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Urban environments represent globally replicated, large-scale disturbances to the landscape, providing an ideal opportunity to study parallel evolution in natural populations on a large scale. In recent years, there has been a rapid increase in the number of studies investigating evolutionary responses of a diverse range of taxa across multiple cities. Although parallel evolutionary responses across independent urban environments will depend on the extent to which urban environments converge on similar biotic and abiotic environments, the extent to which cities are environmentally similar has not yet fully been integrated into studies of urban evolution. This chapter begins by asking: Do species display parallel evolutionary responses across independent urban environments? It then briefly reviews a subset of the environmental factors that have driven parallel responses to cities (heat islands, pollution, and habitat fragmentation) and discusses some of the potential causes of non-parallelism. Finally, it ends with practical considerations for the design of future studies aiming to examine parallel evolutionary responses to urbanization. Understanding the shared and unique features of urban environments and identifying parallel species responses to rapid and ongoing urban development will provide important insight into the ubiquity of parallel evolution in nature.

This chapter describes Charles Darwin’s theory as it related to brain evolution and gods. It then provides basic information about human brains and the nature of the research evidence used for this book. Finally, it explains parallel evolution, a key concept for the book.

This chapter introduces the concept of convergent evolution. It shows that parallel evolution is simply a special case of convergent evolution, and addresses the action of both functional and developmental constraints in the evolutionary process. The functional and developmental constraints that have led in convergent evolution at every level of life are described throughout the book, from the external forms of living organisms down to the very molecules from which they are constructed, from their ecological roles in nature to the way in which their minds function.

Chapter 9 discusses conceptual issues in protein evolution and provides a synthesis of lessons learned from studies of hemoglobin function. Using hemoglobin as a model molecule, we can exploit an unparalleled base of knowledge about structure-function relationships and we can characterize biophysical mechanisms of molecular adaptation at atomic resolution. It is therefore possible to document causal connections between genotype and biochemical phenotype at an unsurpassed level of rigor and detail. Moreover, since the oxygenation properties of hemoglobin provide a direct link between ambient O₂ availability and aerobic metabolism, genetically based changes in protein function can be related to ecologically relevant aspects of organismal physiology. We therefore have a solid theoretical framework for making predictions and for interpreting observed associations between biochemical phenotype and fitness-related measures of whole-animal physiological performance. The chapter explores case studies that illustrate how experimental research on functional properties of a well-chosen model protein can be used to address some of the most conceptually expansive questions in evolutionary biology: Is genetic adaptation predictable? Why does evolution follow some pathways rather than others?

Chapter 8 provides the formal basis to recognize biases in the introduction of variation as a cause of evolutionary biases. The shifting-gene-frequencies theory of the Modern Synthesis posits a “buffet” view in which evolution is merely a process of shifting the frequencies of pre-existing alleles, without new mutations. Within this theory, mutation is represented like selection or drift, as a “force” that shifts frequencies. Yet, within a broader conception of evolution, a second kind of causal process is required: an introduction process that can shift a frequency upwards from 0, which selection and drift cannot do. Abstract models demonstrate the influence of biases in the introduction process in one-step and multi-step adaptive walks. Such biases do not require mutation biases per se, but may arise from effects of development, and from the differential accessibility of alternative forms in abstract possibility-spaces.

Homology—similarity due to common descent—is the cornerstone of comparative evolutionary research. Wake (1994) calls it “the central concept for all of biology”. Yet homology, like “fitness” or “species,” is an elusive concept. There is unceasing debate within evolutionary biology regarding its meaning and use. Combinatorial evolution and the extensive recurrence of similar traits revealed by modern phylogenetic study (see chapter 19) compel biologists to reconsider many ideas about homology. This is already becoming apparent in recent discussions of homology in relation to developmental variation (e.g., Wagner, 1989a,b; Hall, 1994). The traditional idea of homology visualizes a linear series of changes whereby an ancestral trait has been transformed into a descendent one (see discussion by Cartmill, 1994). By this idea different homologues may appear differently modified on different phylogenetic branches, but each descendant homologous trait has at its core a single ancestral trait. If two characters are homologous, that means that each is the modified descendant of a single ancestral trait of a shared common ancestor, and characters can be homologized in simple two-member pairs. Combinatorial evolution raises the possibility that derived traits may often contain elements of more than one ancestral trait, and that what was formerly seen as a de novo modification actually involves the recombined expression of preexisting traits. Homology may involve not just different degrees of similarity, due to divergent modification, but may be “mixed.” The maize ear, for example, combines features of both male and female ancestral inflorescences (see chapter 15), and the insect head evolved by the fusion of six ancestral body segments (Kukalova-Peck, 1997). Tracing mixed homologies requires separately homologizing pairs or series of ancestral and derived states for different elements of the same descendent trait, not just lineal comparisons focusing on the modifications of a single ancestral form. Other problems are raised for the homology concept by the fact that “the same” feature may be conserved via different developmental pathways, and by the frequent and evolutionarily important occurrence of duplication and modification (see chapter 8, on duplication), producing “serial” or “iterative” homology (“homonomy”) and positional shifts (see chapter 12, on heterotopy) of similar and historically related structures (for discussions of these problems, see Roth, 1984, 1988).

Research in urban evolution requires that the features of cities are accurately captured for input into evolutionary models. Until recently, the evolutionary effects of cities have often been addressed using single sites, dichotomous urban–rural contrasts or, to a lesser extent, using urban gradients. However, urbanization does not produce a homogenous spatial continuum: cities are highly heterogeneous environments, with sharp and often non-linear environmental changes related to the amount of impervious surface, green vegetation, air pollution, light, noise, or contrasted temperature profiles. The comprehensive quantification of urban heterogeneity in space and time is essential for exploring the origins of organismal variation and adaptation in cities, and to best identify the strength and directionality of selective pressures and neutral processes occurring in populations of urban organisms. This chapter reviews frameworks that can be used to describe and quantify urbanization—these include classical ecological frameworks, the understudied temporal dimension of urban evolutionary biology, and the concept of replicated insight into urban-driven evolutionary processes. The chapter further discusses how axes of variation capturing the urban environment can be quantified with univariate and multivariate approaches, and presents quantitative results on how urbanization is captured in published studies of urban evolution. Finally, it discusses study design and statistical approaches of interest when testing for urban evolution: these include the question of model selection and variable fitting, spatial autocorrelation, and appropriate scale use in studies of urban evolution.