusses how bacterial experimental evolution studies can and have contributed to our understanding of the form of adaptive landscapes.

Sewall Wright originally conceived of his Adaptive Landscape as a visual device to capture the consequences of non-linear (epistatic) interactions between genes. A useful way to visualise a multivariate non-linear function is through a ‘landscape’, an important factor to consider when applying Adaptive Landscape models to questions about the evolution of development. This chapter examines how a phenotype landscape (also known as phenotypic landscape or developmental landscape) can explicitly map genetic and developmental traits to the phenotypic traits upon which selection acts. After outlining the basic properties of phenotype landscapes, it considers how they are used in concert with an Adaptive Landscape to study the evolution of development. It then describes the formal theory for evolution on phenotype landscapes and how it generalises the quantitative genetic approaches that are often applied to Adaptive Landscapes. The chapter concludes by illustrating how phenotype landscape theory can be used to study the evolution of genetic covariance, heritability, and novelty.

The adaptive landscape metaphor is one of the most persistent in evolutionary biology, and has generated much theoretical debate (if far less empirical investigation). This chapter briefly traces the history of the concept since its introduction by Sewall Wright in the 1930s. It then distinguishes four types of landscapes pertinent to evolutionary theory: fitness landscapes, adaptive landscapes, fitness surfaces, and morphospaces. These are more or less loosely related to each other, and sometimes the relationship is complex and difficult to explore empirically. The chapter argues that some versions of the landscape metaphor have lost their utility and should be replaced by more sophisticated metaphors, or abandoned altogether. It suggests that — somewhat surprisingly — the most useful type of landscape may turn out to be the morphospace, a concept that allows for a productive bridge between theoretical analyses and empirical results, especially in fields such as palaeontology and evolutionary developmental biology. In particular, the chapter discusses examples from the paleontological literature that constitute instances of truly (and stunningly) predictive theoretical analysis in what is often considered an entirely descriptive historical science.

Our understanding of Wright's shifting balance theory (SBT) has deepened and its empirical predictions have been enriched by the theoretical, field and laboratory experimental research. Whereas models with strictly additive genetic effects provide the basis for much of evolutionary genetic theory, studies of the molecular genetic basis of adaptations find that gene interaction is the norm. The impact of Wright's SBT will not be fully understood until we have a better understanding of how physiological interactions affect patterns of phenotypic variation. And, until we understand the theory, it will not be evident whether or not the adaptive landscape is an adequate representation of the adaptive process that Wright envisioned.

The Greater Antillean ecomorphs are renowned for convergence of entire communities, with the same set of ecomorphs evolving repeatedly. The mainland, the Lesser Antilles, and the unique anoles of the Greater Antilles are primarily one of non-convergence, both internally and with the ecomorph radiations. This chapter examines the hypothesis that convergence among the Greater Antillean ecomorphs and non-convergence with the other anole faunas stems directly from similarities and differences in the adaptive landscapes they occupy. It first examines patterns of ecomorph occurrence and evolutionary diversification on species-poor islands in the West Indies to see if any general conclusions can be made about the anole adaptive landscape in the West Indies. The chapter then explores non-convergence in the Lesser Antilles, among the Greater Antillean unique anoles, and on the mainland, and explains why evolution may have gone in different directions in these areas.

Darwin's separation between adaptedness and existence entered into modern evolutionary theory at its root, in the population genetics work of Sewall Wright and J. B. S. Haldane. This chapter shows how the teleological aspect of Darwin's theory was translated into the mathematical language of population genetics, particularly by Sewall Wright. This teleology is exemplified by Wright's metaphor of the adaptive landscape; it is absent from R. A. Fisher's fundamental theorem. The chapter also examines the debate over genetic load, showing that the separation of adaptedness from existence is transferred to the mathematical theory most directly in the form of confusion between absolute and relative fitness.

Space and time represent two of the many dimensions specifying the scale of evolutionary change. Scale adds yet another intimidating level in attempts to thoroughly understand evolution, and even more so when merged with the complications associated with mechanics, function, and structure. Fortunately, abstract short-cuts to model evolution can be used. One effective way is to build so-called fitness-generating functions that incorporate, implicitly, many of the complex mappings embedded in the structure matrix. Fitness-generating functions (also called G-functions) are one solution to the problem of scale. This chapter shows that if the interest is micro-evolution, a G-function should be constructed to model the fitness of different alleles. If the interest is macro-evolution, the G-function should be expanded to include suites of strategy sets. Evolutionary interest should be allowed to be a sliding scale where the assumptions and simplifications that are made to answer one question at one point are different from those at another.

This chapter analyzes how the adaptive landscape concept can be extended from a single population in a single environment to multiple populations in multiple environments. Specifically, different environments produce different fitness peaks and divergent selection then drives different populations toward those different peaks. The chapter outlines methods for inferring adaptive divergence with respect to both phenotypes and fitness. It then turns to a review of empirical data informing several key questions about adaptive divergence in nature, including how prevalent and strong it is, how many peaks adaptive landscapes have, how predictable it is (parallel and convergent evolution), and what the role of sexual selection is in modifying adaptive divergence.

This chapter outlines how to conceptualize and predict adaptive evolution based on information about selection and genetic variation. It introduces and explains adaptive landscapes, a concept that has proven useful in guiding the understanding of evolution. The chapter also reviews empirical data to answer fundamental questions about adaptation in nature, including to what extent short- and long-term evolution is predictable, how fast is phenotypic change, to what extent is adaptation constrained by genetic variation, and how well adapted natural populations are to their local environments. Moving beyond selection and adaptation within populations, the chapter shows how eco-evolutionary dynamics will be shaped by biological diversity: that is, different populations and species have different effects on their environment.

This chapter focuses on the experimental researches on reverse evolution, and discusses adaptive landscape models, which provide a useful framework to quantify contingencies of evolutionary change. Studies that reveal general features of adaptive landscapes in the context of reverse evolution are also presented. The chapter furthermore discusses the genetic mechanisms of reverse evolution and effects of recombination on the likelihood of reverse evolution.

From the viewpoint of the correlated progression model of character change, a long evolving lineage experiences changes in many of its characters, associated with several, indeed in principle with all the parameters of the habitat. This implies that the lineage continually evolves adaptations to a compound ecological gradient comprising gradual change in all the parameters, and that can be envisaged as a ridge in a high-dimensional adaptive landscape. Such long-term, multidimensional ecological gradients are rare in nature, which is why the vast majority of evolving lineages are short, while extremely few achieve the status of new higher taxa. Examples of such ridges are the water-to-land transition associated with the origin of tetrapods and other higher taxa, the low-energy to high-energy life styles tracked by mammals and birds, and the shift to increasingly oxygenated seas in the Early Cambrian associated with the origin of invertebrate phyla.

Fitness maximization, or optimization, is a controversial idea in evolutionary biology. One classical formulation of this idea is that natural selection will tend to push a population up a peak in an adaptive landscape, as Sewall Wright first proposed. However, the hill-climbing property only obtains under particular conditions, and even then the ascent is not usually by the steepest route; this shows why it is misleading to assimilate the process of natural selection to a process of goal-directed choice. A different formulation of the idea of fitness-maximization is R. A. Fisher’s ‘fundamental theorem of natural selection’. However, the theorem points only to a weak sense in which selection is an optimizing process, for it requires that ‘environmental constancy’ be understood in a highly specific way. It does not vindicate the claim that natural selection has an intrinsic tendency to produce adaptation.

This chapter studies the three commonly recognized sources of divergent selection. These include the differences between environments, interactions between populations, and ecologically based sexual selection. The chapter focuses on cases in which divergent selection has been explicitly tested through direct measurements of selection or fitness in two environments. It concludes by considering interactions between the different sources of selection. It raises debates regarding the extent to which evolutionary divergence on adaptive landscapes proceeds through divergent selection on rugged landscapes versus drift along ridges of high fitness in holey landscapes. It also poses questions about the relative importance of each process, especially in terms of the likelihood that they generate reproductive isolation.

This chapter presents the concept of an evolutionary space or adaptive landscape and describes how the process of evolution by natural selection can be conceptualized as a process of hill-climbing on adaptive landscapes. It also describes other evolutionary spaces, including developmental and information spaces, as tools for thinking about the evolution of brain design.