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The Siberian populations that expanded into the New World some 30 000–40 000 years BP grew numerically, diffused geographically, and eventually reached Tierra del Fuego at the tip of South America. The total number of descendants of the original migrants is a function of the ecological factors in the diverse regions of the Americas and the extractive efficiency of the cultures of residents of these regions. For example, the population densities of hunting and gathering societies were much lower than those of the agriculturalists. As a result, the population densities must have differed in the various regions of the New World, with the highest densities occurring in the Highlands of Central America and Peru, where intensive agriculture could maintain populations of large size. In contrast, the Sonoran or Californian deserts could not have sustained populations of hunters and gatherers with densities greater than a few individuals per square kilometer.
How many Amerindians and Eskimos did inhabit the New World in 1492? Estimates of the size of the population have varied from Dobyns'(1966) 90–112.5 million to Kroeber's (1939) 8.4 million. Dobyns based his numerical estimates upon the reconstructions of population sizes by region when they were at their lowest and then corrected these figures by a 20 : 1 or 25 : 1 depopulation ratio. Kroeber, on the other hand, utilized a tribe-by-tribe ‘dead reckoning’ method (developed by Mooney in 1910) gradually building up totals for each geographical region.
METHODS OF ESTIMATION
Douglas Ubelaker (1988) has summarized the various approaches used to estimate the size of the aboriginal population of North America.
In this final chapter the biomedical effects of acculturation and the accompanying changes in lifestyle of the Amerindians who survived the depopulation are considered. The interaction of culture change with the underlying genetics of native people provides a unique opportunity to assess and better understand the mechanisms involved in the etiology of complex diseases. In addition, research into unique Native American responses to various degenerative diseases may shed some light on the mechanisms of interactions between genetic and various environmental factors. The evolutionary consequences of increased genetic admixture between Amerindian populations (resulting from tribes with separate ethnohistories and geographic isolation being forced to coexist in newly created reservations) are also considered in this chapter. The massive infusion of genes from Africans and Europeans into Native American gene pool has undoubtedly altered the risks of diseases in admixed families.
The occupation of the Americas by peoples of Siberian ancestry for possibly 30 000–40 000 years was dramatically disrupted within the past 25 generations (500 years) by a violent collision between Old and New World cultures (see Crawford, 1992a, b). The consequences of this confrontation and the conquest that followed have been, and still are, devastating to the numerical balance that had existed between the environment and the Amerindian populations (see chapter 2). From a total Indian population perhaps approaching 44 million persons at contact, conquest and its numerous sequelae hammered the population down to fewer than 10 million at the nadir. Only recently has the surviving Amerindian population recovered and in some regions of the Americas, such as the Valley of Tlaxcala, begun to increase and perhaps even surpass its pre-Columbian levels (see chapter 2, Fig. 13).
Before we delve into the genetic variation observed in the contemporary native populations of the Americas, some causes of this phenomenon must be explored. It is highly unlikely that the patterns of variation observed in today's Amerindian populations resemble those that existed in pre-Columbian times. The present patterns of observed genetic variation are a result of a melange of factors. These are:
(1) The numbers and sizes of migrations (expansions) across Beringia. As discussed in chapter 1, there is considerable controversy as to the number of migrations or demic expansions, from Siberia to Alaska, which added genes to the populations of the Americas. What proportion of the genetic variation is due to the heterogeneity of the founding populations and what proportion is made in America? If the ancestral groups were small in size, then stochastic processes would have contributed much to the observed variation, especially if these groups were large in number.
(2) The continuation of gene flow into the Americas after the last glaciation. My fieldwork with the Eskimos of St. Lawrence Island and Wales, Alaska, revealed that despite the severest impediments to gene flow, such as political borders and hostile troop concentrations, contact between the Old and New Worlds continued. Up to World War II, Alaskan Eskimos crossed the winter ice pack into Siberia to obtain wives. It is my contention that social contacts persisted in the Norton Sound region between the Eskimo groups of both sides of the Bering Strait and that complete reproductive isolation between the Old and New Worlds is a myth.
The demography of human populations consists in part of their quantitative characteristics, including age/sex structure, size, fertility, mortality and migration patterns. The interrelations between fertility, mortality, emigration and immigration rates permit predictions of the numerical changes that a population may undergo during specific periods. For example, in reproductively closed populations such as species, the relative magnitudes of fertility versus mortality alone determine the size of the population. However, in most human populations it is the interaction of fertility and immigration versus mortality and emigration that determine the numerical trends in population size. This chapter considers the demographic structure of Amerindian populations both before European Contact and today. Given the broad scope of this volume, encompassing all of the indigenous peoples of the Americas and a heterogenous melange of populations of different sizes and subsistence patterns, it is not possible to reconstruct the demographic characteristics population by population. Instead, I shall endeavor to distill some of the common denominators of Amerindian populations. In addition, I shall present some examples that are particularly informative about the processes acting upon the demographic structures of these populations.
DEMOGRAPHY OF PRE-COLUMBIAN AMERINDIANS
The demographic characteristics of the populations of the Americas, prior to European contact, are often estimated from small amounts of information. There are no censuses or vital registers, both sources of data traditionally utilized by demographers. Instead, archeologists and biological anthropologists reconstruct the dynamics of prehistoric populations through the use of cultural artifacts, skeletal remains and the extrapolation of models derived from contemporary populations.
The history of physical (also known as biological) anthropology is intimately bound to the study of morphological traits and their uses in attempts to classify human races. Early physical anthropologists, such as F. Boas and A. Hooton, devoted much of their research energy to the collection of anthropometric data (body measurements) and anthroposcopic data (results of subjective grading of morphological characteristics that cannot be concisely measured) for the characterization of human races. Both the anthropometric and anthroposcopic traits have two distinct disadvantages in the study of human populations: (1) technical error (interobserver variation), which can be reduced to some degree in measurements and observations; and (2) ontogenetic changes in specific measurements, such as girth, height and weight. It is this ontological impermanence of measurements under changing environmental conditions that render anthropometries unsuitable for tracing long-term genetic relationships between the races. These problems associated with morphological traits are the major reasons that there was a ‘stampede’ by scientists to use the genetically based blood groups for evolutionary studies when methods for rapidly identifying these traits became available. The blood phenotypes remain unchanged throughout the life of the individual. Although there can be laboratory error associated with blood typing, this problem can be overcome by using independent determinations from two laboratories (Osborne, 1958). By the 1950s and 1960s, many American biological anthropologists had stopped utilizing anthropometric measurements in their studies of human population relationships.
The realization of the ecosensitivity (environmental responsiveness) of morphological traits shifted the use of these measurements from studies of race to those of processes of genetic–environmental interaction (Kaplan, 1954).
Like the histories – both biological and cultural – of the native peoples to whom this book is dedicated, the making of this book is a story of expansion and confrontation, admixture and adaptation, though, fortunately, on a gentler plain: the plain of science. My interests in the human biology of New World populations were originally stimulated by my association with the late Marshall T. Newman at the University of Washington. Bud, as he was known to his friends, joined the anthropology faculty there in 1966, as I was completing my final year of graduate studies. Although I never received any formal instruction from him, I did sit in on a number of his seminars, and, over the course of that year, we discussed many aspects of Amerindian biology.
The idea for this particular volume came into existence more than twenty years ago, at a dinner at Bud's house in Seattle. Although we had shared many interests and ideas, Bud and I had never published anything together, and, that night, we decided that we should begin work on a volume concerning the biology of the native populations of the New World. Unfortunately, this project never came to fruition, pushed to the back burner by the protracted illness and eventual death of Bud's wife, Judy, and last year by Bud's death.
The next stage in the evolution of this volume occured six years ago, when I was approached by the MAPFRE Foundation to write a volume on the physical anthropology of American Indians.
The variance effective size (Ne) was formulated for populations of monoecious plant species that are partly asexually propagating with discrete or overlapping generations. It was shown that partly asexually reproducing populations have larger or smaller effective sizes (ratios to the census size N) than fully sexually reproducing populations, according to whether the term Vc/c¯ is smaller or larger than the term (Vk/k¯+1−β)/2, where c¯ and Vc are the mean and variance of the number of progeny asexually produced per plant per year, respectively, k¯ and Vk are the mean and variance of the number of gametes contributed per plant per year, respectively, and β is the selfing rate of each plant. Asexual reproduction has no effect on Ne when the two terms are equal, as is true when the numbers of both sexually and asexually produced progeny per plant per year are Poisson-distributed (Vc/c¯=1 and Vk/k¯=1+β). Populations with a larger generation length (L) tend to have a smaller effective size: for a population model of age-independent survival and fecundity with an annual rate δ of asexual reproduction, Ne declines asymptotically to N(2−β)/{3−β+Vk/k¯+(2Vc/c¯−Vk/k¯−1+β).δ} as L gets large, which simplifies to N(2−β)/4 under a Poisson-distributed reproductive contribution. The trade-off relation of Ne and L, however, does not always hold: for stage-structured populations, increase in the survival rate of juveniles may act to increase both Ne and L.
Selective genotyping, i.e. increasing the size of the population phenotyped and genotyping only individuals from the high and low tails of the population, can considerably improve the efficiency of experiments aimed at detecting and locating quantitative trait loci (QTLs) affecting a single trait. In this paper we study how selective genotyping can increase the efficiency of multitrait QTL experiments. By selecting on an index combining the variables of interest and having the maximum correlation with each variable, the efficiency of QTL detection is increased for each trait. The efficiency of selective genotyping relative to random selection strongly depends on the correlation between the index and each variable. The optimum selection rate that minimizes costs for a given experimental power depends also on this correlation and on the genotyping costs relative to phenotyping costs. When the population segregating for the quantitative traits and the markers is not as simple as a backcross or an F2 population, but is composed of several connected or unconnected families, selective genotyping can be used to improve the efficiency of the QTL study. In this case, the extreme individuals should be selected within each family. A method is provided to choose the selection rates within each family in order to optimize the global power of the experiment when the family sizes are unequal.
The historical population genetic processes associated with the divergence of members of the Drosophila virilis species group were examined using DNA sequence variation from two loci. New data on DNA sequence variation from the oskar locus, taken from within and among all five closely related taxa in the virilis phylad of the D. virilis species group, were examined and compared with similar data previously collected from the period locus. Overall, the oskar and period data sets reveal similar patterns of variation. Both loci support the conclusion that the two subspecies of D. americana have had a large historical population size and are exchanging genes in nature. From these data there is little reason to consider them as distinct taxa. In the case of D. novamexicana, from which six lines were sequenced at each locus, there is an intriguing difference in the pattern seen at the two loci. Both loci reveal two distinct groups that are considerably divergent from each other, with very little evidence of gene flow between them. However, the grouping of lines into distinct subgroups based on oskar is different from the grouping based on period. The simplest explanation seems to be that D. novamexicana includes two distinct species, and that the sample of six lines happens to include cases of recent gene exchange. Alternatively, both oskar and period could be linked to sites of strong balancing selection and limited recombination.
Allozyme-associated heterosis has been repeatedly observed in marine bivalves, but its genetic origin remains debatable. A simple explanation is direct overdominance at the enzyme loci scored. An alternative is associative overdominance due to partial inbreeding, affecting the whole genome. The two hypotheses yield different predictions concerning (i) locus-specific effects, (ii) the relationship between heterozygosity and the variance in fitness, and (iii) the expected form of the relationship between the multilocus genotype and mean fitness. The relationship between heterozygosity and growth, a component of fitness, is here analysed in Spisula ovalis (1669 individuals, 9 loci), using statistical models designed to test these predictions. In contrast to most other bivalves, S. ovalis shells display clear annual growth lines allowing accurate quantification of individual age and growth. Our results show (i) that there is no evidence for locus-specific effects, (ii) that the variance in growth decreases significantly when heterozygosity increases, and (iii) that growth is better predicted by a genetic variable optimized for inbreeding than by a variable optimized for overdominance. In addition, the heterozygosity–growth relationship displays a significant variation among annual cohorts, being more pronounced in young cohorts. Although the need to pool alleles and the occurrence of null alleles may limit the efficiency of some of the models used (especially for result (iii)), our results suggest that the heterozygosity–growth relationship is due to inbreeding effects.
Linkage analysis and map construction using molecular markers is far more complicated in full-sib families of outbreeding plant species than in progenies derived from homozygous parents. Markers may vary in the number of segregating alleles. One or both parents may be heterozygous, markers may be dominant or codominant and usually the linkage phases of marker pairs are unknown. Because of these differences, marker pairs provide different amounts of information for the estimation of recombination frequencies and the linkage phases of the markers in the two parents, and usually these have to be estimated simultaneously. In this paper we present a complete overview of all possible configurations of marker pairs segregating in full-sib families. Maximum likelihood estimators for the recombination frequency and LOD score formulas are presented for all cases. Statistical properties of the estimators are studied analytically and by simulation. Specific problems of dominant markers, in particular with respect to the probability of detecting linkage, the probability of obtaining zero estimates, and the ability to distinguish linkage phase combinations, and consequences for mapping studies in outbred progenies are discussed.
Resistance to toxicants is a convenient model for investigating whether adaptive changes are associated with pleiotropic fitness costs. Despite the voluminous literature devoted to this subject, intraspecific comparisons among toxicant resistance genes are rare. We report here results on the pleiotropic effect on adult survival of Culex pipiens mutants involved in the same adaptation: the resistance to organophosphorus insecticides. This field study was performed in southern France where four resistance genes sequentially appeared and increased in frequency in response to intense insecticide control. By repeated sampling of overwintering females through winter, we analysed the impact of each of three resistance genes on adult survival. We showed that (i) the most recent gene seems to be of no disadvantage during winter, (ii) the oldest affects survival in some environmental conditions, and (iii) the third induces a constant, severe and dominant survival cost. Such variability is discussed in relation to the physiological changes involved in resistance.
Individual records from the coding of molecular polymorphism (molecular profiles) are particularly useful for the identification of clones or cultivars, in pedigree analysis, in the estimation of genetic distances and relatedness, and as a tool in genome mapping and population genetics. A parametric statistical analysis of molecular profile components can be infeasible because of the huge number of observed markers, the presence of missing values and the high number of parameters required to evaluate the importance of interactions among markers. Moreover, new powerful molecular techniques make possible the analysis of numerous markers at one time; therefore parametric statistical methods could result in troublesome models with more parameters than data. The field of computer-based techniques offers new strategies to cope with the complexity of molecular profiles. We suggest the use of a Genetic Classifier System to evaluate the importance of profile components. The procedure is based on a Genetic Algorithm approach, a numerical technique that simulates some features of the natural selection process to solve problems. A set of isozyme data from a Norway spruce population is analysed in order to assess their ability to predict the individual plant response to the presence of abiotic stresses. The results, obtained by three different computer simulations, show that this computer-based approach is particularly effective for ranking profile components according to their relevance. Genetic Classifier Systems could also be used as a preliminary step to reduce the complexity of molecular data sets.