Lisette P. Waits

Estimating the probability of identity among genotypes in natural populations: cautions and guidelines

Individual identification using DNA fingerprinting methods is emerging as a critical tool in conservation genetics and molecular ecology. Statistical methods that estimate the probability of sampling identical genotypes using theoretical equations generally assume random associations between alleles within and among loci. These calculations are probably inaccurate for many animal and plant populations due to population substructure. We evaluated the accuracy of a probability of identity (P(ID)) estimation by comparing the observed and expected P(ID), using large nuclear DNA microsatellite data sets from three endangered species: the grey wolf (Canis lupus), the brown bear (Ursus arctos), and the Australian northern hairy‐nosed wombat (Lasiorinyus krefftii). The theoretical estimates of P(ID) were consistently lower than the observed P(ID), and can differ by as much as three orders of magnitude. To help researchers and managers avoid potential problems associated with this bias, we introduce an equation for P(ID) between sibs. This equation provides an estimator that can be used as a conservative upper bound for the probability of observing identical multilocus genotypes between two individuals sampled from a population. We suggest computing the actual observed P(ID) when possible and give general guidelines for the number of codominant and dominant marker loci required to achieve a reasonably low P(ID) (e.g. 0.01–0.0001).

Noninvasive genetic sampling: look before you leap.

Noninvasive sampling allows genetic studies of free-ranging animals without the need to capture or even observe them, and thus allows questions to be addressed that cannot be answered using conventional methods. Initially, this sampling strategy promised to exploit fully the existing DNA-based technology for studies in ethology, conservation biology and population genetics. However, recent work now indicates the need for a more cautious approach, which includes quantifying the genotyping error rate. Despite this, many of the difficulties of noninvasive sampling will probably be overcome with improved methodology.

Putting the "landscape" in landscape genetics.

Landscape genetics has emerged as a new research area that integrates population genetics, landscape ecology and spatial statistics. Researchers in this field can combine the high resolution of genetic markers with spatial data and a variety of statistical methods to evaluate the role that landscape variables play in shaping genetic diversity and population structure. While interest in this research area is growing rapidly, our ability to fully utilize landscape data, test explicit hypotheses and truly integrate these diverse disciplines has lagged behind. Part of the current challenge in the development of the field of landscape genetics is bridging the communication and knowledge gap between these highly specific and technical disciplines. The goal of this review is to help bridge this gap by exposing geneticists to terminology, sampling methods and analysis techniques widely used in landscape ecology and spatial statistics but rarely addressed in the genetics literature. We offer a definition for the term ‘landscape genetics’, provide an overview of the landscape genetics literature, give guidelines for appropriate sampling design and useful analysis techniques, and discuss future directions in the field. We hope, this review will stimulate increased dialog and enhance interdisciplinary collaborations advancing this exciting new field.

NONINVASIVE GENETIC SAMPLING TOOLS FOR WILDLIFE BIOLOGISTS: A REVIEW OF APPLICATIONS AND RECOMMENDATIONS FOR ACCURATE DATA COLLECTION

Abstract Noninvasive genetic sampling provides great potential for research and management applications in wildlife biology. Researchers can obtain DNA from a variety of sources including hair, feces, urine, feathers, shed skin, saliva, and egg shells without handling or observing animals. These samples can then be used to identify the presence of rare or elusive species, count and identify individuals, determine gender, and identify diet items, or samples can be used to evaluate genetic diversity, population structure, and mating system. We review the recent advancements and techniques used for identifying species, individuals, and gender. We also address the potential pitfalls of noninvasive genetic sampling and provide recommendations for laboratory- and field-based methods to improve the reliability and accuracy of data collected from noninvasive genetic samples.

Noninvasive genetic tracking of the endangered Pyrenean brown bear population

Pyrenean brown bears Ursus arctos are threatened with extinction. Management efforts to preserve this population require a comprehensive knowledge of the number and sex of the remaining individuals and their respective home ranges. This goal has been achieved using a combination of noninvasive genetic sampling of hair and faeces collected in the field and corresponding track size data. Genotypic data were collected at 24 micrdsatellite loci using a rigorous multiple‐tubes approach to avoid genotyping errors associated with low quantities of DNA. Based on field and genetic data, the Pyrenean population was shown to be composed at least of one yearling, three adult males, and one adult female. These data indicate that extinction of the Pyrenean brown bear population is imminent without population augmentation. To preserve the remaining Pyrenean gene pool and increase genetic diversity, we suggest that managers consider population augmentation using only females. This study demonstrates that comprehensive knowledge of endangered small populations of mammals can be obtained using noninvasive genetic sampling.

Landscape genetics: where are we now?

Landscape genetics has seen rapid growth in number of publications since the term was coined in 2003. An extensive literature search from 1998 to 2008 using keywords associated with landscape genetics yielded 655 articles encompassing a vast array of study organisms, study designs and methodology. These publications were screened to identify 174 studies that explicitly incorporated at least one landscape variable with genetic data. We systematically reviewed this set of papers to assess taxonomic and temporal trends in: (i) geographic regions studied; (ii) types of questions addressed; (iii) molecular markers used; (iv) statistical analyses used; and (v) types and nature of spatial data used. Overall, studies have occurred in geographic regions proximal to developed countries and more commonly in terrestrial vs. aquatic habitats. Questions most often focused on effects of barriers and/or landscape variables on gene flow. The most commonly used molecular markers were microsatellites and amplified fragment length polymorphism (AFLPs), with AFLPs used more frequently in plants than animals. Analysis methods were dominated by Mantel and assignment tests. We also assessed differences among journals to evaluate the uniformity of reporting and publication standards. Few studies presented an explicit study design or explicit descriptions of spatial extent. While some landscape variables such as topographic relief affected most species studied, effects were not universal, and some species appeared unaffected by the landscape. Effects of habitat fragmentation were mixed, with some species altering movement paths and others unaffected. Taken together, although some generalities emerged regarding effects of specific landscape variables, results varied, thereby reinforcing the need for species‐specific work. We conclude by: highlighting gaps in knowledge and methodology, providing guidelines to authors and reviewers of landscape genetics studies, and suggesting promising future directions of inquiry.

Applications of landscape genetics in conservation biology: concepts and challenges

Landscape genetics plays an increasingly important role in the management and conservation of species. Here, we highlight some of the opportunities and challenges in using landscape genetic approaches in conservation biology. We first discuss challenges related to sampling design and introduce several recent methodological developments in landscape genetics (analyses based on pairwise relatedness, the application of Bayesian methods, inference from landscape resistance and a shift from population-based to individual-based analyses). We then show how simulations can foster the field of landscape genetics and, finally, elaborate on technical developments in sequencing techniques that will dramatically improve our ability to study genetic variation in wild species, opening up new and unprecedented avenues for genetic analysis in conservation biology.

Plucked hair samples as a source of DNA: reliability of dinucleotide microsatellite genotyping.

To test whether plucked hairs are a reliable source of DNA for genotyping microsatellite loci, we carried out experiments using one, three, or 10 hairs per extract for 50 alpine marmots. For each extract, seven independent genotypings were performed for the same locus (multiple‐tubes approach). Two types of genotyping errors were recorded: a false homozygote defined as the detection of only one allele of a true heterozygote, and a false allele defined as a PCR‐generated allele that was not one of the alleles of the true genotype. Using DNA extracted from one, three, or 10 hairs, the overall error rate was 14.00%, 4.86%, and 0.29%, respectively. Based on our results, we conclude that 10 hairs should be used to obtain consistently reliable genotypings using the single‐tube approach, and that a single plucked hair could represent a reliable source of DNA if the multiple‐tubes approach is used. For future studies of dinucleotide repeat diversity using DNA extracted from one to three shed or plucked hairs, we strongly recommend initiating an appropriate pilot study to quantify the error rate and to determine the reliability of the single‐tube approach.

Molecular detection of vertebrates in stream water: a demonstration using Rocky Mountain tailed frogs and Idaho giant salamanders.

Stream ecosystems harbor many secretive and imperiled species, and studies of vertebrates in these systems face the challenges of relatively low detection rates and high costs. Environmental DNA (eDNA) has recently been confirmed as a sensitive and efficient tool for documenting aquatic vertebrates in wetlands and in a large river and canal system. However, it was unclear whether this tool could be used to detect low-density vertebrates in fast-moving streams where shed cells may travel rapidly away from their source. To evaluate the potential utility of eDNA techniques in stream systems, we designed targeted primers to amplify a short, species-specific DNA fragment for two secretive stream amphibian species in the northwestern region of the United States (Rocky Mountain tailed frogs, Ascaphus montanus, and Idaho giant salamanders, Dicamptodon aterrimus). We tested three DNA extraction and five PCR protocols to determine whether we could detect eDNA of these species in filtered water samples from five streams with varying densities of these species in central Idaho, USA. We successfully amplified and sequenced the targeted DNA regions for both species from stream water filter samples. We detected Idaho giant salamanders in all samples and Rocky Mountain tailed frogs in four of five streams and found some indication that these species are more difficult to detect using eDNA in early spring than in early fall. While the sensitivity of this method across taxa remains to be determined, the use of eDNA could revolutionize surveys for rare and invasive stream species. With this study, the utility of eDNA techniques for detecting aquatic vertebrates has been demonstrated across the majority of freshwater systems, setting the stage for an innovative transformation in approaches for aquatic research.

A new method for estimating the size of small populations from genetic mark-recapture data

The use of non‐invasive genetic sampling to estimate population size in elusive or rare species is increasing. The data generated from this sampling differ from traditional mark–recapture data in that individuals may be captured multiple times within a session or there may only be a single sampling event. To accommodate this type of data, we develop a method, named capwire, based on a simple urn model containing individuals of two capture probabilities. The method is evaluated using simulations of an urn and of a more biologically realistic system where individuals occupy space, and display heterogeneous movement and DNA deposition patterns. We also analyse a small number of real data sets. The results indicate that when the data contain capture heterogeneity the method provides estimates with small bias and good coverage, along with high accuracy and precision. Performance is not as consistent when capture rates are homogeneous and when dealing with populations substantially larger than 100. For the few real data sets where N is approximately known, capwires estimates are very good. We compare capwires performance to commonly used rarefaction methods and to two heterogeneity estimators in program capture: Mh‐Chao and Mh‐jackknife. No method works best in all situations. While less precise, the Chao estimator is very robust. We also examine how large samples should be to achieve a given level of accuracy using capwire. We conclude that capwire provides an improved way to estimate N for some DNA‐based data sets. Capwire is available at http://www.cnr.uidaho.edu/lecg/.