The use of a non‐invasive tool for capture–recapture studies on a seahorse Hippocampus guttulatus population

In this study, the spot pattern in Hippocampus guttulatus was analysed using a computer programme algorithm that allowed individual comparison. This methodology was first tested in a controlled environment using 51 adult and 55 juvenile H. guttulatus. Positive matches were obtained in 86·3 and 83·6% of the adults and juveniles, respectively. In a second experiment, monthly surveys were carried out in five selected locations in the Ria Formosa Lagoon, south Portugal, over the course of a year and a total of 980 photographs were analysed. Photographed H. guttulatus were re‐sighted one to nine times during the course of the survey period with an overall re‐sight record of over 30%. Photo‐identification was therefore shown to be a useful tool for non‐invasive mark–recapture studies that can be successfully used to survey the population abundance of H. guttulatus aged 6 months or older in consecutive years. This could be of great value when considering the assessment of H. guttulatus populations and understanding changes over time.     

Comparison of photo‐matching algorithms commonly used for photographic capture–recapture studies

Photographic capture–recapture is a valuable tool for obtaining demographic information on wildlife populations due to its noninvasive nature and cost‐effectiveness. Recently, several computer‐aided photo‐matching algorithms have been developed to more efficiently match images of unique individuals in databases with thousands of images. However, the identification accuracy of these algorithms can severely bias estimates of vital rates and population size. Therefore, it is important to understand the performance and limitations of state‐of‐the‐art photo‐matching algorithms prior to implementation in capture–recapture studies involving possibly thousands of images. Here, we compared the performance of four photo‐matching algorithms; Wild‐ID, I3S Pattern+, APHIS, and AmphIdent using multiple amphibian databases of varying image quality. We measured the performance of each algorithm and evaluated the performance in relation to database size and the number of matching images in the database. We found that algorithm performance differed greatly by algorithm and image database, with recognition rates ranging from 100% to 22.6% when limiting the review to the 10 highest ranking images. We found that recognition rate degraded marginally with increased database size and could be improved considerably with a higher number of matching images in the database. In our study, the pixel‐based algorithm of AmphIdent exhibited superior recognition rates compared to the other approaches. We recommend carefully evaluating algorithm performance prior to using it to match a complete database. By choosing a suitable matching algorithm, databases of sizes that are unfeasible to match “by eye” can be easily translated to accurate individual capture histories necessary for robust demographic estimates.     

Humpback whale abundance in the North Pacific estimated by photographic capture‐recapture with bias correction from simulation studies

We estimated the abundance of humpback whales in the North Pacific by capture‐recapture methods using over 18,000 fluke identification photographs collected in 2004–2006. Our best estimate of abundance was 21,808 (CV = 0.04). We estimated the biases in this value using a simulation model. Births and deaths, which violate the assumption of a closed population, resulted in a bias of +5.2%, exclusion of calves in samples resulted in a bias of ?10.5%, failure to achieve random geographic sampling resulted in a bias of ?0.4%, and missed matches resulted in a bias of +9.3%. Known sex‐biased sampling favoring males in breeding areas did not add significant bias if both sexes are proportionately sampled in the feeding areas. Our best estimate of abundance was 21,063 after accounting for a net bias of +3.5%. This estimate is likely to be lower than the true abundance due to two additional sources of bias: individual heterogeneity in the probability of being sampled (unquantified) and the likely existence of an unknown and unsampled breeding area (?8.7%). Results confirm that the overall humpback whale population in the North Pacific has continued to increase and is now greater than some prior estimates of prewhaling abundance.     

Upper bound estimators of the population size based on ordinal models for capture‐recapture experiments

Capture‐recapture studies have attracted a lot of attention over the past few decades, especially in applied disciplines where a direct estimate for the size of a population of interest is not available. Epidemiology, ecology, public health, and biodiversity are just a few examples. The estimation of the number of unseen units has been a challenge for theoretical statisticians, and considerable progress has been made in providing lower bound estimators for the population size. In fact, it is well known that consistent estimators for this cannot be provided in the very general case. Considering a case where capture‐recapture studies are summarized by a frequency of frequencies distribution, we derive a simple upper bound of the population size based on the cumulative distribution function. We introduce two estimators of this bound, without any specific parametric assumption on the distribution of the observed frequency counts. The behavior of the proposed estimators is investigated using several benchmark datasets and a large‐scale simulation experiment based on the scheme discussed by Pledger.     

Open population maximum likelihood spatial capture‐recapture

Open population capture‐recapture models are widely used to estimate population demographics and abundance over time. Bayesian methods exist to incorporate open population modeling with spatial capture‐recapture (SCR), allowing for estimation of the effective area sampled and population density. Here, open population SCR is formulated as a hidden Markov model (HMM), allowing inference by maximum likelihood for both Cormack‐Jolly‐Seber and Jolly‐Seber models, with and without activity center movement. The method is applied to a 12‐year survey of male jaguars (Panthera onca) in the Cockscomb Basin Wildlife Sanctuary, Belize, to estimate survival probability and population abundance over time. For this application, inference is shown to be biased when assuming activity centers are fixed over time, while including a model for activity center movement provides negligible bias and nominal confidence interval coverage, as demonstrated by a simulation study. The HMM approach is compared with Bayesian data augmentation and closed population models for this application. The method is substantially more computationally efficient than the Bayesian approach and provides a lower root‐mean‐square error in predicting population density compared to closed population models.     

genecap: a program for analysis of multilocus genotype data for non‐invasive sampling and capture‐recapture population estimation

We created genecap to facilitate analysis of multilocus genotype data for use in non‐invasive DNA sampling and genetic capture‐recapture studies. genecap is a Microsoft excel macro that uses multilocus genetic data to match samples with identical genotypes, calculate frequency of alleles, identify sample genotypes that differ by one and two alleles, calculate probabilities of identity, and match probabilities for matching samples. genecap allows the user to include background data and samples with missing genotypes for multiple loci. Capture histories for each user‐defined sampling period are output in formats consistent with commonly employed population estimation programs.     

Inferring causal factors for a declining population of bottlenose dolphins via temporal symmetry capture–recapture modeling

We applied temporal symmetry capture–recapture (TSCR) models to assess the strength of evidence for factors potentially responsible for population decline in bottlenose dolphins (Tursiops truncatus) in Doubtful Sound, New Zealand from 1995 to 2008. Model selection was conducted to estimate recruitment and population growth rates. There were similar levels of support for three different models, each reflecting distinct trends in recruitment. Modeling yielded low overall estimates of recruitment (0.0249, 95% CI: 0.0174–0.0324) and population growth rate (0.9642, 95% CI: 0.9546–0.9737). The TSCR rate of population decline was consistent with an estimate derived from trends in abundance (lambda = 0.9632, 95% CI: 0.9599–0.9665). The TSCR model selection confirmed the influence of a decline in the survival of calves (<1 yr old) since 2002 for population trends. However, TSCR population growth rates did not exceed 1 in any year between 1995 and 2008, indicating the population was declining prior to 2002. A separate reduction in juvenile survival (1–3 yr old) prior to 2002 was identified as a likely contributing factor in the population decline. Thus, TSCR modeling indicated the potential cause of the population decline in Doubtful Sound: cumulative impacts on individuals <3 yr old resulting in a reduced recruitment.     

How common is common? Rapidly assessing population size and structure of the frog Mantidactylus betsileanus at a site in east‐central Madagascar

Population‐level data are urgently needed for amphibians in light of the ongoing amphibian extinction crisis. Studies focused on population dynamics are not only important for rare species but also for common species which shape ecosystems to a greater degree than those that are rare. Some of the greatest global amphibian species diversity is found in Madagascar, yet there are few studies on the ecology of frog species on the island. We carried out a mark‐recapture study on the widespread frog Mantidactylus betsileanus (Mantellidae: Mantellinae: Mantidactylus) at two adjacent rainforest sites in east‐central Madagascar to assess its population size and structure. To do so, we validated and implemented an individual identification protocol using photographs of the ventral patterns of frogs and identified individuals with photographic‐matching software. Using this rapid, non‐invasive survey method, we were able to estimate a density of 26 and 28 frogs per 100 m² at each of the two sites sampled. Our results show the rainforests near the village of Andasibe, Madagascar support remarkably high amphibian abundance, helping illustrate the significant ecological role of frogs in this ecosystem. Further, individual frog markings allowed us to develop more precise estimates than traditional survey methods. This study provides a blueprint to augment existing population studies or develop new monitoring programs in Madagascar and beyond.     

Improved methods for estimating abundance and related demographic parameters from mark‐resight data

Over the past decade, there has been much methodological development for the estimation of abundance and related demographic parameters using mark‐resight data. Often viewed as a less‐invasive and less‐expensive alternative to conventional mark recapture, mark‐resight methods jointly model marked individual encounters and counts of unmarked individuals, and recent extensions accommodate common challenges associated with imperfect detection. When these challenges include both individual detection heterogeneity and an unknown marked sample size, we demonstrate several deficiencies associated with the most widely used mark‐resight models currently implemented in the popular capture‐recapture freeware Program MARK. We propose a composite likelihood solution based on a zero‐inflated Poisson log‐normal model and find the performance of this new estimator to be superior in terms of bias and confidence interval coverage. Under Pollock's robust design, we also extend the models to accommodate individual‐level random effects across sampling occasions as a potentially more realistic alternative to models that assume independence. As a motivating example, we revisit a previous analysis of mark‐resight data for the New Zealand Robin (Petroica australis) and compare inferences from the proposed estimators. For the all‐too‐common situation where encounter rates are low, individual detection heterogeneity is non‐negligible, and the number of marked individuals is unknown, we recommend practitioners use the zero‐inflated Poisson log‐normal mark‐resight estimator as now implemented in Program MARK.     

Trends in bowhead whales in West Greenland: Aerial surveys vs. genetic capture‐recapture analyses

We contrast two methods for estimating the trends of bowhead whales (Balaena mysticetus) in West Greenland: (1) double platform visual aerial survey, corrected for missed sightings and the time the whales are available at the surface; and (2) a genetic capture‐recapture approach based on a 14‐yr‐long biopsy sampling program in Disko Bay. The aerial survey covered 39,000 km² and resulted in 58 sightings, yielding an abundance estimate of 744 whales (CV = 0.34, 95% CI: 357–1,461). The genetic method relied on determining sex, mitochondrial haplotypes and genotypes of nine microsatellite markers. Based on samples from a total of 427 individuals, with 11 recaptures from previous years in 2013, this resulted in an estimate of 1,538 whales (CV = 0.24, 95% CI: 827–2,249). While the aerial survey is considered a snapshot of the local spring aggregation in Disko Bay, the genetic approach estimates the abundance of the source of this aggregation. As the whales in Disko Bay primarily are adult females that do not visit the bay annually, the genetic method would presumably yield higher estimates. The studies indicate that an increase in abundance observed between 1998 and 2006 has leveled off.     

oSCR: a spatial capture–recapture R package for inference about spatial ecological processes

Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. camera traps, non‐invasive genetics) that have vastly improved our ability to collection spatially explicit observation data on individuals. However, the utility of SCR methods reaches far beyond simply convenience and data availability. SCR presents a formal statistical framework that can be used to test explicit hypotheses about core elements of population and landscape ecology, and has profound implications for how we study animal populations. In this software note, we describe the technical basis and analytical workflow of oSCR, an R package for analyzing spatial encounter history data using a multi‐session sex‐structured likelihood. The impetus for developing oSCR was to create an accessible and transparent analysis tool that allows users to conveniently and intuitively formulate statistical models that map directly to fundamental processes of interest in spatial population ecology (e.g. space use, resource selection, density and connectivity). We have placed an emphasis on creating a transparent and accessible code base that is coupled with a logical workflow that we hope stimulates active participation in further technical developments.     

Evaluating otter reintroduction outcomes using genetic spatial capture–recapture modified for dendritic networks

Monitoring the demographics and genetics of reintroduced populations is critical to evaluating reintroduction success, but species ecology and the landscapes that they inhabit often present challenges for accurate assessments. If suitable habitats are restricted to hierarchical dendritic networks, such as river systems, animal movements are typically constrained and may violate assumptions of methods commonly used to estimate demographic parameters. Using genetic detection data collected via fecal sampling at latrines, we demonstrate applicability of the spatial capture–recapture (SCR) network distance function for estimating the size and density of a recently reintroduced North American river otter (Lontra canadensis) population in the Upper Rio Grande River dendritic network in the southwestern United States, and we also evaluated the genetic outcomes of using a small founder group (n = 33 otters) for reintroduction. Estimated population density was 0.23–0.28 otter/km, or 1 otter/3.57–4.35 km, with weak evidence of density increasing with northerly latitude (β = 0.33). Estimated population size was 83–104 total otters in 359 km of riverine dendritic network, which corresponded to average annual exponential population growth of 1.12–1.15/year since reintroduction. Growth was ≥40% lower than most reintroduced river otter populations and strong evidence of a founder effect existed 8–10 years post‐reintroduction, including 13–21% genetic diversity loss, 84%–87% genetic effective population size decline, and rapid divergence from the source population (F _ST accumulation = 0.06/generation). Consequently, genetic restoration via translocation of additional otters from other populations may be necessary to mitigate deleterious genetic effects in this small, isolated population. Combined with non‐invasive genetic sampling, the SCR network distance approach is likely widely applicable to demogenetic assessments of both reintroduced and established populations of multiple mustelid species that inhabit aquatic dendritic networks, many of which are regionally or globally imperiled and may warrant reintroduction or augmentation efforts.     

Validation of photo‐identification as a mark–recapture method in the spotted eagle ray Aetobatus narinari

The spotted eagle ray Aetobatus narinari is characterized by pigmentation patterns that are retained for up to 3·5 years. These pigmentations can be used to identify individuals through photo‐identification. Only one study has validated this technique, but no study has estimated the percentage of correct identification of the rays using this technique. In order to carry out demographic research, a reliable photographic identification technique is needed. To achieve this validation for A. narinari, a double‐mark system was established over 11 months and photographs of the dorsal surface of 191 rays were taken. Three body parts with distinctive natural patterns were analysed (dorsal surface of the cephalic region, dorsal surface of the pectoral fins and dorsal surface of the pelvic fins) in order to determine the body part that could be used to give the highest percentage of correct identification. The dorsal surface of the pectoral fins of A. narinari provides the most accurate photo‐identification to distinguish individuals (88·2%).     

dropout: a program to identify problem loci and samples for noninvasive genetic samples in a capture‐mark‐recapture framework

Abstract Genotyping error, often associated with low‐quantity/quality DNA samples, is an important issue when using genetic tags to estimate abundance using capture‐mark‐recapture (CMR). dropout , an MS‐Windows program, identifies both loci and samples that likely contain errors affecting CMR estimates. dropout uses a ‘bimodal test’, that enumerates the number of loci different between each pair of samples, and a ‘difference in capture history test’ (DCH) to determine those loci producing the most errors. Importantly, the DCH test allows one to determine that a data set is error‐free. dropout has been evaluated in McKelvey & Schwartz (2004) and is now available online.     

A spatially explicit capture–recapture estimator for single‐catch traps

Single‐catch traps are frequently used in live‐trapping studies of small mammals. Thus far, a likelihood for single‐catch traps has proven elusive and usually the likelihood for multicatch traps is used for spatially explicit capture–recapture (SECR) analyses of such data. Previous work found the multicatch likelihood to provide a robust estimator of average density. We build on a recently developed continuous‐time model for SECR to derive a likelihood for single‐catch traps. We use this to develop an estimator based on observed capture times and compare its performance by simulation to that of the multicatch estimator for various scenarios with nonconstant density surfaces. While the multicatch estimator is found to be a surprisingly robust estimator of average density, its performance deteriorates with high trap saturation and increasing density gradients. Moreover, it is found to be a poor estimator of the height of the detection function. By contrast, the single‐catch estimators of density, distribution, and detection function parameters are found to be unbiased or nearly unbiased in all scenarios considered. This gain comes at the cost of higher variance. If there is no interest in interpreting the detection function parameters themselves, and if density is expected to be fairly constant over the survey region, then the multicatch estimator performs well with single‐catch traps. However if accurate estimation of the detection function is of interest, or if density is expected to vary substantially in space, then there is merit in using the single‐catch estimator when trap saturation is above about 60%. The estimator's performance is improved if care is taken to place traps so as to span the range of variables that affect animal distribution. As a single‐catch likelihood with unknown capture times remains intractable for now, researchers using single‐catch traps should aim to incorporate timing devices with their traps.     

Assessing population parameters and trends of Guiana dolphins (Sotalia guianensis): An eight‐year mark‐recapture study

This study represents the first attempt to study the population dynamics of Guiana dolphins (Sotalia guianensis), by evaluating a set of demographic parameters. The population of the Caravelas River estuary, eastern Brazil, was systematically monitored through a long‐term mark‐recapture experiment (2002–2009). Abundance estimates revealed a small population (57–124 dolphins), comprised of resident dolphins and individuals that temporarily leave or pass through the study area. Temporary emigration from the estuary to adjacencies (γ″= 0.33 ± 0.07 SE) and return rate (1 ?γ′= 0 .67) were moderate and constant, indicating that some dolphins use larger areas. Survival rate (?= 0.88 ± 0.07 SE) and abundance were constant throughout the study period. Power analysis showed that the current monitoring effort has high probability of detecting abrupt population declines (1 ?β= 0.9). Although the monitoring is not yet sensitive to subtle population trends, sufficient time to identify them is feasible (additional 3 yr). Despite such apparent stability, this population, as many others, inhabits waters exposed to multiple human‐related threats. Open and closed population modeling applied to photo‐identification data provide a robust baseline for estimating several demographic parameters and can be applied to other populations to allow further comparisons. Such synergistic efforts will allow a reliable definition of conservation status of this species.