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A key contributor to accurate migration rates is the quality of the geographic assignment of state and county codes to each matched set of tax returns.
The presence of a maximum in survival probability at intermediate migration rates is potentially relevant in conservation biology and epidemiology in that controlling migration might lead to desired outcomes such as population stability or disease eradication.
Statistical examination of meteorological variables in this study indicates that 24% of the variation of sand dune migration rates is attributed to temperature, precipitation and wind speed, which is increased to 45% when incorporating lag time.
Across all states the correlation between the Census & ENOE 5-year international migration rates is 92.1%.
The systematic over-estimation of migration rates is less pronounced (and sometimes disappear) in the in-silico experiments, possibly because of differences between the real evolution process and the models used in-silico (for simulations and analysis of data).
Conversely, the hypothesis that the program BayesAss+ may, at least in the conditions investigated here, overestimate migration rates is partly supported by the observation that the migration rates are also over-estimated with in-silico generated datasets (see for example Figure 3b(i) and 3b(ii)).
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Spontaneous migration rates were examined without adding SDF-1.
Daily migration rates are calculated for each site.
Migration rates were remarkable: Argentina added 30% to its population in immigrants alone, from-1910.
When compared to the CM collected from MDC that were not pre-treated, no significant differences in migration rates were observed.
Simulated migration rates were more consistent with observed behavior when the Brooks Corey/Burdine model was employed.
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