So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Both the magnitude and the urgency of the task of assessing global biodiversity require that we make the most of what we know through the use of estimation and extrapolation. Likewise, future biodiversity inventories need to be designed around the use of effective sampling and estimation procedures, especially for 'hyperdiverse' groups of terrestrial organisms, such as arthropods, nematodes, fungi, and microorganisms. The challenge of estimating patterns of species richness from samples can be separated into (i) the problem of estimating local species richness, and (ii) the problem of estimating the distinctness, or complementarity, of species assemblages. These concepts apply on a wide range of spatial, temporal, and functional scales. Local richness can be estimated by extrapolating species accumulation curves, fitting parametric distributions of relative abundance, or using non-parametric techniques based on the distribution of individuals among species or of species among samples. We present several of these methods and examine their effectiveness for an example data set. We present a simple measure of complementarity, with some biogeographic examples, and outline the difficult problem of estimating complementarity from samples. Finally, we discuss the importance of using 'reference' sites (or sub-sites) to assess the true richness and composition of species assemblages, to measure ecologically significant ratios between unrelated taxa, to measure taxon/sub-taxon (hierarchical) ratios, and to 'calibrate' standardized sampling methods. This information can then be applied to the rapid, approximate assessment of species richness and faunal or floral composition at 'comparative' sites.

Estimating Terrestrial Biodiversity through Extrapolation

In its simplest definition, a trait is a surrogate of organismal performance, and this meaning of the term has been used by evolutionists for a long time. Over the last three decades, developments in community and ecosystem ecology have forced the concept of trait beyond these original boundaries, and trait-based approaches are now widely used in studies ranging from the level of organisms to that of ecosystems. Despite some attempts to fix the terminology, especially in plant ecology, there is currently a high degree of confusion in the use, not only of the term "trait" itself, but also in the underlying concepts it refers to. We therefore give an unambiguous definition of plant trait, with a particular emphasis on functional trait. A hierarchical perspective is proposed, extending the "performance paradigm" to plant ecology. "Functional traits" are defined as morpho-physiophenological traits which impact fitness indirectly via their effects on growth, reproduction and survival, the three components of individual performance. We finally present an integrative framework explaining how changes in trait values due to environmental variations are translated into organismal performance, and how these changes may influence processes at higher organizational levels. We argue that this can be achieved by developing "integration functions" which can be grouped into functional response (community level) and effect (ecosystem level) algorithms.

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Let the concept of trait be functional

Studies of local adaptation provide important insights into the power of natural selection relative to gene flow and other evolutionary forces. They are a paradigm for testing evolutionary hypotheses about traits favoured by particular environmental factors. This paper is an attempt to summarize the conceptual framework for local adaptation studies. We first review theoretical work relevant for local adaptation. Then we discuss reciprocal transplant and common garden experiments designed to detect local adaptation in the pattern of deme · habitat interaction for fitness. Finally, we review research questions and approaches to studying the processes of local adaptation ‐ divergent natural selection, dispersal and gene flow, and other processes affecting adaptive differentiation of local demes. We advocate multifaceted approaches to the study of local adaptation, and stress the need for experiments explicitly addressing hypotheses about the role of particular ecological and genetic factors that promote or hinder local adaptation. Experimental evolution of replicated populations in controlled spatially heterogeneous environments allow direct tests of such hypotheses, and thus would be a valuable way to complement research on natural populations.

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Conceptual issues in local adaptation

Genetics and analysis of quantitative traits

Natural selection acts on phenotypes, regardless of their genetic basis, and produces immediate phenotypic effects within a generation that can be measured without recourse to principles of heredity or evolution. In contrast, evolutionary response to selection, the genetic change that occurs from one generation to the next, does depend on genetic variation. Animal and plant breeders routinely distinguish phenotypic selection from evolutionary response to selection (Mayo, 1980; Falconer, 1981). Upon making this critical distinction, emphasized by Haldane (1954), precise methods can be formulated for the measurement of phenotypic natural selection. Correlations between characters seriously complicate the measurement of phenotypic selection, because selection on a particular trait produces not only a direct effect on the distribution of that trait in a population, but also produces indirect effects on the distribution of correlated characters. The problem of character correlations has been largely ignored in current methods for measuring natural selection on quantitative traits. Selection has usually been treated as if it acted only on single characters (e.g., Haldane, 1954; Van Valen, 1965a; O'Donald, 1968, 1970; reviewed by Johnson, 1976 Ch. 7). This is obviously a tremendous oversimplification, since natural selection acts on many characters simultaneously and phenotypic correlations between traits are ubiquitous. In an important but neglected paper, Pearson (1903) showed that multivariate statistics could be used to disentangle the direct and indirect effects of selection to determine which traits in a correlated ensemble are the focus of direct selection. Here we extend and generalize Pearson's major results. The purpose of this paper is to derive measures of directional and stabilizing (or disruptive) selection on each of a set of phenotypically correlated characters. The analysis is retrospective, based on observed changes in the multivariate distribution of characters within a generation, not on the evolutionary response to selection. Nevertheless, the measures we propose have a close connection with equations for evolutionary change. Many other commonly used measures of the intensity of selection (such as selective mortality, change in mean fitness, variance in fitness, or estimates of particular forms of fitness functions) have little predictive value in relation to evolutionary change in quantitative traits. To demonstrate the utility of our approach, we analyze selection on four morphological characters in a population of pentatomid bugs during a brief period of high mortality. We also summarize a multivariate selection analysis on nine morphological characters of house sparrows caught in a severe winter storm, using the classic data of Bumpus (1899). Direct observations and measurements of natural selection serve to clarify one of the major factors of evolution. Critiques of the "adaptationist program" (Lewontin, 1978; Gould and Lewontin, 1979) stress that adaptation and selection are often invoked without strong supporting evidence. We suggest quantitative measurements of selection as the best alternative to the fabrication of adaptive scenarios. Our optimism that measurement can replace rhetorical claims for adaptation and selection is founded in the growing success of field workers in their efforts to measure major components of fitness in natural populations (e.g., Thornhill, 1976; Howard, 1979; Downhower and Brown, 1980; Boag and Grant, 1981; Clutton-Brock et

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1983.tb00236.x

The measurement of selection on correlated characters

Synopsis. Selection can be measured in natural populations by the changes it causes in the means, variances and covariances of phenotypic characters. Furthermore the force of selection can be measured in conventional statistical terms that also play a key role in theoreticai equations for evolutionary change. The problem of measuring selection on morphological traits is simplified by breaking the task into two parts: measurement of the effects of morphological variation on performance and measurement of the effects of performance on fitness. The first part can be pursued in the laboratory but the second part is best accomplished in the field. The approach is illustrated with a hypothetical analysis of selection acting on the complex trophic morphology of snakes.

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Morphology, Performance and Fitness

The aim of this paper is to illustrate an approach to the empirical measurement of selection that is directly related to formal evolutionary theory. Recent field studies have demonstrated that it is feasible to measure fitness in natural populations. The most successful studies have yielded accurate tallies of survivorship, mating success and fertility (e.g., Tinkle, 1965; Howard, 1979; Downhower and Brown, 1980; Lennington, 1980; Kluge, 1981; Clutton-Brock et al., 1982). Despite this success, no concensus has been reached on how to analyze the data and relate them to evolutionary theory. We present here a mode of data analysis that describes selection in useful, theoretical terms, so that field or experimental results will have a tangible relationship to equations for evolutionary change. Multivariate, polygenic theory (Lande, 1979, 1980, 1981; Bulmer, 1980) is particularly useful as a conceptual framework because it is concerned with the evolution of continuously distributed traits such as those commonly studied in laboratory and field situations. Multivariate equations have been used for many years by plant and animal breeders in order to impose selection and predict its impact (Smith, 1936; Hazel, 1943; Dickerson et al., 1954, 1974; Yamada, 1977), but this quantitative genetic theory has only recently been applied to evolutionary problems. Definitions and Aims. -It is critical to distinguish between selection and evolutionary response to selection (Fisher, 1930; Haldane, 1954). Selection causes observable changes within a generation in the means, variances and covariances of phenotypic distributions. Thus selection can be described in purely phenotypic terms without recourse to the inheritance of characters. In contrast, evolutionary response to selection, for example, the change in phenotypic mean from one generation to the next, certainly does depend on inheritance. In the following sections we show how knowledge of inheritance can be combined with purely phenotypic measures of selection to predict evolutionary response to selection. By distinguishing between selection and response to selection we can measure selection on characters whose mode of inheritance may be unknown and make prediction of evolutionary response a separate issue. Thus knowledge of inheritance is essential for complete

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1984.tb00344.x

On the measurement of natural and sexual selection: theory.

In this paper, we use measures of selection developed by quantitative geneticists and some new results (Arnold and Wade, 1984) to analyze multiple episodes of selection in natural populations of amphibians, reptiles, and insects. These examples show how different methods of data collection influence the potential for relating field observations to formal evolutionary theory. We adhere to the Darwinian tradition of distinguishing between natural and sexual selection (Darwin, 1859, 1871; Ghiselin, 1974). We view sexual selection as selection arising from variance in mating success and natural selection as arising from variance in other components of fitness. The justification for this formal distinction is developed by Wade (1979), Lande (1980), Wade and Arnold (1980), Arnold and Houck (1982) and Arnold (1 983 a). (We define mating success as the number of mates that bear progeny given survival of the mating organsim to sexual maturity. We do not equate mating success with mere copulatory success.) The utility of the distinction between sexual and natural selection is that the two forms of selection may often act in opposite directions on particular characters (Darwin, 1859, 1871). While we find the distinction between these two forms of selection useful, the difference is not crucial to our analysis. The essential point is that the recognition of selection episodes permits analysis of selection that may change in magnitude and direction during the life cycle. Defining Fitness Components. -The key first step in the analysis of data is to define multiplicative components of fitness so that selection can be partitioned into parts corresponding to these components or episodes of selection. Using an animal example, if the number of offspring zygotes is taken as total fitness, we can define the following components of fitness: viability (survivorship to sexual maturity), mating success (the number of mates) and fertility per mate (the average number of zygotes produced per mate). These components of fitness are defined so that their product gives total fitness. As a second example, consider the components of fitness in a plant in which yield (seeds/plant) is taken as the measure of total fitness (Primack and Antonovics, 1981). We might define the following components of fitness: number of stems per plant, average number of inflorescences per stem, average number of seed capsules per inflorescence, and average number of seeds per capsule. Again, these four fitness components are defined so that their product gives total fitness. We will need to measure each component of fitness and each character on each individual in order to partition selection into parts corresponding to the separate episodes of selection or to the separate components of fitness. Thus in the animal example, we need to measure the viability, mating success and fertility of each individual. With this accomplished we can estimate the separate forces of viability, sexual and fertility selection on each phenotypic character. In addition we can calculate the opportunities of selection corresponding to these three episodes and covariances between the different kinds of selection. In the plant example, we might begin with the intuition that larger plants have a greater yield. Using our methodology we can reword and extend this intuition. We can not only test the proposition of

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1984.tb00345.x

On the measurement of natural and sexual selection: applications.

Constraints on phenotypic evolution can take a variety of forms. Constraints can arise from inheritance, selection, development, and design limits. Contemporary visions of the evolutionary process often focus on one or two of these varieties and ignore the others. A unifying framework that considers all four major varieties of constraint is emerging within the discipline of quantitative genetics. I attempt to sketch that emerging framework and summarize recent efforts toward unification. Although couched in the technical language of quantitative genetics, the ongoing search for a common framework promises a rapprochement among the approaches of optimality theorists, population geneticists, and developmental biologists.

Stevan J. Arnold

Papers

The measurement of selection on correlated characters

Morphology, Performance and Fitness

On the measurement of natural and sexual selection: theory.

On the measurement of natural and sexual selection: applications.

Constraints on phenotypic evolution.