Detecting population declines via monitoring the effective number of breeders (Nb)
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Abstract
Estimating the effective population size and effective number of breeders per year (Nb) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of Nb in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. Nb 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 Nb 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 Nb was small (Nb < 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 Nb = 50 when the true Nb = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject Nb = 500 when the true Nb = 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 Nb when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate Nb for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in Nb and population declines.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Detecting population declines via monitoring the effective number of breeders (Nb) |
Series title | Molecular Ecology Resources |
DOI | 10.1111/1755-0998.13251 |
Volume | 21 |
Issue | 2 |
Year Published | 2021 |
Language | English |
Publisher | Wiley |
Contributing office(s) | Northern Rocky Mountain Science Center |
Description | 15 p. |
First page | 379 |
Last page | 393 |
Google Analytic Metrics | Metrics page |