Bridging the gaps between non-invasive genetic sampling and population parameter estimation

Reliable estimates of population parameters are necessary for effective management and conservation actions. The use of genetic data for capture–recapture (CR) analyses has become an important tool to estimate population parameters for elusive species. Strong emphasis has been placed on the genetic analysis of non-invasive samples, or on the CR analysis; however, little attention has been paid to the simultaneous overview of the full non-invasive genetic CR analysis, and the important insights gained by understanding the interactions between the different parts of the technique. Here, we review the three main steps of the approach: designing the appropriate sampling scheme, conducting the genetic lab analysis, and applying the CR analysis to the genetic results; and present a synthesis of this topic with the aim of discussing the primary limitations and sources of error. We discuss the importance of the integration between these steps, the unique situations which occur with non-invasive studies, the role of ecologists and geneticists throughout the process, the problem of error propagation, and the sources of biases which can be present in the final estimates. We highlight the importance of team collaboration and offer a series of recommendations to wildlife ecologists who are not familiar with this topic yet but may want to use this tool to monitor populations through time.     

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.     

From connectivity to isolation: genetic consequences of population fragmentation in capercaillie across Europe

The capercaillie inhabits a continuous range in large parts of the Palearctic boreal forest, but is patchily distributed in temperate Europe. An ongoing population decline, largely related to human land use changes, has been most pronounced in central and western Europe, where some local populations have become extinct. In this study, we document the genetic differentiation of capercaillie populations at different stages along a gradient of spatial structuring from high connectivity (continuous range in the boreal forest) to a metapopulation systems (Alps) and recent (central Europe) and historic (Pyrenees) isolation. Four hundred and sixty individuals from 14 sample sites were genotyped at 10 polymorphic microsatellite loci to assess genetic structure and variation of capercaillie populations across its European range. As expected, differentiation was least pronounced within the continuous range in the boreal forest. Within the metapopulation system of the Alps, differentiation was less than among the isolated populations of central Europe (Black Forest, Fichtelgebirge, Thuringia, Vosges). In the long-isolated population of the Pyrenees, and the recently isolated populations of central Europe, genetic diversity was significantly reduced compared with the Alps and boreal forest. Our results agree with the concept of a gradual increase in genetic differentiation from connectivity to isolation, and from recent to historic isolation. Anthropogenic habitat deterioration and fragmentation thus not only leads to range contractions and extinctions, but may also have significant genetic and evolutionary consequences for surviving populations. To maintain high levels of genetic variation in species in fragmented habitats, conservation should aim at securing connectivity between spatially distinct populations.     

Quantification and reduction of bias from sampling larvae to infer population and landscape genetic structure

A well-designed sampling scheme is critical for obtaining accurate results from population genetic studies. Larval samples contain only the genetic material of successful breeders, often of a single year, and may be biased towards particular families. To quantify the bias of using larval samples to infer population and landscape genetic structure and explore how this bias may be reduced using sibship analysis, we analysed eight microsatellite loci from 484 tissue samples of larvae and adults of Columbia spotted frogs (Rana luteiventris) and long-toed salamanders (Ambystoma macrodactylum) at nine breeding sites in north Idaho. Differences in allele frequencies between adult and larval samples were not detected after full-siblings were removed from the larval data set for Columbia spotted frogs; for long-toed salamanders, these differences remained at two out of four ponds. Data from Columbia spotted frog larvae indicated higher levels of differentiation among populations (median difference in F_ST = 0.020, P < 0.01), as predicted by population genetic theory, whereas data from larval samples of long-toed salamanders showed some evidence of lower levels of differentiation among populations (median difference in F_ST = 0.012, P = 0.06). For both species, removing all but one individual from each full-sibling family led to parameter estimates that were closer to those calculated from adult samples for both population and landscape genetic measures. Removal of full-siblings is likely to improve estimates of population genetic parameters; however, knowledge of the species’ breeding system is essential for understanding additional sources of bias when inferring population genetic structure from larval samples.     

Littoral macroinvertebrates of acidified lakes in the Bohemian Forest

Mountain lakes in the Bohemian Forest, on both the Czech and German sides, were atmospherically acidified mainly in the 1960s–1980s and have since been recovering from acidification. In 2007, we performed the first complete study on littoral macroinvertebrates in all eight lakes. The goals of the study were to 1) compare macroinvertebrates in the lakes during the process of recovery and 2) investigate relations between the occurrence of taxa and water chemistry. Lake water pH varied from 4.6 to 5.7, concentrations of dissolved reactive Al and labile Al ranged from 118–601 and 11–470 μg L^?1, respectively, and DOC concentrations were < 6 mg L^?1. Altogether 73 taxa were identified from all lakes; a positive relationship was found between pH and the number of macroinvertebrate taxa. The highest number of taxa was found in the least acidic lakes Laka and Grosser Arbersee, including the mollusk Pisidium casertanum. In contrast, the lowest diversity was found in the most acidified ?ertovo jezero. Cluster analyses of macroinvertebrates and water chemistry suggested pH as the key factor influencing the occurrence of macroinvertebrate taxa. An interesting finding was the occurrence of the boreo-montane water beetle Nebrioporus assimilis in Prá?ilské record of this species in the Czech Republic since 1960.     

Extensive population genetic structure in the giraffe

Background  

A central question in the evolutionary diversification of large, widespread, mobile mammals is how substantial differentiation can arise, particularly in the absence of topographic or habitat barriers to dispersal. All extant giraffes (Giraffa camelopardalis) are currently considered to represent a single species classified into multiple subspecies. However, geographic variation in traits such as pelage pattern is clearly evident across the range in sub-Saharan Africa and abrupt transition zones between different pelage types are typically not associated with extrinsic barriers to gene flow, suggesting reproductive isolation.     

Detecting populations in the 'ambiguous' zone: kinship-based estimation of population structure at low genetic divergence

Identifying population structure is one of the most common and important objectives of spatial analyses using population genetic data. Population structure is detected either by rejecting the null hypothesis of a homogenous distribution of genetic variation, or by estimating low migration rates. Issues arise with most current population genetic inference methods when the genetic divergence is low among putative populations. Low levels of genetic divergence may be as a result of either high ongoing migration or historic high migration but no current, ongoing migration. We direct attention to recent developments in the use of the tempo-spatial distribution of closely related individuals to detect population structure or estimate current migration rates. These 'kinship-based' approaches complement more traditional population-based genetic inference methods by providing a means to detect population structure and estimate current migration rates when genetic divergence is low. However, for kinship-based methods to become widely adopted, formal estimation procedures applicable to a range of species life histories are needed.     

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.     

Genetic variability and size estimates of the Eurasian otter (Lutra lutra) population in the Bohemian Forest Ecosystem

Even though recent years have shown a slow recovery of the Eurasian otter (Lutra lutra) populations from their previous lows, the species is still highly endangered in most parts of its European distribution range. Surprisingly, only a few studies have so far assessed the species’ genetic variability and population density, and they have mostly been carried out only in small territories. In Germany, most otter populations live in protected areas whose management urgently needs data on population sizes and densities as well as on genetic variability of the species under their custody. Thus, we analyzed genetic variability and assessed size and density of the otter population in the Bohemian Forest Ecosystem, an area that had not been included in the few previous molecular studies. The study area comprised of 1500 km², divided into fifteen squares of 10 × 10 km², each of which was sampled in two collection periods. Overall we collected 261 fecal samples (spraints), of which 60 (23%) could be genotyped at least at eight microsatellite loci, yielding 38 distinct otter genotypes. The low genotyping success rate was the result of high ambient temperature at the time of sampling rather than that of high humidity. The population did not show signs of a past bottleneck, indicating a small yet stable population size. Population size was estimated to be 118 (CI_95% 64–163) individuals, with a mean density of 1 animal per 8.5 km² or 3.1 km river length. Our results imply that hunting, requested by local fishpond owners, should remain banned to avoid a decline in (effective) population size.     

The genetic structure of the Swedish population

Patterns of genetic diversity have previously been shown to mirror geography on a global scale and within continents and individual countries. Using genome-wide SNP data on 5174 Swedes with extensive geographical coverage, we analyzed the genetic structure of the Swedish population. We observed strong differences between the far northern counties and the remaining counties. The population of Dalarna county, in north middle Sweden, which borders southern Norway, also appears to differ markedly from other counties, possibly due to this county having more individuals with remote Finnish or Norwegian ancestry than other counties. An analysis of genetic differentiation (based on pairwise F(st)) indicated that the population of Sweden's southernmost counties are genetically closer to the HapMap CEU samples of Northern European ancestry than to the populations of Sweden's northernmost counties. In a comparison of extended homozygous segments, we detected a clear divide between southern and northern Sweden with small differences between the southern counties and considerably more segments in northern Sweden. Both the increased degree of homozygosity in the north and the large genetic differences between the south and the north may have arisen due to a small population in the north and the vast geographical distances between towns and villages in the north, in contrast to the more densely settled southern parts of Sweden. Our findings have implications for future genome-wide association studies (GWAS) with respect to the matching of cases and controls and the need for within-county matching. We have shown that genetic differences within a single country may be substantial, even when viewed on a European scale. Thus, population stratification needs to be accounted for, even within a country like Sweden, which is often perceived to be relatively homogenous and a favourable resource for genetic mapping, otherwise inferences based on genetic data may lead to false conclusions.     

The genetic structure of the Kuwaiti population

Summary Frequency estimates were determined on seventeen blood group, serum protein, and red-cell enzyme markers on random samples of 193 individuals from two Bedouin tribes in addition to the general population in Kuwait. Genetic heterogeneity between the three communities is evident from the significant differences in allelic distribution of the polymorphic markers.Genetic distance measurements were used to compare the results with the oral history of descent of the two tribal communities. Results were in agreement with tribal history.     

Biological recovery of the Bohemian Forest lakes from acidification

A limnological survey of eight small, atmospherically acidified, forested glacial lakes in the Bohemian Forest (?umava, Böhmerwald) was performed in September 2003. Water chemistry of the tributaries and surface layer of each lake was determined, as well as species composition and biomass of the plankton along the water column, and littoral macrozoobenthos to assess the present status of the lakes. The progress in chemical reversal and biological recovery from acid stress was evaluated by comparing the current status of the lakes with results of a survey four years ago (1999) and former acidification data since the early 1990s. Both the current chemical lake status and the pelagic food web structure reflected the acidity of the tributaries and their aluminium (Al) and phosphorus (P) concentrations. One mesotrophic (Ple?né jezero) and three oligotrophic lakes (?erné jezero, ?ertovo jezero, and Rachelsee) are still chronically acidified, while four other oligotrophic lakes (Kleiner Arbersee, Prá?ilské jezero, Grosser Arbersee, and Laka) have recovered their carbonate buffering system. Total plankton biomass was very low and largely dominated by filamentous bacteria in the acidified oligotrophic lakes, while the mesotrophic lake had a higher biomass and was dominated by phytoplankton, which apparently profited from the higher P input. In contrast, both phytoplankton and crustacean zooplankton accounted for the majority of plankton biomass in the recovering lakes. This study has shown further progress in the reversal of lake water chemistry as well as further evidence of biological recovery compared to the 1999 survey. While no changes occurred in species composition of phytoplankton, a new ciliate species was found in one lake. In several lakes, this survey documented a return of zooplankton (e.g., Cladocera: Ceriodaphnia quadrangula and Rotifera: three Keratella species) and macrozoobenthos species (e.g., Ephemeroptera and Plecoptera). The beginning of biological recovery has been delayed for ～20 years after chemical reversal of the lakes.     

Isozymes,plant population genetic structure and genetic conservation

Summary The exploration, conservation and use of the genetic resources of plants is a contemporary issue which requires a multidisciplinary approach. Here the role of population genetic data, particularly those derived from electrophoretic analysis of protein variation, is reviewed. Measures of the geographic structure of genetic variation are used to check on sampling theory. Current estimates justify the contention that alleles which have a highly localised distribution, yet are in high frequency in some neighbourhoods, represent a substantial fraction of the variation. This class, which is the most important class in the framing of sampling strategies, accounts for about 20–30% of variants found in 12 plant species. The importance of documenting possible coadapted complexes and gene-environment relationships is discussed. Furthermore, the genetic structure of natural populations of crop relatives might suggest the best structure to use in the breeding of crops for reduced vulnerability to pest and disease attack, or for adaptation to inferior environments. The studies reported to date show that whilst monomorphic natural populations do occur, particularly in inbreeding colonisers, or at the extreme margins of the distribution, polymorphism seems to be the more common mode. It is stressed here that the genetic resources of the wild relatives of crop plants should be systematically evaluated. These sources will supplement, and might even rival, the primitive land races in their effectiveness in breeding programmes. We may look forward to a wider application of gel electrophoresis in the evaluation of plant genetic resources because this technique is currently the best available for detecting genetic differences close to the DNA level on samples of reasonable size.     

Assessing population genetic structure via the maximisation of genetic distance

Background

The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.

Methods

In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a simulated annealing algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.

Results

The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for F_ST ≥ 0.03, but only STRUCTURE estimates the correct number of clusters for F_ST as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.

Conclusion

This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.     

The population structure associated with the Ewens sampling formula

Models for selectively neutral mutation, in which mutation always yields a new allele, seem always to lead, in the limit of large population size, to a sampling formula first propounded by Ewens in 1972. It is shown that the asymptotic validity of the Ewens formula is equivalent to a certain limiting joint distribution for the allele proportions in the population, arranged in descending order. The familiar diffusion approximations are corollaries of this limiting distribution, and therefore share the apparent robustness of the sampling formula.     

Noninvasive genetic analyses for estimating population size and genetic diversity of the remaining Far Eastern leopard (Panthera pardus orientalis) population

Understanding and monitoring the population status of endangered species is vital for developing appropriate management interventions. We used noninvasive genetic analyses to obtain ecological and genetic data on the last remaining Far Eastern leopard population in the world. During seven winters from 2000–2001 to 2007–2008, we collected feces, hair, and saliva from most of the leopard habitat. Of the 239 leopard samples collected during the study period, 155 were successfully genotyped at 13 microsatellite loci and 37 individuals (18 males and 19 females) were identified. Population size estimates based on the Capwire model were 28 (95 % CI 19–38) in 2002–03 and 26 (95 % CI 13–33) in 2007–2008. The leopard population had a low level of genetic diversity (expected and observed heterozygosity = 0.43; average number of alleles per locus = 2.62), and effective population size was estimated to be low (N _e = 7–16) by two genetic-based methods. We observed little improvement in the genetic diversity during the study period and did find an indication of allele loss compared with individuals from the mid-1990s, suggesting that the remaining population will continue to suffer loss of genetic diversity. Given the small population size and the low genetic diversity, with little expectation of replenishment of the genetic variation by natural immigration, successful expansion of available habitat and development of a second population based on captive individuals may be crucial for persistence of this leopard subspecies in the wild.     

Multilocus estimation of genetic structure within populations

Spatial structure of genetic variation within populations is well measured by statistics based on the distribution of pairs of individual genotypes, and various such statistics have been widely used in experimental studies. However, the problem of uncharacterized correlations among statistics for different alleles has limited the applications of multiallelic, multilocus summary measures, since these had unknown sampling distributions. Usually multiple alleles and/or multiple loci are required in order to precisely measure spatial structures, and to provide precise indirect estimates of the amount of dispersal in samples of reasonable size. This article examines the correlations among pair-wise statistics, including Moran I-statistics and various measures of conditional kinship, for different alleles of a locus. First the correlations are mathematically derived for random spatial distributions, which allow averages over alleles and loci to be used as more powerful yet exact test statistics for the null hypothesis. Then extensive computer simulations are conducted to examine the correlations among values for different alleles under isolation by distance processes. For loci with more than three alleles, the results show that the correlations are remarkably and perhaps surprisingly small, establishing the principle that then alleles behave as nearly independent realizations of space-time stochastic processes. The results also show that the correlations are largely robust with respect to the degree of spatial structure, and they can be used in a straightforward manner to form confidence intervals for averages. The results allow a precise connection between observations in experimental studies and levels of dispersal in theoretical models.     

Assessment of genetic diversity and population structure in mungbean

This study was carried out to assess the genetic diversity and to analyze the population genetic structure for a total of 692 mungbean accessions preserved at National Agrobiodiversity Center (NAC) of the Rural Development Administration (RDA), Korea. Mungbean accessions were collected from 27 countries in nine different geographic regions, and were genotyped using 15 microsatellite markers, which were developed in our previous study. A total of 66 alleles were detected among 692 accessions at all the loci with an average of 4.4 alleles per locus. All the microsatellite loci were found to be polymorphic. The expected heterozygosity (H _E ) and polymorphism information content (PIC) ranged from 0.081 to 0.588 (mean = 0.345) and from 0.080 to 0.544 (mean = 0.295), respectively. Of the 66 alleles, 17 (25.8%) were common (frequency range between 0.05 and 0.5), 15 (22.7%) were abundant (frequency range > 0.5), and 34 (51.5%) were rare (frequency range < 0.05). Locus GB-VR-7 provided the highest number of rare alleles(eight), followed by GB-VR-91(six) and GB-VR-113(four). Country-wide comparative study on genetic diversity showed that accessions from the USA possessed the highest genetic diversity (PIC) followed by Nepal, Iran, and Afghanistan. And region-wide showed that accessions from Europe possessed the highest average genetic diversity, followed by accessions from the USA, South Asia, West Asia, and Oceania. Twenty-seven countries were grouped into seven clades by phylogenetic relationship analysis, but clustering pattern did not strictly follow their geographical origin because of extensive germplasm exchange between/among countries and regions. As a result of a model-based analysis (STRUCTURE) of microsatellite data, two distinct genetic groups were identified which shared more than 75% membership with one of the two genetic groups. However the genetic group pattern did not reflect their geographical origin. The Duncan’s Multiple Range Test among these two genetic groups and an admixed group, with a mean of 16 phenotypic traits, showed significant difference in 12 quantitative and qualitative traits on the basis of ANOVA. These 15 newly developed SSR markers proved to be useful as DNA markers to detect genetic variation in mungbean germplasm for reasonable management and crossbreeding purposes.