Capture Heterogeneity Research Articles

A Test of Positive Association for Detecting Heterogeneity in Capture for Capture\u2013Recapture Data

The Cormack–Jolly–Seber (CJS) model assumes that all marked animals have equal recapture probabilities at each sampling occasion, but heterogeneity in capture often occurs and should be taken into account to avoid biases in parameter estimates. Although diagnostic tests are generally used to detect trap-dependence or transience and assess the overall fit of the model, heterogeneity in capture is not routinely tested for. In order to detect and identify this phenomenon in a CJS framework, we propose a test of positive association between previous and future encounters using Goodman–Kruskal’s gamma. This test is based solely on the raw capture histories and makes no assumption on model structure. The development of the test is motivated by a dataset of Sandwich terns (Thalasseus sandvicensis), and we use the test to formally show that they exhibit heterogeneity in capture. We use simulation to assess the performance of the test in the detection of heterogeneity in capture, compared to existing and corrected diagnostic goodness-of-fit tests, Leslie’s test of equal catchability and Carothers’ extension of the Leslie test. The test of positive association is easy to use and produces good results, demonstrating high power to detect heterogeneity in capture. We recommend using this new test prior to model fitting as the outcome will guide the model-building process and help draw more accurate biological conclusions. Supplementary materials accompanying this paper appear online.

Individual heterogeneity and capture–recapture models: what, why and how?

Variation between and within individuals in life history traits is ubiquitous in natural populations. When affecting fitness‐related traits such as survival or reproduction, individual heterogeneity plays a key role in population dynamics and life history evolution. However, it is only recently that properly accounting for individual heterogeneity when studying population dynamics of free‐ranging populations has been made possible through the development of appropriate statistical models. We aim here to review case studies of individual heterogeneity in the context of capture–recapture models for the estimation of population size and demographic parameters with imperfect detection. First, we define what individual heterogeneity means and clarify the terminology used in the literature. Second, we review the literature and illustrate why individual heterogeneity is used in capture–recapture studies by focusing on the detection of life‐history tradeoffs, including senescence. Third, we explain how to model individual heterogeneity in capture–recapture models and provide the code to fit these models (https://github.com/oliviergimenez/indhet_in_CRmodels). The distinction is made between situations in which heterogeneity is actually measured and situations in which part of the heterogeneity remains unobserved. Regarding the latter, we outline recent developments of random‐effect models and finite‐mixture models. Finally, we discuss several avenues for future research.

Age, sex, and climate factors show different effects on survival of three different bat species in a woodland bat community

1. Bats are the second largest mammalian Order and important providers of ecosystem services including insect pest control, pollination and seed dispersal. Yet, the lack of basic information on their demographic rates hampers detecting changes in population trends, and thus conservation efforts.2. The elusive life-styles, that leads to imperfect and biased detection, limits the quantity of individually based information as well as the extent to which information can be utilised to assess accurate and unbiased demographic rates.3. We overcome the problem of imperfect and biased detection using a multilevel capture-mark-recapture framework to produce robust estimates of survival during hibernation period, and to evaluate the effect of age, sex, social group, and external weather factors on survival and capture heterogeneity in three vespertilionid species (Myotis daubentonii, M. nattereri, and Plecotus auritus) from the same woodland community.4. While controlling for emigration and for the species-specific roosting group structure, we show that females survive better than males in two species, and that adults survive better than juveniles in all species - these survival differences being species-specific. Only one external environmental factor (average summer temperature) explained a substantial proportion of the between-year variation in M. daubentonii survival.5. Our study provides, for the first time, a robust estimate of annual survival in bats. We advocate careful attention to possible sources of biases when studying survival rates in the wild, considering species-specific life-history and population-specific features. Considering these factors that influence wider community responses to environmental conditions is important for the effective conservation management of an area.

State-space mark-recapture estimates reveal a recent decline in abundance of North Atlantic right whales.

North Atlantic right whales (Eubalaena glacialis Müller 1776) present an interesting problem for abundance and trend estimation in marine wildlife conservation. They are long lived, individually identifiable, highly mobile, and one of the rarest of cetaceans. Individuals are annually resighted at different rates, primarily due to varying stay durations among several principal habitats within a large geographic range. To date, characterizations of abundance have been produced that use simple accounting procedures with differing assumptions about mortality. To better characterize changing abundance of North Atlantic right whales between 1990 and 2015, we adapted a state–space formulation with Jolly‐Seber assumptions about population entry (birth and immigration) to individual resighting histories and fit it using empirical Bayes methodology. This hierarchical model included accommodation for the effect of the substantial individual capture heterogeneity. Estimates from this approach were only slightly higher than published accounting procedures, except for the most recent years (when recapture rates had declined substantially). North Atlantic right whales' abundance increased at about 2.8% per annum from median point estimates of 270 individuals in 1990 to 483 in 2010, and then declined to 2015, when the final estimate was 458 individuals (95% credible intervals 444–471). The probability that the population's trajectory post‐2010 was a decline was estimated at 99.99%. Of special concern was the finding that reduced survival rates of adult females relative to adult males have produced diverging abundance trends between sexes. Despite constraints in recent years, both biological (whales' distribution changing) and logistical (fewer resources available to collect individual photo‐identifications), it is still possible to detect this relatively recent, small change in the population's trajectory. This is thanks to the massive dataset of individual North Atlantic right whale identifications accrued over the past three decades. Photo‐identification data provide biological information that allows more informed inference on the status of this species.

Spatially explicit population estimates for black bears based on cluster sampling

ABSTRACTWe estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala‐St. Johns, Big Cypress) in Florida, USA with spatially explicit capture‐mark‐recapture (SCR) by extracting DNA from hair samples collected at barbed‐wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site‐specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model‐averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala‐St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture‐recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution. © 2017 The Wildlife Society.

Efficient energy modelling of heterogeneous building portfolios

The paper reports the energy modelling process of 11 university buildings with the use of a normative energy calculation method. The broad aim of this exercise is to model a set of buildings efficiently so as to capture heterogeneity across buildings and minimize auditing requirements. First, energy model inputs are scrutinized and improved to better represent the actual use of the buildings. The second set of model improvements aim to identify and test those parameters that can be uniformly described across all the buildings, thus reducing overall modelling effort. Using sensitivity analysis of parameters per building, we demonstrate the validity of assigning a common range of values to key input parameters across the building portfolio. Gas and electricity consumption are analyzed separately. Our results show that for electricity consumption, a deeper sub-categorization of activities within buildings is important. On the other hand, accuracy of gas consumption relies on parameters associated with the building fabric.

Characterization of Field-of-View for Energy Efficient Application-Aware Visual Sensor Networks

Energy consumption is one of the primary concerns in a resource-constrained visual sensor network (VSN). The existing VSN design solutions under particular resource-constrained scenarios are application specific, whereas the degree of sensitivity of the resource constraints varies from one application to another. This limits the implementation of the existing energy efficient solutions within a VSN node, which may be considered to be a part of a heterogeneous network. The heterogeneity of image capture and processing within a VSN can be adaptively reflected with a dynamic field-of-view (FoV) realization. This is expected to allow the implementation of a generalized energy efficient solution to adapt with the heterogeneity of the network. In this paper, an energy efficient FoV characterization framework is proposed, which can support a diverse range of applications. The context of adaptivity in the proposed FoV characterization framework is considered to be: 1) sensing range selection; 2) maximizing spatial coverage; 3) adaptive task classification; and 4) minimizing the number of required nodes. Soft decision criteria is exploited, and it is observed that for a given detection reliability, the proposed framework provides energy efficient solutions, which can be implemented within heterogeneous networks. It is also found that the proposed design solution for heterogeneous networks leads to 49.8% energy savings compared with the trivial design solution.

Emerging Molecular Biomarkers in Advanced Prostate Cancer: Translation to the Clinic.

Recent clinical and preclinical studies focused on understanding the molecular landscape of castration-resistant prostate cancer (CRPC) have provided insights into mechanisms of treatment resistance, disease heterogeneity, and potential therapeutic targets. This work has served as a framework for several ongoing clinical studies focused on bringing novel observations into the clinic in the form of tissue, liquid, and imaging biomarkers. Resistance in CRPC typically is driven through reactivation of androgen receptor (AR) signaling, which can occur through AR-activating point mutations, amplification, splice variants (such as AR-V7), or other bypass mechanisms. Detection of AR aberrations in the circulation negatively impacts response to subsequent AR-directed therapies such as abiraterone and enzalutamide. Other potentially clinically relevant alterations in CRPC include defects in DNA damage repair (at either the somatic or germline level) in up to 20% of patients (with implications for PARP1 inhibitor therapy), PI3K/PTEN/Akt pathway activation, WNT signaling pathway alterations, cell cycle gene alterations, and less common but potentially targetable alterations involving RAF and FGFR2. Imaging biomarkers that include those focused on incorporating overexpressed androgen-regulated genes/proteins, such as prostate-specific membrane antigen (PSMA) and dihydrotestosterone (DHT) in combination with CT, can noninvasively identify patterns of AR-driven distribution of CRPC tumor cells, monitor early metastatic lesions, and potentially capture heterogeneity of response to AR-directed therapies and other therapeutics. This article focuses on the current state of clinical biomarker development and future directions for how they might be implemented into the clinic in the near term to improve risk stratification and treatment selection for patients.

Population size estimation and heterogeneity in capture–recapture data: a linear regression estimator based on the Conway–Maxwell–Poisson distribution

The purpose of the study is to estimate the population size under a truncated count model that accounts for heterogeneity. The proposed estimator is based on the Conway–Maxwell–Poisson distribution. The benefit of using the Conway–Maxwell–Poisson distribution is that it includes the Bernoulli, the Geometric and the Poisson distributions as special cases and, furthermore, allows for heterogeneity. Parameter estimates can be obtained by exploiting the ratios of successive frequency counts in a weighted linear regression framework. The results of the comparisons with Turing’s, the maximum likelihood Poisson, Zelterman’s and Chao’s estimators reveal that our proposal can be beneficially used. Furthermore, our proposal outperforms its competitors under all heterogeneous settings. The empirical examples consider the homogeneous case and several heterogeneous cases, each with its own features, and provide interesting insights on the behavior of the estimators.

Photosynthetic activity of variegated leaves of Coleus × hybridus hort. cultivars characterised by chlorophyll fluorescence techniques

Different pigments often occur together and affect photosynthetic characteristics of the respective leaf portions. In this study, photosynthetic activity in variegated leaves of five cultivars of the ornamental and medicinal plant, Coleus × hybridus hort., was estimated by image analysis and point data measurements of major chlorophyll (Chl) fluorescence parameters and related to the amount of photosynthetic pigments measured with a Chl meter or spectrophotometrically in leaf extracts. Significant differences in Chl and carotenoid (Car) contents were noticed among differentially pigmented sectors of a leaf and among the cultivars. Although the higher Chl concentration was noticed in purple parts compared to green parts of the leaves, the values of minimal and maximal fluorescence yield at the dark- and light-adapted state (F0, Fm, F0', Fm', respectively) were a little lower than those in the green sectors, indicating photoprotective effects provided by anthocyanins and Car, more abundant in the red parts. The lowest Chl and Car content was detected in creamy-yellow and pink sectors and this contributed to low F0, Fm, and Fm', maximal quantum yield of PSII photochemistry, and nonphotochemical and photochemical quenching but high PSII maximum efficiency and effective quantum yield of PSII photochemistry. Both methods of Chl fluorescence analysis revealed heterogeneity in capture, transfer, and dissipation of excitation energy but Chl fluorescence imaging was more suitable in examining very narrow pigmented leaf areas.

Bayesian population size estimation using Dirichlet process mixtures.

We introduce a new Bayesian nonparametric method for estimating the size of a closed population from multiple-recapture data. Our method, based on Dirichlet process mixtures, can accommodate complex patterns of heterogeneity of capture, and can transparently modulate its complexity without a separate model selection step. Additionally, it can handle the massively sparse contingency tables generated by large number of recaptures with moderate sample sizes. We develop an efficient and scalable MCMC algorithm for estimation. We apply our method to simulated data, and to two examples from the literature of estimation of casualties in armed conflicts.

Casting wider diagnostic nets for anxiety and depression: Disability-driven cross-diagnostic subtypes in a large population study

IntroductionData-driven techniques are frequently applied to identify subtypes of depression and anxiety. Although they are highly comorbid and often grouped under a single internalizing banner, most subtyping studies have focused on either depression or anxiety. Furthermore, most previous subtyping studies have not taken into account experienced disability.ObjectivesTo incorporate disability into a data-driven cross-diagnostic subtyping model.AimsTo capture heterogeneity of depression and anxiety symptomatology and investigate the importance of domain-specific disability-levels to distinguish between homogeneous subtypes.MethodsSixteen symptoms were assessed without skips using the MINI-interview in a population sample (LifeLines; n = 73403). Disability was measured with the RAND-36. To identify the best-fitting subtyping model, different nested latent variable models (latent class analysis, factor analysis and mixed-measurement item response theory [MM-IRT]) with and without disability covariates were compared. External variables were compared between the best model's classes.ResultsA five-class MM-IRT model incorporating disability showed the best fit (Fig. 1). Accounting for disability improved the differentiation between classes reporting isolated non-specific symptoms (“Somatic” [13.0%], and “Worried” [14.0%]) and those reporting more psychopathological symptoms (“Subclinical” [8.8%], and “Clinical” [3.3%]). A “Subclinical” class reported symptomatology at subthreshold levels. No pure depression or anxiety, but only mixed classes were observed.ConclusionsAn overarching subtyping model incorporating both symptoms and disability identified distinct cross-diagnostic subtypes. Diagnostic nets should be cast wider than current phenomenology-based categorical systems.Figure not available.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Identification and Density Estimation of American Martens (Martes americana) Using a Novel Camera-Trap Method

Camera-traps are increasingly used to estimate wildlife abundance, yet few studies exist for small-sized carnivores or comparing efficacy against traditional methods. We developed a camera-trap to identify the unique ventral patches of American martens (Martes americana). Our method was designed to: (1) determine the optimal trap configuration to photograph ventral patches; (2) evaluate the use of temporally clustered photographs to determine independence and improve identification; and (3) determine factors that influence identification probability. We tested our method by comparing camera- and live-trap density estimates using spatial capture–recapture (SCR) models. The ventral patches of radio-collared martens were most visible when traps were placed 15–20 cm above a feeding platform. Radio-collared martens (n = 14) visited camera-traps for long periods (median = 7 min) with long intervals between visits (median = 419 min), and visits by different martens at the same trap <15 min apart was infrequent (n = 3) during both years. Similarly, there was complete agreement among observers that clustered photos of un-collared martens were always of the same individual. Pairwise agreement was high between observers; eight un-collared martens were identifiable by consensus on 90% (54 of 60) of recorded visits. Factors influencing identification probability were directly related to the time martens spent feeding at traps (β = 0.143, P = 0.01) and inversely proportional to the time that elapsed since traps were baited (β = −0.344, P = 0.006). Density estimates were higher and more precise for camera-trapping (0.60, 0.35–1.01 martens/km2) than live-trapping (0.45, 0.16–1.22 martens/km2), providing evidence that SCR density estimates may be biased when capture heterogeneity is present, yet cannot be accounted for due to small sample size. Our camera-trap method provides a minimally invasive and accurate tool for monitoring marten populations.

Emerging Molecular Biomarkers in Advanced Prostate Cancer: Translation to the Clinic

Recent clinical and preclinical studies focused on understanding the molecular landscape of castration-resistant prostate cancer (CRPC) have provided insights into mechanisms of treatment resistance, disease heterogeneity, and potential therapeutic targets. This work has served as a framework for several ongoing clinical studies focused on bringing novel observations into the clinic in the form of tissue, liquid, and imaging biomarkers. Resistance in CRPC typically is driven through reactivation of androgen receptor (AR) signaling, which can occur through AR-activating point mutations, amplification, splice variants (such as AR-V7), or other bypass mechanisms. Detection of AR aberrations in the circulation negatively impacts response to subsequent AR-directed therapies such as abiraterone and enzalutamide. Other potentially clinically relevant alterations in CRPC include defects in DNA damage repair (at either the somatic or germline level) in up to 20% of patients (with implications for PARP1 inhibitor therapy), PI3K/PTEN/Akt pathway activation, WNT signaling pathway alterations, cell cycle gene alterations, and less common but potentially targetable alterations involving RAF and FGFR2. Imaging biomarkers that include those focused on incorporating overexpressed androgen-regulated genes/proteins, such as prostate-specific membrane antigen (PSMA) and dihydrotestosterone (DHT) in combination with CT, can noninvasively identify patterns of AR-driven distribution of CRPC tumor cells, monitor early metastatic lesions, and potentially capture heterogeneity of response to AR-directed therapies and other therapeutics. This article focuses on the current state of clinical biomarker development and future directions for how they might be implemented into the clinic in the near term to improve risk stratification and treatment selection for patients.

Problem drug use prevalence estimation revisited: heterogeneity in capture-recapture and the role of external evidence.

Background and AimsCapture–recapture (CRC) analysis is recommended for estimating the prevalence of problem drug use or people who inject drugs (PWID). We aim to demonstrate how naive application of CRC can lead to highly misleading results, and to suggest how the problems might be overcome.MethodsWe present a case study of estimating the prevalence of PWID in Bristol, UK, applying CRC to lists in contact with three services. We assess: (i) sensitivity of results to different versions of the dominant (treatment) list: specifically, to inclusion of non‐incident cases and of those who were referred directly from one of the other services; (ii) the impact of accounting for a novel covariate, housing instability; and (iii) consistency of CRC estimates with drug‐related mortality data. We then incorporate formally the drug‐related mortality data and lower bounds for prevalence alongside the CRC into a single coherent model.ResultsFive of 11 models fitted the full data equally well but generated widely varying prevalence estimates, from 2740 [95% confidence interval (CI) = 2670, 2840] to 6890 (95% CI = 3740, 17680). Results were highly sensitive to inclusion of non‐incident cases, demonstrating the presence of considerable heterogeneity, and were sensitive to a lesser extent to inclusion of direct referrals. A reduced data set including only incident cases and excluding referrals could be fitted by simpler models, and led to much greater consistency in estimates. Accounting for housing stability improved model fit considerably more than did the standard covariates of age and gender. External data provided validation of results and aided model selection, generating a final estimate of the number of PWID in Bristol in 2011 of 2770 [95% credible interval (Cr‐I) = 2570, 3110] or 0.9% (95% Cr‐I = 0.9, 1.0%) of the population aged 15–64 years.ConclusionsSteps can be taken to reduce bias in capture–recapture analysis, including: careful consideration of data sources, reduction of lists to less heterogeneous subsamples, use of covariates and formal incorporation of external data.

Assessing the design and power of capture-recapture studies to estimate demographic parameters for the Endangered Oceania humpback whale population

Capture−recapture studies offer a powerful tool to assess abundance, survival and population rate of change (λ). A previous capture−recapture study, based on DNA profiles, esti- mated that the IUCN-listed Endangered Oceania population of humpback whales had a super- population size of 4329 whales (95% confidence limits, CL: 3345, 5315) and λ = 1.03 (95% CL: 0.90−1.18) for the period 1999−2005. This low estimate of λ contrasts with the high estimated λ for the neighbouring east Australia population (1.11; 95% CL: 1.105−1.113). A future assessment of Oceania humpbacks through capture−recapture methodology has been proposed to meet 3 objec- tives: (1) estimate population size with a coefficient of variation of < 20%, and detect if λ is signif- icantly different from (2) 1.00 or (3) λ of east Australia. The proposed survey design involves using DNA profiles to identify whales on principal breeding grounds within Oceania in proportion to the abundance of whales on these grounds over the 10 to 12 wk wintering period, to minimise capture heterogeneity between individuals and to maximise capture probabilities. Simulations of the idealised survey design incorporating data from the previous surveys (1999−2005) with 3 new survey years were conducted under a range of scenarios for the 'true' demographic status of the population. Simulations of the entire Oceania region showed that the proposed design will give sufficient power to meet objectives (1) under all scenarios, (2) if the true λ≥ 1.05 and (3) if the true λ≤ 1.05. Region-specific simulations suggested there was scope to test for differences in recovery between principal breeding sites within Oceania.

Bayesian estimation of a cancer population by capture-recapture with individual capture heterogeneity and small sample.

BackgroundCancer incidence and prevalence estimates are necessary to inform health policy, to predict public health impact and to identify etiological factors. Registers have been used to estimate the number of cancer cases. To be reliable and useful, cancer registry data should be complete. Capture-recapture is a method for estimating the number of cases missed, originally developed in ecology to estimate the size of animal populations. Capture recapture methods in cancer epidemiology involve modelling the overlap between lists of individuals using log-linear models. These models rely on assumption of independence of sources and equal catchability between individuals, unlikely to be satisfied in cancer population as severe cases are more likely to be captured than simple cases.MethodsTo estimate cancer population and completeness of cancer registry, we applied Mth models that rely on parameters that influence capture as time of capture (t) and individual heterogeneity (h) and compared results to the ones obtained with classical log-linear models and sample coverage approach. For three sources collecting breast and colorectal cancer cases (Histopathological cancer registry, hospital Multidisciplinary Team Meetings, and cancer screening programmes), individual heterogeneity is suspected in cancer population due to age, gender, screening history or presence of metastases. Individual heterogeneity is hardly analysed as classical log-linear models usually pool it with between-“list” dependence. We applied Bayesian Model Averaging which can be applied with small sample without asymptotic assumption, contrary to the maximum likelihood estimate procedure.ResultsCancer population estimates were based on the results of the Mh model, with an averaged estimate of 803 cases of breast cancer and 521 cases of colorectal cancer. In the log-linear model, estimates were of 791 cases of breast cancer and 527 cases of colorectal cancer according to the retained models (729 and 481 histological cases, respectively).ConclusionsWe applied Mth models and Bayesian population estimation to small sample of a cancer population. Advantage of Mth models applied to cancer datasets, is the ability to explore individual factors associated with capture heterogeneity, as equal capture probability assumption is unlikely. Mth models and Bayesian population estimation are well-suited for capture-recapture in a heterogeneous cancer population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0029-7) contains supplementary material, which is available to authorized users.

A long-term population monitoring approach for a wide-ranging carnivore: Noninvasive genetic sampling of gray wolf rendezvous sites in Idaho, USA

Various monitoring methods have been developed for large carnivores, but not all are practical or sufficiently accurate for long-term monitoring over large spatial scales. From 2009 to 2010, we used a predictive habitat model to locate gray wolf rendezvous sites in 4 study areas in Idaho, USA and conducted noninvasive genetic sampling (NGS) of scat and hair found at the sites. We evaluated species and individual identification PCR success rates across the study areas, and estimated population size with a single-session population estimator using 2 different recapture-coding methods. We then compared NGS population estimates to estimates generated concurrently from telemetry data. We collected 1,937 scat and 166 hair samples and identified 193 unique individuals over 2 years. For fecal DNA samples, species identification success rates were consistently high (>92%) across areas. Individual identification success rates ranged from 78% to 80% in the drier study areas and dropped to 50% in the wettest study area. The degree of agreement between NGS- and telemetry-derived population estimates varied by recapture-coding method with considerable variability in 95% confidence intervals. Population estimates derived from NGS methods were most influenced by the average number of detections per individual. We demonstrate how changes in field effort and recapture-coding method can affect population estimates in a widely used single-session population estimation model. Our study highlights the need to further develop reliable population estimation tools for single-session NGS data, especially those with large differences in capture frequencies among individuals stemming from severe capture heterogeneity (i.e., overdispersion). © 2014 The Wildlife Society.

Density of threatened ocelotLeopardus pardalisin the Sierra Abra-Tanchipa Biosphere Reserve, San Luis Potosí, Mexico

AbstractThere is little information on the population status of the ocelotLeopardus pardalisin Mexico. In the Sierra Abra-Tanchipa Biosphere Reserve, in San Luis Potosí, ocelots are affected by habitat loss and fragmentation as a result of increased agricultural development. We used photographic identification in camera-trapping capture–recapture surveys to determine population abundance and density during the dry season and subsequent early and late humid seasons during April 2011–March 2012. We recorded 80 photographs of 15 individuals (10 males, one female, and four of undetermined sex) in 7,786 camera-days. Abundance was estimated using a closed capture heterogeneity model, yielding an estimated population of 9 ± SE 3 in the dry season and 21 ± SE 8 and 15 ± SE 5 during the subsequent early and late humid seasons, respectively. Spatially explicit density estimates were 0.04 and 0.03–0.18 individuals per km2for the dry and humid seasons, respectively, and were similar (P &gt; 0.612) among seasons. Peaks in ocelot activity occurred during 20.00–04.00. We conclude that the ocelots of the Sierra Abra-Tanchipa Reserve have a low population density and may face geographical and biological isolation as a result of habitat conversion. Continued monitoring and improved understanding of the movements and habitat preferences of ocelots are necessary to ensure their continued persistence, and connectivity between this population and others in north-east Mexico.

Lifetime abstainers and mortality risk in the United States

We examine variability in mortality risk among heterogeneous nondrinking statuses. We employ Cox proportional hazard models and the United States National Health Interview Survey-Linked Mortality Files (NHIS-LMF) to examine the risk of death associated with drinking and nondrinking statuses, net of demographic, socioeconomic, behavioural, health and geographic factors. Mortality risk is low for light drinkers and many individuals who abstain from drinking&#x2014;including those who abstain for religious and moral reasons, have a responsibility to family, were brought up not to drink and are not social. Mortality is higher among former, infrequent and moderate drinkers, and among individuals who abstain because they do not like the taste of alcohol, are concerned that they will lose control or are concerned about adverse consequences. Unsurprisingly, mortality risk is by far the highest for heavy drinkers. Our results show that reasons for abstention capture heterogeneity in the risk of death among lifetime abstainers.