Evaluating the interaction of faecal pellet deposition rates and DNA degradation rates to optimize sampling design for DNA‐based mark–recapture analysis of Sonoran pronghorn

Knowledge of population demographics is important for species management but can be challenging in low‐density, wide‐ranging species. Population monitoring of the endangered Sonoran pronghorn (Antilocapra americana sonoriensis) is critical for assessing the success of recovery efforts, and noninvasive DNA sampling (NDS) could be more cost‐effective and less intrusive than traditional methods. We evaluated faecal pellet deposition rates and faecal DNA degradation rates to maximize sampling efficiency for DNA‐based mark–recapture analyses. Deposition data were collected at five watering holes using sampling intervals of 1–7 days and averaged one pellet pile per pronghorn per day. To evaluate nuclear DNA (nDNA) degradation, 20 faecal samples were exposed to local environmental conditions and sampled at eight time points from one to 124 days. Average amplification success rates for six nDNA microsatellite loci were 81% for samples on day one, 63% by day seven, 2% by day 14 and 0% by day 60. We evaluated the efficiency of different sampling intervals (1–10 days) by estimating the number of successful samples, success rate of individual identification and laboratory costs per successful sample. Cost per successful sample increased and success and efficiency declined as the sampling interval increased. Results indicate NDS of faecal pellets is a feasible method for individual identification, population estimation and demographic monitoring of Sonoran pronghorn. We recommend collecting samples >7 days old and estimate that a sampling interval of 4–7 days in summer conditions (i.e. extreme heat and exposure to UV light) will achieve desired sample sizes for mark–recapture analysis while also maximizing efficiency.     

Optimizing ultrasonic sampling effort for monitoring forest bats

Landscape‐scale monitoring is a key approach for assessing changes in indicators. However, great care needs to be taken to collect rigorous data and avoid wasting resources in long‐term programmes. Insect‐eating bats are diverse, functionally important and are often proposed as indicator species of environmental health. We used acoustic (ultrasonic) data from pilot bat surveys undertaken in forests and woodlands to optimize sampling effort to produce precise estimates of bat activity and occupancy. We also carried out simulations to evaluate the statistical power of different sampling designs to detect changes in activity and occupancy levels of individual bat species. There was little gain in precision for estimates of bat activity by sampling beyond five to six detector nights. To ensure spatial heterogeneity was sampled around a monitoring point, three detectors for two nights or two detectors for three nights would be required. This level of sampling was also sufficient to be 90% certain of recording occupancy for 11 of 12 taxa. Power simulations revealed that a sampling design using two detectors per monitoring point for two nights could detect a 30% decline within 10 years with 90% power for all species, except the white‐striped free tail bat (Tadarida australis), using either changes in activity levels or occupancy. However, fewer years were required when using occupancy. Setting detectors either on‐flyways or off‐flyways contributed only minor differences to the time taken to reach 90% power for both occupancy and activity levels, though sampling both locations has major implications for interpreting trends in bats. We suggest that bat activity levels are more sensitive for detecting change than occupancy because one pass or 1000 passes can be recorded per night by an acoustic detector, and this is not differentiated by occupancy. Bats can be monitored cost‐effectively and should be included in monitoring programmes.     

Sequential hypothesis testing with spatially correlated presence-absence data

A pest management decision to initiate a control treatment depends upon an accurate estimate of mean pest density. Presence-absence sampling plans significantly reduce sampling efforts to make treatment decisions by using the proportion of infested leaves to estimate mean pest density in lieu of counting individual pests. The use of sequential hypothesis testing procedures can significantly reduce the number of samples required to make a treatment decision. Here we construct a mean-proportion relationship for Oligonychus perseae Tuttle, Baker, and Abatiello, a mite pest of avocados, from empirical data, and develop a sequential presence-absence sampling plan using Bartlett's sequential test procedure. Bartlett's test can accommodate pest population models that contain nuisance parameters that are not of primary interest. However, it requires that population measurements be independent, which may not be realistic because of spatial correlation of pest densities across trees within an orchard. We propose to mitigate the effect of spatial correlation in a sequential sampling procedure by using a tree-selection rule (i.e., maximin) that sequentially selects each newly sampled tree to be maximally spaced from all other previously sampled trees. Our proposed presence-absence sampling methodology applies Bartlett's test to a hypothesis test developed using an empirical mean-proportion relationship coupled with a spatial, statistical model of pest populations, with spatial correlation mitigated via the aforementioned tree-selection rule. We demonstrate the effectiveness of our proposed methodology over a range of parameter estimates appropriate for densities of O. perseae that would be observed in avocado orchards in California.     

Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance

Monitoring large carnivores is difficult because of intrinsically low densities and can be dangerous if physical capture is required. Noninvasive genetic sampling (NGS) is a safe and cost‐effective alternative to physical capture. We evaluated the utility of two NGS methods (scat detection dogs and hair sampling) to obtain genetic samples for abundance estimation of coyotes, black bears and Canada lynx in three areas of Newfoundland, Canada. We calculated abundance estimates using program capwire , compared sampling costs, and the cost/sample for each method relative to species and study site, and performed simulations to determine the sampling intensity necessary to achieve abundance estimates with coefficients of variation (CV) of <10%. Scat sampling was effective for both coyotes and bears and hair snags effectively sampled bears in two of three study sites. Rub pads were ineffective in sampling coyotes and lynx. The precision of abundance estimates was dependent upon the number of captures/individual. Our simulations suggested that ~3.4 captures/individual will result in a < 10% CV for abundance estimates when populations are small (23–39), but fewer captures/individual may be sufficient for larger populations. We found scat sampling was more cost‐effective for sampling multiple species, but suggest that hair sampling may be less expensive at study sites with limited road access for bears. Given the dependence of sampling scheme on species and study site, the optimal sampling scheme is likely to be study‐specific warranting pilot studies in most circumstances.     

Optimum effort to estimate habitat use when the individual animal is the sampling unit

• 1 Studies of habitat use in which the individual animal is the sampling unit should ideally sample each individual sufficiently to achieve a stable estimate of its habitat use. Data are typically obtained by radio-tracking, which can be labour-intensive. Hence, optimization of sampling effort is desirable. A method to determine optimum sampling effort is described with reference to an example from a study of Natterer's bat Myotis nattereri, in which data were collected by radio-tracking with individual bats followed continuously for entire nights.
• 2 Habitat use by Natterer's bat was assessed by compositional analysis, which compares the composition of habitats used with those potentially available. Therefore, we plotted running per cent foraging time spent over a range of habitat types against the cumulative foraging time recorded. We visually estimated the optimum sum of foraging time required to determine stable estimates of the composition of habitat use from the plots. Then, by reference to the full-time budget, the total tracking effort expended at the point when this optimum amount of foraging data had been recorded was determined and expressed in units of the number of nightly tracking sessions that had been undertaken to collect that amount of foraging data.
• 3 Stable estimates of habitat use were attained after a mean of 22 ± 7.7 h of foraging time, which were obtained in a mean of 4.6 ± 1.9 nights of radio-tracking effort. Thus, in this Natterer's bat study, where habitat preference was assessed by compositional analysis, it was appropriate to aim to collect foraging data during five nights of radio-tracking for each bat sampled.
• 4 The method presented is also applicable to studies where tracking data are discontinuous. A variation of the method can be applied in studies where a Euclidean distance method is to be used for the analysis of habitat use.

     

Estimating Coyote Densities with Local,Discrete Bayesian Capture-Recapture Models

Recent advances in noninvasive genetic sampling and spatial capture-recapture (SCR) techniques are particularly useful for monitoring cryptic wildlife species such as carnivores. In southern Arizona, USA, coyotes (Canis latrans) are thought to negatively affect endangered Sonoran pronghorn (Antilocapra americana sonoriensis), although no estimates of coyote abundance or monitoring programs exist. Sonoran pronghorn are provided supplemental feed and water in this region, resulting in areas where pronghorn and other species are congregated. Because of the higher density of artificial water sources for Sonoran pronghorn on the Cabeza Prieta National Wildlife Refuge (CPNWR), we predicted that coyote density would be higher relative to the Barry M. Goldwater Range (BMGR), where artificial water sources are less dense. We used discrete Bayesian SCR models in a local evaluation approach to provide baseline estimates of coyote abundance and understand how coyote density varied between 2 contrasting areas of land use. We identified 106 individuals from scat samples across 3 sessions in 2013 and 2014 and achieved high genotyping and individual identification success rates (~78%). Encounter rates at water catchments were nearly 11 times higher compared to road and trail transects. As predicted, we found that coyote density was on average 2 times higher on the CPNWR (11.2 coyotes/100 km²) compared to the BMGR (5.3 coyotes/100 km²). The local evaluation approach significantly reduced computational time, making the discrete Bayesian approach more practical to implement across a large study area. Our study represents an important contribution towards developing a robust monitoring program for coyotes. We hope that our novel implementation of the local evaluation approach increases the ability of wildlife managers to understand the effects of land use and other ecological influences on large carnivore populations. © 2020 The Wildlife Society.     

Evaluating outcomes of restoration ecology projects on limited budgets: assessment of variation in sampling intensity and sampling frequency for four habitat types

While best practices for evaluating restoration ecology projects are emerging rapidly, budget constraints often limit postrestoration monitoring, which emphasizes the need for practical and efficient monitoring strategies. We examined the postrestoration outcome for an ENGO (Nature Conservancy of Canada) project, to assess retroactively how variation in intensity and frequency of sampling would have affected estimates of plant species composition, diversity, and richness over time. The project restored four habitat types (mesic forest, oak woodland, wet meadow, and sand barren) using sculptured seeding of tallgrass prairie and woody species. Species‐level plant cover was monitored annually for 10 years in 168 2 × 2–m quadrats. We performed randomization tests to examine estimates of species diversity and richness as a function of the number of quadrats sampled, and assessed the necessity of annual sampling for describing changes in species composition and successional trajectories. The randomization tests revealed that sampling 10–17 quadrats, depending on habitat type, was sufficient to obtain estimates of species diversity that were at least 95% of values obtained from the whole dataset. Species richness as a function of number of quadrats sampled did not plateau, which suggests that rather than increasing the number of sampling quadrats, richness could be estimated more efficiently using nonquadrat based sampling techniques. Nonmetric multidimensional scaling analysis revealed that plant species composition largely stabilized by 3–5 years postrestoration depending on habitat type. By that time, native, seeded species dominated the restoration, and the benefits of annual sampling for tracking changes in species composition diminished.     

A Dry Summer Diminishes Mate Search Effort by Pronghorn Females: Evidence for a Significant Cost of Mate Search

In the 2 weeks before estrus, pronghorn (Antilocapra americana) females on the National Bison Range in northwestern Montana, USA usually move actively among several widely spaced, mature, site‐faithful males in a mate search process that identifies vigorous mates. Typically, at least 90% of females practice this active sampling each year; each of the remaining females moves, before the rut begins, to a peripheral, isolated location with a single male and mates there without sampling. In 2001 and 2002, 90 and 100% of females, respectively, used the sampling strategy. The summer of 2003 was unusually hot and dry in western Montana. By September, when the pronghorn rut occurs, many pronghorn females were in visibly poor condition. In the winter that followed, 38% of females and 79% of males died, and in the following spring, only 17% of the surviving females gave birth. In the rut of 2003, 19% of females practiced the active sampling strategy. In 2004, 68% of females attempted to sample, even though there were only three mature males in the population. Among females that sampled, the number of switches away from harems and the number of males visited did not vary across years, except in 2004. The proportion of samplers in 2003 that died over winter was not different from the proportion of non‐samplers that died over winter, and among the survivors, the proportion of samplers that completed gestation was not different from the proportion of non‐samplers that completed gestation. The data suggest that pronghorn females have a strong motivation to sample potential mates, that sampling is abandoned when energy stores are low, and that yearly variation in the percent of females that sample is explained by variation in female condition.     

Analysis of population genetic structure with RAPD markers

Recent advances in the application of the polymerase chain reaction make it possible to score individuals at a large number of loci. The RAPD (random amplified polymorphic DNA) method is one such technique that has attracted widespread interest. The analysis of population structure with RAPD data is hampered by the lack of complete genotypic information resulting from dominance, since this enhances the sampling variance associated with single loci as well as induces bias in parameter estimation. We present estimators for several population-genetic parameters (gene and genotype frequencies, within- and between-population heterozygosities, degree of inbreeding and population subdivision, and degree of individual relatedness) along with expressions for their sampling variances. Although completely unbiased estimators do not appear to be possible with RAPDs, several steps are suggested that will insure that the bias in parameter estimates is negligible. To achieve the same degree of statistical power, on the order of 2 to 10 times more individuals need to be sampled per locus when dominant markers are relied upon, as compared to codominant (RFLP, isozyme) markers. Moreover, to avoid bias in parameter estimation, the marker alleles for most of these loci should be in relatively low frequency. Due to the need for pruning loci with low-frequency null alleles, more loci also need to be sampled with RAPDs than with more conventional markers, and some problems of bias cannot be completely eliminated.     

Challenges of DNA-Based Mark-Recapture Studies of American Black Bears

Abstract: We explored whether genetic sampling would be feasible to provide a region-wide population estimate for American black bears (Ursus americanus) in the southern Appalachians, USA. Specifically, we determined whether adequate capture probabilities (p > 0.20) and population estimates with a low coefficient of variation (CV < 20%) could be achieved given typical agency budget and personnel constraints. We extracted DNA from hair collected from baited barbed-wire enclosures sampled over a 10-week period on 2 study areas: a high-density black bear population in a portion of Great Smoky Mountains National Park and a lower density population on National Forest lands in North Carolina, South Carolina, and Georgia. We identified individual bears by their unique genotypes obtained from 9 microsatellite loci. We sampled 129 and 60 different bears in the National Park and National Forest study areas, respectively, and applied closed mark-recapture models to estimate population abundance. Capture probabilities and precision of the population estimates were acceptable only for sampling scenarios for which we pooled weekly sampling periods. We detected capture heterogeneity biases, probably because of inadequate spatial coverage by the hair-trapping grid. The logistical challenges of establishing and checking a sufficiently high density of hair traps make DNA-based estimates of black bears impractical for the southern Appalachian region. Alternatives are to estimate population size for smaller areas, estimate population growth rates or survival using mark-recapture methods, or use independent marking and recapturing techniques to reduce capture heterogeneity.     

Cryptic population genetic structure: the number of inferred clusters depends on sample size

Clustering methods have been used extensively to unravel cryptic population genetic structure. We investigated the effect of the number of individuals sampled in each location on the resulting number of clusters. Our study was motivated by recent results in Arabidopsis thaliana: studies in which more than one individual was sampled per location apparently have led to a much higher number of clusters than studies where only one individual was sampled in each location, as is generally done in this species. We show, using computer simulations and microsatellite data in A. thaliana, that the number of sampled individuals indeed has a strong impact on the number of resulting clusters. This effect is smaller if the sampled populations have a hierarchical structure. In most cases, sampling 5–10 individuals per population should be enough. The results argue for abandoning the concept of ‘accessions’ in partially selfing organisms.     

Contrasting management paradigms for pronghorn in the arid Southwest and their northern range: a review

Pronghorn (Antilocapra americana), a symbol of western North America, experienced diverging population trajectories since the mid-twentieth century, with northern populations showing signs of recovery while those in the arid Southwest have struggled to persist. We conducted a systematic literature review of papers published through August 2023 to understand 3 questions. What are the habitat conditions needed for pronghorn to persist? What management actions can be taken to foster higher quality habitat? Do these actions differ for populations in the arid Southwest compared to their northern counterparts? Although the fundamental habitat requirements for pronghorn persistence have remained constant since the early 2000s, it has become clear that precipitation is a key factor influencing pronghorn populations in the arid Southwest. The precise mechanisms by which precipitation influences pronghorn population dynamics are not yet clear, whether through the availability of free water, by affecting forage quality, or indirectly via predator-prey dynamics. Although range-wide forage enhancement may be impractical, providing additional free water sources could facilitate greater movement, enabling pronghorn to access more and higher quality forage and areas with lower predation risk. To clarify how pronghorn persisted for thousands of years in this harsh environment, we must gain a better understanding of their historical metapopulation and migratory behaviors in the arid Southwest.     

Economic injury level and sequential sampling plan for Bemisia tabaci in outdoor tomato

Abstract:  This work aimed to determine the economic injury levels and to establish sequential sampling plans for nymphs and adults of the whitefly Bemisia tabaci Genn. (Sternorrhyncha: Aleyrodidae) in tomato fields. Densities of nymphs and adults, as well as crop yield were evaluated in 13 commercial tomato fields to determine the economic injury levels. The whitefly nymphs were sampled by direct counting in a leaf from the lower part of the canopy and the adults were sampled by beating an apical leaf against a white plastic tray. The sequential sampling plan was based on data collected in eight commercial tomato fields. The validation of the sequential sampling plan was carried out based on the curves of operational characteristics and average sample numbers. The decisions reached with the conventional and the sequential sampling plans in 21 commercial fields were compared for the intended validation of the sequential plan. The economic injury levels were four nymphs per leaf and one adult per tray. The decisions taken based on the sequential sampling plan were similar to those obtained through the conventional sampling plan. Most of the decisions taken with the sequential sampling plan were obtained through the minimum number of seven samples per field for nymphs and 11 samples per field for adults, with reductions of 84.44% and 54.17% in the number of samples required to reach a decision with the sequential sampling plan compared with the conventional sampling plan.     

Assessing noninvasive hair and fecal sampling for monitoring the distribution and abundance of river otter

Monitoring the distribution and abundance of populations is an important component of efforts to meet management or conservation goals. Although the objectives for such studies are easy to define, cost-effective, precise, and accurate estimates are often elusive. We tested the efficacy and compared the cost-effectiveness of methods for estimating the number and recording the distribution of river otter (Lontra canadensis). We genotyped otter hair sampled using two noninvasive instruments and compared those results with a hypothetical study design based on DNA extracted from fecal matter. Patterns of distribution generated from DNA collected at latrine sites were then compared to observations of otter collected using VHF radiotelemetry. We achieved a high probability of genotyping river otter with a small number of hairs (i.e., 59.0 % probability of producing a genotype with 1 guard hair and >5 under hair samples) collected using wire body snares and knaplock hair snags. Body snares were more effective at collecting otter hair, but there was relatively little additional cost to using both sampling instruments. Genotyped hair resulted in a high multi-year recapture rate (61.9 %). Hair collection and genotyping was the most cost-effective method for monitoring populations of river otter ($168.50 US/datum) followed by radiotelemetry ($264.50 US/datum), and the extraction of DNA from fecal matter ($266.00 US/datum). However, the noninvasive techniques did not represent the full distribution and fine-scale movements of otter, as observed using radiotelemetry. There has been much recent reporting of the efficacy of fecal matter as a source of DNA for conducting mark–recapture population estimates for mesocarnivores. Our data suggested that collecting DNA in hair may be a more cost-effective and efficient approach.     

Effects of sampling regime on the mean and variance of home range size estimates

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.     

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.     

Reliable confidence intervals in quantitative genetics: narrow-sense heritability

Many quantitative genetic statistics are functions of variance components, for which a large number of replicates is needed for precise estimates and reliable measures of uncertainty, on which sound interpretation depends. Moreover, in large experiments the deaths of some individuals can occur, so methods for analysing such data need to be robust to missing values. We show how confidence intervals for narrow-sense heritability can be calculated in a nested full-sib/half-sib breeding design (males crossed with several females) in the presence of missing values. Simulations indicate that the method provides accurate results, and that estimator uncertainty is lowest for sampling designs with many males relative to the number of females per male, and with more females per male than progenies per female. Missing data generally had little influence on estimator accuracy, thus suggesting that the overall number of observations should be increased even if this results in unbalanced data. We also suggest the use of parametrically simulated data for prior investigation of the accuracy of planned experiments. Together with the proposed confidence intervals an informed decision on the optimal sampling design is possible, which allows efficient allocation of resources.     

Inferring recent migration rates from individual genotypes

We present a novel and straightforward method for estimating recent migration rates between discrete populations using multilocus genotype data. The approach builds upon a two-step sampling design, where individual genotypes are sampled before and after dispersal. We develop a model that estimates all pairwise backwards migration rates ( m_ij , the probability that an individual sampled in population i is a migrant from population j ) between a set of populations. The method is validated with simulated data and compared with the methods of BayesAss and Structure. First, we use data for an island model and then we consider more realistic data simulations for a metapopulation of the greater white-toothed shrew ( Crocidura russula ). We show that the precision and bias of estimates primarily depend upon the proportion of individuals sampled in each population. Weak sampling designs may particularly affect the quality of the coverage provided by 95% highest posterior density intervals. We further show that it is relatively insensitive to the number of loci sampled and the overall strength of genetic structure. The method can easily be extended and makes fewer assumptions about the underlying demographic and genetic processes than currently available methods. It allows backwards migration rates to be estimated across a wide range of realistic conditions.     

类群取样与系统发育分析精确度之探索

Appropriate and extensive taxon sampling is one of the most important determinants of accurate phylogenetic estimation. In addition, accuracy of inferences about evolutionary processes obtained from phylogenetic analyses is improved significantly by thorough taxon sampling efforts. Many recent efforts to improve phylogenetic estimates have focused instead on increasing sequence length or the number of overall characters in the analysis, and this often does have a beneficial effect on the accuracy of phylogenetic analyses. However, phylogenetic analyses of few taxa (but each represented by many characters) can be subject to strong systematic biases, which in turn produce high measures of repeatability (such as bootstrap proportions) in support of incorrect or misleading phylogenetic results. Thus, it is important for phylogeneticists to consider both the sampling of taxa, as well as the sampling of characters, in designing phylogenetic studies. Taxon sampling also improves estimates of evolutionary parameters derived from phylogenetic trees, and is thus important for improved applications of phylogenetic analyses. Analysis of sensitivity to taxon inclusion, the possible effects of long-branch attraction, and sensitivity of parameter estimation for model-based methods should be a part of any careful and thorough phylogenetic analysis. Furthermore, recent improvements in phylogenetic algorithms and in computational power have removed many constraints on analyzing large, thoroughly sampled data sets. Thorough taxon sampling is thus one of the most practical ways to improve the accuracy of phylogenetic estimates, as well as the accuracy of biological inferences that are based on these phylogenetic trees.     

Using pedigree reconstruction to estimate population size: genotypes are more than individually unique marks

Estimates of population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Noninvasive genetic methods are increasingly used to estimate population size, particularly in elusive species such as large carnivores, which are difficult to count by most other methods. In most such studies, genotypes are treated simply as unique individual identifiers. Here, we develop a new estimator of population size based on pedigree reconstruction. The estimator accounts for individuals that were directly sampled, individuals that were not sampled but whose genotype could be inferred by pedigree reconstruction, and individuals that were not detected by either of these methods. Monte Carlo simulations show that the population estimate is unbiased and precise if sampling is of sufficient intensity and duration. Simulations also identified sampling conditions that can cause the method to overestimate or underestimate true population size; we present and discuss methods to correct these potential biases. The method detected 2–21% more individuals than were directly sampled across a broad range of simulated sampling schemes. Genotypes are more than unique identifiers, and the information about relationships in a set of genotypes can improve estimates of population size.