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PubMed2003

Estimating seed vs. pollen dispersal from spatial genetic structure in the common ash.

Spatial genetic structure was analysed with five highly polymorphic microsatellite loci in a Romanian population of common ash (Fraxinus excelsior L.), a wind-pollinated and wind-dispersed tree species occurring in mixed deciduous forests over almost all of Europe. Contributions of seed and pollen dispersal to total gene flow were investigated by analysing the pattern of decrease in kinship coefficients among pairs of individuals with geographical distance and comparing it with simulation results. Plots of kinship against the logarithm of distance were decomposed into a slope and a shape component. Simulations showed that the slope is informative about the global level of gene flow, in agreement with theoretical expectations, whereas the shape component was correlated with the relative importance of seed vs. pollen dispersal. Hence, our results indicate that insights into the relative contributions of seed and pollen dispersal to overall gene flow can be gained from details of the pattern of spatial genetic structure at biparentally inherited loci. In common ash, the slope provided an estimate of total gene dispersal in terms of Wright's neighbourhood size of Nb = 519 individuals. No precise estimate of seed vs. pollen flow could be obtained from the shape because of the stochasticity inherent to the data, but the parameter combinations that best fitted the data indicated restricted seed flow, sigmas pound 14 m, and moderate pollen flow, 70 m pound sigmap pound 140 m.

Computer Simulation↗

PubMed2003

Patterns of spatial genetic structuring in a hydropsychid caddisfly (Cheumatopsyche sp. AV1) from southeastern Australia.

We assessed levels of mitochondrial genetic spatial structuring in the hydropsychid caddisfly Cheumatopsyche sp. AV1 in southeastern New South Wales, Australia. No significant spatial structuring was detected within or between catchments using analysis of molecular variance, and nested clade contingency analysis suggested no strong relationship between haplotypes and geographical location, at any clade level. However, tests for association among haplotypes incorporating geographical distance in the nested clade analysis, revealed patterns of historical range expansion and recent restricted gene flow. Most likely, population fragmentation preceded range expansion, although subsequent recontact and gene flow among the previously sundered populations has apparently obscured the geographical signature of the former fragmentation. Taken together, our analyses suggest that a number of populations fragmented during the Pleistocene evolved in isolation for a time and subsequently expanded into secondary contact. Since expansion, there has apparently been substantial (albeit somewhat restricted) dispersal and gene flow of adult female Cheumatopsyche sp. AV1, throughout the study area.

Analysis of Variance↗

PubMed1991

On deriving spatial protein structure from NMR or X-ray diffraction data.

During the last decade it has become possible to derive the spatial structure of small proteins in solution using multidimensional NMR spectroscopy measurements and interpreting the data in terms of a chemical atomic model. The NMR experiments generate a set of interproton distance constraints, which is subsequently used to generate spatial structures that satisfy the experimental data. Correspondingly, crystallographic least-squares and molecular dynamics refinement is routinely applied to obtain a protein structure that is compatible with the observed structure factor amplitudes. The quality of the structure obtained will depend on the number and quality of the experimental data and on the searching power of the refinement method and protocol. The potential energy annealing conformational search (PEACS) algorithm is shown to be an improvement over standard molecular dynamics search methods. The use of time-dependent distance or structure factor restraints in molecular dynamics refinement yields a much better representation of experimental information than the fixed, static restraints which have generally been used until now. Conventional structure refinement methods lead to a too static and rigid picture of a protein in solution or in the crystalline state.

Algorithms↗

PubMed2005

Clonal and spatial genetic structures of aspen (Populus tremuloides Michx.).

To portray aspen clonal and spatial genetic structures, we mapped and genotyped trees in two 1-ha plots, each containing three aspen cohorts originating from fire or subsequent secondary disturbances. We used four microsatellite loci to identify aspen clones and increment core analysis to determine tree age. Clonal dimensions were measured by the maximum distance between two ramets and the number of ramets per genet. Standard normal deviate (SND) was used to assess the spatial distribution of aspen genets and cohorts, and multivariate spatial genetic autocorrelations to assess the spatial distribution of aspen genetic variation. Most aspen genets consisted of only one ramet (> 75%). Median clonal dimensions were 19 and 29 m (maxima: 104 and 72 m in the two plots). No segregation was observed between clones. Aspen cohorts were spatially segregated but trees were spatially aggregated within old and medium-aged cohorts. In contrast, trees were more randomly distributed within the youngest cohorts. This coincided with a spatial genetic autocorrelation at small scales (up to 30 m) in the older cohorts and a more random genetic distribution in the youngest ones. Our results suggest that aspen spatial genetic structuring reflects the spatial patterns produced by the regeneration of discrete cohorts at different stages of succession. Vegetative reproduction leads to aspen genetic spatial structuring at small scales (few metres) until midsuccession. However, as the stand gets older, the spatial distribution of aspen trees and genetic structure evolve from a structured pattern to a more random one under a gap disturbances regime.

Clone Cells↗

PubMed2001

Fine-scale spatial genetic structure of eight tropical tree species as analysed by RAPDs.

The fine-scale spatial genetic structure of eight tropical tree species (Chrysophyllum sanguinolentum, Carapa procera, Dicorynia guianensis, Eperua grandiflora, Moronobea coccinea, Symphonia globulifera, Virola michelii, Vouacapoua americana) was studied in populations that were part of a silvicultural trial in French Guiana. The species analysed have different spatial distribution, sexual system, pollen and seed dispersal agents, flowering phenology and environmental demands. The spatial position of trees and a RAPD data set for each species were combined using a multivariate genetic distance method to estimate spatial genetic structure. A significant spatial genetic structure was found for four of the eight species. In contrast to most observations in temperate forests, where spatial structure is not usually detected at distances greater than 50 m, significant genetic structure was found at distances up to 300 m. The relationships between spatial genetic structure and life history characteristics are discussed.

DNA, Plant↗

PubMed1992

Spatial and temporal contributions to the structure of spatial memory.

Three experiments investigated the effects of spatial and temporal contiguity in item recognition, location judgment, and distance estimation tasks. Ss learned the locations of object names in spatial arrays, which were divided into 2 regions. The names of locations were presented during map learning so that critical pairs appeared close in space and close in time, close in space but far in time, far in space but close in time, and far in space and far in time. Names primed each other in recognition only when they were neighbors in both space and time. In contrast, the effects of spatial and temporal contiguity in priming in location judgments were additive. Finally, temporal contiguity affected estimates of Euclidean distance when locations were close together, but not when they were far apart.

Adult↗

PubMed2001

Spatial population structure in a patchily distributed beetle.

The dynamics and evolution of populations will critically depend on their spatial structure. Hence, a recent emphasis on one particular type of structure--the metapopulation concept of Levins--can only be justified by empirical assessment of spatial population structures in a wide range of organisms. This paper focuses on Aphodius fossor, a dung beetle specialized on cattle pastures. An agricultural database was used to locate nearly 50 000 local populations of A. fossor in Finland. Several independent methods were then used to quantify key processes in this vast population system. Allozyme markers and mitochondrial DNA (mtDNA) sequences were applied to examine genetic differentiation of local populations and to derive indirect estimates of gene flow. These estimates were compared to values expected on the basis of direct observations of dispersing individuals and assessments of local effective population size. Molecular markers revealed striking genetic homogeneity in A. fossor. Differentiation was only evident in mtDNA haplotype frequencies between the isolated Aland islands and the Finnish mainland. Thus, indirect estimates of gene flow agreed with direct observations that local effective population size in A. fossor is large (hundreds of individuals), and that in each generation, a substantial fraction (approximately one-fifth) of the individuals move between populations. Large local population size, extreme haplotype diversity and a high regional incidence of A. fossor all testify against recurrent population turnover. Taken together, these results provide strong evidence that the whole mainland population of A. fossor is better described as one large 'patchy population', with substantial movement between relatively persistent local populations, than as a classical metapopulation.

Animals↗

PubMed1984

Spatial dissipative structures formed by spontaneous molecular aggregation at interfaces.

Interfacial processes as well as formation of dissipative structures have been suggested to play a key role in early pre-biotic evolutionary stages, mainly due to the ability of such processes to induce aggregation and spatial structuring. In this context we would like to draw attention to our recent findings regarding a remarkably wide collection of interfacial chemical reactions which form dissipative spatial structures. Three types of interfacial processes were found to yield this phenomenon: photochemical oxidations at liquid/air and liquid/liquid interfaces; gas/solution reactions; and reactions at membrane surfaces. The phenomenon we describe is the first major example of a network of chemical reactions that develop into macroscopic far-from-equilibrium concentration patterns.

Aniline Compounds↗

PubMed2005

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.

A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.

Analysis of Variance↗

PubMed1980

Human aging and spatial vision.

The ability to see spatial structures of a wide range of sizes was measured for two groups of observers (mean ages, 18 and 73 years). All observers had good visual acuity. Although older and younger observers did not differ in ability to see targets with fine structure (high spatial frequencies), older observers were only one-third as sensitive to targets with coarse structure (low spatial frequencies) as were younger observers or to changes in criterion. Older observers were also less able than younger observers to see moving targets. The reduced sensitivity of the older observers may adversely affect routine perceptual activities, such as face recognition and visually guided postural behavior, that depend upon low spatial frequencies.

Adult↗

PubMed1979

Spatial-temporal structure of coincident-timing responses.

The spatial temporal structure of coincident timing responses was investigated using an 86-cm movement from a microswitch to a barrier. The speed of the movement was monitored by a series of photocells placed at equal intervals along the movement line. Subjects (N = 24) watched a timer and attempted to displace the barrier at the precise moment that the timer sweep-hand reached a "target position" (250, 500, 1000 msec.) All subjects were given 100 trials of practice at a particular target position. The results indicate that rapid responses have similar spatial temporal structures but that this pattern is altered in slower movements.

Female↗

PubMed2005

The "Kriging" model of spatial genetic structure in human population genetics.

This paper presents the application of Kriging technique in the field of human population genetics for quantifying the spatial genetic heterogeneity of HLA-A locus in the area of China,and for mapping its spatial genetic structure using the measurement of synthetic genetic structure (SPC) and the principal components (PC). Both principles of the method and the basic equations are given. The Kriging model has several advantages over other interpolation and smoothing methods. Firstly, it relies on the structure of the spatial genetic semivariogram model, which can be used to quantify the spatial genetic heterogeneity of the locus (loci) before mapping its spatial genetic structure. Secondly, it is virtually unbiased in the interpolation situation,where the location to be estimated is surrounded by data on all sides and is influenced within the range of these data. Thirdly, it allows of estimative error of interpolation, which can be used to appraise the predicting effect for the spatial estimation,and the error maps can be used to decide where to introduce new sampling population genetic data. However, the "Kriging" model also has some disadvantages. Firstly,when the theoretical spatial genetic semivariogram can not be fitted by any models, the "Kriging" model can not be set up. Secondly, if the Kriging model was built by a poor spatial genetic semivariogram,the Kriging estimation standard deviation is remarkably high in the whole area, hence the Kriging model can not be suitable to estimating the distribution of spatial genetic structure. In these situations,the interpolation algorithm, whose assumption is spatial random rather than spatial autocorrelation,such as the Cavalli-Sforza method in Genography, inverse distance-weighted methods, splines, should be used to estimate or map the distribution of spatial genetic structure.

Genetics, Population↗

PubMed1998

Fine-scale spatial genetic structure with nonuniform distribution of individuals.

This paper presents the first theoretical study of spatial genetic structure within nonuniformly distributed continuous plant populations. A novel individual-based model of isolation by distance was constructed to simulate genetic evolution within such populations. We found larger values of spatial genetic autocorrelations in highly clumped populations than in uniformly distributed populations. Most of this difference was caused by differences in mean dispersal distances, but aggregation probably also produced a slight increase in spatial genetic structure. Using an appropriate level of approximation of the continuous distribution of individuals in space, we assessed the potential effects of density, seed and pollen dispersal, generation overlapping, and overdominance selection at an independent locus, on fine-scale genetic structure, by varying them separately in a few particular cases with extreme clumping. When selfing was allowed, all these input variables influenced both aggregation and spatial genetic structure. Most variations in spatial genetic structure were closely linked to variations in clumping and/or local density. When selfing was not allowed, spatial genetic structure was lower in most cases.

Biological Evolution↗

PubMed2005

Spatial genetic structure of two sympatric neotropical palms with contrasting life histories.

The spatial genetic structure within sympatric populations of two neotropical dioecious palm species with contrasting life histories was characterized to evaluate the influence of life history traits on the extent of genetic isolation by distance. Chamaedorea tepejilote is a common wind-pollinated arboreal understory palm. Chamaedorea elatior is an uncommon climbing subcanopy palm with entomophilous pollination syndrome. A total of 59 allozyme alleles for C. tepejilote and 53 alleles for C. elatior was analyzed using both unweighted (Iu) and weighted (Iw) Moran's I spatial autocorrelation statistics. The spatial genetic structure detected within these populations is consistent with those reported for highly dispersed plants. A significance test for differences between mean Moran's I-coefficients revealed less spatial genetic structure within the C. tepejilote population than that in the C. elatior population. Adjacent individuals of C. elatior exhibited significant spatial genetic autocorrelation (Iu=0.039, Iw=0.034), indicating a Wright's neighborhood size of about 100 individuals. For C. tepejilote, nonrandom genetic distribution among nearest neighbors was detected, even from small spatial autocorrelation values (Iu=0.008, Iw=0.009), consistent with a neighborhood size of about 300 individuals. For both species, seed dispersal, mortality among life cycle stages, overlapping generations, and contrasting traits of mating and reproduction influence the standing spatial genetic structure within populations.

Arecaceae↗

PubMed2002

In situ spatial patterns of soil bacterial populations, mapped at multiple scales, in an arable soil.

Very little is known about the spatial organization of soil microbes across scales that are relevant both to microbial function and to field-based processes. The spatial distributions of microbes and microbially mediated activity have a high intrinsic variability. This can present problems when trying to quantify the effects of disturbance, management practices, or climate change on soil microbial systems and attendant function. A spatial sampling regime was implemented in an arable field. Cores of undisturbed soil were sampled from a 3 x 3 x 0.9 m volume of soil (topsoil and subsoil) and a biological thin section, in which the in situ distribution of bacteria could be quantified, prepared from each core. Geostatistical analysis was used to quantify the nature of spatial structure from micrometers to meters and spatial point pattern analysis to test for deviations from complete spatial randomness of mapped bacteria. Spatial structure in the topsoil was only found at the microscale (micrometers), whereas evidence for nested scales of spatial structure was found in the subsoil (at the microscale, and at the centimeter to meter scale). Geostatistical ranges of spatial structure at the micro scale were greater in the topsoil and tended to decrease with depth in the subsoil. Evidence for spatial aggregation in bacteria was stronger in the topsoil and also decreased with depth in the subsoil, though extremely high degrees of aggregation were found at very short distances in the deep subsoil. The data suggest that factors that regulate the distribution of bacteria in the subsoil operate at two scales, in contrast to one scale in the topsoil, and that bacterial patches are larger and more prevalent in the topsoil.

Agriculture↗

PubMed1999

Spatial autocorrelation of cancer in Western Europe.

We applied the techniques of spatial autocorrelation (SA) analysis to 40 cancer mortality distributions in Western Europe. One of the aims of these methods is to describe the scale over which spatial patterns of mortalities occur, which may provide suggestions concerning the agents bringing about the patterns. We analyzed 355 registration areas, applying one- and two-dimensional SA as well as local SA techniques. We find that cancer mortalities are unusually strongly spatially structured, implying similar spatial structuring of the responsible agents. The small number of spatial patterns (4 or 5) in the 40 cancer mortalities suggests there are fewer spatially patterned agents than the number of cancers studied. SA present in variables will bias the results of conventional statistical tests applied to them. After correcting for such bias, some pairwise correlations of cancer mortality distributions remain significant, suggesting inherent, epidemiologically meaningful correlations. Local SA is a useful technique for exploring epidemiological maps. It found homogeneous high overall cancer mortalities in Denmark and homogeneous low mortalities in southern Italy, as well as a very heterogeneous pattern for ovarian cancer in Ireland.

Cluster Analysis↗

PubMed2005

Spatial genetic structure of two HIV-I-resistant polymorphisms (CCR2-64 I and SDF1-3'A) alleles in population of Shandong Province, China.

OBJECTIVE: To explore the spatial genetic structure of two HIV-I-resistant polymorphisms (CCR2-64 I and SDF1-3'A) alleles in the population of Shandong Province, China. METHODS: Using the techniques of spatial stratified sampling and spatial statistics, the spatial genetic structure of the locus (CCR2-64 I and SDF1-3'A), which was shown to be important co-receptor for HIV infection, was quantified from the populations of 36 sampled counties of Shandong Province, and a total of 3147 and 3172 samples were taken for testing CCR2-64I and SDF1-3'A respectively from individuals without known history of HIV-I infection and AIDS symptoms. RESULTS: There were significantly spatial genetic structures of the two alleles at different spatial distance classes on the scale of populations, but on the scale of individuals, no spatial structure was found in either the whole area of Shandong Province or the area of each sampled county. Although the change of frequencies of the two alleles with geographic locations in Shandong Province both showed gradual increase trends, their changing directions were inverse. The frequency of CCR2-64I allele gradually increased from the southwest to the northeast, while the frequency of SDF1-3'A allele gradually increased from the northeast to the southwest. However the RH to AIDS of combined types of their different genotypes did not represent obvious geographic diversity on the whole area of the Province. CONCLUSION: The frequency of allele usually has some spatial genetic structures or spatial autocorrelation with different spatial distance classes, but the genotypes of individuals have random distribution in the same geographic area. Evaluating spatial distribution of the genetic susceptibility of HIV (AIDS) to CCR2-64I and SDF1-3'A alleles, should focus on the frequencies of combined genotypes of CCR2 and SDF1 based on the two-locus genotypes of each individual rather than the frequencies of CCR2-64I and SDF1-3'A alleles.

Acquired Immunodeficiency Syndrome↗

PubMed2004

Spatial genetic structure in a metapopulation of the land snail Cepaea nemoralis (Gastropoda: Helicidae).

Habitat fragmentation is a major force affecting demography and genetic structure of wild populations, especially in agricultural landscapes. The land snail Cepaea nemoralis (L.) was selected to investigate the impact of habitat fragmentation on the spatial genetic structure of an organism with limited dispersal ability. Genetic and morphological patterns were investigated at a local scale of a 500 m transect and a mesoscale of 4 x 4 km in a fragmented agricultural landscape while accounting for variation in the landscape using least-cost models. Analysis of microsatellite loci using expected heterozygosity (HE), pairwise genetic distance (FST/1-FST) and spatial autocorrelograms (Moran's I) as well as shell characteristics revealed spatial structuring at both scales and provided evidence for a metapopulation structure. Genetic diversity was related to morphological diversity regardless of landscape properties. This pointed to bottlenecks caused by founder effects after (re)colonization. Our study suggests that metapopulation structure depended on both landscape features and the shape of the dispersal function. A range of genetic spatial autocorrelation up to 80 m at the local scale and up to 800 m at the mesoscale indicated leptokurtic dispersal patterns. The metapopulation dynamics of C. nemoralis resulted in a patchwork of interconnected, spatially structured subpopulations. They were shaped by gene flow which was affected by landscape features, the dispersal function and an increasing role of genetic drift with distance.

Animals↗