Sentence examples for classification of populations from inspiring English sources

For tree species, two aspects were considered: one, classification of populations for biomass modeling should be compatible with that for volume modeling; two, assurance that the amount of stand area and volume stock for each separate modeling population of certain tree species (or group) is sufficient.

Initially, the program was allowed to assign individuals to clusters without a priori classification of populations.

In contrast, no alleles were observed in Dokai Bay that were not also observed in Tokyo Bay. STRUCTURE analysis of nuclear microsatellite data without a priori classification of populations indicates that Japanese Carcinus are substantially diverged from their native congeners (Figure 4).

Actually, this low genetic differentiation between most Sahelian and East African populations suggests a possible climate and biome link that is supported by the significant association of NAT2 genetic structure with a classification of populations according to ecoregions.

On the other hand, Bolnick et al. [ 8] suggest that the expectation based on classification of populations as patrilocal or matrilocal is robust in Native Americans, at least with respect to the linguistic differences.

Tabachnik and Powell 16 also made the distinction between hybrid populations made up of largely F1 individuals and the stable freely interbreeding populations they observed, and noted that taxonomic classification of populations in California as Cx.

A major advantage of the MST approach is that the algorithm may result in trees with star-like branches, which allows for a correct classification of population systems that have a strong mutational or recombinational rate, such as P. aeruginosa, and where a large number of single locus variants (SLVs) may evolve from one common type [7].

Part of our research has consisted in assessing whether visits to health clinics by vulnerable groups (the bottom quintile in the classification of population based on income) have been made any easier by free healthcare policies [ 50].

These features were used for machine learning for the classification of two populations composed of osteoporotic and healthy subjects.

PAMELA's measurements are supported by an accurate analysis of particle trajectories in the Earth's magnetosphere based on a realistic geomagnetic field modeling, which allows the classification of particle populations of different origin and the investigation of the asymptotic directions of arrival.

The first is to provide a subjective classification of the populations of sixteen Latin American countries into low, middle, and upper classes, based on a self-perceived social ranking.