Mpd. Telles et Jaf. Diniz, Null expectation of spatial correlograms under a stochastic process of genetic divergence with small sample sizes, GENET MOL B, 23(4), 2000, pp. 739-743
An Ornstein-Uhlenbeck process was used to simulate the exponential relation
ship between genetic divergence and geographic distances, as predicted by s
tochastic processes of population differentiation, such as isolation-by-dis
tance, stepping-stone or coalescence models. These simulations were based o
nly on the spatial coordinates of the local populations that defined a spat
ial unweighted pair-group method using arithmetic averages (UPGMA) link amo
ng them. The simulated gene frequency surfaces were then analyzed using spa
tial autocorrelation procedures and Nei's genetic distances, constructed wi
th different numbers of variables (gene frequencies). Stochastic divergence
in space produced strong spatial patterns at univariate and mutivariate le
vels. Using a relatively small number of local populations, the correlogram
profiles varied considerably, with Manhattan distances greater than those
defined by other simulation studies. This method allows one to establish a
range of correlogram profiles under the same stochastic process of spatial
divergence, thereby avoiding the use of unnecessary explanations of genetic
divergence based on other microevolutionary processes.