Probit models for capture-recapture data subject to imperfect detection, individual heterogeneity and misidentification

As noninvasive sampling techniques for animal populations have become more popular, there has been increasing interest in the development of capture-recapture models that can accommodate both imperfect detection and misidentification of individuals (e.g., due to genotyping error). However, current methods do not allow for individual variation in parameters, such as detection or survival probability. Here we develop misidentification models for capture-recapture data that can simultaneously account for temporal variation, behavioral effects and individual heterogeneity in parameters. To facilitate Bayesian inference using our approach, we extend standard probit regression techniques to latent multinomial models where the dimension and zeros of the response cannot be observed. We also present a novel Metropolis-Hastings within Gibbs algorithm for fitting these models using Markov chain Monte Carlo. Using closed population abundance models for illustration, we re-visit a DNA capture-recapture population study of black bears in Michigan, USA and find evidence of misidentification due to genotyping error, as well as temporal, behavioral and individual variation in detection probability. We also estimate a salamander population of known size from laboratory experiments evaluating the effectiveness of a marking technique commonly used for amphibians and fish. Our model was able to reliably estimate the size of this population and provided evidence of individual heterogeneity in misidentification probability that is attributable to variable mark quality. Our approach is more computationally demanding than previously proposed methods, but it provides the flexibility necessary for a much broader suite of models to be explored while properly accounting for uncertainty introduced by misidentification and imperfect detection. In the absence of misidentification, our probit formulation also provides a convenient and efficient Gibbs sampler for Bayesian analysis of traditional closed population capture-recapture data.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS783 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

When to be discrete: the importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal (Callorhinus ursinus) biotelemetry data.Fil: McClintock, Brett T.. National Marine Mammal Laboratory; Estados UnidosFil: Johnson, Devin S.. National Marine Mammal Laboratory; Estados UnidosFil: Hooten, Mevin B.. State University Of Colorado - Fort Collins; Estados UnidosFil: Ver Hoef, Jay M.. National Marine Mammal Laboratory; Estados UnidosFil: Morales, Juan Manuel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentin

From pup to predator; generalized hidden Markov models reveal rapid development of movement strategies in a naïve long‐lived vertebrate

Rapid development of a successful foraging strategy is critical for juvenile survival, especially for naïve animals that receive no parental guidance. However, this process is poorly understood for many species. Although observation of early‐life movements is increasingly possible with miniaturisation of animal‐borne telemetry devices, analytical limitations remain. Here, we tracked 29 recently‐weaned, grey seal Halichoerus grypus pups from colonies in two geographically distinct regions of the United Kingdom. We analysed at‐sea movements of pups throughout their initial months of nutritional independence to investigate the ontogeny of behaviour‐specific (foraging and travelling) movement patterns. Using generalized hidden Markov models (HMMs), we extended the conventional HMM framework to account for temporal changes in putative foraging and travelling movement characteristics, and investigate the effects of intrinsic (sex) and extrinsic (environment) factors on this process. Putative foraging behaviour became more tortuous with time, and travelling became faster and more directed, suggesting a reduction in search scale and an increase in travel efficiency as pups shifted from exploration to an adult‐like repeatable foraging strategy. Sex differences in movement characteristics were evident from colony departure, but sex‐specific activity budgets were only detected in one region. We show that sex‐specific behavioural strategies emerge before sexual size dimorphism in grey seals, and suggest that this phenomenon may occur in other long‐lived species. Our results also indicate that environmental variation may affect the emergence of sex‐specific foraging behaviour, highlighting the need to consider interacting intrinsic and extrinsic factors in shaping movement strategies of long‐lived vertebrates. Moreover, comparing the behavioural state estimations to those of a conventional HMM (no variation in state‐specific movement parameters) revealed differences in the amount and location of foraging activity, with implications for spatial conservation management. Overlooking intrinsic and extrinsic variation in movement processes could distort our understanding of foraging ecology, population dynamics, and conservation requirements

A search for evidence of irradiation in Centaurus X-4 during quiescence

We present a study of the neutron star X-Ray Transient Cen X-4. Our aim is to look for any evidence of irradiation of the companion with a detailed analysis of its radial velocity curve, relative contribution of the donor star and Doppler tomography of the main emission lines. To improve our study all our data are compared with a set of simulations that consider different physical parameters of the system, like the disc aperture angle and the mass ratio. We conclude that neither the radial velocity curve nor the orbital variation of the relative donor's contribution to the total flux are affected by irradiation. On the other hand, we do see emission from the donor star at H${\alpha}$ and HeI 5876 which we tentatively attribute to irradiation effects. In particular, the H${\alpha}$ emission from the companion is clearly asymmetric and we suggest is produced by irradiation from the hot-spot. Finally, from the velocity of the HeI 5876 spot we constrain the disc opening angle to alpha=7-14 deg.Comment: 4 pages, 5 figures, accepted for publication in A&A as a R

Increased Asymmetric Dimethylarginine in Severe Falciparum Malaria: Association with Impaired Nitric Oxide Bioavailability and Fatal Outcome

Asymmetrical dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase (NOS), is a predictor of mortality in critical illness. Severe malaria (SM) is associated with decreased NO bioavailability, but the contribution of ADMA to the pathogenesis of impaired NO bioavailability and adverse outcomes in malaria is unknown. In adults with and without falciparum malaria, we tested the hypotheses that plasma ADMA would be: 1) increased in proportion to disease severity, 2) associated with impaired vascular and pulmonary NO bioavailability and 3) independently associated with increased mortality. We assessed plasma dimethylarginines, exhaled NO concentrations and endothelial function in 49 patients with SM, 78 with moderately severe malaria (MSM) and 19 healthy controls (HC). Repeat ADMA and endothelial function measurements were performed in patients with SM. Multivariable regression was used to assess the effect of ADMA on mortality and NO bioavailability. Plasma ADMA was increased in SM patients (0.85 µM; 95% CI 0.74–0.96) compared to those with MSM (0.54 µM; 95%CI 0.5–0.56) and HCs (0.64 µM; 95%CI 0.58–0.70; p<0.001). ADMA was an independent predictor of mortality in SM patients with each micromolar elevation increasing the odds of death 18 fold (95% CI 2.0–181; p = 0.01). ADMA was independently associated with decreased exhaled NO (rs = −0.31) and endothelial function (rs = −0.32) in all malaria patients, and with reduced exhaled NO (rs = −0.72) in those with SM. ADMA is increased in SM and associated with decreased vascular and pulmonary NO bioavailability. Inhibition of NOS by ADMA may contribute to increased mortality in severe malaria

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

PROBIT MODELS FOR CAPTURE-RECAPTURE DATA SUBJECT TO IMPERFECT DETECTION, INDIVIDUAL HETEROGENEITY AND MISIDENTIFICATION1

As noninvasive sampling techniques for animal populations have become more popular, there has been increasing interest in the development of capture-recapture models that can accommodate both imperfect detection and misidentification of individuals (e.g., due to genotyping error). However, current methods do not allow for individual variation in parameters, such as detection or survival probability. Here we develop misidentification models for capture-recapture data that can simultaneously account for temporal variation, behavioral effects and individual heterogeneity in parameters. To facilitate Bayesian inference using our approach, we extended standard probit regression techniques to latent multinomial models where the dimension and zeros of the response cannot be observed. We also present a novel Metropolis-Hastings within Gibbs algorithm for fitting these models using Markov chain Monte Carlo. Using closed population abundance models for illustration, we re-visit a DNA capture-recapture population study of black bears in Michigan, USA and find evidence of misidentification due to genotyping error, as well as temporal, behavioral and individual variation in detection probability. We also estimate a salamander population of known size from laboratory experiments evaluating the effectiveness of a marking technique commonly used for amphibians and fish. Our models was able to reliably estimate the size of this population and provided evidence of individual heterogeneity in misidentification probability that is attributable to variable mark quality. Our approach is more computationally demanding than previously proposed methods, but it provides the flexibility necessary for a much broader suite of models to be explored while properly accounting for uncertainty introduced by misidentification and imperfect detection. In the absence of misidentification, our probit formulation also provides a convenient and efficient Gibbs sampler for Bayesian analysis of traditional closed population capture-recapture data

Marine mammals trace anthropogenic structures at sea

D.J.F.R., G.H., V.M.J., S.E.W.M. and B.M. were funded by the UK Department of Energy and Climate Change (DECC) as part of their Offshore Energy Strategic Environmental Assessment programme. The tags and their deployment were funded by GSP, NUON, RWE, Eneco and Gemini, DECC, Natural Environment Research Council, Scottish Natural Heritage and Marine Scotland.On land, species from all trophic levels have adapted to fill vacant niches in environments heavily modified by humans (e.g. [1]). In the marine environment, ocean infrastructure has led to artificial reefs, resulting in localized increases in fish and crustacean density [2]. Whether marine apex predators exhibit behavioural adaptations to utilise such a scattered potential resource is unknown. Using high resolution GPS data we show how infrastructure, including wind turbines and pipelines, shapes the movements of individuals from two seal species (Phoca vitulina and Halichoerus grypus). Using state-space models, we infer that these animals are using structures to forage. We highlight the ecological consequences of such behaviour, at a time of unprecedented developments in marine infrastructure.PostprintPostprintPeer reviewe

Capture-recapture abundance estimation using a semi-complete data likelihood approach

Capture–recapture data are often collected when abundance estimation is of interest. In this manuscript we focus on abundance estimation of closed populations. In the presence of unobserved individual heterogeneity, specified on a continuous scale for the capture probabilities, the likelihood is not generally available in closed form, but expressible only as an analytically intractable integral. Model-fitting algorithms to estimate abundance most notably include a numerical approximation for the likelihood or use of a Bayesian data augmentation technique considering the complete data likelihood. We consider a Bayesian hybrid approach, defining a “semi-complete” data likelihood, composed of the product of a complete data likelihood component for individuals seen at least once within the study and a marginal data likelihood component for the individuals not seen within the study, approximated using numerical integration. This approach combines the advantages of the two different approaches, with the semi-complete likelihood component specified as a single integral (over the dimension of the individual heterogeneity component). In addition, the models can be fitted within BUGS/JAGS (commonly used for the Bayesian complete data likelihood approach) but with significantly improved computational efficiency compared to the commonly used superpopulation data augmentation approaches (between about 10 and 77 times more efficient in the two examples we consider). The semi-complete likelihood approach is flexible and applicable to a range of models, including spatially explicit capture–recapture models. The model-fitting approach is applied to two different data sets: the first relates to snowshoe hares where model Mh is applied and the second to gibbons where a spatially explicit capture–recapture model is applied

Appendix B. Large-sample simulation experiments.

Large-sample simulation experiments