Our purpose was to identify an experimental procedure using PCR that provides a reliable genotype at a microsatellite locus using only a few picograms of template DNA. Under these circumstances, it is possible (i) that one allele of a heterozygous individual will not be detected and (ii) that PCR-generated alleles or 'false alleles' will arise. A mathematical model has been developed to account for stochastic events when pipetting template DNA in a very dilute DNA extract and computer simulations have been performed. Laboratory experiments were also carried out using DNA extracted from a bear feces sample to determine if experimental results correlate with the mathematical model. The results of 150 typing experiments are consistent with the proposed model. Based on this model and the level of observed false alleles, an experimental procedure using the multiple tubes approach is proposed to obtain reliable genotypes with a confidence level of 99%. This multiple tubes procedure should be systematically used when genotyping nuclear loci of ancient or forensic samples, museum specimens and hair or feces of free ranging animals.

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating ''spurious'' bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.T HE idea that molecular data should contain information on the recent evolutionary history of populations is not new and traces back to the beginning of the 20th century (e.g., Hirschfeld and Hirschfeld 1919). However, much of the work carried out today owes to the seminal work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality (Watterson 1975;Tajima 1989b) or stationarity (Nei et al. 1975;Tajima 1989a). Following this period most studies have primarily been concerned with the statistical properties of relatively simple models such as the Wright-Fisher (WF) or Moran models (Ewens 2004). During the last 20 years the detection of population size changes (e.g., Tajima 1989b;Slatkin and Hudson 1991;Rogers and Harpending 1992;Cornuet and Luikart 1996;Beaumont 1999;Garza and Williamson 2001;Storz and Beaumont 2002) has usually been carried ou...

Great ape populations are undergoing a dramatic decline, which is predicted to result in their extinction in the wild from entire regions in the near future. Recent findings have particularly focused on African apes, and have implicated multiple factors contributing to this decline, such as deforestation, hunting, and disease. Less well-publicised, but equally dramatic, has been the decline in orang-utans, whose distribution is limited to parts of Sumatra and Borneo. Using the largest-ever genetic sample from wild orang-utan populations, we show strong evidence for a recent demographic collapse in North Eastern Borneo and demonstrate that this signature is independent of the mutation and demographic models used. This is the first demonstration that genetic data can detect and quantify the effect of recent, human-induced deforestation and habitat fragmentation on an endangered species. Because current demographic collapses are usually confounded by ancient events, this suggests a much more dramatic decline than demographic data alone and emphasises the need for major conservation efforts.