Estimating abundance of a recovering transboundary brown bear population with capture-recapture models

Abundance of small populations of large mammals may be assessed using complete counts of the different individuals detected over a time period, so-called minimum detected size (MDS). However, as population is growing larger and its distribution is expanding wider, the risk of under-estimating population size using MDS is increasing sharply due to the rarely fulfilled assumption of perfect detection of all individuals of the population, and as a result, the need to report uncertainty in population size estimates becomes crucial. We addressed these issues within the framework of the monitoring of the critically endangered Pyrenean brown bear population that was on the edge of extinction in the mid-1990s with only five individuals remaining, but was reinforced by 11 bears originated from Slovenia since then. We used Pollock's closed robust design (PCRD) capture-recapture models applied to the cross-border non-invasive sampling data from France, Spain and Andorra to provide the first published annual abundance estimates of the Pyrenean brown bear population and its trends over time. Annual population size increased and displayed a fivefold rise between 2008 and 2020, reaching > 60 individuals in 2020. Detection heterogeneity among individuals may stem from intraspecific home range size disparities making it more likely to find signs of individuals who move more. We found a lower survival rate in cubs than in adults and subadults, since the formers suffer from more mortality risks (such as infanticides, predations, mother death or abandonments) than the latters. Our study provides evidence that the PCRD capture-recapture modelling approach can provide reliable estimates of the size of and trend in large mammal populations, while minimizing bias due to inter-individual heterogeneity in detection probabilities and allowing the quantification of sampling uncertainty surrounding these estimates. Such information is vital for informing management decision-making and assessing population conservation status.

Comparison of Minimally Invasive Monitoring Methods and Live Trapping in Mammals

The conservation and management of wildlife requires the accurate assessment of wildlife population sizes. However, there is a lack of synthesis of research that compares methods used to estimate population size in the wild. Using a meta-analysis approach, we compared the number of detected individuals in a study made using live trapping and less invasive approaches, such as camera trapping and genetic identification. We scanned 668 papers related to these methods and identified data for 44 populations (all focused on mammals) wherein at least two methods (live trapping, camera trapping, genetic identification) were used. We used these data to quantify the difference in number of individuals detected using trapping and less invasive methods using a regression and used the residuals from each regression to evaluate potential drivers of these trends. We found that both trapping and less invasive methods (camera traps and genetic analyses) produced similar estimates overall, but less invasive methods tended to detect more individuals compared to trapping efforts (mean = 3.17 more individuals). We also found that the method by which camera data are analyzed can significantly alter estimates of population size, such that the inclusion of spatial information was related to larger population size estimates. Finally, we compared counts of individuals made using camera traps and genetic data and found that estimates were similar but that genetic approaches identified more individuals on average (mean = 9.07 individuals). Overall, our data suggest that all of the methods used in the studies we reviewed detected similar numbers of individuals. As live trapping can be more costly than less invasive methods and can pose more risk to animal well-fare, we suggest minimally invasive methods are preferable for population monitoring when less-invasive methods can be deployed efficiently.

Estimation and Probabilistic Linkage in Sample Surveys of Anonymous Organisations

<p>Drug use takes on many forms, normally this will be just the occasional alcoholic drink, certain individuals drug use develops into habitual use, or more extreme drugs, and then into full addiction. Some of these addicted individuals realise the harmful nature of their addition and join the anonymous support group, Narcotics Anonymous. This study focus' on the creation of population size estimates, and an estimate of the size of the persistent population between two survey years. These estimates are created from the 2004 and 2008 surveys run by the Narcotics Anonymous Fellowship, as this is an anonymous organisation with no register of the membership database maintained. Population size estimation for an anonymous organisation is established using simulation methods. The bootstrap estimation was used to estimate characteristics about the two populations. Probabilistic matching was used to identify individuals who were in both the 2004, and 2008 surveys. Once identi ed, a logistic regression model was used to establish what impacts an individual to remain in the programme. Factors that impacted an individual being persistent in the population included the individual education, employment status, and if they had worked through all the 12 steps of Narcotics Anonymous.</p>

Estimation and Probabilistic Linkage in Sample Surveys of Anonymous Organisations

<p>Drug use takes on many forms, normally this will be just the occasional alcoholic drink, certain individuals drug use develops into habitual use, or more extreme drugs, and then into full addiction. Some of these addicted individuals realise the harmful nature of their addition and join the anonymous support group, Narcotics Anonymous. This study focus' on the creation of population size estimates, and an estimate of the size of the persistent population between two survey years. These estimates are created from the 2004 and 2008 surveys run by the Narcotics Anonymous Fellowship, as this is an anonymous organisation with no register of the membership database maintained. Population size estimation for an anonymous organisation is established using simulation methods. The bootstrap estimation was used to estimate characteristics about the two populations. Probabilistic matching was used to identify individuals who were in both the 2004, and 2008 surveys. Once identi ed, a logistic regression model was used to establish what impacts an individual to remain in the programme. Factors that impacted an individual being persistent in the population included the individual education, employment status, and if they had worked through all the 12 steps of Narcotics Anonymous.</p>

The Remnant Leiopelma Pakeka (Anura: Leiopelmatidae) Population on Maud Island: Population Size, Distribution and Morphology

<p>Leiopelma pakeka is an archaic frog native to New Zealand, and until recently was restricted to a 15ha forest remnant on the south-east face of Maud Island. The L.pakeka population appears to be growing and spreading out from the forest remnant. This study investigated the population size, structure, and distribution of L. pakeka on Maud Island in 2006. The forest remnant was searched using 106 randomly placed 25m2 plots. Population size was estimated using a bootstrap method repeated 10,000 times, adjusted for likelihood of emergence, likely maximum plot population size, and area. The average population size was 34,449 frogs, which is much higher than a 1994 minimum number alive estimate of 19,312. The new figure, however, is similar to another recent estimate of 39,563, based on an update of the 1994 figure. Distributional patterns within the forest remnant were similar to the 1994 study, with most frogs between 90-170m above sea level. The comparability of the population size estimates indicates that L. pakeka numbers have reached the carrying capacity of the forest remnant. The distribution of the remnant L. pakeka population was determined by thoroughly searching the south-east face of Maud Island, thereby minimising the possibility of missing frogs. A total of 232 frogs were found. Frogs generally colonised areas within 50m of the remnant; movement was greater in regenerating forest (75m in the southwest and 100m in the north east) than in pastoral areas (<25m). The size of frogs increased with distance from the forest remnant (weight, girth, condition index, and average snout-vent and tibio-fibula lengths). The size increases may be indications of competitive release, as frog density decreased with distance from the forest remnant. The size range of Leiopelma pakeka was extended by the current study from 50.5mm to at least 52mm snout-vent length. A total of 15 L. pakeka were found on Fort Road, approximately 350m from the remnant. These frogs were most likely in the area before 1994. The Fort Road frogs were compared to the forest remnant L. pakeka, and were not morphologically distinct as only patterning differed significantly. Fort Road L. pakeka may belong to a separate subpopulation. L. pakeka distribution was significantly affected by habitat. Important variables were vegetation type, and rock, canopy, sub-canopy, and leaf litter cover. The size of emergent frogs (tibio-fibula length) was significantly and positively correlated with relative humidity.</p>

The Remnant Leiopelma Pakeka (Anura: Leiopelmatidae) Population on Maud Island: Population Size, Distribution and Morphology

<p>Leiopelma pakeka is an archaic frog native to New Zealand, and until recently was restricted to a 15ha forest remnant on the south-east face of Maud Island. The L.pakeka population appears to be growing and spreading out from the forest remnant. This study investigated the population size, structure, and distribution of L. pakeka on Maud Island in 2006. The forest remnant was searched using 106 randomly placed 25m2 plots. Population size was estimated using a bootstrap method repeated 10,000 times, adjusted for likelihood of emergence, likely maximum plot population size, and area. The average population size was 34,449 frogs, which is much higher than a 1994 minimum number alive estimate of 19,312. The new figure, however, is similar to another recent estimate of 39,563, based on an update of the 1994 figure. Distributional patterns within the forest remnant were similar to the 1994 study, with most frogs between 90-170m above sea level. The comparability of the population size estimates indicates that L. pakeka numbers have reached the carrying capacity of the forest remnant. The distribution of the remnant L. pakeka population was determined by thoroughly searching the south-east face of Maud Island, thereby minimising the possibility of missing frogs. A total of 232 frogs were found. Frogs generally colonised areas within 50m of the remnant; movement was greater in regenerating forest (75m in the southwest and 100m in the north east) than in pastoral areas (<25m). The size of frogs increased with distance from the forest remnant (weight, girth, condition index, and average snout-vent and tibio-fibula lengths). The size increases may be indications of competitive release, as frog density decreased with distance from the forest remnant. The size range of Leiopelma pakeka was extended by the current study from 50.5mm to at least 52mm snout-vent length. A total of 15 L. pakeka were found on Fort Road, approximately 350m from the remnant. These frogs were most likely in the area before 1994. The Fort Road frogs were compared to the forest remnant L. pakeka, and were not morphologically distinct as only patterning differed significantly. Fort Road L. pakeka may belong to a separate subpopulation. L. pakeka distribution was significantly affected by habitat. Important variables were vegetation type, and rock, canopy, sub-canopy, and leaf litter cover. The size of emergent frogs (tibio-fibula length) was significantly and positively correlated with relative humidity.</p>

Key population size estimation in Nigeria: applying novel Bayesian methods for analysis of three-source capture-recapture data (Preprint)

BACKGROUND Nigeria has the fourth largest burden of HIV globally. Key populations (KP) including female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have poor social visibility and are more vulnerable to HIV than the general population due to stigma, discrimination, and criminalization of KP-defining behaviors. Reliable, empirical population size estimates (PSE) are needed to guide focused and appropriately scaled HIV epidemic response efforts for KP. We used novel approaches to sampling and analysis to calculate PSE in Nigeria. OBJECTIVE We sampled the population using three-source capture-recapture (3S-CRC) and analyzed results using Bayesian nonparametric latent-class models to generate median PSE with 80% highest density intervals. METHODS During October–December 2018, we used three-source capture-recapture (3S-CRC) to estimate the size of KP in seven United States President’s Emergency Plan for AIDS Relief (PEPFAR) priority states in Nigeria. Hotspots were mapped before 3S-CRC started. We sampled FSW, MSM, and PWID during three independent captures approximately one week apart. During encounters in KP hotspots, distributors offered inexpensive and memorable objects to KP, unique to each capture round and KP type. In subsequent rounds, participants were offered an object and asked to produce or identify objects received during previous rounds (if any); affirmative responses were tallied upon producing or identifying the correct object. Distributors recorded responses on tablets and uploaded to a secure server after each encounter. Data were aggregated by KP and state for analysis. Median PSE were derived using Bayesian nonparametric latent-class models with 80% highest density intervals for precision. RESULTS We sampled approximately 310,000 persons at 9,015 hotspots during three independent captures in all seven states. Overall, FSW PSE ranged from 14,500-64,300; MSM PSE, 3,200-41,400; and PWID PSE, 3,400-30,400. CONCLUSIONS This study represents the first implementation of these 3S-CRC sampling and novel analysis methods for large-scale population size estimation in Nigeria. Overall, our estimates were larger than previously documented for each KP in all states. The current Bayesian models account for factors (i.e., social visibility and stigma) that influence heterogeneous capture probabilities resulting in more reliable PSE. The larger estimates suggest a need for programmatic scale-up to reach these populations at highest risk for HIV.

Insights Into Sea Turtle Population Composition Obtained With Stereo-Video Cameras in situ Across Nearshore Habitats in the Northeastern Gulf of Mexico

Population size estimates are key parameters used in assessments to evaluate and determine a species’ conservation status. Typically, sea turtle population estimates are made from nesting beach surveys which capture only hatchling and adult female life stages and can display trends opposite of the full population. As such, in-water studies are critical to improve our understanding of sea turtle population dynamics as they can target a broader range of life stages – though they are more logistically and financially challenging to execute compared to beach-based surveys. Stereo-video camera systems (SVCS) hold promise for improving in-water assessments by removing the need to physically capture individuals and instead extract 3D measurements from video footage, thereby simplifying monitoring logistics and improving safety for the animals and surveyors. To demonstrate this potential, snorkel surveys were conducted at artificial habitats in the northeastern Gulf of Mexico (neGOM) to collect size and photo-identification data on sea turtles in situ using a SVCS. Over 29.86 survey hours, 35 sea turtles were observed across three species (Caretta caretta, Chelonia mydas, and Lepidochelys kempii) and all neritic life stages (juvenile, sub-adult, and adult) utilizing different habitats, including artificial reefs, jetties, and fishing piers. Greens straight carapace length ranged from 28.55 to 66.96 cm (n = 23, mean 43.07 cm ± 11.26 cm standard deviation; SD) and loggerheads ranged from 59.71 to 91.77 cm (n = 10, mean 74.50 cm ± 11.35 cm SD), and Kemp’s ridleys ranged from 42.23 cm to 44.98 cm (mean 43.61 cm ± 1.94 cm SD). Using a linear mixed model, we found that species and habitat type were the most important predictors of sea turtle body length distribution. Overall, this case study demonstrates the potential of SVCS surveys to enhance our understanding of the population structure of sea turtle species within the neGOM and elsewhere.

Genetic Diversity and Relatedness among Captive African Painted Dogs in North America

African painted dogs (Lycaon pictus, APD) are highly endangered, with fewer than 7000 remaining in nature. Captive breeding programs can preserve a genetically diverse population and provide a source of individuals for reintroductions. However, most programs are initiated from few founders and suffer from low genetic diversity and inbreeding. The aims of this study were to use molecular markers to assess genetic variation, inbreeding, and relatedness among APDs in the North American captive population, to use these data to realign studbook records, and to compare these data to wild populations and to the European captive population to facilitate the development of a global management plan. We sequenced mitochondrial and major histocompatibility (MHC) class II loci and genotyped 14 microsatellite loci from 109 APDs from 34 institutions in North America. We identified three likely studbook errors and resolved ten cases of uncertain paternity. Overall, microsatellite heterozygosity was higher than reported in Europe, but effective population size estimates were lower. Mitochondrial sequence variation was extremely limited, and there were fewer MHC haplotypes than in Europe or the wild. Although the population did not show evidence of significant inbreeding overall, several individuals shared high relatedness values, which should be incorporated into future breeding programs.