"Neighbourhood" size, dispersal and density estimates in the prickly forest skink (Gnypetoscincus queenslandiae) using individual genetic and demographic methods

Dispersal, or the amount of dispersion between an individual's birthplace and that of its offspring, is of great importance in population biology, behavioural ecology and conservation, however, obtaining direct estimates from field data on natural populations can be problematic. The prickly forest skink, Gnypetoscincus queenslandiae, is a rainforest endemic skink from the wet tropics of Australia. Because of its log-dwelling habits and lack of definite nesting sites, a demographic estimate of dispersal distance is difficult to obtain. Neighbourhood size, defined as 4piDsigma2 (where D is the population density and sigma2 the mean axial squared parent-offspring dispersal rate), dispersal and density were estimated directly and indirectly for this species using mark-recapture and microsatellite data, respectively, on lizards captured at a local geographical scale of 3 ha. Mark-recapture data gave a dispersal rate of 843 m2/generation (assuming a generation time of 6.5 years), a time-scaled density of 13 635 individuals * generation/km2 and, hence, a neighbourhood size of 144 individuals. A genetic method based on the multilocus (10 loci) microsatellite genotypes of individuals and their geographical location indicated that there is a significant isolation by distance pattern, and gave a neighbourhood size of 69 individuals, with a 95% confidence interval between 48 and 184. This translates into a dispersal rate of 404 m2/generation when using the mark-recapture density estimation, or an estimate of time-scaled population density of 6520 individuals * generation/km2 when using the mark-recapture dispersal rate estimate. The relationship between the two categories of neighbourhood size, dispersal and density estimates and reasons for any disparities are discussed.     

Population structure analysis using polygenic traits: estimation of migration matrices

Many studies of subdivided populations have attempted to determine the underlying migration rates that generate observed patterns of genetic differentiation. Most previous analyses have yielded only qualitative inferences about migration. In this paper I present a new method for estimating the full migration matrix from information on polygenic trait variation. The method employs multivariate quantitative genetic theory to provide a matrix formulation of the expected covariance structure in multigenerational subdivided populations for which information is available at different points in the life cycle. I develop a restricted maximum likelihood technique (REML) to take account of this additional life-cycle information and to estimate both the migration matrix and the ratio of effective population size to census size. To make the problem computationally tractable, the migration matrix is modeled as a log-linear function of a few covariates, such as subdivision size and geographic distance. I apply the technique to data on dermatoglyphic ridge counts for 1015 individuals of the Jirel population of east Nepal, considering two different age cohorts. In the adult cohort (individuals over 21 years of age) I examine data by both birthplace and residence and for the subadult cohort (under 21 years of age), by birthplace. Results from the REML technique reveal that the best-fitting migration model is a finite island model with an estimated endemicity of 0.730 +/- 0.105 and an estimated ratio of effective size to census size of 0.287 +/- 0.095. Both estimates are reasonable given known demographic data. In addition, Fst values predicted by the migration model are concordant with REML estimates obtained directly from the dermatoglyphic variation.     

An integrated framework for the inference of viral population history from reconstructed genealogies

We describe a unified set of methods for the inference of demographic history using genealogies reconstructed from gene sequence data. We introduce the skyline plot, a graphical, nonparametric estimate of demographic history. We discuss both maximum-likelihood parameter estimation and demographic hypothesis testing. Simulations are carried out to investigate the statistical properties of maximum-likelihood estimates of demographic parameters. The simulations reveal that (i) the performance of exponential growth model estimates is determined by a simple function of the true parameter values and (ii) under some conditions, estimates from reconstructed trees perform as well as estimates from perfect trees. We apply our methods to HIV-1 sequence data and find strong evidence that subtypes A and B have different demographic histories. We also provide the first (albeit tentative) genetic evidence for a recent decrease in the growth rate of subtype B.     

Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the ‘true’ cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the ‘true’ costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the ‘true’ scenario (cost distance Mantel correlations), but this ‘true’ scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the ‘true’ scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.     

Parentage analysis detects cryptic precapture dispersal in a philopatric rodent

Locating birthplaces using genetic parentage determination can increase the precision and accuracy with which animal dispersal patterns are established. We re-analyse patterns of movement away from the birthplace as a function of time, sex and population density for a sample of 303 banner-tailed kangaroo rats, Dipodomys spectabilis. We located birth sites using a combination of likelihood-based parentage analysis with live-trapping of mothers during the breeding season. The results demonstrate that natal-breeding site distances are density dependent in this species; in particular, both sexes emigrate earlier in the year, and females disperse farther than males, at low population densities. Banner-tailed kangaroo rats were chosen as a study system because live-trapping easily detects maternal and offspring locations; nevertheless, parentage analysis reveals that some offspring evade early detection and move substantial distances before their first capture. In a few cases, the approach even detects dispersal out of the natal 'deme' prior to first capture. Parentage analysis confirms the extreme philopatry of both sexes but indicates that prior estimates of median dispersal distance were too low. For D. spectabilis, more accurate location of individual birthplaces clarifies patterns of sex bias and density dependence in dispersal, and may resolve apparent discrepancies between direct and indirect estimates of dispersal distance. For species in which mothers can be more reliably trapped than juveniles, using offspring genotypes to locate parents is a novel way that genetic techniques can contribute to the analysis of animal dispersal.     

Spatial and geographic characteristics of marriage migration in the Lugansk population

Data from the Lugansk City Registry Office archives of 1960, 1985, 1990, and 2000 were used to calculate genetic demographic parameters characterizing marriage migration. The migration coefficients (m) in these years were 0.69, 0.54, 0.47, and 0.36; the endogamy indices were 12.1, 24.4, 30.5, and 43.2%, and the marriage contingency coefficients with respect to birthplace (K) were 0.12, 0.10, 0.11, and 0.13, respectively. The mean migration distance increased by a factor of 1.5 (from 599 to 870 km), and the mean parent-offspring distance decreased by a factor of 1.3 (from 415 to 317 km) during the period between 1960 and 2000. The mean marriage distance increased from 654 to 718 km between 1960 and 1985 and then decreased to 594 km by the year 2000. The proportion of "long-distance" migrations calculated using Malecot's model increased from 0.013 to 0.021 between 1960 and 1990 and decreased to 0.005 by 2000. The proportion of "short-distance" migrations was 0.77 in 1960 and 0.51 in 2000. The migration efficiency increased from 0.09 to 0.18 between 1960 and 1990 and decreased to 0.07 by 2000. In the years studied, the indices of isolation by distance (b) were 0.0005, 0.0004, 0.0005, and 0.0002, and the population "radii" were 90, 118, 119, and 168 km, respectively.     

Prediction model for sequence variation in the glycoprotein gene of infectious hematopoietic necrosis virus in California, U.S.A

The influence of spatio-temporal factors on genetic variation of infectious hematopoietic necrosis virus (IHNV) is an active area of research. Using host-isolate pairs collected from 1966 to 2004 for 237 IHNV isolates from California and southern Oregon, we examined genetic variation of the mid-G gene of IHNV that could be quantified across times and geographic locations. Information hypothesized to influence genetic variation was environmental and/or fish host demographic factors, viz. location (inland or coastal), year of isolation, habitat (river, lake, or hatchery), the agent factors of subgroup (LI or LII) and serotype (1, 2, or 3), and the host factors of fish age (juvenile or adult), sex (male or female), and season of spawning run (spring, fall, late fall, winter). Inverse distance weighting (IDW) was performed to create isopleth maps of the genetic distances of each subgroup. IDW maps showed that more genetic divergence was predicted for isolates found inland (for both subgroups: LI and LII) than for coastal watershed isolates. A mixed-effect beta regression with a logit link function was used to seek associations between genetic distances and hypothesized explanatory factors. The model that best described genetic distance contained the factors of location, year of isolation, and the interaction between location and year. Our model suggests that genetic distance was greater for isolates collected from 1966 to 2004 at inland locations than for isolates found in coastal watersheds during the same years. The agreement between the IDW and beta regression analyses quantitatively supports our conclusion that, during this time period, more genetic variation existed within subgroup LII in inland watersheds than within coastal LI isolates.     

Spatial characteristics of marriage migration in the Belgorod population

Data from marriage records of the city of Belgorod for 1960, 1985, and 1995 have been used to calculate parameters characterizing migration in the Belgorod population. The marriage migration coefficients (m) in these years were 0.83, 0.68, and 0.58, respectively, and the endogamy indices were 0.05, 0.13, and 0.22, respectively. The marriage convergence (K) with respect to birthplace in the same years were 0.15, 0.13, and 0.14, respectively. In the period studied, spatial parameters reflecting the genetic efficiency of migration increased. The mean migration distance also increased; it was 430, 667, and 926 km in 1960, 1985, and 1995, respectively. The migration distances for men and women in the same years were 477, 725, and 986 km and 383, 609, and 866 km, respectively. The radius of the Belgorod population in terms of Malecot's isolation by distance model increased in the period studied (55, 81, and 95 km in 1960, 1985, and 1995, respectively). The parameter b in that period decreased (0.00110, 0.00074, and 0.00062, respectively), which indicates a decrease in the inbred component. The increase in marital distance (590, 796, and 891 km in 1960, 1985, and 1995, respectively) indicates a steady increase in the outbred component of the population.     

Spatial and geographic characteristics of marriage migration in the Lugansk population

Data from the Lugansk City Registry Office archives of 1960, 1985, 1990, and 2000 were used to calculate genetic demographic parameters characterizing marriage migration. The migration coefficients (m) in these years were 0.69, 0.54, 0.47, and 0.36; the endogamy indices were 12.1, 24.4, 30.5, and 43.2%, and the marriage contingency coefficients with respect to birthplace (K) were 0.12, 0.10, 0.11, and 0.13, respectively. The mean migration distance increased by a factor of 1.5 (from 599 to 870 km), and the mean parent-offspring distance decreased by a factor of 1.3 (from 415 to 317 km) during the period between 1960 and 2000. The mean marriage distance increased from 654 to 718 km between 1960 and 1985 and then decreased to 594 km by the year 2000. The proportion of “long-distance” migrations calculated using Malecot’s model increased from 0.013 to 0.021 between 1960 and 1990 and decreased to 0.005 by 2000. The proportion of “short-distance” migrations was 0.77 in 1960 and 0.51 in 2000. The migration efficiency increased from 0.09 to 0.18 between 1960 and 1990 and decreased to 0.07 by 2000. In the years studied, the indices of isolation by distance (b) were 0.0005, 0.0004, 0.0005, and 0.0002, and the population “radii” were 90, 118, 119, and 168 km, respectively.     

Replication of linkage studies of complex traits: an examination of variation in location estimates.

In linkage studies, independent replication of positive findings is crucial in order to distinguish between true positives and false positives. Recently, the following question has arisen in linkage studies of complex traits: at what distance do we reject the hypothesis that two location estimates in a genomic region represent the same gene? Here we attempt to address this question. Sampling distributions for location estimates were constructed by computer simulation. The conditions for simulation were chosen to reflect features of "typical" complex traits, including incomplete penetrance, phenocopies, and genetic heterogeneity. Our findings, which bear on what is considered a replication in linkage studies of complex traits, suggest that, even with relatively large numbers of multiplex families, chance variation in the location estimate is substantial. In addition, we report evidence that, for the conditions studied here, the standard error of a location estimate is a function of the magnitude of the expected LOD score.     

Combining genetic, historical and geographical data to reconstruct the dynamics of bioinvasions: application to the cane toad Bufo marinus

We developed a spatially explicit model of a bioinvasion and used an approximate Bayesian computation (ABC) framework to make various inferences from a combination of genetic (microsatellite genotypes), historical (first observation dates) and geographical (spatial coordinates of introduction and sampled sites) information. Our method aims to discriminate between alternative introduction scenarios and to estimate posterior densities of demographically relevant parameters of the invasive process. The performance of our landscape-ABC method is assessed using simulated data sets differing in their information content (genetic and/or historical data). We apply our methodology to the recent introduction and spatial expansion of the cane toad, Bufo marinus, in northern Australia. We find that, at least in the context of cane toad invasion, historical data are more informative than genetic data for discriminating between introduction scenarios. However, the combination of historical and genetic data provides the most accurate estimates of demographic parameters. For the cane toad, we find some evidence for a strong bottleneck prior to introduction, a small initial number of founder individuals (about 15), a large population growth rate (about 400% per generation), a standard deviation of dispersal distance of 19 km per generation and a high invasion speed at equilibrium (50 km per year). Our approach strengthens the application of the ABC method to the field of bioinvasion by allowing statistical inferences to be made on the introduction and the spatial expansion dynamics of invasive species using a combination of various relevant sources of information.     

LOCATING EVOLUTIONARY PRECURSORS ON A PHYLOGENETIC TREE

Conspicuous innovations in the history of life are often preceded by more cryptic genetic and developmental precursors. In many cases, these appear to be associated with recurring origins of very similar traits in close relatives (parallelisms) or striking convergences separated by deep time (deep homologies). Although the phylogenetic distribution of gain and loss of traits hints strongly at the existence of such precursors, no models of trait evolution currently permit inference about their location on a tree. Here we develop a new stochastic model, which explicitly captures the dependency implied by a precursor and permits estimation of precursor locations. We apply it to the evolution of extrafloral nectaries (EFNs), an ecologically significant trait mediating a widespread mutualism between plants and ants. In legumes, a species‐rich clade with morphologically diverse EFNs, the precursor model fits the data on EFN occurrences significantly better than conventional models. The model generates explicit hypotheses about the phylogenetic location of hypothetical precursors, which may help guide future studies of molecular genetic pathways underlying nectary position, development, and function.     

Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm

MOTIVATION: To resolve the high-dimensionality of the genetic network inference problem in the S-system model, a problem decomposition strategy has been proposed. While this strategy certainly shows promise, it cannot provide a model readily applicable to the computational simulation of the genetic network when the given time-series data contain measurement noise. This is a significant limitation of the problem decomposition, given that our analysis and understanding of the genetic network depend on the computational simulation. RESULTS: We propose a new method for inferring S-system models of large-scale genetic networks. The proposed method is based on the problem decomposition strategy and a cooperative coevolutionary algorithm. As the subproblems divided by the problem decomposition strategy are solved simultaneously using the cooperative coevolutionary algorithm, the proposed method can be used to infer any S-system model ready for computational simulation. To verify the effectiveness of the proposed method, we apply it to two artificial genetic network inference problems. Finally, the proposed method is used to analyze the actual DNA microarray data.     

QUANTITATIVE GENETIC MODELING AND INFERENCE IN THE PRESENCE OF NONIGNORABLE MISSING DATA

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.     

The benefits of increasing the number of microsatellites utilized in genetic population studies: an empirical perspective

One of the key issues concerning the application of microsatellite DNA data in evolutionary studies is how the number of loci applied may influence the stability of genetic distances and corresponding phylograms. While computer simulations have suggested that over 30 microsatellites are required for accurate evolutionary inference, we show that a median of only six loci have been generally applied in studies of wild populations. Factors contributing to this contrast include: i) uncertainty regarding the potential benefits that can be gained from a realistic increase in the number of loci used; and ii) the lack of empirical studies assessing the influence of the number of microsatellites on the reliability of genetic distance estimation and phylogeny construction. In order to address these issues, we applied resampling techniques to microsatellite data in widely distributed populations of European grayling (Thymallus thymallus, Salmonidae). In agreement with expectations based on simulated data, we demonstrate empirically that the stability of commonly used genetic distances (DCE, DA and (deltamu)2) and the corresponding neighbor-joining phylograms is positively associated with the number of microsatellites utilized. For instance, increasing the number of loci from six to 17 resulted in a striking 75% increase in the proportion of DCE phylogram nodes supported by a bootstrap estimate of over 70%. Our results demonstrate that even moderately increasing the number of loci can be very beneficial--a finding extremely relevant for studies of natural populations for which optimally high microsatellite numbers are out of reach. Furthermore, the number of loci most commonly used to date may lead to erroneous inference of the evolutionary relationships between populations.     

Overground versus underground: a genetic insight into dispersal and abundance of the Cape dune mole‐rat

Molecular methods are commonly used to investigate cryptic populations that are difficult to locate or observe directly. The population dynamics of many subterranean organisms have been overlooked, at least in part, as a result of the absence of appropriate molecular markers. Recent studies in African mole‐rats have raised questions about the modes of dispersal and mate acquisition. In the present study, we apply a suite of 25 microsatellite markers to test the overground/underground dispersal hypotheses. Using these data, we also apply an approach to estimate population size and look for signal of demographic expansion or contraction. The genetic data suggest that the same breeding population extends between locations (approximately 50 km), with elevated inbreeding coefficients suggestive of some degree of isolation of the urban location. Low genetic differentiation between study sites supports the proposed high levels of vagility of dispersing individuals overground. We find a signal of long‐term population decline of Bathyergus suillus in this region. Their adherence to mesic conditions potentially recommends B. suillus to be of utility in monitoring the proposed climate‐induced desiccation of the Western Cape. Of potential interest is the discovery of a second divergent population at the rural location, with microsatellite data suggesting contemporary reproductive isolation and a mitochondrial divergence putatively dated at approximately 0.6 Mya. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, 110 , 890–897.     

Population homeostasis in sub-Saharan Africa

Global population growth remains one of the major challenges of the twenty-first century. This is particularly true for African countries which have been undergoing their demographic transitions. To investigate whether predicted increasing population density and urbanization can help to stabilize African population, we construct a database for 84 georeferenced Demographic and Health Survey (DHS) samples including 947,191 individuals in sub-Saharan Africa and match each location with gridded population density from NASA. We apply a proportional hazard model to evaluate the quantitative impact of local population density on the transitions from childlessness to motherhood, and from celibacy to marriage. Moving from the 5th to the 95th percentile of population density increases the median age at first birth by 2.2 years. This roughly decreases completed fertility by half a child. The same increase in population density increases the median age at first marriage by 3.3 years. These findings contribute to the understanding of why fertility has not dropped in Africa as fast as expected. One part of the answer is that population density remains low. Yet the total effect of increased density on fertility remains limited and counting on it to stabilize the population would be unrealistic.     

An attempt at the historical reconstruction of the genetic demographic structure of the Moscow population at the turn of the 20th century]

The genetic demographic structure of the Moscow population at the turn of the 20th century was studied based on the data from parish books and census records. The main sources of population gene pool replenishment were analyzed, and migration coefficients and the main parameters of the model of isolation by distance were estimated. Data on so-called quasigenetic markers (ethnicity and birthplace) were used to reveal intrapopulation heterogeneity, which facilitates the adaptation of migrants to a new ethnic and cultural environment. The spatial subdivision was analyzed with the use of GST statistics. Muscovites exhibited a considerable positive assortative mating with respect to birthplace. The results of this study provide the necessary historical perspective for predicting the current genetic demographic trends in the Moscow population. It was shown that the co-efficients of marriage migration were almost the same (0.7 < m < 0.8) in the late 19th and mid-20th centuries; however, these values were two times greater than in the late 20th century. This decrease in marriage migration was accompanied by a threefold increase in the radius of centripetal migration and a threefold decrease in the level of isolation by distance. It was determined that the increase in the ethnic and genetic diversity of the Moscow population in the 20th century had started in the 1860s.     

Combining capture–recapture data and pedigree information to assess heritability of demographic parameters in the wild

Quantitative genetic analyses have been increasingly used to estimate the genetic basis of life‐history traits in natural populations. Imperfect detection of individuals is inherent to studies that monitor populations in the wild, yet it is seldom accounted for by quantitative genetic studies, perhaps leading to flawed inference. To facilitate the inclusion of imperfect detection of individuals in such studies, we develop a method to estimate additive genetic variance and assess heritability for binary traits such as survival, using capture–recapture (CR) data. Our approach combines mixed‐effects CR models with a threshold model to incorporate discrete data in a standard ‘animal model’ approach. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data from a wild population of blue tits (Cyanistes caeruleus) and present the first estimate of heritability of adult survival in the wild. In agreement with the prediction that selection should deplete additive genetic variance in fitness, we found that survival had low heritability. Because the detection process is incorporated, capture–recapture animal models (CRAM) provide unbiased quantitative genetics analyses of longitudinal data collected in the wild.     

Biased estimators of quantitative trait locus heritability and location in interval mapping

In many empirical studies, it has been observed that genome scans yield biased estimates of heritability, as well as genetic effects. It is widely accepted that quantitative trait locus (QTL) mapping is a model selection procedure, and that the overestimation of genetic effects is the result of using the same data for model selection as estimation of parameters. There are two key steps in QTL modeling, each of which biases the estimation of genetic effects. First, test procedures are employed to select the regions of the genome for which there is significant evidence for the presence of QTL. Second, and most important for this demonstration, estimates of the genetic effects are reported only at the locations for which the evidence is maximal. We demonstrate that even when we know there is just one QTL present (ignoring the testing bias), and we use interval mapping to estimate its location and effect, the estimator of the effect will be biased. As evidence, we present results of simulations investigating the relative importance of the two sources of bias and the dependence of bias of heritability estimators on the true QTL heritability, sample size, and the length of the investigated part of the genome. Moreover, we present results of simulations demonstrating the skewness of the distribution of estimators of QTL locations and the resulting bias in estimation of location. We use computer simulations to investigate the dependence of this bias on the true QTL location, heritability, and the sample size.