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Habitual self-fertilization by hermaphroditic individuals is a sexual route by which genetically identical individuals can arise. The phenomenon occurs in various plants and invertebrates but is known in only one vertebrate species: the mangrove killifish. Selfing is an extreme form of inbreeding (even less severe cases of which often result in inbreeding depression), and for this and other reasons constitutive self-fertilization is rare in the biological world. Instead, most selfing species also outcross occasionally, and thus have a mixed mating system. Habitual selfers nevertheless have some special adaptive advantages not shared by their sexual counterparts. This chapter compares population-genetic and ecological features of mangrove killifish with those of analogous plants and invertebrate animals that likewise have mixed-mating systems. Such species probably gain the best of two worlds by capitalizing jointly on the short-term advantages of selfing (fertilization assurance, and the propagation of fit “clonal” genoypes) and also the long-term as well as short-term advantages of outcrossing (genetic health and adaptability).

This chapter focuses on Allee effects in relation to genetics and evolution. These topics intersect in four different ways. First, genetics creates its own set of Allee effect mechanisms (e.g., via inbreeding depression). Second, there may be genetic differences among members of a population in their susceptibility to ecological Allee effects. Third, Allee effects are considered in the light of evolution — have populations evolved mechanisms to avoid Allee effects, and if so, how is it possible to find anything other than the ‘ghosts of Allee effects past’ in modern populations? Finally, Allee effects themselves may act as a selection pressure, and members of populations subject to Allee effects may thus evolve different characteristics as compared with those bounded only by negative density dependence. The chapter considers all these four issues in turn.

Although much is known about the consequences of sexual abuse and the characteristics of the individuals and families involved, these pieces of information have yet to be arranged to form a clear picture of why sexual abuse occurs. This chapter provides an account of how an evolutionary computational framework can help organize what is currently known about sexual abuse and provide a set of answers to the question of why it happens. It focuses specifically on one component of our evolved psychology hypothesized to play a significant role in explaining why sexual abuse occurs: inbreeding avoidance mechanisms. Identifying the cues our evolved psychology uses to detect kin and generate sexual aversions towards them can help illuminate why sexual aversions fail to develop, leading, in some circumstances, to an increased risk of incest or sexual abuse within the family.

The guppy raises three different classes of conservation issues. First, the species is a useful model for freshwater fish species — one of the most endangered vertebrate groups. Second, although guppy populations are generally large and the species is widely distributed across Trinidad, some of the diversity that has provided such rich material for evolutionary biology is under threat from pollution, habitat loss, exotic introductions, and so on. Guppy populations are also potentially at risk from scientists who observe, collect, and manipulate guppy populations. Artificial introductions have proved very informative but may lead to irreversible changes in a river. Finally, introductions of guppies to countries outside their range, either for the control of malaria vectors, or through escapes of ornamental fish, can adversely affect vulnerable faunas. This chapter discusses these issues.

This chapter begins with a brief introduction to the focus of this book, which is the idea that extinction of species is somehow related to loss of genetic variation. Theoretical considerations suggest that small — that is, endangered — populations are different from large ones in two important aspects. The level of inbreeding is increased and likewise the importance of genetic drift, the stochastic loss of alleles, in shaping a population's genetic architecture is increased. Both these processes ultimately lead to loss of genetic variation. The chapter examines each of these arguments. It considers experimental studies that tested whether inbreeding and/or reduced levels of genetic variation leads to greater extinction risk. It shows that many studies of genetic causes for extinction seem to suggest that inbreeding depression is the main genetic problem in conservation biology. On the other hand, hardly any study has convincingly shown that reduced adaptability or fixation of mildly deleterious alleles have contributed to extinction. Thus, it seems prudent for conservation geneticists to focus on inbreeding and inbreeding depression.

This chapter outlines the theory of inbreeding including a brief account on the theory of population subdivision and gene flow. This is of relevance to conservation issues because habitat loss and fragmentation induces elevated levels of population structure in endangered species through reduced migration between remaining habitat fragments. Population structure is a major cause of inbreeding. The relationship between genetic diversity and fitness is discussed, covering the issues of inbreeding depression and heterosis.

In this chapter, Corey J. A. Bradshaw and Barry W. Brook, discuss measures of biodiversity patterns followed by an overview of experimental design and associated statistical paradigms. Conservation biology is a highly multidisciplinary science employing methods from ecology, Earth systems science, genetics, physiology, veterinary science, medicine, mathematics, climatology, anthropology, psychology, sociology, environmental policy, geography, political science, and resource management. Here we focus primarily on ecological methods and experimental design. It is impossible to census all species in an ecosystem, so many different measures exist to compare biodiversity: these include indices such as species richness, Simpson's diversity, Shannon's index and Brouillin's index. Many variants of these indices exist. The scale of biodiversity patterns is important to consider for biodiversity comparisons: α (local), β (between‐site), and γ (regional or continental) diversity. Often surrogate species ‐ the number, distribution or pattern of species in a particular taxon in a particular area thought to indicate a much wider array of taxa ‐ are required to simplify biodiversity assessments. Many similarity, dissimilarity, clustering, and multivariate techniques are available to compare biodiversity indices among sites. Conservation biology rarely uses completely manipulative experimental designs (although there are exceptions), with mensurative (based on existing environmental gradients) and observational studies dominating. Two main statistical paradigms exist for comparing biodiversity: null hypothesis testing and multiple working hypotheses – the latter paradigm is more consistent with the constraints typical of conservation data and so should be invoked when possible. Bayesian inferential methods generally provide more certainty when prior data exist. Large sample sizes, appropriate replication and randomization are cornerstone concepts in all conservation experiments. Simple relative abundance time series (sequential counts of individuals) can be used to infer more complex ecological mechanisms that permit the estimation of extinction risk, population trends, and intrinsic feedbacks. The risk of a species going extinct or becoming invasive can be predicted using cross‐taxonomic comparisons of life history traits. Population viability analyses are essential tools to estimate extinction risk over defined periods and under particular management interventions. Many methods exist to implement these, including count‐based, demographic, metapopulation, and genetic. Many tools exist to examine how genetics affects extinction risk, of which perhaps the measurement of inbreeding depression, gene flow among populations, and the loss of genetic diversity with habitat degradation are the most important.

Contemplate the descent of a piece of DNA (or RNA in organisms using this as their genetic material). The DNA is copied, and copies are passed to descendants. If the copies were error-free we could rightly think of them as perfect clones that pass down indefinitely through the eons. This logic led Richard Dawkins to speak of immortal coils in his book on selfish genes; here, it instead brings up issues of the common ancestry of genes and of individuals, and of the definition and consequences of inbreeding and outbreeding, the subjects of this chapter. When two individuals share one or more ancestor, they are relatives, both in common parlance and by technical definition in biology. The consequence of their mating is inbreeding, that is, the production of offspring receiving copies of a given gene through both mother and father that can be traced to the common ancestor(s). These gene copies are identical by descent (IBD; not to be confused with an acronym for inbreeding depression, see below), a shorthand for “identical by the fact of descending as copies of the same original piece of DNA”. The probability that two gene copies are IBD in a diploid individual, or its inbreeding coefficient, symbolized by f, is a simple function of the genetic relatedness of its parents and the segregation of genes during meiosis and gametogenesis. Because the probability is one-half that two gametes from the same individual carry identical gene copies, fertilization by self produces f of one-half, a brother-sister mating or parent-offspring mating produces f of one-quarter, a first-cousin mating produces f of one-sixteenth, and so on (see “Measurement of Inbreeding and Outbreeding,” below). In these examples, we assume that neither common ancestor(s) nor parents themselves are inbred; such inbreeding reflects additional common ancestry and so inflates f. From all of this, a definition of outbreeding as “mating of nonrelatives” follows automatically. As just defined, inbreeding and outbreeding rely on an absolute measure of relatedness. An alternative definition that may be of more value in real, finite populations (as opposed to ideal, infinite ones) is that inbreeding is mating with relatives more often than expected by chance, and outbreeding the opposite.

Inbreeding and its consequences are the main subject of Chapter 3, beginning with the concepts of identity by descent versus identity by state, the inbreeding coefficient F, genotype frequencies with inbreeding, and calculation of the inbreeding coefficient from pedigrees. Inbreeding and heterosis are discussed along with the effects of inbreeding in humans and other organisms, regular systems of mating (selfing and partial selfing, sib mating), and the utility of recombinant inbred lines. The chapter emphasizes the intimate connection between inbreeding and hierarchical population structure as measured by the F-statistics.

This chapter presents an overview of the development of medieval incest law, in relation to biblical teaching and Greco-Roman law. It raises questions about the rationale for a system of taboos that had become so complex by the early 13th century that to avoid hardship the number of prohibited degrees of relationship were drastically reduced by the Fourth Lateran Council in 1215. Various modern hypotheses about the medieval taboo are reviewed. Fear of inbreeding and deformity is rarely mentioned. What justified the inclusion of such distant relatives, and why the ban on in-laws and ‘spiritual incest’? How seriously did medieval people take these laws? Among the aristocracy, at least, they seem often to have been honoured in the breach. The practice of selling of dispensations to marry within the prohibited degrees was condemned by Luther, among others.

Incest seems an ever-present danger in medieval literature, although it can be absolved by repentance and grace. The genetic consequences of inbreeding are ignored: children of incest are usually heroic and beautiful (Adonis), with a few exceptions (Mordred). Medieval incest narratives are compared with Renaissance drama, where incest leads to many deaths and represents corruption in society, not individual sinfulness. The one exception to the taboo is the Virgin Mary, regularly described in medieval texts as the mother/sister/daughter/bride of Christ. Her ‘incest’ is necessary for Christian salvation; it happens only once, and is spiritual not sexual, a victory rather than a moral defeat. It is suggested that this trope may have developed as a response to the carnality of the pagan gods, and to the frequent accusations of sexual misbehaviour aimed at the early Christians. Medieval incest stories reflect a strong sense of human sinfulness, but incest is also a productive literary theme.

Population structure is a ubiquitous feature of natural populations that has an important influence on evolutionary change. In the real world, populations are not homogenous units; instead, they develop an internal structure, created by the physical properties of the environment and the biological characteristics of the species (such as dispersal ability). However, our basic ecological and population genetic models generally ignore population structure and focus on randomly mating (panmictic) populations. Such structure can profoundly change the evolution of a population. In fact, the myriad of influences that population structure exerts can only be hinted at in a single chapter. Since an exhaustive review is not possible, I will focus on presenting the conceptual issues linking mathematical models of population structure to empirical studies. To do this, it is useful to recognize two different kinds of population structure that both reflect and influence evolutionary change. The first is genetic structure. This is defined as the nonrandom distribution of genotypes in space and time. Thus, genetic structure reflects the genetic differences that develop among the different components of one or more populations. The second is what I will call proximity structure, defined by the size and composition of the group of neighbors that influence an individual’s fitness. Fitness is commonly influenced by local intraspecific interactions. Perhaps the most obvious example is competition. When individuals compete for some resource, they don’t usually compete equally with every other member of the population; in general, they compete only with a few of the most proximate individuals. These two forms of population structure, genetic structure and proximity structure, provide a foundation for understanding why we have shifted away from viewing populations as homogenous units. For good reason, this is a theme that is explored in many of the other chapters in this book. Genetic structure can develop within a population over a single generation, generally either as a result of local family associations or as a result of spatial variation in selection. For example, limited seed dispersal results in genetic correlations among neighbors even in the face of long-distance pollen movement, due to the clustering of maternal half sibs.

I have a Hardin cartoon on my office door. It shows a series of animals thinking about the meaning of life. In sequence, we see a lobe-finned fish, a salamander, a lizard, and a monkey, all thinking, “Eat, survive, reproduce; eat, survive, reproduce.” Then comes man: “What's it all about?” he wonders. Organisms live to reproduce. The ultimate selective pressure on any organism is to survive long enough and well enough to pass genetic material to a next generation that will also be successful in reproducing. In this sense, then, every morphological, physiological, biochemical, or behavioral adaptation contributes to reproductive success, making the field of life cycle evolution a very broad one indeed. Key components include mode of sexuality, age and size at first reproduction (Roff, this volume), number of reproductive episodes in a lifetime, offspring size (Messina and Fox, this volume), fecundity, the extent to which parents protect their offspring and how that protection is achieved, source of nutrition during development, survival to maturity, the consequences of shifts in any of these components, and the underlying mechanisms responsible for such shifts. Many of these issues are dealt with in other chapters. Here I focus exclusively on animals, and on a particularly widespread sort of life cycle that includes at least two ecologically distinct free-living stages. Such “complex life cycles” (Istock 1967) are especially common among amphibians and fishes (Hall and Wake 1999), and within most invertebrate groups, including insects (Gilbert and Frieden 1981), crustaceans, bivalves, gastropods, polychaete worms, echinoderms, bryozoans, and corals and other cnidarians (Thorson 1950). In such life cycles, the juvenile or adult stage is reached by metamorphosing from a preceding, free-living larval stage. In many species, metamorphosis involves a veritable revolution in morphology, ecology, behavior, and physiology, sometimes taking place in as little as a few minutes or a few hours. In addition to the issues already mentioned, key components of such complex life cycles include the timing of metamorphosis (i.e., when it occurs), the size at which larvae metamorphose, and the consequences of metamorphosing at particular times or at particular sizes. The potential advantages of including larval stages in the life history have been much discussed.

We recommend augmentation of gene flow for isolated population fragments that are suffering inbreeding and low genetic diversity, provided that proposed population crosses have low risks of outbreeding depression, and the predicted benefits justify the financial costs.

This chapter provides an overview of beaver dispersal. There are a number of reasons why beavers have to disperse from their native family. As a relatively long-lived species, beavers produce 3–4 newborns every year. If the young stay with their parents and siblings, the colony would grow huge in a few years and soon outstrip its food resources. More importantly, grown-up offpring must find mates to start reproducing themselves. Mating with close relatives would often result in disastrous genetic defects, a phenomenon called inbreeding depression. This chapter discusses the risks that come with dispersal and explains how natural dispersal differs from translocation and homing. It also considers the age at which beavers usually leave their family, along with the timing, direction, distance, and duration of dispersal.

It is assumed that dominance genetic variance contributes little to the prediction of evolutionary change in polygenic traits. This is based on the assumption that populations are large, panmictic, and randomly mating. However, the ecological contexts of most wild populations studied to date violate one, if not several, of these assumptions, and the widespread occurrence of inbreeding and inbreeding depression of phenotypic traits and fitness suggests dominance genetic effects are ubiquitous. This chapter reviews what genetic dominance represents at the level of a single locus and how this contributes to phenotypic variation and discusses how to estimate dominance variance with emphasis on the complications arising in wild populations and with inbreeding. Next, empirical estimates of dominance variance are reviewed. Since no estimates exist of dominance variance in the wild (except for humans), laboratory and agricultural populations are examined, and it is shown that dominance variance is a major contributor to phenotypic variation and in some cases contributes as much as additive genetic variance. This chapter also discusses how inbreeding and dominance affect predictions of evolutionary change, and ends with a review of some of the empirical questions for which genetic dominance is an important quantity in its own right. In this chapter, it is argued that dominance variance has been ignored for too long, may hamper the ability to predict evolutionary change, can be a major contributor to phenotypic variance, is interesting to study in its own right, and provides many avenues of research to be addressed by empirical study.

Understanding the allocation of energy is the goal of the evolutionary analysis of sex allocation. Whether one is concerned with the relative sizes of male and female flower parts in plants like those discussed by Campbell (1998), the ratio of males and females in insects like those discussed by Orzack et al. (1991), or the relative sizes of male and female reproductive organs in hermaphroditic fish like those discussed by Leonard (1993), one is concerned with how energy allocated toward reproduction is apportioned into one sex as opposed to the other (or more in the case of some kinds of organisms). Here, the sexes are entities that at regular or irregular intervals produce gametes, some of which come together to produce zygotes. The abstract nature of this description underscores the degree to which there are common evolutionary aspects to all of these problems, despite the fact that the biological details involved are so diverse. One of the most influential and important agendas for evolutionary studies of sex allocation was laid out by Charnov (1982). He described the underlying evolutionary similarities between phenomena as diverse as sex change in shrimp and sex ratio in vertebrates like us. Even more important, he promoted sex allocation as a central evolutionary problem by describing how seemingly unrelated allocation problems could all be analyzed with a kind of mathematical approach elaborated by Shaw and Mohler (1953). I consider in turn four important examples of this approach. Shaw and Mohler’s goal was to understand the evolution of the proportions of males and females. This problem of the sex ratio was most famously addressed by Darwin in his 1871 book, The Descent of Man, and Selection in Relation to Sex, as well as by others in the subsequent decades. The most influential analysis is that of Fisher (1930); however, Carl Düsing, who worked in the 1880s, can rightly be regarded as the progenitor of modern sex ratio theory (see Edwards 1998).