Age is not just a number: How incorrect ageing impacts close-kin mark-recapture estimates of population size

Population size is a key parameter for the conservation of animal species. Close-kin mark-recapture (CKMR) relies on the observed frequency and type of kinship among individuals sampled from the population to estimate population size. Knowledge of the age of the individuals, or a surrogate thereof, is essential for inference with acceptable precision. One common approach, particularly in fish studies, is to measure animal length and infer age using an assumed age-length relationship (a 'growth curve'). We used simulation to test the effect of misspecifying the length measurement error and the growth curve on population size estimation. Simulated populations represented two fictional shark species, one with a relatively simple life history and the other with a more complex life history based on the grey reef shark (Carcharhinus amblyrhynchos). We estimated sex-specific adult abundance, which we assumed to be constant in time. We observed small median biases in these estimates ranging from 1.35% to 2.79% when specifying the correct measurement error standard deviation and growth curve. CI coverage was adequate whenever the growth curve was correctly specified. Introducing error via misspecified growth curves resulted in changes in the magnitude of the estimated adult population, where underestimating age negatively biased the abundance estimates. Over- and underestimating the standard deviation of length measurement error did not introduce a bias and had negligible effect on the variance in the estimates. Our findings show that assuming an incorrect standard deviation of length measurement error has little effect on estimation, but having an accurate growth curve is crucial for CKMR whenever ageing is based on length measurements. If ageing could be biased, researchers should be cautious when interpreting CKMR results and consider the potential biases arising from inaccurate age inference.

Sources of bias in applying close-kin mark-recapture to terrestrial game species with different life histories

Close-kin mark-recapture (CKMR) is a method analogous to traditional mark-recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species' and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent-offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Reliability of trans-generational genetic mark-recapture (tGMR) for enumerating Pacific salmon

As Pacific salmon (Oncorhynchus spp.) decline across much of their range, it is imperative to further develop minimally invasive tools to quantify population abundance. One such advancement, trans-generational genetic mark-recapture (tGMR), uses parentage analysis to estimate the size of wild populations. Our study examined the precision and accuracy of tGMR through a comparison to a traditional mark-recapture estimate for Chilkat River Chinook salmon (O. tshawytscha) in Southeast Alaska. We examined how adult sampling location and timing impact tGMR by comparing estimates derived using samples collected in the lower river mainstem to those using samples obtained in upriver spawning tributaries. Results indicated that tGMR estimates using a representative sample of mainstem adults were most concordant with, and 3% more precise than, the traditional mark-recapture estimate for this stock. Importantly, the timing and location of adult sampling were found to impact abundance estimates, depending on what proportion of the population dies or moves to unsampled areas between downriver and upriver sampling events. Additionally, we identified potential sources of bias in tGMR arising from violations of key assumptions using a novel individual-based modeling framework, parameterized with empirical values from the Chilkat River. Simulations demonstrated that increased reproductive success and sampling selectivity of older, larger individuals, introduced negative bias into tGMR estimates. Our individual-based model offers a customizable and accessible method to identify and quantify these biases in tGMR applications (https://github.com/swrosenbaum/tGMR_simulations). We underscore the critical role of system-specific sampling design considerations in ensuring the precision and accuracy of tGMR projects. This study validates tGMR as a potentially useful tool for improved population enumeration in semelparous species.

Accounting for unobserved population dynamics and aging error in close-kin mark-recapture assessments

Obtaining robust estimates of population abundance is a central challenge hindering the conservation and management of many threatened and exploited species. Close-kin mark-recapture (CKMR) is a genetics-based approach that has strong potential to improve the monitoring of data-limited species by enabling estimates of abundance, survival, and other parameters for populations that are challenging to assess. However, CKMR models have received limited sensitivity testing under realistic population dynamics and sampling scenarios, impeding the application of the method in population monitoring programs and stock assessments. Here, we use individual-based simulation to examine how unmodeled population dynamics and aging uncertainty affect the accuracy and precision of CKMR parameter estimates under different sampling strategies. We then present adapted models that correct the biases that arise from model misspecification. Our results demonstrate that a simple base-case CKMR model produces robust estimates of population abundance with stable populations that breed annually; however, if a population trend or non-annual breeding dynamics are present, or if year-specific estimates of abundance are desired, a more complex CKMR model must be constructed. In addition, we show that CKMR can generate reliable abundance estimates for adults from a variety of sampling strategies, including juvenile-focused sampling where adults are never directly observed (and aging error is minimal). Finally, we apply a CKMR model that has been adapted for population growth and intermittent breeding to two decades of genetic data from juvenile lemon sharks (Negaprion brevirostris) in Bimini, Bahamas, to demonstrate how application of CKMR to samples drawn solely from juveniles can contribute to monitoring efforts for highly mobile populations. Overall, this study expands our understanding of the biological factors and sampling decisions that cause bias in CKMR models, identifies key areas for future inquiry, and provides recommendations that can aid biologists in planning and implementing an effective CKMR study, particularly for long-lived data-limited species.

Close-kin mark-recapture informs critically endangered terrestrial mammal status

Reliable information on population size is fundamental to the management of threatened species. For wild species, mark-recapture methods are a cornerstone of abundance estimation. Here, we show the first application of the close-kin mark-recapture (CKMR) method to a terrestrial species of high conservation value; the Christmas Island flying-fox (CIFF). The CIFF is the island's last remaining native terrestrial mammal and was recently listed as critically endangered. CKMR is a powerful tool for estimating the demographic parameters central to CIFF management and circumvents the complications arising from the species' cryptic nature, mobility, and difficult-to-survey habitat. To this end, we used genetic data from 450 CIFFs captured between 2015 and 2019 to detect kin pairs. We implemented a novel CKMR model that estimates sex-specific abundance, trend, and mortality and accommodates observations from the kin-pair distribution of male reproductive skew and mate persistence. CKMR estimated CIFF total adult female abundance to be approximately 2050 individuals (95% CI (950, 4300)). We showed that on average only 23% of the adult male population contributed to annual reproduction and strong evidence for between-year mate fidelity, an observation not previously quantified for a Pteropus species in the wild. Critically, our population estimates provide the most robust understanding of the status of this critically endangered population, informing immediate and future conservation initiatives.

SNP Panel and Genomic Sex Identification in Atlantic Halibut (Hippoglossus hippoglossus)

The ability to identify sex is necessary in population biology for a proper understanding of the dynamics of a population. In Atlantic halibut, phenotypic sex identification is not possible due to the lack of significant external morphological differences. We developed an Illumina SNP panel for Atlantic halibut with 4000 SNPs spread evenly throughout the genome with a minor allele frequency MAF ≥ 0.4, except for N = 249 SNPs located in a sex-determining region on chromosome 12, N = 176 of these SNPs were selected to genetically identify male and female individuals using a DAPC analysis. The genomic identification of sex allows for non-lethal sex determination and validation of sex identification in the field. The SNP panel is a new genomic resource for Atlantic halibut that will make it possible to generate the genotypic data for the large number of individuals needed to estimate population abundance using genomics and the Close Kin Mark Recapture (CKMR) approach, an emerging component of fisheries management and stock monitoring.

Burmese pythons in Florida: A synthesis of biology, impacts, and management tools

Burmese pythons (Python molurus bivittatus) are native to southeastern Asia, however, there is an established invasive population inhabiting much of southern Florida throughout the Greater Everglades Ecosystem. Pythons have severely impacted native species and ecosystems in Florida and represent one of the most intractable invasive-species management issues across the globe. The difficulty stems from a unique combination of inaccessible habitat and the cryptic and resilient nature of pythons that thrive in the subtropical environment of southern Florida, rendering them extremely challenging to detect. Here we provide a comprehensive review and synthesis of the science relevant to managing invasive Burmese pythons. We describe existing control tools and review challenges to productive research, identifying key knowledge gaps that would improve future research and decision making for python control.

A simulation-based evaluation of methods for estimating census population size of terrestrial game species from genetically-identified parent-offspring pairs

Estimates of wildlife population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Several methods have recently been developed that estimate abundance using kinship relationships observed in genetic samples, particularly parent-offspring pairs. While these methods are similar to traditional Capture-Mark-Recapture, they do not need physical recapture, as individuals are considered recaptured if a sample contains one or more close relatives. This makes methods based on genetically-identified parent-offspring pairs particularly interesting for species for which releasing marked animals back into the population is not desirable or not possible (e.g., harvested fish or game species). However, while these methods have successfully been applied in commercially important fish species, in the absence of life-history data, they are making several assumptions unlikely to be met for harvested terrestrial species. They assume that a sample contains only one generation of parents and one generation of juveniles of the year, while more than two generations can coexist in the hunting bags of long-lived species, or that the sampling probability is the same for each individual, an assumption that is violated when fecundity and/or survival depend on sex or other individual traits. In order to assess the usefulness of kin-based methods to estimate population sizes of terrestrial game species, we simulated population pedigrees of two different species with contrasting demographic strategies (wild boar and red deer), applied four different methods and compared the accuracy and precision of their estimates. We also performed a sensitivity analysis, simulating population pedigrees with varying fecundity characteristics and various levels of harvesting to identify optimal conditions of applicability of each method. We showed that all these methods reached the required levels of accuracy and precision to be effective in wildlife management under simulated circumstances (i.e., for species within a given range of fecundity and for a given range of sampling intensity), while being robust to fecundity variation. Despite the potential usefulness of the methods for terrestrial game species, care is needed as several biases linked to hunting practices still need to be investigated (e.g., when hunting bags are biased toward a particular group of individuals).

Commerson's dolphin population structure: evidence for female phylopatry and male dispersal

A key in species conservation is understanding the amount and distribution of genetic diversity and how environmental changes that occurred in the recent past may have influenced current patterns of population structure. Commerson's dolphin, Cephalorhynchus commersonii, has two subspecies, one of which is endemic to South America (C. commersonii commersonii) and little is known about its population genetics. Our objective was to investigate the population genetics of this subspecies throughout its distribution. Using 70 skin samples and information available in GenBank, 308 mitochondrial DNA sequences and 28 species-specific microsatellites were analyzed. The species presented low genetic diversity when compared to other dolphin species, but was consistent with other species within the genus. Strong population structure based on mitochondrial DNA was exhibited throughout its entire distribution, a pattern consistent with female philopatry. However, this pattern was not detected when using microsatellites, suggesting male-mediated gene flow. Demographic tests suggested a population expansion beginning approximately 15,000 years ago, after the Last Glacial Maximum. In a climate change scenario, we recommended considering each sampling location as an independent population management unit in order to evaluate the impact of possible environmental changes on the distribution of genetic information within the species.

Rapid assessment of adult abundance and demographic connectivity from juvenile kin pairs in a critically endangered species

The viability of spatially structured populations depends on the abundance and connectivity between subpopulations of breeding adults. Yet, for many species, both are extremely difficult to assess. The speartooth shark is a critically endangered elasmobranch inhabiting tropical rivers with only three adults ever recorded in Australia. Close-kin mark-recapture models, informed by sibling pairs among 226 juveniles, were developed to estimate adult abundance and connectivity in two Australian river systems. Sixty-eight sibling pairs were found, and adult abundance was estimated at 892 for the Adelaide River and 1128 for the Alligator Rivers. We found strong evidence for female philopatry, with most females returning to the same river to pup. Adelaide River males appear largely philopatric, whereas Alligator Rivers males are highly connected to the Adelaide River. From only 4 years of sampling, our results demonstrate that juvenile-only kin pairs can inform simultaneous estimates of abundance and connectivity in a rare and threatened species.

Close-kin mark-recapture methods to estimate demographic parameters of mosquitoes

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance.

Population Structure of White Sturgeon (Acipenser transmontanus) in the Columbia River Inferred from Single-Nucleotide Polymorphisms

White sturgeon (Acipenser transmontanus) are the largest freshwater fish in North America, with reproducing populations in the Sacramento-San Joaquin, Fraser, and Columbia River Basins. Of these, the Columbia River is the largest, but it is also highly fragmented by hydroelectric dams, and many segments are characterized by declining abundance and persistent recruitment failure. Efforts to conserve and supplement these fish requires an understanding of their spatial genetic structure. Here, we assembled a large set of samples from throughout the Columbia River Basin, along with representative collections from adjacent basins, and genotyped them using a panel of 325 single-nucleotide markers. Results from individual- and group-based analyses of these data indicate that white sturgeon in the uppermost Columbia River Basin, in the Kootenai and upper Snake Rivers, are the most distinct, while the remaining populations downstream in the basin can be described as a genetic gradient consistent with an isolation-by-distance effect. Notably, the population in the lowest reaches of the Columbia River is more distinct from the middle or upper reaches than from outside basins, and suggests historically a higher or more recent gene exchange through coastal routes than with populations in the interior Columbia Basin. Nonetheless, proximal reaches were generally only marginally or non-significantly divergent, suggesting that transplanting larvae or juveniles from nearby sources poses relatively little risk of outbreeding depression. Indeed, we inferred examples of dispersal between reaches via close-kin mark-recapture and genetic mark-recapture that indicate movement between nearby reaches is not unusual. Samples from the Kootenai and upper Snake Rivers exhibited notably lower genetic diversity than the remaining samples as a result of population bottlenecks, genetic drift, and/or historical divergence. Conservation actions, such as supplementation, are underway to maintain population viability and will require balanced efforts to increase demographic abundance while maintaining genetic diversity.

Low levels of sibship encourage use of larvae in western Atlantic bluefin tuna abundance estimation by close-kin mark-recapture

Globally, tunas are among the most valuable fish stocks, but are also inherently difficult to monitor and assess. Samples of larvae of Western Atlantic bluefin tuna Thunnus thynnus (Linnaeus, 1758) from standardized annual surveys in the northern Gulf of Mexico provide a potential source of "offspring" for close-kin mark-recapture (CKMR) estimates of abundance. However, the spatial patchiness and highly skewed numbers of larvae per tow suggest sampled larvae may come from a small number of parents, compromising the precision of CKMR. We used high throughput genomic profiling to study sibship within and among larval tows from the 2016 standardized Gulf-wide survey compared to targeted sampling carried out in 2017. Full- and half-siblings were found within both years, with 12% of 156 samples in 2016 and 56% of 317 samples in 2017 having at least one sibling. There were also two pairs of cross cohort half-siblings. Targeted sampling increased the number of larvae collected per sampling event but resulted in a higher proportion of siblings. The combined effective sample size across both years was about 75% of the nominal size, indicating that Gulf of Mexico larval collections could be a suitable source of juveniles for CKMR in Western Atlantic bluefin tuna.

How continuing mortality affects recovery potential for prohibited sharks: The case of white sharks in South Africa

It can be difficult to determine whether a prohibition to exploitation ensures effective conservation or recovery for species that remain exposed to fishing effort and other sources of mortality throughout their range. Here we used simulation modeling of four life history scenarios (different productivity and population size) to contextualize potential population response to multiple levels of mortality, using white sharks (Carcharodon carcharias) in South Africa as a case study. The species has been protected since 1991, yet substantial uncertainty about population dynamics persists and recent declines at two aggregation sites have renewed conservation concern. All scenarios indicated that annual removals in the 10s of individuals would substantially limit the potential for and magnitude of any abundance increase following prohibition. Because average known removals from the KwaZulu-Natal Sharks Board’s Bather Protection Program have typically remained higher than these thresholds, they likely eliminated much of the conservation benefit derived from prohibition. The only life history scenario to achieve appreciable increase when simulated removals were similar to published averages assumed maturation occurred at a much younger age than currently understood. Our results demonstrate why general application of life history-based simulations can provide a useful mechanism to evaluate the biological plausibility of life history information and abundance trends, and to explore the scope for population response to recovery actions. For South Africa, our results suggest that even known levels of white shark removals, which likely underestimate total removals within their range, may be sufficient to drive abundance decline and new mitigation measures may be required to ensure population recovery.

Genome-wide analysis reveals the genetic stock structure of hoki (Macruronus novaezelandiae)

The assessment of the genetic structuring of biodiversity is crucial for management and conservation. This is particularly critical for widely distributed and highly mobile deep-water teleosts, such as hoki (Macruronus novaezelandiae). This species is significant to Māori people and supports the largest commercial fishery in New Zealand, but uncertainty about its stock structure presents a challenge for management. Here, we apply a comprehensive genomic analysis to shed light on the demographic structure of this species by (1) assembling the genome, (2) generating a catalogue of genome-wide SNPs to infer the stock structure and (3) identifying regions of the genome under selection. The final genome assembly used short and long reads and is near complete, representing 93.8% of BUSCO genes, and consisting of 566 contigs totalling 501 Mb. Whole-genome re-sequencing of 510 hoki sampled from 14 locations around New Zealand and Australia, at a read depth greater than 10×, produced 227,490 filtered SNPs. Analyses of these SNPs were able to resolve the stock structure of hoki into two genetically and geographically distinct clusters, one including the Australian and the other one all New Zealand locations, indicating genetic exchange between these regions is limited. Location differences within New Zealand samples were much more subtle (global F ST  = 0.0006), and while small and significant differences could be detected, they did not conclusively identify additional substructures. Ten putative adaptive SNPs were detected within the New Zealand samples, but these also did not geographically partition the dataset further. Contemporary and historical N e estimation suggest the current New Zealand population of hoki is large yet declining. Overall, our study provides the first genomic resources for hoki and provides detailed insights into the fine-scale population genetic structure to inform the management of this species.

Individual haplotyping of whale sharks from seawater environmental DNA

Population genetic data can provide valuable information on the demography of a species. For rare and elusive marine megafauna, samples for generating the data are traditionally obtained from tissue biopsies, which can be logistically difficult and expensive to collect and require invasive sampling techniques. Analysis of environmental DNA (eDNA) offers an alternative, minimally invasive approach to provide important genetic information. Although eDNA approaches have been studied extensively for species detection and biodiversity monitoring in metabarcoding studies, the potential for the technique to address population-level questions remains largely unexplored. Here, we applied "eDNA haplotyping" to obtain estimates of the intraspecific genetic diversity of a whale shark (Rhincodon typus) aggregation at Ningaloo reef, Australia. Over 2 weeks, we collected seawater samples directly behind individual sharks prior to taking a tissue biopsy sample from the same animal. Our data showed a 100% match between mtDNA sequences recovered in the eDNA and tissue sample for all 28 individuals sampled. In the seawater samples, >97% of all reads were assigned to six dominant haplotypes, and a clear dominant signal (~99% of sample reads) was recovered in each sample. Our study demonstrates accurate individual-level haplotyping from seawater eDNA. When DNA from one individual clearly dominates each eDNA sample, it provides many of the same opportunities for population genetic analyses as a tissue sample, potentially removing the need for tissue sampling. Our results show that eDNA approaches for population-level analyses have the potential to supply critical demographic data for the conservation and management of marine megafauna.

Population abundance in arctic grayling using genetics and close-kin mark-recapture

Arctic Grayling (Thymallus arcticus) are among the most widely distributed and abundant freshwater fish in the Yukon Territory of Canada, yet little information exists regarding their broad and fine-scale population structures or the number and size of these populations. The estimation of population abundance is fundamental for robust management and conservation, yet estimating abundance in the wild is often difficult. Here, we estimated abundance of an Arctic Grayling population using multiple genetic markers and the close-kin mark-recapture (CKMR) method. A total of N = 1,104 Arctic Grayling collected from two systems in Yukon were genotyped at 38 sequenced microsatellites. We first identified structure and assessed genetic diversity (effective population size,N ^ e ). Collections from one of the systems (Lubbock River) comprised adults and young-of-the-year sampled independently allowing the identification of parent-offspring pairs (POPs), and thus, the estimation of abundance using CKMR. We used COLONY and CKMRsim to identify POPs and both provided similar results leading to indistinguishable estimates (95% CI) of census size, that is,N ^ c ( C O L O N Y ) = 1858 (1259-2457) andN ^ c ( C K M R s i m ) = 1812 (1229-2389). The accuracy of the population abundance estimates can in the future be improved with temporal sampling and more precise age or size-specific fecundity estimates for Arctic Grayling. Our study demonstrates that the method can be used to inform management and conservation policy for Arctic Grayling and likely also for other fish species for which the assumption of random and independent sampling of adults and offspring can be assured.

Considering sampling bias in close-kin mark-recapture abundance estimates of Atlantic salmon

Genetic methods for the estimation of population size can be powerful alternatives to conventional methods. Close-kin mark-recapture (CKMR) is based on the principles of conventional mark-recapture, but instead of being physically marked, individuals are marked through their close kin. The aim of this study was to evaluate the potential of CKMR for the estimation of spawner abundance in Atlantic salmon and how age, sex, spatial, and temporal sampling bias may affect CKMR estimates. Spawner abundance in a wild population was estimated from genetic samples of adults returning in 2018 and of their potential offspring collected in 2019. Adult samples were obtained in two ways. First, adults were sampled and released alive in the breeding habitat during spawning surveys. Second, genetic samples were collected from out-migrating smolts PIT-tagged in 2017 and registered when returning as adults in 2018. CKMR estimates based on adult samples collected during spawning surveys were somewhat higher than conventional counts. Uncertainty was small (CV < 0.15), due to the detection of a high number of parent-offspring pairs. Sampling of adults was age- and size-biased and correction for those biases resulted in moderate changes in the CKMR estimate. Juvenile dispersal was limited, but spatially balanced sampling of adults rendered CKMR estimates robust to spatially biased sampling of juveniles. CKMR estimates based on returning PIT-tagged adults were approximately twice as high as estimates based on samples collected during spawning surveys. We suggest that estimates based on PIT-tagged fish reflect the total abundance of adults entering the river, while estimates based on samples collected during spawning surveys reflect the abundance of adults present in the breeding habitat at the time of spawning. Our study showed that CKMR can be used to estimate spawner abundance in Atlantic salmon, with a moderate sampling effort, but a carefully designed sampling regime is required.

Estimating Population Abundance of Burying Beetles Using Photo-Identification and Mark-Recapture Methods

Successful conservation and management of protected wildlife populations require reliable population abundance data. Traditional capture-mark-recapture methods can be costly, time-consuming, and invasive. Photographic mark-recapture (PMR) is a cost-effective, minimally invasive way to study population dynamics in species with distinct markings or color patterns. We tested the feasibility and the application of PMR using the software Hotspotter to identify Nicrophorus spp. from digital images of naturally occurring spot patterns on their elytra. We conducted a laboratory study evaluating the identification success of Hotspotter on Nicrophorus americanus (Olivier, 1790) and Nicrophorus orbicollis (Say, 1825) before implementation of a mark-recapture study in situ. We compared the performance of Hotspotter using both 'high-quality' and 'low-quality' photographs. For high-quality photographs, Hotspotter had a false rejection rate of 2.7-3.0% for laboratory-reared individuals and 3.9% for wild-caught individuals. For low-quality photographs, the false rejection rate was much higher, 48.8-53.3% for laboratory-reared individuals and 28.3% for wild-caught individuals. We subsequently analyzed encounter histories of wild-caught individuals with closed population models in Program MARK to estimate population abundance. In our study, we demonstrated the utility of using PMR in estimating population abundance for Nicrophorus spp. based on elytral spot patterns.

Effective number of white shark (Carcharodon carcharias, Linnaeus) breeders is stable over four successive years in the population adjacent to eastern Australia and New Zealand

Population size is a central parameter for conservation; however, monitoring abundance is often problematic for threatened marine species. Despite substantial investment in research, many marine species remain data-poor presenting barriers to the evaluation of conservation management outcomes and the modeling of future solutions. Such is the case for the white shark (Carcharodon carcharias), a highly mobile apex predator for whom recent and substantial population declines have been recorded in many globally distributed populations. Here, we estimate the effective number of breeders that successfully contribute offspring in one reproductive cycle (Nb) to provide a snapshot of recent reproductive effort in an east Australian-New Zealand population of white shark. Nb was estimated over four consecutive age cohorts (2010, 2011, 2012, and 2013) using two genetic estimators (linkage disequilibrium; LD and sibship assignment; SA) based on genetic data derived from two types of genetic markers (single nucleotide polymorphisms; SNPs and microsatellite loci). While estimates of Nb using different marker types produced comparable estimates, microsatellite loci were the least precise. The LD and SA estimates of Nb within cohorts using SNPs were comparable; for example, the 2013 age cohort Nb(SA) was 289 (95% CI 200-461) and Nb(LD) was 208.5 (95% CI 116.4-712.7). We show that over the time period studied, Nb was stable and ranged between 206.1 (SD ± 45.9) and 252.0 (SD ± 46.7) per year using a combined estimate of Nb(LD+SA) from SNP loci. In addition, a simulation approach showed that in this population the effective population size (Ne) per generation can be expected to be larger than Nb per reproductive cycle. This study demonstrates how breeding population size can be monitored over time to provide insight into the effectiveness of recovery and conservation measures for the white shark, where the methods described here may be applicable to other data-poor species of conservation concern.

Robustness of close-kin mark-recapture estimators to dispersal limitation and spatially varying sampling probabilities

Close-kin mark-recapture (CKMR) is a method for estimating abundance and vital rates from kinship relationships observed in genetic samples. CKMR inference only requires animals to be sampled once (e.g., lethally), potentially widening the scope of population-level inference relative to traditional monitoring programs.One assumption of CKMR is that, conditional on individual covariates like age, all animals have an equal probability of being sampled. However, if genetic data are collected opportunistically (e.g., via hunters or fishers), there is potential for spatial variation in sampling probability that can bias CKMR estimators, particularly when genetically related individuals stay in close proximity.We used individual-based simulation to investigate consequences of dispersal limitation and spatially biased sampling on performance of naive (nonspatial) CKMR estimators of abundance, fecundity, and adult survival. Population dynamics approximated that of a long-lived mammal species subject to lethal sampling.Naive CKMR abundance estimators were relatively unbiased when dispersal was unconstrained (i.e., complete mixing) or when sampling was random or subject to moderate levels of spatial variation. When dispersal was limited, extreme variation in spatial sampling probabilities negatively biased abundance estimates. Reproductive schedules and survival were well estimated, except for survival when adults could emigrate out of the sampled area. Incomplete mixing was readily detected using Kolmogorov-Smirnov tests.Although CKMR appears promising for estimating abundance and vital rates with opportunistically collected genetic data, care is needed when dispersal limitation is coupled with spatially biased sampling. Fortunately, incomplete mixing is easily detected with adequate sample sizes. In principle, it is possible to devise and fit spatially explicit CKMR models to avoid bias under dispersal limitation, but development of such models necessitates additional complexity (and possibly additional data). We suggest using simulation studies to examine potential bias and precision of proposed modeling approaches prior to implementing a CKMR program.