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Bryan K Epperson

Publications and source records attributed to Bryan K Epperson.

4 recordsLinked to original sources

Mutation at high rates reduces spatial structure within populations.

The question of whether or not the high rates (mu) of mutation that occur for some hypervariable markers can affect commonly used empirical measures of spatial structure of genetic variation within populations is addressed. The results show that values of these measures are approximately halved when mu is 10(-2). Finest spatial-scale correlations, measured by either Moran's I-statistics or conditional kinship, are reduced by 30%-50%. When the mutation rate is 10 times lower, much smaller reductions result, e.g. averaging 7% for the finest scale correlations. Still smaller orders of magnitude of mu cause negligible changes in spatial structure, where any effects normally would not be detectable. The reductions are caused by forward mutations, and when the reductions are measured as percentages, they are nearly independent of the amount of structure produced sans mutation, except when dispersal is nearly minimal. The percent reductions are also nearly independent of the number of alleles and of back mutations, hence of the nature of the mutation process (e.g. stepwise or not). The results demonstrate that some hypervariable loci should have reduced spatial structuring, and that marker choice may affect the values observed in experimental surveys. Moreover, if fine-scale correlations are used to indirectly estimate dispersal distances, then mutation at high rates could inflate estimates, easily up to two- to three-fold.

Computer Simulation↗

Spatial and population genetic structure of microsatellites in white pine.

We evaluated the population genetic structure of seven microsatellite loci for old growth and second growth populations of eastern white pine (Pinus strobus). From each population, located within Hartwick Pines State Park, Grayling, Michigan, USA, 120-122 contiguous trees were sampled for genetic analysis. Within each population, genetic diversity was high and inbreeding low. When comparing these populations, there is a significant, but small (less than 1%), genetic divergence between populations. Spatial distance between populations or timber harvest at the second growth site were reasonable explanations for the observed minor differences in allele frequencies between populations. Spatial autocorrelation analysis suggested that, for the old growth population, weak positive structuring at 15 m fits the isolation by distance model for a neighbourhood size of about 100 individuals. In comparison, genotypes were randomly distributed in the second growth population. Thus, logging may have decreased spatial structuring at the second growth site, suggesting that management practices may be used to alter natural spatial patterns. In addition, the amount of autocorrelation in the old growth population appears to be lower for some of the microsatellites, suggesting higher numbers of rare alleles and that higher mutation rates may have directly affected spatial statistics by reducing structure.

Forestry↗

Covariances among join-count spatial autocorrelation measures.

Spatial distributions of biological variables are often well-characterized with pairwise measures of spatial autocorrelation. In this article, the probability theory for products and covariances of join-count spatial autocorrelation measures are developed for spatial distributions of multiple nominal (e.g. species or genotypes) types. This more fully describes the joint distributions of pairwise measures in spatial distributions of multiple (i.e. more than two) types. An example is given on how the covariances can be used for finding standard errors of weighted averages of join-counts in spatial autocorrelation analysis of more than two types, as is typical for genetic data for multiallelic loci.

Analysis of Variance↗

Genetic structure of age classes in Camellia japonica (Theaceae).

Camellia japonica L. (Theaceae), an insect- and bird-pollinated, broad-leaved evergreen tree, is widely distributed in Japan and the southern Korean peninsula. The species has a relatively even age distribution within populations, which may influence the spatial genetic structure of different age classes relative to species with typical L-shaped age distributions. To determine whether the internal spatial genetic structure found in seedlings and young individuals carries over into adults, we used allozyme loci, F-statistics, spatial autocorrelation statistics (Moran's I), and coancestry measures to examine changes in genetic structure among seven age classes in a population (60-m x 100-m area) in southern Korea. In seedlings, weak but significant positive values of Moran's I-statistics and coancestry measures were found for distances less than 14 m, which is consistent with a mechanism of limited seed dispersal combined with overlapping seed shadows. This spatial structure, however, dissipates in older age classes, and in adults genetic variation has an essentially random spatial distribution. Morisita's index of dispersion of individuals in each age class showed that seedlings and juveniles are more highly clustered than are older individuals. These results suggest that self-thinning changes the spatial relationships of individuals, and thus genotypes. A multilocus estimate of FST (0.008) shows a small but statistically significant difference in allele frequencies among age classes. In summary, intrapopulation genetic structure within and among age classes of C. japonica was significant but weak. Despite presumably limited seed dispersal, weak spatial genetic structure in juveniles suggests overlapping seed shadows followed by self-thinning during recruitment. The present study also demonstrates that studies of spatial genetic structure focusing on limited numbers of generations may not be sufficient to reveal the entire picture of genetic structure in populations with overlapping generations.

Electrophoresis↗