A test for deviation from island-model population structure

The neutral island model forms the basis for several estimation models that relate patterns of genetic structure to microevolutionary processes. Estimates of gene flow are often based on this model and may be biased when the model's assumptions are violated. An appropriate test for violations is to compare FST scores for individual loci to a null distribution based on the average FST taken over multiple loci. A parametric bootstrap method is described here based on Wright's beta-distribution to generate null distributions of FST for each locus. These null distributions account for error introduced by sampling populations, individuals and loci, and also biological sources of error, including variable alleles/locus and inbreeding. Confidence limits can be obtained directly from these distributions. Significant deviations from the island model may be the result of selection, deviations from the island model's migration pattern, nonequilibrium conditions, or other deviations from island-model assumptions. Only strong biases are likely to be detected because of the inherently large sampling variation of FST. Nevertheless, a coefficient, Nb, describing bias in the spread of the beta-distribution in units comparable to the gene flow parameter, Nm, can be obtained for each locus. In samples from populations of the butterfly Coenonympha tullia, the loci Idh-1, Mdh-1, Pgi and Pgm showed significantly lower FST than expected.     

A statistical theory for sampling species abundances

The pattern of species abundances is central to ecology. But direct measurements of species abundances at ecologically relevant scales are typically unfeasible. This limitation has motivated a long-standing interest in the relationship between the abundance distribution in a large, regional community and the distribution observed in a small sample from the community. Here, we develop a statistical sampling theory to describe how observed patterns of species abundances are influenced by the spatial distributions of populations. For a wide range of regional-scale abundance distributions we derive exact expressions for the sampled abundance distributions, as a function of sample size and the degree of conspecific spatial aggregation. We show that if populations are randomly distributed in space then the sampled and regional-scale species-abundance distribution typically have the same functional form: sampling can be expressed by a simple scaling relationship. In the case of aggregated spatial distributions, however, the shape of a sampled species-abundance distribution diverges from the regional-scale distribution. Conspecific aggregation results in sampled distributions that are skewed towards both rare and common species. We discuss our findings in light of recent results from neutral community theory, and in the context of estimating biodiversity.     

Range dynamics,rather than convergent selection,explain the mosaic distribution of red‐winged blackbird phenotypes

Geographic distributions of genetic and phenotypic characters can illuminate historical evolutionary processes. In particular, mosaic distributions of phenotypically similar populations can arise from parallel evolution or from irregular patterns of dispersal and colonization by divergent forms. Two phenotypically divergent forms of the red‐winged blackbird (Agelaius phoeniceus) show a mosaic phenotypic distribution, with a “bicolored” form occurring disjunctly in California and Mexico. We analyzed the relationships among these bicolored populations and neighboring typical populations, using ~600 bp of mitochondrial DNA sequence data and 10 nuclear short tandem repeat loci. We find that bicolored populations, although separated by ~3000 km, are genetically more similar to one other than they are to typical populations separated by ~400 km. We also find evidence of ongoing gene flow among populations, including some evidence of asymmetric gene flow. We conclude that the current distribution of bicolored forms represents incomplete speciation, where recent asymmetric hybridization with typical A. phoeniceus is dividing the range of a formerly widespread bicolored form. This hypothesis predicts that bicolored forms may suffer extinction by hybridization. Future work will use fine‐scaled geographical sampling and nuclear sequence data to test for hybrid origins of currently typical populations and to more precisely quantify the directionality of gene flow.     

Comparison of distance based density estimates for some arid rangeland vegetation

A method was required for determining the effect of management on extensive populations of trees and shrubs in central Australian rangelands. One useful indicator of change in these populations is the density of individuals, and there are several methods available based on distance measurement for density estimation. This study compared those procedures. Samples were drawn by computer from ground maps of actual plant distributions for Acacia aneura, Cassia nemophila and Atalaya hemiglauca and from a map generated at random. These samples were drawn to examine the properties of the nearest neighbour, point centred quarter, conditioned distance and compound T-square estimates of density. Samples were drawn by two methods: simple random sampling and semisystematic sampling. In general, there was a tendency for all estimators of density to underestimate the true density of naturally occurring populations with the compound T-square method (Byth 1982) being most robust. The compound T-square method was least biased but its variance increased for more aggregated spatial distributions. Estimates of density were not altered by the use of semisystematic sampling, when compared to simple random sampling. The spatial distributions examined in this study have not previously been studied as theoretical models. Acacia aneura and Cassia nemophila showed some aggregation of clusters, while the Atalaya hemiglauca showed a more extreme form of clustering due to its root suckering propagation.     

Public human microbiome data are dominated by highly developed countries

The importance of sampling from globally representative populations has been well established in human genomics. In human microbiome research, however, we lack a full understanding of the global distribution of sampling in research studies. This information is crucial to better understand global patterns of microbiome-associated diseases and to extend the health benefits of this research to all populations. Here, we analyze the country of origin of all 444,829 human microbiome samples that are available from the world’s 3 largest genomic data repositories, including the Sequence Read Archive (SRA). The samples are from 2,592 studies of 19 body sites, including 220,017 samples of the gut microbiome. We show that more than 71% of samples with a known origin come from Europe, the United States, and Canada, including 46.8% from the US alone, despite the country representing only 4.3% of the global population. We also find that central and southern Asia is the most underrepresented region: Countries such as India, Pakistan, and Bangladesh account for more than a quarter of the world population but make up only 1.8% of human microbiome samples. These results demonstrate a critical need to ensure more global representation of participants in microbiome studies.

The importance of sampling from globally representative populations has been well established in human genomics, but what about the microbiome? This study shows that metadata from almost half a million samples reveals worldwide human microbiome research is skewed heavily in favor of Europe and North America and excludes large but less developed nations in Asia and Africa.     

Distribution and abundance of parasite nematodes: ecological specialisation,phylogenetic constraint or simply epidemiology?

We investigate the patterns of abundance‐spatial occupancy relationships of adult parasite nematodes in mammal host populations (828 populations of nematodes from 66 different species of terrestrial mammals). A positive relationship between mean parasite abundance and host occupancy, i.e. prevalence, is found which suggests that local abundance is linked to spatial distribution across species. Moreover, the frequency distribution of the parasite prevalence is bimodal, which is consistent with a core‐satellite species distribution. In addition, a strong positive relationship between the abundance (log‐transformed) and its variance (log‐transformed) is observed, the distribution of worm abundance being lognormally distributed when abundance values have been corrected for host body size.
Hanski et al. proposed three distinct hypotheses, which might account for the positive relationship between abundance and prevalence in free and associated organisms: 1) ecological specialisation, 2) sampling artefact, and 3) metapopulation dynamics. In addition, Gaston and co‐workers listed five additional hypotheses. Four solutions were not applicable to our parasitological data due to the lack of relevant information in most host‐parasite studies. The fifth hypothesis, i.e. the confounded effects exerted by common history on observed patterns of parasite distributions, was considered using a phylogeny‐based comparison method. Testing the four possible hypotheses, we obtained the following results: 1) the variation of parasite distribution across host species is not due to phylogenetic confounding effects; 2) the positive relationship between mean abundance and prevalence of nematodes may not result from an ecological specialisation, i.e. host specificity, of these parasites; 3) both a positive abundance‐prevalence relationship and a negative coefficient of variation of abundance‐prevalence relationship are likely to occur which corroborates the sampling model developed by Hanski et al. We argue that demographic explanations may be of particular importance to explain the patterns of bimodality of prevalence when testing Monte‐Carlo simulations using epidemiological modelling frameworks, and when considering empirical findings. We conclude that both the bimodal distribution of parasite prevalence and the mean‐variance power function simply result from demographic and stochastic patterns (highlighted by the sampling model), which present compelling evidence that nematode parasite species might adjust their spatial distribution and burden in mammal hosts for simple epidemiological reasons.     

棉田蜘蛛混合种群空间格局分析及应用

1996年5月上旬至下旬,在山西运城地区临猗县,选择高水肥及中水肥棉田进行蜘蛛混合种群空间格局的调查分析。用经典频次法分析,大部分样本符合负二项分布,少数样本有多解和无解现象。9种聚集指标结果均符合聚集分布型,聚类分析结果表明,9种指标可按其性质分成3类。Iwao M~＃-m模型为M~＃=3.5151 1.4765 m,改进的M~＃-M模型为M~＃=2.6423 1.9587 m-0.0246 m~2,Taylor的幂法则式为S~2=22.089M~(2.6466),其结果均为聚集分布。应用以上分析结果,建立棉田蜘蛛混合种群调查的简化抽样方案。用零样出现的百分率来估计百株蜘蛛数量的指数回归式为:P_O=(0.6011/(0.6011 m)~(0.6011);用有蜘蛛的株率来估计百株蛛量,则用以下指数回归式:Y=256.52~(1.5345)。     

Long-term occurrence of hybrids between Japan Sea and Pacific Ocean forms of threespine stickleback, <Emphasis Type="Italic">Gasterosteus aculeatus</Emphasis>, in Hokkaido Island,Japan

The distribution patterns of two genetically divergent forms (Japan Sea and Pacific Ocean forms) of Gasterosteus aculeatus and their hybrids in the Hokkaido Island, Japan were investigated. Hybrid frequencies and the mating pattern of natural F1-hybrids and backcrosses, were examined by using allozyme analysis. The distribution patterns matched those previously reported. All three sympatric localities in eastern Hokkaido Island included hybrids between the two forms in each year examined. A low frequency of hybrids of sticklebacks has been maintained in areas of sympatry of the two forms in Hokkaido Island for several years. The proportion of F1-hybrids was significantly lower than expected by random mating in six samples from four sympatric populations, suggesting form-assortative mating. Mating crosses of natural F1-hybrids existed in both patterns. Natural F1-hybrids backcrossed more frequently with Pacific Ocean form than Japan Sea form. However, the proportions of backcross individuals in two of three samples were not significantly different from the expected proportions by random mating between F1-hybrids and their parent forms. In other samples, despite the Pacific Ocean form predominant in a population, F1-hybrid predominantly backcrossed with the Japan Sea form. These results support the hypothesis of gene flow from Pacific Ocean to Japan Sea forms.     

Using Museum Collections to Estimate Diversity Patterns along Geographical Gradients

Quantifying species-richness patterns along geographical gradients (typically latitude and elevation) has a long history in ecology and can be based on more-or-less complete censuses from a specified area (plot sampling), selective collection within a specified area (e.g. museum collections), or general information about species distributions (e.g. observations of extremes along the gradient, distribution maps). All these approaches require complete sampling to give the true richness in an area, but the richness pattern (i.e., the relative changes in richness along the gradient) may be estimated without complete sampling, although equal sampling between areas is necessary. This is relatively easy to do for fine-scale plot sampling, but rarely easy for other types of data. For data extracted from museum collections, a correct perception of the species richness pattern therefore depends on post-sampling treatment of data. Two commonly applied techniques for quantifying species richness patterns with these types of data are discussed, namely interpolation of species ranges and rarefaction. Such treatment may correct for unequal sampling in some instances, but may in other cases introduce artificial patterns. With incomplete sampling interpolation introduces an artificial humped pattern and rarefaction requires similar species abundance distributions to make unbiased comparisons among samples. One must therefore be cautious when applying these methods for estimating species richness patterns along geographical gradients.     

Optimal sampling and spatial distribution of Ixodes pacificus, Dermacentor occidentalis and Dermacentor variabilis ticks (Acari: Ixodidae)

A common method for sampling tick populations is flagging, which is a method of dragging a white cloth over a plant substrate for a fixed distance along a transect. Flagging over rough physical surfaces or using long subtransect lengths could lead to the underestimation of tick densities. Using estimates of the drop-off rates of adult Ixodes pacificus in flag sampling, optimal sampling schemes (the length and number of subtransects) were examined using the relationships between the tick drop-off rates (c), the tick density and distribution patterns and the roughness of the sampled plant substrate. It was found that the optimal number of subtransects and Lmax, the longest subtransect length which did not significantly underestimate the tick density from c, were affected by the tick density, substrate roughness and tick distribution pattern. This study also showed that the density and distribution of I. pacificus and Dermacentor occidentalis varied greatly over time in the populations sampled, while the Dermacentor variabilis densities were low and showed no significant changes over time. Both I. pacificus and D. occidentalis had clumped distributions along trails and these clumps were aggregated. However, the clump sizes (or individual clump areas) changed significantly over time because of density fluctuation or the movement of ticks. Finally, a positive association between the number of I. pacificus and D. occidentalis adults was observed from 2 m subtransect flag collections in March 1995; no relationship was found in 1994. © Rapid Science Ltd. 1998     

The influence of coarse‐scale environmental features on current and predicted future distributions of narrow‐range endemic crayfish populations

1. A major limitation to effective management of narrow‐range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2. Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate‐change scenarios. 3. The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 65–87% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4. Current models created using two spatial resolutions (1 and 4.5 km²) showed that fine‐resolution data more accurately represented current distributions. For three of the four species, the 1‐km² resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1‐km² resolution models were more accurate than 4.5‐km² resolution models. 5. Future projected (4.5‐km² resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low‐emission scenario, whereas two of four species would be severely restricted in range under moderate–high emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species‐distribution models. 6. These model predictions illustrate possible impacts of climate change on narrow‐range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.     

Performance of individual vs. group sampling for inferring dispersal under isolation‐by‐distance

Models of isolation‐by‐distance formalize the effects of genetic drift and gene flow in a spatial context where gene dispersal is spatially limited. These models have been used to show that, at an appropriate spatial scale, dispersal parameters can be inferred from the regression of genetic differentiation against geographic distance between sampling locations. This approach is compelling because it is relatively simple and robust and has rather low sampling requirements. In continuous populations, dispersal can be inferred from isolation‐by‐distance patterns using either individuals or groups as sampling units. Intrigued by empirical findings where individual samples seemed to provide more power, we used simulations to compare the performances of the two methods in a range of situations with different dispersal distributions. We found that sampling individuals provide more power in a range of dispersal conditions that is narrow but fits many realistic situations. These situations were characterized not only by the general steepness of isolation‐by‐distance but also by the intrinsic shape of the dispersal kernel. The performances of the two approaches are otherwise similar, suggesting that the choice of a sampling unit is globally less important than other settings such as a study's spatial scale.     

中华通草蛉卵、幼虫和成虫在麦田分布型的研究

研究了中华通草蛉卵、幼虫和成虫在麦田的分布型,均属聚集分布,分析提出适宜的取样调查方法,即双对象线或棋盘式10点,每点调查1m^2麦株。     

The MAD legacy: How meaningful is mean age-at-death in skeletal samples

This study examines the representativeness of palaeodemographic reconstructions from human skeletal remains. Mean age-at-death (MAD) is the primary statistic used in interpretations of changing patterns of health and well being from palaeodemographic analyses. A series of sampling experiments were conducted on three documented 19th century samples representing the total cemetery population from which skeletal samples could be drawn. Comparisons of the age-at-death distributions of simulated skeletal samples to the parent population were made to assess the relative magnitude of deviation associated with different types of bias (age, sex, temporal). From the examples presented, variability in age-at-death distribution is high in samples of less than 100, suggesting that for samples of less than 100analyzable individuals, it is probable that the mortality profiles constructed are not an accurate reflection of the cemetery. It is proposed that whateverprocess mean age-at-death reflects for past populations (fertility or mortality), is irrelevant if the sample on which the statistic is calculated is not representative of the population. Given that most cemetery samples will be subject, differentially, to biases at a variety of levels, comparative studies based on palaeodemographic data cannot be considered reliablewithout careful control for those biases. It is suggested that representativeness is the primary theoretical obstacle for researches to overcome, and that it is necessary to shift our focus to rigorously exploring those factors that bias our samples. Without some direct quantification of the representativeness of a sample, palaeodemographic estimators such as mean age-at-death are meaningless and any subsequent interpretations regarding the past, dubious at best.     

Apolipoprotein B signal peptide polymorphism distribution among south Amerindian populations

We report the distribution of the APOB signal peptide polymorphism in 5 native populations of South America: 2 samples of Mataco and 1 sample each of Pilagá and Toba from the Argentinian Chaco and 1 sample of Ache from the Paraguay forest. A randomly selected subsample of a previously studied sample from the Cayapa of Ecuador (Scacchi et al. 1997) was reanalyzed to investigate probable differences attributable to sampling, laboratory techniques, or interobserver error. The polymorphism observed in the signal peptide region of the APOB gene among native populations of South America exhibits the same range of variation found among geographic continental populations, confirming the high genetic heterogeneity of South Amerindians. Extremes in the allele prevalences were found among the Mataco and Ache, populations not far apart geographically. The small differences in genotype and allele frequencies between the subsample of the Cayapa analyzed here and the original Cayapa sample and between the 2 Mataco samples were not statistically significant and most likely were due to sampling error.     

Cytonuclear discordance across a leopard frog contact zone

We conducted a genetic analysis of the extent of hybridization within and outside a contact zone between two North American leopard frogs, Rana blairi and Rana pipiens by comparing distribution patterns of mitochondrial and nuclear haplotypes. The contact zone, located between South Dakota, Nebraska, and Iowa, USA, was previously examined using morphological data in the 1970s, leading to the conclusion that hybridization was rare between R. pipiens and R. blairi. Our genetic analysis of 51 populations (611 samples) shows strong cytonuclear discordance. Mitochondrial-haplotype distribution matches the same pattern as the documented species spatial distributions based on morphology. However, the geographic distribution of the nuclear haplotypes reveals asymmetrical swamping of the R. pipiens nuclear haplotypes by R. blairi haplotypes. Phylogenetic analyses of both mitochondrial and nuclear markers provide strong evidence for the presence of R. blairi-R. pipiens introgression for the nuclear marker. A pattern of mitochondrial isolation with nuclear introgression is extremely unusual, and predicted to occur much less often than the reverse.     

The Evolutionary History of the Rediscovered Austrian Population of the Giant Centipede Scolopendra cingulata Latreille 1829 (Chilopoda,Scolopendromorpha)

The thermophilous giant centipede Scolopendra cingulata is a voracious terrestrial predator, which uses its modified first leg pair and potent venom to capture prey. The highly variable species is the most common of the genus in Europe, occurring from Portugal in the west to Iran in the east. The northernmost occurrences are in Hungary and Romania, where it abides in small isolated fringe populations. We report the rediscovery of an isolated Austrian population of Scolopendra cingulata with the first explicit specimen records for more than 80 years and provide insights into the evolutionary history of the northernmost populations utilizing fragments of two mitochondrial genes, COI and 16S, comprising 1,155 base pairs. We test the previously proposed hypothesis of a speciation by distance scenario, which argued for a simple range expansion of the species from the southeast, via Romania, Hungary and finally to Austria, based on a comprehensive taxon sampling from seven countries, including the first European mainland samples. We argue that more complex patterns must have shaped the current distribution of S. cingulata and that the Austrian population should be viewed as an important biogeographical relict in a possible microrefugium. The unique haplotype of the Austrian population could constitute an important part of the species genetic diversity and we hope that this discovery will initiate protective measures not only for S. cingulata, but also for its habitat, since microrefugia are likely to host further rare thermophilous species. Furthermore, we take advantage of the unprecedented sampling to provide the first basic insights into the suitability of the COI fragment as a species identifying barcode within the centipede genus Scolopendra.     

Sampling Considerations for Disease Surveillance in Wildlife Populations

Abstract Disease surveillance in wildlife populations involves detecting the presence of a disease, characterizing its prevalence and spread, and subsequent monitoring. A probability sample of animals selected from the population and corresponding estimators of disease prevalence and detection provide estimates with quantifiable statistical properties, but this approach is rarely used. Although wildlife scientists often assume probability sampling and random disease distributions to calculate sample sizes, convenience samples (i.e., samples of readily available animals) are typically used, and disease distributions are rarely random. We demonstrate how landscape-based simulation can be used to explore properties of estimators from convenience samples in relation to probability samples. We used simulation methods to model what is known about the habitat preferences of the wildlife population, the disease distribution, and the potential biases of the convenience-sample approach. Using chronic wasting disease in free-ranging deer (Odocoileus virginianus) as a simple illustration, we show that using probability sample designs with appropriate estimators provides unbiased surveillance parameter estimates but that the selection bias and coverage errors associated with convenience samples can lead to biased and misleading results. We also suggest practical alternatives to convenience samples that mix probability and convenience sampling. For example, a sample of land areas can be selected using a probability design that oversamples areas with larger animal populations, followed by harvesting of individual animals within sampled areas using a convenience sampling method.     

Linking biodiversity patterns by autocorrelated random sampling

Biodiversity macroecology deals with the commonly measured variables of abundance, distribution, occupancy, and range size across two scales: the local (or α) and regional (γ). There are ca. 15 patterns consisting of the frequency distributions of the variables, variables as a function of area or sample size, and interrelationships between variables that appear to be very general if not close to universal. A number of links can be drawn between these patterns. In particular, I show that local communities can be seen as random samples of the regional pool, but only as a special form of sampling that is autocorrelated due to the spatial clumping of individuals within a species. I describe two distinct sets of mathematical machinery that can start with the regional species abundance distribution and then predict local species richness, local species abundance distributions, and β-diversity (in the form of species area relationships or decay of similarity with distance). I conclude by examining some of the implications of the fact that biodiversity patterns are linked by autocorrelated sampling.     

Stream insect occupancy-frequency patterns and metapopulation structure

An understanding of the distribution patterns of organisms and the underlying factors is a fundamental goal of ecology. One commonly applied approach to visualize these is the analysis of occupancy-frequency patterns. We used data sets describing stream insect distributions from different regions of North America to analyze occupancy-frequency patterns and assess the effects of spatial scale, sampling intensity, and taxonomic resolution on these patterns. Distributions were dominated by satellite taxa (those occurring in or=90% of sites) determined the overall modality of occupancy-frequency patterns. The proportions of satellite taxa increased with spatial scale and showed positive relationships with sampling intensity (r2=0.74-0.96). Furthermore, analyses of data sets from New York (USA) showed that generic-level assessments underestimated the satellite class and occasionally shifted occupancy-frequency distributions from unimodal to bimodal. Our results indicate that, regardless of species- or generic-level taxonomy, stream insect communities are characterized by satellite species and that the proportion of satellite species increases with spatial scale and sampling intensity. Thus, niche-based models of occupancy-frequency patterns better characterize stream insect communities than metapopulation models such as the core-satellite species hypothesis.