Capture-recapture Data Research Articles

Demography, genetics, and decline of a spatially structured population of lekking bird.

Understanding the mechanisms underlying population decline is a critical challenge for conservation biologists. Both deterministic (e.g. habitat loss, fragmentation, and Allee effect) and stochastic (i.e. demographic and environmental stochasticity) demographic processes are involved in population decline. Simultaneously, a decrease of population size has far-reaching consequences for genetics of populations by increasing the risk of inbreeding and the strength of genetic drift, which together inevitably results in a loss of genetic diversity and a reduced effective population size ([Formula: see text]). These genetic factors may retroactively affect vital rates (a phenomenon coined 'inbreeding depression'), reduce population growth, and accelerate demographic decline. To date, most studies that have examined the demographic and genetic processes driving the decline of wild populations have neglected their spatial structure. In this study, we examined demographic and genetic factors involved in the decline of a spatially structured population of a lekking bird, the western capercaillie (Tetrao urogallus). To address this issue, we collected capture-recapture and genetic data over a 6-years period in the Vosges Mountains (France). Our study showed that the population of T. urogallus experienced a severe decline between 2010 and 2015. We did not detect any Allee effect on survival and recruitment. By contrast, individuals of both sexes dispersed to avoid small subpopulations, thus suggesting a potential behavioral response to a mate finding Allee effect. In parallel to this demographic decline, the population showed low levels of genetic diversity, high inbreeding and low effective population sizes at both subpopulation and population levels. Despite this, we did not detect evidence of inbreeding depression: neither adult survival nor recruitment were affected by individual inbreeding level. Our study underlines the benefit from combining demographic and genetic approaches to investigate processes that are involved in population decline.

Spatial capture-recapture with random thinning for unidentified encounters.

Spatial capture–recapture (SCR) models have increasingly been used as a basis for combining capture–recapture data types with variable levels of individual identity information to estimate population density and other demographic parameters. Recent examples are the unmarked SCR (or spatial count model), where no individual identities are available and spatial mark–resight (SMR) where individual identities are available for only a marked subset of the population. Currently lacking, though, is a model that allows unidentified samples to be combined with identified samples when there are no separate classes of “marked” and “unmarked” individuals and when the two sample types cannot be considered as arising from two independent observation models. This is a common scenario when using noninvasive sampling methods, for example, when analyzing data on identified and unidentified photographs or scats from the same sites.Here we describe a “random thinning” SCR model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model. Our model was fitted in a Bayesian framework using NIMBLE.We investigate the improvement in parameter estimates by including the unknown identity samples, which was notable (up to 79% more precise) in low‐density populations with a low rate of identified encounters. We then applied the random thinning SCR model to a noninvasive genetic sampling study of brown bear (Ursus arctos) density in Oriental Cantabrian Mountains (North Spain).Our model can improve density estimation for noninvasive sampling studies for low‐density populations with low rates of individual identification, by making use of available data that might otherwise be discarded.

How Ideas from Ecological Capture-Recapture Models May Inform Multiple Systems Estimation Analyses

Abundance estimation, for both human and animal populations, informs policy decisions and population management. Capture-recapture and multiple sources data share a common structure; the population can be partially enumerated and individuals are identifiable. Consequently, the analytical methods were developed simultaneously. However, whilst ecological models have been developed to describe highly complex, biologically realistic scenarios, for example modeling population changes through time and combining different forms of data, multiple systems estimation has changed comparatively less so. In this paper we provide a brief description of the historical development of ecological and epidemiological capture-recapture and discuss the associated underlying differences that have led to model divergence. We identify three key areas where ecological modeling methods may inform and improve multiple systems estimation.

Not Singing in the Rain: Linking Migratory Songbird Declines With Increasing Precipitation and Brood Parasitism Vulnerability

Few empirical studies have quantified relationships between changing weather and migratory songbirds, but such studies are vital in a time of rapid climate change. Climate change has critical consequences for avian breeding ecology, geographic ranges, and migration phenology. Changing precipitation and temperature patterns affect habitat, food resources, and other aspects of birds’ life history strategies. Such changes may disproportionately affect species confined to rare or declining ecosystems, such as temperate grasslands, which are among the most altered and endangered ecosystems globally. We examined the influence of changing weather on the dickcissel (Spiza americana), a migratory songbird of conservation concern that is an obligate grassland specialist. Our study area in the North American Great Plains features high historic weather variability, where climate change is now driving higher precipitation and temperatures as well as higher frequencies of extreme weather events including flooding and droughts. Dickcissels share their breeding grounds with brown-headed cowbirds (Molothrus ater), brood parasites that lay their eggs in the nests of other songbirds, reducing dickcissel productivity. We used 9 years of capture-recapture data collected over an 18-year period to test the hypothesis that increasing precipitation on dickcissels’ riparian breeding grounds is associated with abundance declines and increasing vulnerability to cowbird parasitism. Dickcissels declined with increasing June precipitation, whereas cowbirds, by contrast, increased. Dickcissel productivity appeared to be extremely low, with a 3:1 ratio of breeding male to female dickcissels likely undermining reproductive success. Our findings suggest that increasing precipitation predicted by climate change models in this region may drive future declines of dickcissels and other songbirds. Drivers of these declines may include habitat and food resource loss related to flooding and higher frequency precipitation events as well as increased parasitism pressure by cowbirds. Positive correlations of June-July precipitation, temperature, and time since grazing with dickcissel productivity did not mitigate dickcissels’ declining trend in this ecosystem. These findings highlight the importance of empirical research on the effects of increasing precipitation and brood parasitism vulnerability on migratory songbird conservation to inform adaptive management under climate change.

Sharing wintering grounds does not synchronize annual survival in a high Arctic seabird, the little auk

Sharing the same wintering grounds by avian populations breeding in various areas may synchronize fluctuations in vital rates, which could increase the risk of extinction. Here, by combining multi-colony tracking with long-term capture-recapture data, we studied the winter distribution and annual survival of the most numerous Arctic seabird, the little aukAlle alle. We assessed whether little auks from different breeding populations in Svalbard and Franz Josef Land use the same wintering grounds and if this leads to synchronized survival. Our results indicate that birds from the Svalbard colonies shared similar wintering grounds, although differences existed in the proportion of birds from each colony using the different areas. Little auks from Franz Josef Land generally spent the winter in a separate area, but some individuals wintered in the Iceland Sea with Svalbard populations. Survival data from 3 Svalbard colonies collected in 2005-2018 indicated that sharing wintering grounds did not synchronize little auk annual survival rates. However, it is clear that the Iceland Sea is an important wintering area for little auks, and environmental changes in this area could have widespread impacts on many populations.

Capture-recapture Techniques in Estimating the HIV/Hepatitis Prevalence in Gboko, Benue State Nigeria

Capture-Recapture technique is used to estimate the number of individuals in a population. This study aimed at estimating the number of HIV/Hepatitis co-infection individuals in Gboko Local Government Area of Benue state, in order to plan or create more awareness of HIV/Hepatitis and to take control measures and prevention. The data were sourced from three data sources namely; General Hospital Gboko, Myom Hospital Gboko and NKST Hospital Mkar. The records showed that, between year 2015-2018, 1,205 HIV/Hepatitis patients registered in Gboko Local Government Area, 662 (54.94%) were identified in General Hospital (GH), 357 (29.63%) in Myom Hospital (MH) and 186 (15.44%) in Nongo Kristu u ser u Sha Tar (NKST) Hospital. Matching the records revealed that, 62 HIV/Hepatitis co-infection individuals or patients were captured by the three data source all together; 31(50%) were captured in General Hospital and Myom Hospital, 15(24.19%) in General Hospital and NKST Hospital, 5(8.07%) in Myom and NKST Hospitals and 11(17.74%) in General Hospital, Myom and NKST Hospitals. The three (3) health facilities were treated as 3 source capture-recapture (C-R) data to estimate the population size of HIV/Hepatitis co-infection in the study Area. The data was analyzed using record linkage/matching and log-linear model techniques, also R statistical package software was used to run the data. The results show that, the model that best fit the data is model (4) with interaction GH+MH+NKST+NKST*GH+NKST*MH with the estimated HIV/Hepatitis co-infected patients at 7182 with a 95% confidence interval of, 5348-10128. The total coverage stood at 16% , this implies that only 16% of the HIV/Hepatitis infected persons are recorded in the study area. Thus expanded data collection and analysis is recommended.

Glucocorticoid levels are linked to lifetime reproductive success and survival of adult barn owls.

Glucocorticoid hormones, such as corticosterone, are crucial in regulating daily life metabolism and energy expenditure, as well as promoting short-term physiological and behavioural responses to unpredictable environmental challenges. Therefore, glucocorticoids are considered to mediate trade-offs between survival and reproduction. Relatively little is known about how selection has shaped glucocorticoid levels. We used 15years of capture-recapture and dead recovery data combined with 13years of corticosterone and breeding success data taken on breeding barn owls (Tyto alba) to investigate such trade-offs. We found that survival was positively correlated with stress-induced corticosterone levels in both sexes, whereas annual and lifetime reproductive success (i.e. the sum of young successfully fledged during the entire reproductive career) was positively correlated with both baseline and stress-induced corticosterone levels in females only. Our results suggest that, in the barn owl, the stress-induced corticosterone response is a good proxy for adult survival and lifetime reproductive success. However, selection pressure appears to act differently on corticosterone levels of males and females.

Abundance, survival and population growth of killer whales Orcinus orca at subantarctic Marion Island

Killer whales, Orcinus orca, are a cosmopolitan species with large ecological and demographic variation across populations. Population‐specific demographic studies are, therefore, crucial in accurately assessing the status and trends of local killer whale populations. Such studies require long‐term datasets and remain scarce, particularly in the Southern Ocean where detailed population specific studies have only been conducted at a single archipelago – Îles Crozet. Here, we analysed 12 years of capture–recapture data (comprising nearly 90 000 identification photographs taken from 2006 to 2018) of killer whales at subantarctic Marion Island (46°54′S, 37°45′E) to estimate the abundance, survival and growth rate of this population. Demographic parameters were estimated using multistate capture recapture models, and Pradel Survival‐Lambda and POPAN single‐state models implemented in the program MARK. Annual survival probability (0.98 [95% CI: 0.96–0.99]) was constant over time, and no important differences between sexes and age‐classes (calves, juveniles, adults) were found. This estimate of survival suggests a life expectancy of approximately 48 years. Realised mean population growth rate (λ) was 1.012 (0.987–1.037) with an estimated population size of 54 (54–60) individuals and a mean calving rate of 0.13 (0.06–0.20) calves born per year per reproductive female. The survival and reproduction rates of killer whales at Marion Island are similar to those of killer whale populations in the eastern North Pacific, Norway and Îles Crozet. However, subtle differences in survival and reproduction rates are present. These are likely the result of local differences in resource abundances, historical impacts on social structure and/or stressors. Also, the presence and scale of fisheries (legal and illegal) in the area may provide opportunities for direct interactions with fishing activities impacting survival and reproduction rates.

Monomorphic call structure and dimorphic vocal phenology in a sex-role reversed frog

Sexual signals in different animals are expected to be dimorphic when both sexes signal, but cases of monomorphism are known to occur, and we lack a clear understanding about the factors that modulate the level of sexual dimorphism in signals. In this study, we evaluated the hypothesis that the lack of dimorphism in sexual signals might evolve in systems experiencing temporal changing conditions of intra-sexual competition. We used the Darwin’s frog (Rhinoderma darwinii), a species with paternal care, as a model. We compared advertisement calls and examined call distinctiveness among females, pregnant and non-pregnant males in a wild population from Chiloe island, Chile. We also recorded the vocal activity of both sexes along the reproductive season. Additionally, we compared the acoustic properties of their advertisement calls in terms of sexual distinctiveness and individual repeatability. We found that the proportion of females and pregnant males vocalizing changed over time following distinct patterns. Females produced calls with lower dominant frequency and longer note and call durations than males, and these acoustic differences were related to body size differences between sexes, but only dominant frequency contributed significantly to the distinctiveness of calls between sexes. Also, individual repeatability was high, indicating that calling can be relevant for social recognition. Overall, our results suggest that mutual selective pressures could be involved in the limited dimorphism of the advertisement calls in Darwin’s frogs, as the sex ratio of individuals vocalizing (i.e. females vs. reproductive males) is reversed along the breeding period. Whether sexually monomorphic signals are evidence of adaptive mutual choice or a by-product of genetic constraints on females remains as an open question. In species with exclusive parental care of males, it would be expected that males and females alternate their reproductive availability while performing slightly differentiated sexual signals. Using acoustic recordings and capture-recapture data of the Darwin’s frog, we found that advertisement calls of this frog tend to be monomorphic. Interestingly, the males performing parental care were calling actively and the population had a clear bias in the number of males. Males and females of this endangered frog called actively, but the vocalization rate of each sex peaked at different times along the breeding season. These findings open new questions about the mechanisms of sexual recognition under restricted signal dimorphism.

Survival during the pre-fledging period rather than during post-fledging drives variation in local recruitment of an endangered migratory shorebird, the Southern Dunlin Calidris alpina schinzii

The declines in wet-grassland breeding shorebird populations are considered to mainly result from changes in reproduction. While there is plenty of information on nest survival, little reliable information exists on local recruitment due to confounding effects of permanent emigration. Furthermore, few studies have been able to study the roles of pre- and post-fledging survival on local recruitment. Therefore, it is unclear whether local recruitment of young reflects conditions at the breeding sites or at non-breeding sites. We studied an isolated population of the endangered Southern Dunlin (Calidris alpina schinzii) breeding on the west coast of Sweden to examine (1) brood survival (probability of at least one chick fledging) by following broods fates and (2) local recruitment (survival from hatching to 1 year old) using capture-recapture data. We then examined how much of the annual variation in juvenile survival was explained by variation in brood survival. Brood survival was on average 0.58 (annual range 0.08–1.00) and explained 64% of variation in annual local recruitment. Still local recruitment was rather high for a shorebird (0.17, SE = 0.023), which reflects the isolated nature of the study population. Our results suggest that local recruitment seems to be mainly constrained by chick survival during the pre-fledging period. Therefore, management of breeding sites leading to increased brood survival, e.g., reducing predation on chicks, should have strong impacts on local recruitment and local population growth.

Modeling dispersal using capture–recapture data: A comparison of dispersal models

AbstractCapture–recapture methods have been a cornerstone of field‐based dispersal ecology. However, obtaining unbiased estimates of dispersal parameters from capture–recapture data is challenging because it is impossible to survey all possible range of dispersal in the field. There are several approaches to address this critical issue of capture–recapture methods. Still, a lack of formal comparisons among these modeling approaches has confused about which is the best practice given the available dataset. Here, I compared the performance of three dispersal models using test datasets simulated under various sampling designs. In the first approach, a probability distribution (a dispersal kernel) was simply fitted to the capture–recapture data (the “simple dispersal model”). In the second approach, a truncated probability distribution was used to account for the finite range of observations (the “truncated dispersal model”). Finally, the dispersal and observation processes were coupled to consider the spatial organization of sampling designs (the “dispersal–observation model”). The simulation study provided three important insights. First, the dispersal–observation model provided reliable estimates of dispersal parameters, even under sampling designs with a few recaptures. Second, the truncated dispersal model was also effective, but only when the number of recaptures was large. Finally, the use of the simple dispersal model caused a substantial underestimation of dispersal parameters regardless of sampling designs; this modeling approach should be avoided where possible. The results of this simulation study should help choose a suitable modeling approach.

Size estimation of key populations in the HIV epidemic in eSwatini using incomplete and misaligned capture-recapture data

In 2020, our understanding of the distributions of HIV risks in the most burdened settings, including eSwatini, remains limited. In part, this is driven by the limited availability of the size and burden of the populations at the greatest risk for HIV. Given pervasive social and healthcare stigmas, the size estimations of these populations often rely on the multiplier method—a variant of the capture-recapture approach where the first survey is replaced by an enumeration of population members who used some service or attended an event. To characterize the distributions of marginalized communities in eSwatini, multiple data sources are available at each region for the multiplier method. Current practices in such circumstances produce multiple population size estimates at each region ignoring the correlation among these estimates. We recast the multiple multiplier method as a special case of capture-recapture problem with incomplete data and propose a fully model based approach for size estimation using multiple capture-recapture data with arbitrary pattern of incompleteness. We use a data augmentation scheme that allows us to model the correlations in the data and produce a unified estimate of population size per region. A hierarchical model ties together the models for multiple regions, allowing us to borrow strength across the regions and enabling extrapolation to areas without data. In eSwatini we also encounter data misalignment where counts from some of the data sources are not available for each region but as an aggregate over few regions. We propose a solution to the general misalignment problem which considers data-source-specific patterns of misalignment. We use simulation studies to demonstrate the accurate inferential capabilities of our Bayesian multiplier method. This approach is then used to produce uncertainty-quantified population size estimates of key populations in eSwatini. Lastly, we propose a Bayesian nonparametric extension for incomplete capture-recapture that allows nonindependent data sources.

On the sampling design of spatially explicit integrated population models

Abstract It is important to understand metapopulation dynamics and underlying demographic processes in heterogeneous landscapes. Traditionally, demographic parameters are estimated using capture–recapture data that can be difficult to collect. Spatially explicit dynamic N‐mixture models allow inference for demographic parameters, including dispersal, using count data of unmarked animals, but these models have only been shown effective under constant demographic parameters and dispersal between adjacent local populations. In this study, I aimed to compensate the weakness of spatially explicit dynamic N‐mixtures and multistate capture–recapture models by jointly analysing count and capture–recapture data. This spatially explicit integrated population model allows for spatiotemporal variation of demographic parameters in relation to environmental and density covariates and dispersal between any local populations. I conducted simulations to evaluate this model (a) for species with distinct life histories under different detection and capture probabilities, (b) when spatial sampling intensity varied, (c) when the length of survey period varied, (d) when the robust sampling design was adopted or not and (e) when auxiliary information is partially available. I also provided an empirical example of Gadwall Mareca strepera metapopulation dynamics in North American prairies. The results showed that the model provided unbiased parameter estimates under a variety of ecological and sampling conditions, even when the spatial sampling intensity of capture–recapture survey was low (20% of the patches) with the complement of count data (≥60% of the patches). Also, the model only required a relatively short survey period (6~8 years) to provide unbiased inferences. The robust sampling design was not necessary for the model to provide unbiased inferences when spatial counts were intense, but became critical when spatial counts were sparse. Parameter estimates remain unbiased when auxiliary information is partially available. The model showed that Gadwall had low emigration probability (11.8%) but could disperse more than 200 km. Based on the results, I provide recommendations about the trade‐off between spatial sampling intensity, length of survey period and the use of the robust sampling design when applying this model in real‐world studies. The model could have wide applications in the interface of metapopulation ecology and landscape ecology.

Performance of spatial capture-recapture models with repurposed data: Assessing estimator robustness for retrospective applications.

Advancements in statistical ecology offer the opportunity to gain further inferences from existing data with minimal financial cost. Spatial capture-recapture (SCR) models extend traditional capture-recapture models to incorporate spatial position of capture and enable direct estimation of animal densities across a region of interest. The additional inferences provided are both ecologically interesting and valuable for decision making, which has resulted in traditional capture-recapture data being repurposed using SCR. Yet, many capture-recapture studies were not designed for SCR and the limitations of repurposing data from such studies are rarely assessed in practice. We used simulation to evaluate the robustness of SCR for retrospectively estimating large mammal densities over a variety of scenarios using repurposed capture-recapture data collected by an asymmetrical sampling grid and covering a broad spatial extent in a heterogenous landscape. We found performance of SCR models fit using repurposed data simulated from the existing grid was not robust, but instead bias and precision of density estimates varied considerably among simulations scenarios. For example, while the smallest relatives bias of density estimates was 3%, it ranged by 14 orders of magnitude among scenarios and was most strongly influenced by detection parameters. Our results caution against the casual repurposing of non-spatial capture-recapture data using SCR and demonstrate the importance of using simulation to assessing model performance during retrospective applications.

Proximity to humans affects local social structure in a giraffe metapopulation.

Experimental laboratory evidence suggests that animals with disrupted social systems express weakened relationship strengths and have more exclusive social associations, and that these changes have functional consequences. A key question is whether anthropogenic pressures have a similar impact on the social structure of wild animal communities. We addressed this question by constructing a social network from 6years of systematically collected photographic capture-recapture data spanning 1,139 individual adult female Masai giraffes inhabiting a large, unfenced, heterogeneous landscape in northern Tanzania. We then used the social network to identify distinct social communities, and tested whether social or anthropogenic and other environmental factors predicted differences in social structure among these communities. We reveal that giraffes have a multilevel social structure. Local preferences in associations among individuals scale up to a number of distinct, but spatially overlapping, social communities, that can be viewed as a large interconnected metapopulation. We then find that communities that are closer to traditional compounds of Indigenous Masai people express weaker relationship strengths and the giraffes in these communities are more exclusive in their associations. The patterns we characterize in response to proximity to humans reflect the predictions of disrupted social systems. Near bomas, fuelwood cutting can reduce food resources, and groups of giraffes are more likely to encounter livestock and humans on foot, thus disrupting the social associations among group members. Our results suggest that human presence could potentially be playing an important role in determining the conservation future of this megaherbivore.

Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales.

Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual-level data are available for some species. Integrated population modeling (IPM) offers a mechanism for leveraging these data sets into a single estimation framework. IPMs that incorporate both population- and individual-level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population-level visual survey data, individual-level capture-recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; Delphinapterus leucas) as a case study. Our state-space IPM included a population process model and three observational submodels: (1) a group detection model to describe group size estimates from aerial survey data; (2) a capture-recapture model to describe individual photographic capture-recapture data; and (3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three data sets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect data sets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.

Drivers of amphibian population dynamics and asynchrony at local and regional scales.

Identifying the drivers of population fluctuations in spatially distinct populations remains a significant challenge for ecologists. Whereas regional climatic factors may generate population synchrony (i.e. the Moran effect), local factors including the level of density dependence may reduce the level of synchrony. Although divergences in the scaling of population synchrony and spatial environmental variation have been observed, the regulatory factors that underlie such mismatches are poorly understood. Few previous studies have investigated how density-dependent processes and population-specific responses to weather variation influence spatial synchrony at both local and regional scales. We addressed this issue in a pond-breeding amphibian, the great crested newt Triturus cristatus. We used capture-recapture data collected through long-term surveys in five T. cristatus populations in Western Europe. In all populations-and subpopulations within metapopulations-population size, annual survival and recruitment fluctuated over time. Likewise, there was considerable variation in these demographic rates between populations and within metapopulations. These fluctuations and variations appear to be context-dependent and more related to site-specific characteristics than local or regional climatic drivers. We found a low level of demographic synchrony at both local and regional levels. Weather has weak and spatially variable effects on survival, recruitment and population growth rate. In contrast, density dependence was a common phenomenon (at least for population growth) in almost all populations and subpopulations. Our findings support the idea that the Moran effect is low in species where the population dynamics more closely depends on local factors (e.g. population density and habitat characteristics) than on large-scale environmental fluctuation (e.g. regional climatic variation). Such responses may have far-reaching consequences for the long-term viability of spatially structured populations and their ability to respond to large-scale climatic anomalies.

Response of a remnant marmot population to habitat enhancement yields insights into marmot ecology.

We evaluated the response of a remnant population of yellow-bellied marmots (Marmota flaviventris) to targeted habitat enhancement in an ecological system that had been degraded during ~100 years of intensive livestock management, including marmot eradication. We used capture-recapture data and a novel use of a multistate framework to evaluate geographic expansion of the marmot population pre- and post-habitat enhancement. We also estimated age-structured survival, reproduction, and sex ratios. The marmot population appeared to respond positively to new habitat opportunities created by habitat enhancement: the number of marmots captured increased from three marmots pre-habitat enhancement to 54 (28 adults and yearlings, 26 young) post-habitat enhancement at the end of the study. Marmots expanded geographically by transitioning into habitat-enhanced areas, and adult females occupied and reproduced in all habitat-enhanced areas. The sex ratio of the young population in 2019 was strongly female-biased, which may have been influenced by poor body condition of breeding females owing to unusually prolonged snow cover that year. Adult and yearling survival were within the range of that reported for colonial adults and yearlings in Colorado. Our results suggest that active habitat enhancement can assist in the recovery of marmot populations in systems where marmots historically existed.

Estimation of lung and bronchial cancer registry completeness via capture-recapture method using population-based cancer registry in Khuzestan province in 2011

IntroductionPopulation-based cancer registry (PBCR) plays a significant role in burden of cancer estimation. Estimating the completeness of cancer registry is one of the criteria to assess the quality of data (results). Also, Capture-recapture is one of the methods used to assess completeness of cancer registry. ObjectiveThis study was aimed to estimate the completeness of lung and bronchial cancer registry using three-source capture-recapture method in Khuzestan province. Materials and methodsThis study was carried out using three-source capture-recapture method and data were obtained from three sources including medical records, death certificates and pathology labs (reports) in Khuzestan. In this study, total new cases of lung and bronchial cancer registered by the three sources in 2011, were enrolled. Among the sources, the common cases were identified and the completeness rate of lung and bronchial cancer registry was calculated by log-linear method using R software, finally. ResultsTotally, 426 new cases for lung cancer had reported from the three sources in 2011. The completeness index of lung cancer registry was totally estimated 72%, as well as it was independently 40%, 25% and 37.6% for the medical records, pathology reports and death certificates sources, respectively. ConclusionAccording to the results, after collection and remove repetition of the cases related to lung cancer, it should be added their number registered by the pathology (labs), medical records and death certificates sources by 28%–40%, to estimate actual incidence of lung cancer. Also, the actual incidence of lung cancer cases related to each of medical records, pathology and death certificates was calculated by adding the reported values by 60%, 75% and 63%, respectively.

Population position along the fast-slow life-history continuum predicts intraspecific variation in actuarial senescence.

Patterns of actuarial senescence can be highly variable among species. Previous comparative analyses revealed that both age at the onset of senescence and rates of senescence are linked to position of a species along the fast-slow life-history continuum. As there are few long-term datasets of wild populations with known-age individuals, intraspecific (i.e. between-population) variation in senescence is understudied and limited to comparisons of wild and captive populations of the same species, mostly birds and mammals. In this paper, we examined how population position along the fast-slow life-history continuum affects intraspecific variation in senescence in an amphibian, Bombina variegata. We used capture-recapture data collected in four populations with contrasting life-history strategies. Senescence trajectories were analysed using Bayesian capture-recapture models. We show that in populationswith fast life histories the onset of actuarial senescence was earlier and individuals aged at a faster rate than individuals in populationswith slow life histories. Our study provides one of the few empirical examples of among-population variation in actuarial senescence patterns in the wild and confirms that the fast-slow life-history gradient is associated with both macroevolutionary and microevolutionary patterns of actuarial senescence.