The mind, the lab, and the field: Three kinds of populations in scientific practice

Tribolium beetles as a model system in evolution and ecology

Flour beetles of the genus Tribolium have been utilised as informative study systems for over a century and contributed to major advances across many fields. This review serves to highlight the significant historical contribution that Tribolium study systems have made to the fields of ecology and evolution, and to promote their use as contemporary research models. We review the broad range of studies employing Tribolium to make significant advances in ecology and evolution. We show that research using Tribolium beetles has contributed a substantial amount to evolutionary and ecological understanding, especially in the fields of population dynamics, reproduction and sexual selection, population and quantitative genetics, and behaviour, physiology and life history. We propose a number of future research opportunities using Tribolium, with particular focus on how their amenability to forward and reverse genetic manipulation may provide a valuable complement to other insect models.

Assessing the performance of qpAdm: a statistical tool for studying population admixture

qpAdm is a statistical tool for studying the ancestry of populations with histories that involve admixture between two or more source populations. Using qpAdm, it is possible to identify plausible models of admixture that fit the population history of a group of interest and to calculate the relative proportion of ancestry that can be ascribed to each source population in the model. Although qpAdm is widely used in studies of population history of human (and nonhuman) groups, relatively little has been done to assess its performance. We performed a simulation study to assess the behavior of qpAdm under various scenarios in order to identify areas of potential weakness and establish recommended best practices for use. We find that qpAdm is a robust tool that yields accurate results in many cases, including when data coverage is low, there are high rates of missing data or ancient DNA damage, or when diploid calls cannot be made. However, we caution against co-analyzing ancient and present-day data, the inclusion of an extremely large number of reference populations in a single model, and analyzing population histories involving extended periods of gene flow. We provide a user guide suggesting best practices for the use of qpAdm.

Models on the Runway: How Do We Make Replicas of the World?

Models are universal in science, both as theoretical formulations of reality and as model systems, representatives of other organisms. A recent paper on how scientists view the world divides our work into the mind, the lab, and the field and suggests that models must not be conflated with reality. But in practice, these distinctions are blurred. For example, are flour beetles a model system for other insects when their natural habitat is the same as the way they live in the lab? In addition, models can become restrictive when they are viewed as archetypes, making us overgeneralize about the world and ignoring meaningful variation. The study of sexual conflict in insects illustrates some of the pitfalls of relying on Drosophila as a model system for sexual selection. Microbes can be used as models for populations and communities and are essential parts of larger biological systems. Finally, some models are not meant to replicate the world but are worlds unto themselves in which diverse possibilities can be directly observed.

Like Hercules and the Hydra: Trade-offs and strategies in ecological model-building and experimental design

Experimental ecologists often invoke trade-offs to describe the constraints they encounter when choosing between alternative experimental designs, such as between laboratory, field, and natural experiments. In making these claims, they tend to rely on Richard Levins' analysis of trade-offs in theoretical model-building. But does Levins' framework apply to experiments? In this paper, I focus this question on one desideratum widely invoked in the modelling literature: generality. Using the case of generality, I assess whether Levins-style treatments of modelling provide workable resources for assessing trade-offs in experimental design. I argue that, of four strategies modellers employ to increase generality, only one may be unproblematically applied to experimental design. Furthermore, modelling desiderata do not have obvious correlates in experimental design, and when we define these desiderata in a way that seem consistent with ecologists' usage, the trade-off framework falls apart. I conclude that a Levins-inspired framework for modelling does not provide the content for a similar approach to experimental practice; this does not, however, mean that it cannot provide the form.

Putting humanity back into the teaching of human biology

In this paper, I draw upon debates about race in biology and philosophy as well as the concepts of ineliminable pluralism and psychological essentialism to outline the necessary subject matter knowledge that teachers should possess if they desire to: (i) increase student understanding of scientific research on genetic and behavioral variation in humans; and (ii) attenuate inegalitarian beliefs about race amongst students.

Thinking about populations and races in time

Biologists and philosophers have offered differing concepts of biological race. That is, they have offered different candidates for what a biological correlate of race might be; for example, races might be subspecies, clades, lineages, ecotypes, or genetic clusters. One thing that is striking about each of these proposals is that they all depend on a concept of population. Indeed, some authors have explicitly characterized races in terms of populations. However, including the concept of population into concepts of race raises three puzzles, all having to do with time. In this paper, I extend the causal interactionist population concept (CIPC) by introducing some simple assumptions about how to understand populations through time. These assumptions help to shed light on the three puzzles, and in the process show that if we want to understand races in terms of populations, we will need to revise our concept(s) of race.

Gould on Morton, Redux: What can the debate reveal about the limits of data?

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.'s thesis that Morton was "right." We maintain that Gould was right to reject Morton's analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the "populations" in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.

A reconsideration of the role of self-identified races in epidemiology and biomedical research

A considerable number of studies in epidemiology and biomedicine investigate the etiology of complex diseases by considering (self-identified) race as a relevant variable and focusing on the differences in risk among racial groups in the United States; they extensively draw on a genetic hypothesis--viz. the hypothesis that differences in the risk of complex diseases among racial groups are largely due to genetic differences covarying with genetic ancestry--that appears highly problematic in the light of both current biological evidence and the theory of human genome evolution. Is this reason for dismissing self-identified races? No. An alternative promising use of self-identified races exists, and ironically is suggested by those studies that investigate the etiology of complex diseases without focusing on racial differences. These studies provide a large amount of empirical evidence supporting the primacy of the contribution of non-genetic as opposed to genetic factors to the risk of complex diseases. We show that differences in race--or, better, in racial self-identification--may be critically used as proxies for differences in risk-related exposomes and epigenomes in the context of the United States. Self-identified race is what we need to capture the complexity of the effects of present and past racism on people's health and investigate risk-related external and internal exposures, gene-environment interactions, and epigenetic events. In fact patterns of racial self-identifications on one side, and patterns of risk-related exposomes and epigenomes on the other side, constantly coevolve and tend to match each other. However, there is no guarantee that using self-identified races in epidemiology and biomedical research will be beneficial all things considered: special attention must be paid at balancing positive and negative consequences.

Philosophy of race meets population genetics

In this paper, I respond to four common semantic and metaphysical objections that philosophers of race have launched at scholars who interpret recent human genetic clustering results in population genetics as evidence for biological racial realism. I call these objections 'the discreteness objection', 'the visibility objection', 'the very important objection', and 'the objectively real objection.' After motivating each objection, I show that each one stems from implausible philosophical assumptions about the relevant meaning of 'race' or the nature of biological racial realism. In order to be constructive, I end by offering some advice for how we can productively critique attempts to defend biological racial realism based on recent human genetic clustering results. I also offer a clarification of the relevant human-population genetic research.