Detecting population declines via monitoring the effective number of breeders (N ).

Estimating the effective population size and effective number of breeders per year (N ) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of N in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. N estimates were biased by ~5%-10% when using SNPs or microsatellites in species ranging from fishes to mosquitoes, frogs, and seaweed. The bias (high or low) was similar for different life history types within a species suggesting that life history variation in populations will not influence N estimation. Precision was higher for 100 SNPs (H ≈ 0.30) than for 15 microsatellites (H ≈ 0.70). Confidence intervals (CIs) were occasionally too narrow, and biased high when N was small (N  < 50); however, the magnitude of bias would unlikely influence management decisions. The CIs (from LDNe) were sufficiently narrow to achieve high statistical power (≥0.80) to reject the null hypothesis that N  = 50 when the true N  = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject N  = 500 when the true N  = 400 and when sampling 200 individuals and 5,000 loci. Finally, we present a linear regression method that provides high power to detect a decline in N when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate N for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in N and population declines.