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Keywords:

  • Dispersal;
  • hypervariable loci;
  • microsatellite;
  • mutation;
  • spatial autocorrelation;
  • spatial structure

Abstract

The question of whether or not the high rates (µ) 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 µ 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 µ 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.