Friday, August 6, 2010

New paper online: Early detection of population declines: high power of genetic monitoring using effective population size estimators

It is free available online in the publisher's web: http://www3.interscience.wiley.com/journal/123601431/abstract

Early detection of population declines: high power of genetic monitoring using effective population size estimators
Tiago Antao, Andrés Pérez-Figueroa and Gordon Luikart

KEYWORDS
bottleneck • computational simulations • effective population size • endangered species • habitat fragmentation • population monitoring • statistical power

ABSTRACT
Early detection of population declines is essential to prevent extinctions and to ensure sustainable harvest. We evaluated the performance of two Ne estimators to detect population declines: the two-sample temporal method and a one-sample method based on linkage disequilibrium (LD). We used simulated data representing a wide range of population sizes, sample sizes and number of loci. Both methods usually detect a population decline only one generation after it occurs if Ne drops to less than approximately 100, and 40 microsatellite loci and 50 individuals are sampled. However, the LD method often out performed the temporal method by allowing earlier detection of less severe population declines (Ne approximately 200). Power for early detection increased more rapidly with the number of individuals sampled than with the number of loci genotyped, primarily for the LD method. The number of samples available is therefore an important criterion when choosing between the LD and temporal methods. We provide guidelines regarding design of studies targeted at monitoring for population declines. We also report that 40 single nucleotide polymorphism (SNP) markers give slightly lower precision than 10 microsatellite markers. Our results suggest that conservation management and monitoring strategies can reliably use genetic based methods for early detection of population declines.

Received: 15 June 2010 Accepted: 25 June 2010

DIGITAL OBJECT IDENTIFIER (DOI)
10.1111/j.1752-4571.2010.00150.x