TABLE 1.

Summary of 19 studies that have evaluated sampling designs using different markers (Microsatellites, AFLPs, SNPs); empirical vs. simulated data; and varying the number of loci, individuals, and populations.

References	Dataset	Type of sampling	No. of populations	No. of individuals	No. of Loci	Principal conclusions
Miyamoto et al. (2008)	Microsatellite	Empirical	1	480	4	> 30 individuals increases the precision in Hs Between 200 and 300 individuals increase the precision of allelic richness estimates.
Pruett and Winker (2008)	Microsatellite	Empirical	1	200	8	Precision in summary statistics is increased when > 20 individuals are genotyped.
González-Ramos et al. (2015)	Microsatellite	Empirical	2	64	15	Above 6 polymorphic markers are enough to adequately define the genetic structure between populations.
Peterman et al. (2016)	Microsatellite	Empirical	5	80	15	Increasing the number of loci does not change the mean summary statistics, but increases the precision across replicates. IBD patterns are sensitive to fewer loci genotyped.
Sánchez-Montes et al. (2017)	Microsatellite	Empirical	17–21 (different species)	547, 652, and 516	18, 16, and 15	> 20 individuals and between 50 and 80 individuals per population are needed to estimate HS with precision, and allelic richness, respectively.
Rico (2017)	Microsatellite	Simulation	17 and 34 (different species)	5,000 and 3,000	20	Spatial sampling design (random, systemic, cluster) affect IBD patterns. Increasing loci, over individuals, increases the accuracy of IBD estimates.
Schwartz and McKelvey (2009)	Microsatellite	Simulation	1	10,000	15	Different sampling designs generate different FST estimates, and different Structure outputs.
Landguth et al. (2012)	Microsatellite	Simulation	1	1,000	25	Increasing the number of polymorphic loci increases the precision of patterns of isolation by resistance (IBR).
Oyler-McCance et al. (2013)	Microsatellite	Simulation	1	1,000	25	Increasing the number of polymorphic loci, individuals, and number of alleles increases the precision and the accurate estimation of patterns of (IBR).
Landguth and Schwartz (2014)	Microsatellite	Simulation	64	64	20	Increasing the number of populations (even if fewer individuals are sampled) increases the possibility of finding correct patterns of IBD.
Smith and Wang (2014)	Microsatellite	Simulation	3	100	100	Reducing the number of samples do not affect Hs, FST estimates, but reduces the power to detect accurate allelic richness.
Hale et al. (2012)	Microsatellite	Mixed (Simulation and empirical)	4	100	9, 5, 7, and 8	For four different species, sampling between 25 and 30 individuals are enough to estimate accurately HS and FST.
Dubois et al. (2017)	Microsatellite	Mixed (Simulation and empirical)	4	4 different taxa: 726, 408, 372, 384	16	Sex proportions do not affect summary statistics estimates. >20 individuals increase the precision of summary statistics. Empirical and simulated data show different patterns of deviation.
Sinclair and Hobbs (2009)	AFLPs	Empirical	6	159	59 and 117	>30 individuals per population needed to estimate accurately FST.
Willing et al. (2012)	SNPs	Simulation	2	1,000	21,000	Fewer individuals are needed to accurately estimate FST for MPS datasets.
Fumagalli (2013)	SNPs	Simulation	1	1,000	20,000	Low individual sampling, with a high genome coverage underestimates the number of segregating sites, HS estimates and genetic structure.
Nazareno et al. (2017)	SNPs	Empirical	2	70	3,500	Fewer individuals (8) but with a large number of SNPs (>1,000) increase the precision of HS and FST.
Flesch et al. (2018)	SNPs	Empirical	4	120	14,000	>25 individuals (with 10,000 SNPs) are needed to estimate accurate kinship indexes (10,000 SNPs), identifying as identical by descent alleles and FST values.
Puckett and Eggert (2016)	Mixed (SNPs and Microsatellite)	Empirical	34	Microsatellites dataset: 506 SNP dataset: 96	Microsatellite dataset: 15 SNP dataset: 1,000	1,000 SNPs are more precise than microsatellites for assigning birth areas, even if fewer individuals are sampled.