Negative density-dependent dispersal in the American black bear (Ursus americanus) revealed by noninvasive sampling and genotyping

Although the dispersal of animals is influenced by a variety of factors, few studies have used a condition-dependent approach to assess it. The mechanisms underlying dispersal are thus poorly known in many species, especially in large mammals. We used 10 microsatellite loci to examine population density effects on sex-specific dispersal behavior in the American black bear, Ursus americanus. We tested whether dispersal increases with population density in both sexes. Fine-scale genetic structure was investigated in each of four sampling areas using Mantel tests and spatial autocorrelation analyses. Our results revealed male-biased dispersal pattern in low-density areas. As population density increased, females appeared to exhibit philopatry at smaller scales. Fine-scale genetic structure for males at higher densities may indicate reduced dispersal distances and delayed dispersal by subadults.

Genetic diversity in different populations of sloths assessed by DNA fingerprinting

In this study we analyzed a population of Bradypus torquatus with individuals originally distributed in different localities of Bahia, and two populations of B. variegatus with individuals from Bahia and São Paulo States. Using the DNA fingerprinting method, we assessed the genetic variability within and between populations. Analysis of the DNA profiles revealed genetic similarity indices ranging from 0.34 +/- 0.07 to 0.87 +/- 0.04. Similar low levels of genetic variability were found only in isolated mammalian populations or among related individuals. This study presents the first analyses of genetic diversity in sloth populations.

DNA fingerprinting data and the analysis of population genetic structure by comparing band-sharing patterns

Genetic isolation among populations can be effectively investigated by multilocus DNA fingerprinting. If populations have diverged, it is expected that the mean proportion of bands shared by individuals from the same population, Bw, exceeds the corresponding mean, Bb, calculated from pairs of individuals from distinct populations. A problem arises in deciding whether any difference between Bw and Bb is statistically significant. In fact, any two band-sharing data (bij), contributing to Bw or Bb, are not independent if they share a common individual (like bij and bjl). This prevents a correct application of parametric tests, such as the Student's t-test. Recently, a modification of this test has been proposed that should avoid the independence problem. Using a large number of samples of fingerprints, simulated from an appropriate 'genetic' model, under a wide range of conditions, we compared the performances of the Student's t-test, the modified t-test and five new permutation tests, where individuals, rather than bij values, are permuted. We found that: (i) the Student's t-test can be very permissive, rejecting too often the null hypothesis when true, but is correct or conservative in certain cases; (ii) the modified t-test is extremely conservative when the null hypothesis is true and very inefficient otherwise; (iii) all five permutation tests are strictly correct, provided that individuals are ordered randomly on gels; and (iv) in this case, the permutation tests are equally efficient, and are not inferior to the Student's t-test when the latter is approximately correct and provides a fair benchmark.