Estimating Alpine ibex Capra ibex abundance from photographic sampling

Monitoring procedures for Alpine ibex Capra ibex are limited in habitats with reduced visibility and when physical capture and marking of the animals is not intended. Photographic sampling, involving using camera‐trap data and identifying ibex from natural markings, was adopted with capture‐recapture models to estimate the abundance of ibex in Austria. The software CAPTURE's model produced an average capture probability of 0.44 with an estimate of 34–51 ibex and a mean population size of 38 ibex. This first study showed the applicability of photographic capture‐recapture techniques to estimate the abundance of ibex based on their natural markings.     

Statistical properties of the variation at linked microsatellite loci: implications for the history of human Y chromosomes [published erratum appears in Mol Biol Evol 1997 Mar;14(3):354]

It has recently been suggested that observed levels of variation at microsatellite loci can be used to infer patterns of selection in genomes and to assess demographic history. In order to evaluate the feasibility of these suggestions it is necessary to know something about how levels of variation at microsatellite loci are expected to fluctuate due simply to stochasticity in the processes of mutation and inheritance (genetic sampling). Here we use recently derived properties of the stepwise mutation model to place confidence intervals around the variance in repeat score that is expected at mutation-drift equilibrium and outline a statistical test for whether an observed value differs significantly from expectation. We also develop confidence intervals for the time course of the buildup of variation following a complete elimination of variation, such as might be caused by a selective sweep or an extreme population bottleneck. We apply these methods to the variation observed at human Y-specific microsatellites. Although a number of authors have suggested the possibility of a very recent sweep, our analyses suggest that a sweep or extreme bottleneck is unlikely to have occurred anytime during the last approximately 74,000 years. To generate this result we use a recently estimated mutation rate for microsatellite loci of 5.6 x 10(-4) along with the variation observed at autosomal microsatellite loci to estimate the human effective population size. This estimate is 18,000, implying an effective number of 4,500 Y chromosomes. One important general conclusion to emerge from this study is that in order to reject mutation-drift equilibrium at a set of linked microsatellite loci it is necessary to have an unreasonably large number of loci unless the observed variance is far below that expected at mutation-drift equilibrium.      

Estimating population size by genotyping faeces.

Population size is a fundamental biological parameter that is difficult to estimate. By genotyping coyote (Canis latrans) faeces systematically collected in the Santa Monica Mountains near Los Angeles, California, we exemplify a general, non-invasive method to census large mammals. Four steps are involved in the estimation. First, presumed coyote faeces are collected along paths or roadways where coyotes, like most carnivores, often defaecate and mark territorial boundaries. Second, DNA is extracted from the faeces and species identity and sex is determined by mitochondrial DNA and Y-chromosome typing. Third, hypervariable microsatellite loci are typed from the faeces. Lastly, rarefaction analysis is used to estimate population size from faecal genotypes. This method readily provides a point count estimate of population size and sex ratio. Additionally, we show that home range use paternity and kinship can be inferred from the distribution and relatedness patterns of faecal genotypes.     

Characterisation of 30 microsatellite loci for the Tehuelche scallop,Aequipecten tehuelchus (d’Orbigny, 1842) and their use for estimating demographic parameters relevant to fisheries management

Aequipecten techuelchus is an endemic scallop of the Argentine biogeographic province in the southwest Atlantic Ocean which supports a commercial fishery that has presented strong fluctuations since the 1960s. It is unclear if distinct localities constitute a single panmictic population. We used next-generation sequencing to obtain microsatellite loci that could be used to evaluate genetic diversity and differentiation among populations. We developed 30 polymorphic microsatellite loci, of which 13 meet the standard criteria required for population genetic analyses, including Hardy-Weinberg equilibrium, not being linked and with a low frequency of null alleles. The described microsatellite loci were used to estimate relatedness and effective population size, and to test for recent and historic population bottlenecks. Our results suggest that the population of the Tehuelche scallop from San Román, Gulf of San José, Patagonia shows a relatively large effective population size, high levels of genetic polymorphism, low levels of inbreeding and no signs of recent or historic drastic population reductions. These preliminary results should be confirmed with larger sample sizes and the inclusion of other nearby populations.     

Low genotyping error rates in wild ungulate faeces sampled in winter

We show that Alpine ibex (Capra ibex) and Corsican mouflon (Ovis musimon) faeces yield useful DNA for microsatellite analysis, however, we detected higher genotyping error rates for spring faeces than for winter faeces. We quantified the genotyping error rate by repeatedly genotyping four microsatellites. Respectively, 99 and 95% of mouflon and ibex genotyping repetitions provided a correct genotype using winter samples, whereas spring samples provided only 52 and 59% correct genotypes. Thus, before starting a noninvasive study, we recommend that researchers conduct a pilot study to quantify genotyping error rates for each season, population and species to be studied.     

Microsatellite DNA and recent statistical methods in wildlife conservation management: applications in Alpine ibex [Capra ibex(ibex)

We evaluated the usefulness of microsatellites and recently developed statistical methods for the conservation management of fragmented and reintroduced populations, using the alpine ibex (Capra ibex) as a model species. First, we assessed the effects of past reintroduction programmes on genetic diversity and population differentiation considering different population sizes and histories. We show that genetic variability in ibex populations (HE 0.13) is among the lowest reported from microsatellites in mammal species, and that the Alpi Marittime-Mercantour population has suffered from a severe genetic bottleneck associated with its reintroduction. Second, using a computer-simulation approach, we provide examples and rough guidelines for translocation programmes concerning the number and origin of individuals for future reintroductions and for the reinforcement of populations with low genetic variability. Finally, we use the ibex microsatellite data to assess the usefulness of several published statistical tests for detecting population bottlenecks and assigning individuals to their population of origin. This study illustrates that microsatellites allow: (i) evaluation of alternative translocation scenarios by simulating different numbers and origins of migrants; (ii) identification of bottlenecked populations (especially using the Wilcoxon signed-ranks test); and (iii) population assignment with a high certainty (P < 0.001) of almost 100 of the individuals (or trophies or carcasses) from two distant populations (especially using stucture or whichrun software).     

Temporal variation in the genetic structure of a drone congregation area: an insight into the population dynamics of wild African honeybees (Apis mellifera scutellata)

The mating system of the honeybee ( Apis mellifera ) has been regarded as one of the most panmictic in the animal kingdom, with thousands of males aggregating in drone congregation areas (DCAs) that virgin queens visit to mate with tens of partners. Although males from many colonies gather at such congregations, the temporal changes in the colonies contributing drones remain unknown. Yet, changes in the DCAs' genetic structure will ultimately determine population gene flow and effective population size. By repeatedly sampling drones from an African DCA over a period of 3 years, we studied the temporal changes in the genetic structure of a wild honeybee population. Using three sets of tightly linked microsatellite markers, we were able to reconstruct individual queen genotypes with a high accuracy, follow them through time and estimate their rate of replacement. The number of queens contributing drones to the DCA varied from 12 to 72 and was correlated with temperature and rainfall. We found that more than 80% of these queens were replaced by mostly unrelated ones in successive eight months sampling intervals, which resulted in a clear temporal genetic differentiation of the DCA. Our results suggest that the frequent long-range migration of colonies without nest-site fidelity is the main driver of this high queen turnover. DCAs of African honeybees should thus be regarded as extremely dynamic systems which together with migration boost the effective population size and maintain a high genetic diversity in the population.     

Population growth of human Y chromosomes: a study of Y chromosome microsatellites

We use variation at a set of eight human Y chromosome microsatellite loci to investigate the demographic history of the Y chromosome. Instead of assuming a population of constant size, as in most of the previous work on the Y chromosome, we consider a model which permits a period of recent population growth. We show that for most of the populations in our sample this model fits the data far better than a model with no growth. We estimate the demographic parameters of this model for each population and also the time to the most recent common ancestor. Since there is some uncertainty about the details of the microsatellite mutation process, we consider several plausible mutation schemes and estimate the variance in mutation size simultaneously with the demographic parameters of interest. Our finding of a recent common ancestor (probably in the last 120,000 years), coupled with a strong signal of demographic expansion in all populations, suggests either a recent human expansion from a small ancestral population, or natural selection acting on the Y chromosome.     

Microsatellite DNA markers: evaluating their potential for estimating the proportion of hatchery-reared offspring in a stock enhancement programme

We describe a statistical method for estimating the effectiveness of a stock enhancement programme using nuclear DNA loci. It is based on knowing the population allele frequencies and the genotypes of the hatchery parents (mother only, or mother and father), and on determining the probability that a wild-born animal will by chance have a genotype consistent with hatchery origin. We show how to estimate the proportion of released animals in the wild population, and its standard error. The method is applied to a data set of eight microsatellite loci in brown tiger prawns (Penaeus esculentus), prior to the start of a possible enhancement programme. We conclude that, for this particular data set, the effectiveness of such an enhancement programme could be quantified accurately if both maternal and paternal genotypes are known, but not if maternal genotypes only are known. Full paternal genotyping would require offspring genotyping and thus would be expensive, but a partly typed paternal genotype from a mass homogenate of offspring would be almost as effective and much cheaper. The experiment would become feasible based on maternal genotypes alone, if a further three typical microsatellite loci could be found to add to the existing panel of eight. The methods detailed should be of interest to any enhancement project that relies on nuclear DNA markers to provide tags.     

Techniques for noninvasive genetic monitoring of Alpine Ibex <Emphasis Type="Italic">Capra ibex</Emphasis>

Noninvasive sampling is of increasing importance for the molecular genetic monitoring of wild animal populations, although reduced quality and quantity of such samples’ DNA can affect genetic data and their subsequent interpretation. Consequently, we performed a pilot study to establish a feasible approach for the genetic investigation of free-ranging Alpine ibex Capra ibex Linnaeus, 1758 populations. Establishing an ibex-specific PCR-RFLP based on Cytochrome b gene differences allowed the discrimination of noninvasive ibex samples from those of other sympatric ungulates. In addition, we established a quantitative PCR for ibex samples. The quantification of 35 faecal samples clearly exhibited a strong variability of DNA contents among samples and individuals. Furthermore, we performed threefold genotyping experiments on six microsatellite loci to determine the extent of genotyping errors in reference to blood samples of the respective individuals. The analyses exhibited a strong dependence of erroneous microsatellite genotypes on the starting amount of template DNA. Variability in reliability was observed between individual loci, resulting in a mandatory high DNA concentration necessary for consistent genotyping. This study serves as basis for further ibex research and we propose the application of DNA quantification of faecal samples to focus genotyping efforts solely on suitable samples.     

Importance of a pilot study for non-invasive genetic sampling: genotyping errors and population size estimation in red deer

Population size information is critical for managing endangered or harvested populations. Population size can now be estimated from non-invasive genetic sampling. However, pitfalls remain such as genotyping errors (allele dropout and false alleles at microsatellite loci). To evaluate the feasibility of non-invasive sampling (e.g., for population size estimation), a pilot study is required. Here, we present a pilot study consisting of (i) a genetic step to test loci amplification and to estimate allele frequencies and genotyping error rates when using faecal DNA, and (ii) a simulation step to quantify and minimise the effects of errors on estimates of population size. The pilot study was conducted on a population of red deer in a fenced natural area of 5440 ha, in France. Twelve microsatellite loci were tested for amplification and genotyping errors. The genotyping error rates for microsatellite loci were 0–0.83 (mean=0.2) for allele dropout rates and 0–0.14 (mean=0.02) for false allele rates, comparable to rates encountered in other non-invasive studies. Simulation results suggest we must conduct 6 PCR amplifications per sample (per locus) to achieve approximately 97% correct genotypes. The 3% error rate appears to have little influence on the accuracy and precision of population size estimation. This paper illustrates the importance of conducting a pilot study (including genotyping and simulations) when using non-invasive sampling to study threatened or managed populations.     

Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates

We propose a two‐step procedure for estimating multiple migration rates in an approximate Bayesian computation (ABC) framework, accounting for global nuisance parameters. The approach is not limited to migration, but generally of interest for inference problems with multiple parameters and a modular structure (e.g. independent sets of demes or loci). We condition on a known, but complex demographic model of a spatially subdivided population, motivated by the reintroduction of Alpine ibex (Capra ibex) into Switzerland. In the first step, the global parameters ancestral mutation rate and male mating skew have been estimated for the whole population in Aeschbacher et al. (Genetics 2012; 192 : 1027). In the second step, we estimate in this study the migration rates independently for clusters of demes putatively connected by migration. For large clusters (many migration rates), ABC faces the problem of too many summary statistics. We therefore assess by simulation if estimation per pair of demes is a valid alternative. We find that the trade‐off between reduced dimensionality for the pairwise estimation on the one hand and lower accuracy due to the assumption of pairwise independence on the other depends on the number of migration rates to be inferred: the accuracy of the pairwise approach increases with the number of parameters, relative to the joint estimation approach. To distinguish between low and zero migration, we perform ABC‐type model comparison between a model with migration and one without. Applying the approach to microsatellite data from Alpine ibex, we find no evidence for substantial gene flow via migration, except for one pair of demes in one direction.     

Molecular tracking of mountain lions in the Yosemite valley region in California: genetic analysis using microsatellites and faecal DNA

Twelve microsatellite loci were characterized in California mountain lions (Puma concolor) and sufficient polymorphism was found to uniquely genotype 62 animals sampled at necropsy. Microsatellite genotypes obtained using mountain lion faecal DNA matched those from muscle for all of 15 individuals examined. DNA from potential prey species and animals whose faeces could be misidentified as mountain lion faeces were reliably distinguished from mountain lions using this microsatellite panel. In a field application of this technique, 32 faecal samples were collected from hiking trails in the Yosemite Valley region where seven mountain lions previously had been captured, sampled, and released. Twelve samples yielded characteristic mountain lion genotypes, three displayed bobcat-type genotypes, and 17 did not amplify. The genotype of one of the 12 mountain lion faecal samples was identical to one of the mountain lions that previously had been captured. Three of the 12 faecal samples yielded identical genotypes, and eight new genotypes were detected in the remaining samples. This analysis provided a minimum estimate of 16 mountain lions (seven identified by capture and nine identified by faecal DNA) living in or travelling through Yosemite Valley from March 1997 to August 1998. Match probabilities (probabilities that identical DNA genotypes would be drawn at random a second time from the population) indicated that the samples with identical genotypes probably came from the same mountain lion. Our results demonstrate that faecal DNA analysis is an effective method for detecting and identifying individual mountain lions.     

River otter population size estimation using noninvasive latrine surveys

Across much of North America, river otter (Lontra canadensis) populations were extirpated or greatly reduced by the early 20th century. More recently, reintroductions have resulted in restored populations and the recommencement of managed trapping. Perhaps the best example of these river otter reintroductions occurred in Missouri, regarded as one of the most successful carnivore recovery programs in history. However, abundance estimates for river otter populations are difficult to obtain and often contentious when used to underpin management activities. We assessed the value of latrine site monitoring as a mechanism for quantifying river otter abundance. Analyses of fecal DNA to identify individual animals may result in an improved population estimate and have been used for a variety of mammal species. We optimized laboratory protocols, redesigned existing microsatellite primers, and calculated genotyping error rates to enhance genotyping success for a large quantity of river otter scat samples. We also developed a method for molecular sexing. We then extracted DNA from 1,421 scat samples and anal sac secretions (anal jelly) collected during latrine site counts along 22–34-km stretches representing 8–77% of 8 rivers in southern Missouri in 2009. Error rates were low for the redesigned microsatellites. We obtained genotypes at 7–10 microsatellite loci for 24% of samples, observing highest success for anal jelly samples (71%) and lowest for fresh samples (collected within 1 day of defecation). We identified 63 otters (41 M, 22 F) in the 8 rivers, ranging from 2 to 14 otters per river. Analyses using program CAPWIRE resulted in population estimates similar to the minimum genotyping estimate. Density estimates averaged 0.24 otters/km. We used linear regression to develop and contrast models predicting population size based on latrine site and scat count indices, which are easily collected in the field. Population size was best predicted by a combination of scats per latrine and latrines per kilometer. Our results provide methodological approaches to guide wildlife managers seeking to initiate similar river otter fecal genotyping studies, as well as to estimate and monitor river otter population sizes. © 2011 The Wildlife Society.     

Effect of breeding structure on population genetic parameters in Drosophila

The breeding structure of populations has been neglected in studies of Drosophila, even though Wright and Dobzhansky's pioneering work on the genetics of natural populations was an attempt to tackle what they regarded as an essential factor in evolution. We compared the breeding structure of sympatric populations of D. melanogaster and D. simulans, two sibling species that are widely used in evolutionary studies. We recorded changes in population density and microsatellite variation patterns for 3 years in a temperate environment of southwestern France. Results were distinctively different in the two species. Maximum population levels in summer and in autumn were similar and fluctuated greatly over years, each species being in turn the most abundant. However, genetic data showed that D. melanogaster made up a continuous breeding population in time and space of practically infinite effective size. D. simulans was fragmented into isolates with a local effective size of between 50 and 350 individuals. A consequence of this was that, while a local sample provided a reliable estimate of regional genetic variability in D. melanogaster, a sample from the same area provided an underestimate of this parameter in D. simulans. In practical terms, this means that variations in breeding structure should be accounted for in sampling schemes and in designing evolutionary genetic models. More generally, this suggests the existence of differential reactions to local environments that might contribute to several genomic differences observed between these species.     

Determining colony densities in wild honeybee populations (<Emphasis Type="Italic">Apis mellifera</Emphasis>) with linked microsatellite DNA markers

Estimating the population size of social bee colonies in the wild is often difficult because nests are highly cryptic. Because of the honeybee (Apis mellifera) mating behaviour, which is characterized by multiple mating of queens at drone congregation areas (DCA), it is possible to use genotypes of drones caught at these areas to infer the number of colonies in a given region. However, DCAs are difficult to locate and we assess the effectiveness of an alternative sampling technique to determine colony density based on inferring male genotypes from queen offspring. We compare these methods in the same population of wild honeybees, Apis mellifera scutellata. A set of linked microsatellite loci is used to decrease the frequency of recombination among marker loci and therefore increase the precision of the estimates. Estimates of population size obtained through sampling of queen offspring is significantly larger than that obtained by sampling drones at DCAs. This difference may be due to the more extensive flying range of queens compared with drones on mating flights. We estimate that the population size sampled through queen offspring is about double that sampled through drones.     

Estimating Effective Population Size from Linkage Disequilibrium between Unlinked Loci: Theory and Application to Fruit Fly Outbreak Populations

There is a substantial literature on the use of linkage disequilibrium (LD) to estimate effective population size using unlinked loci. The estimates are extremely sensitive to the sampling process, and there is currently no theory to cope with the possible biases. We derive formulae for the analysis of idealised populations mating at random with multi-allelic (microsatellite) loci. The ‘Burrows composite index’ is introduced in a novel way with a ‘composite haplotype table’. We show that in a sample of diploid size , the mean value of or from the composite haplotype table is biased by a factor of , rather than the usual factor for a conventional haplotype table. But analysis of population data using these formulae leads to estimates that are unrealistically low. We provide theory and simulation to show that this bias towards low estimates is due to null alleles, and introduce a randomised permutation correction to compensate for the bias. We also consider the effect of introducing a within-locus disequilibrium factor to , and find that this factor leads to a bias in the estimate. However this bias can be overcome using the same randomised permutation correction, to yield an altered with lower variance than the original , and one that is also insensitive to null alleles. The resulting formulae are used to provide estimates on 40 samples of the Queensland fruit fly, Bactrocera tryoni, from populations with widely divergent expectations. Linkage relationships are known for most of the microsatellite loci in this species. We find that there is little difference in the estimated values from using known unlinked loci as compared to using all loci, which is important for conservation studies where linkage relationships are unknown.     

Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches

The effective population size (N(e) ) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating N(e) from a single sample of genotypes to trace temporal change in N(e) for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both N(e) and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (N(b) ) using linkage disequilibrium, sibship assignment and approximate Bayesian computation methods and extrapolated these estimates to N(e) using the generation interval. The N(e) estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of N(e) > 50 but short of the long-term minimum viable population goal of N(e) > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in N(e) probably in the late 1990s and early 2000s. The new single-sample approaches to the estimation of N(e) provide efficient means for including N(e) in monitoring frameworks and will be of great importance for future management and conservation.     

The influence of sample size on two approaches to estimate Black Grouse Lyrurus tetrix population size using non-invasive sampling methods

Population size is an important parameter to monitor for species conservation and management. This is especially important for rare and endangered species, as declines can give information about anthropogenic impacts and the need for new conservation measures. To estimate population size, various methods of analysis can be used, for which sample size is an important factor. Sample size is particularly important to consider when applying non-invasive sampling strategies such as sampling faeces or feathers/hairs as a source of DNA, as a means to limit disturbance and stress for the species of concern. We investigated a Black Grouse Lyrurus tetrix population in the eastern part of the Alps, in East Tyrol (Austria), and estimated population size using two approaches: capture–recapture and rarefaction. With a set of 12 polymorphic microsatellite markers, we identified genotypes from faeces and feathers (backed up with 23 tissue samples) and checked for population substructure and gene flow among sampling sites. We estimated population size using four different models from the two approaches (molecular capture–recapture: TIRM, TIRMpart; rarefaction: hyperbolic function – Kohn, exponential function – Eggert). To evaluate the impact of sample size on the estimations, we used the full dataset of 500 samples (‘complete’ dataset) and half the dataset of 250 samples (‘half’ dataset). We also estimated the population size for each sex separately using complete and half datasets to check for sex-specific differences in population size. We found similar results in three of four models (capture–recapture: capwire TIRM, capwire TIRMpart; rarefaction: rarefaction Kohn). Using just half of the data increased the uncertainties in the estimation of population size in all models used and deviations were particularly large in females, which indicated a sex bias. Only the complete dataset of males had an observation rate of more than two observations/individual, and this observation rate meets the recommendation for using the capwire models. This indicates that, for species with different sex-specific detectability, larger sample sizes do not generally imply higher observation rates. We conclude that calculating the observation rates and population-size estimations for each sex separately can improve overall population-size estimation, especially in species with biased sex ratios and those that exhibit sex-specific behaviour.     

The effects of sample size on population genetic diversity estimates in song sparrows Melospiza melodia

To empirically determine the effects of sample size on commonly used measures of average genetic diversity, we genotyped 200 song sparrows Melospiza melodia from two populations, one genetically depauperate (n=100) and the other genetically diverse (n=100), using eight microsatellite loci. These genotypes were used to randomly create 10,000 datasets of differing sizes (5 to 50) for each population to determine what the effects of sample size might be on several estimates of genetic diversity (number of alleles per locus, average observed heterozygosity, and unbiased average expected heterozygosity) in natural populations of conservation concern. We found that at small sample sizes of 5 to 10 individuals, estimates of unbiased heterozygosity outperformed those based on observed heterozygosity or allelic diversity for both low- and high-diversity populations. We also found that when comparing across populations in which different numbers of individuals were sampled, rarefaction provided a useful way to compare estimates of allelic diversity. We recommend that standard errors should be reported for all diversity estimators, especially when sample sizes are small. We also recommend that at least 20 to 30 individuals be sampled in microsatellite studies that assess genetic diversity when working in a population that has an unknown level of diversity. However, research on critically endangered populations (where large sample sizes are impossible or extremely difficult to obtain) should include measures of genetic diversity even if sample sizes are less than ideal. These estimates can be useful in assessing the genetic diversity of the population.