@article{parsons_dawrs_nelson_norton_virdi_hasan_epperson_holst_chan_leos-barajas_et al._2022, title={Soil Properties and Moisture Synergistically Influence Nontuberculous Mycobacterial Prevalence in Natural Environments of Hawai'i}, volume={4}, ISSN={["1098-5336"]}, DOI={10.1128/aem.00018-22}, abstractNote={Nontuberculous mycobacteria (NTM) are ubiquitous in the environment, being found commonly in soils and natural bodies of freshwater. However, little is known about the environmental niches of NTM and how they relate to NTM prevalence in homes and other human-dominated areas. ABSTRACT Nontuberculous mycobacteria (NTM) are opportunistic pathogens that cause chronic pulmonary disease (PD). NTM infections are thought to be acquired from the environment; however, the basal environmental factors that drive and sustain NTM prevalence are not well understood. The highest prevalence of NTM PD cases in the United States is reported from Hawai’i, which is unique in its climate and soil composition, providing an opportunity to investigate the environmental drivers of NTM prevalence. We used microbiological sampling and spatial logistic regression complemented with fine-scale soil mineralogy to model the probability of NTM presence across the natural landscape of Hawai’i. Over 7 years, we collected and microbiologically cultured 771 samples from 422 geographic sites in natural areas across the Hawaiian Islands for the presence of NTM. NTM were detected in 210 of these samples (27%), with Mycobacterium abscessus being the most frequently isolated species. The probability of NTM presence was highest in expansive soils (those that swell with water) with a high water balance (>1-m difference between rainfall and evapotranspiration) and rich in Fe-oxides/hydroxides. We observed a positive association between NTM presence and iron in wet soils, supporting past studies, but no such association in dry soils. High soil-water balance may facilitate underground movement of NTM into the aquifer system, potentially compounded by expansive capabilities allowing crack formation under drought conditions, representing further possible avenues for aquifer infiltration. These results suggest both precipitation and soil properties are mechanisms by which surface NTM may reach the human water supply. IMPORTANCE Nontuberculous mycobacteria (NTM) are ubiquitous in the environment, being found commonly in soils and natural bodies of freshwater. However, little is known about the environmental niches of NTM and how they relate to NTM prevalence in homes and other human-dominated areas. To characterize NTM environmental associations, we collected and cultured 771 samples from 422 geographic sites in natural areas across Hawai’i, the U.S. state with the highest prevalence of NTM pulmonary disease. We show that the environmental niches of NTM are most associated with highly expansive, moist soils containing high levels of iron oxides/hydroxides. Understanding the factors associated with NTM presence in the natural environment will be crucial for identifying potential mechanisms and risk factors associated with NTM infiltration into water supplies, which are ultimately piped into homes where most exposure risk is thought to occur.}, journal={APPLIED AND ENVIRONMENTAL MICROBIOLOGY}, author={Parsons, Arielle W. and Dawrs, Stephanie N. and Nelson, Stephen T. and Norton, Grant J. and Virdi, Ravleen and Hasan, Nabeeh A. and Epperson, L. Elaine and Holst, Brady and Chan, Edward D. and Leos-Barajas, Vianey and et al.}, year={2022}, month={Apr} }
 @article{oetting_langrock_deutscher_leos-barajas_2020, title={The hot hand in professional darts}, volume={183}, ISSN={["1467-985X"]}, DOI={10.1111/rssa.12527}, abstractNote={We investigate the hot hand hypothesis in professional darts in a nearly ideal setting with minimal to no interaction between players. Considering almost 1 year of tournament data, corresponding to 167492 dart throws in total, we use state space models to investigate serial dependence in throwing performance. In our models, a latent state process serves as a proxy for a player's underlying form, and we use auto‐regressive processes to model how this process evolves over time. Our results regarding the persistence of the latent process indicate a weak hot hand effect, but the evidence is inconclusive.}, number={2}, journal={JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY}, author={Oetting, Marius and Langrock, Roland and Deutscher, Christian and Leos-Barajas, Vianey}, year={2020}, month={Feb}, pages={565–580} }
 @article{ruiz-suarez_leos-barajas_alvarez-castro_manuel morales_2020, title={Using approximate Bayesian inference for a "steps and turns'' continuous-time random walk observed at regular time intervals}, volume={8}, ISSN={["2167-8359"]}, DOI={10.7717/peerj.8452}, abstractNote={The study of animal movement is challenging because movement is a process modulated by many factors acting at different spatial and temporal scales. In order to describe and analyse animal movement, several models have been proposed which differ primarily in the temporal conceptualization, namely continuous and discrete time formulations. Naturally, animal movement occurs in continuous time but we tend to observe it at fixed time intervals. To account for the temporal mismatch between observations and movement decisions, we used a state-space model where movement decisions (steps and turns) are made in continuous time. That is, at any time there is a non-zero probability of making a change in movement direction. The movement process is then observed at regular time intervals. As the likelihood function of this state-space model turned out to be intractable yet simulating data is straightforward, we conduct inference using different variations of Approximate Bayesian Computation (ABC). We explore the applicability of this approach as a function of the discrepancy between the temporal scale of the observations and that of the movement process in a simulation study. Simulation results suggest that the model parameters can be recovered if the observation time scale is moderately close to the average time between changes in movement direction. Good estimates were obtained when the scale of observation was up to five times that of the scale of changes in direction. We demonstrate the application of this model to a trajectory of a sheep that was reconstructed in high resolution using information from magnetometer and GPS devices. The state-space model used here allowed us to connect the scales of the observations and movement decisions in an intuitive and easy to interpret way. Our findings underscore the idea that the time scale at which animal movement decisions are made needs to be considered when designing data collection protocols. In principle, ABC methods allow to make inferences about movement processes defined in continuous time but in terms of easily interpreted steps and turns.}, journal={PEERJ}, author={Ruiz-Suarez, Sofia and Leos-Barajas, Vianey and Alvarez-Castro, Ignacio and Manuel Morales, Juan}, year={2020}, month={Feb} }
 @article{adam_griffiths_leos‐barajas_meese_lowe_blackwell_righton_langrock_2019, title={Joint modelling of multi‐scale animal movement data using hierarchical hidden Markov models}, volume={10}, ISSN={2041-210X 2041-210X}, url={http://dx.doi.org/10.1111/2041-210x.13241}, DOI={10.1111/2041-210x.13241}, abstractNote={Hidden Markov models are prevalent in animal movement modelling, where they are widely used to infer behavioural modes and their drivers from various types of telemetry data. To allow for meaningful inference, observations need to be equally spaced in time, or otherwise regularly sampled, where the corresponding temporal resolution strongly affects what kind of behaviours can be inferred from the data. Recent advances in biologging technology have led to a variety of novel telemetry sensors which often collect data from the same individual simultaneously at different time‐scales, for example step lengths obtained from GPS tags every hour, dive depths obtained from time‐depth recorders once per dive, or accelerations obtained from accelerometers several times per second. However, to date, statistical machinery to address the corresponding complex multi‐stream and multi‐scale data is lacking. We propose hierarchical hidden Markov models as a versatile statistical framework that naturally accounts for differing temporal resolutions across multiple variables. In these models, the observations are regarded as stemming from multiple connected behavioural processes, each of which operates at the time‐scale at which the corresponding variables were observed. By jointly modelling multiple data streams, collected at different temporal resolutions, corresponding models can be used to infer behavioural modes at multiple time‐scales and in particular, help to draw a much more comprehensive picture of an animal's movement patterns, for example with regard to long‐term versus short‐term movement strategies. The suggested approach is illustrated in two real‐data applications, where we jointly model (a) coarse‐scale horizontal and fine‐scale vertical Atlantic cod Gadus morhua movements throughout the English Channel, and (b) coarse‐scale horizontal movements and corresponding fine‐scale accelerations of a horn shark Heterodontus francisci tagged off the Californian coast.}, number={9}, journal={Methods in Ecology and Evolution}, publisher={Wiley}, author={Adam, Timo and Griffiths, Christopher A. and Leos‐Barajas, Vianey and Meese, Emily N. and Lowe, Christopher G. and Blackwell, Paul G. and Righton, David and Langrock, Roland}, editor={Auger‐Méthé, MarieEditor}, year={2019}, month={Jul}, pages={1536–1550} }
 @article{gardiner_hamer_leos‐barajas_peñaherrera‐palma_jones_johnson_2019, title={State‐space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape}, volume={9}, ISSN={2045-7758 2045-7758}, url={http://dx.doi.org/10.1002/ece3.5519}, DOI={10.1002/ece3.5519}, abstractNote={Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches.Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer-scale individual behaviors. We applied hidden Markov models (HMM) to movement data from 26 eastern bettongs (Bettongia gaimardi) in fragmented landscapes. HMMs are able to identify distinct behavior states associated with different movement patterns and discover how these behaviors are associated with habitat features.Three distinct behavior states were identified and interpreted as denning, foraging, and fast-traveling. The probability of occurrence of each state, and of transitions between them, was predicted by variation in tree-canopy cover and understorey vegetation density. Denning was associated with woodland with low canopy cover but high vegetation density, foraging with high canopy cover but low vegetation density, and fast-traveling with low canopy cover and low vegetation density.Bettongs did move outside woodland patches, often fast-traveling through pasture and using smaller stands of trees as stepping stones between neighboring patches. Males were more likely to fast-travel and venture outside woodlands patches, while females concentrated their movement within woodland patches. Synthesis and applications: Our work demonstrates the value of using animal movement to understand how animals respond to variation in habitat structure, including fragmentation. Analysis using HMMs was able to characterize distinct habitat types needed for foraging and denning, and identify landscape features that facilitate movement between patches. Future work should extend the use of individual movement analyses to guide management of fragmented habitat in ways that support persistence of species potentially threatened by habitat loss.}, number={17}, journal={Ecology and Evolution}, publisher={Wiley}, author={Gardiner, Riana and Hamer, Rowena and Leos‐Barajas, Vianey and Peñaherrera‐Palma, Cesar and Jones, Menna E. and Johnson, Chris}, year={2019}, month={Aug}, pages={9804–9814} }
 @article{papastamatiou_watanabe_demšar_leos-barajas_bradley_langrock_weng_lowe_friedlander_caselle_2018, title={Activity seascapes highlight central place foraging strategies in marine predators that never stop swimming}, volume={6}, ISSN={2051-3933}, url={http://dx.doi.org/10.1186/s40462-018-0127-3}, DOI={10.1186/s40462-018-0127-3}, abstractNote={Central place foragers (CPF) rest within a central place, and theory predicts that distance of patches from this central place sets the outer limits of the foraging arena. Many marine ectothermic predators behave like CPF animals, but never stop swimming, suggesting that predators will incur 'travelling' costs while resting. Currently, it is unknown how these CPF predators behave or how modulation of behavior contributes to daily energy budgets. We combine acoustic telemetry, multi-sensor loggers, and hidden Markov models (HMMs) to generate 'activity seascapes', which combine space use with patterns of activity, for reef sharks (blacktip reef and grey reef sharks) at an unfished Pacific atoll.Sharks of both species occupied a central place during the day within deeper, cooler water where they were less active, and became more active over a larger area at night in shallower water. However, video cameras on two grey reef sharks revealed foraging attempts/success occurring throughout the day, and that multiple sharks were refuging in common areas. A simple bioenergetics model for grey reef sharks predicted that diel changes in energy expenditure are primarily driven by changes in swim speed and not body temperature.We provide a new method for simultaneously visualizing diel space use and behavior in marine predators, which does not require the simultaneous measure of both from each animal. We show that blacktip and grey reef sharks behave as CPFs, with diel changes in activity, horizontal and vertical space use. However, aspects of their foraging behavior may differ from other predictions of traditional CPF models. In particular, for species that never stop swimming, patch foraging times may be unrelated to patch travel distance.}, number={1}, journal={Movement Ecology}, publisher={Springer Science and Business Media LLC}, author={Papastamatiou, Yannis P. and Watanabe, Yuuki Y. and Demšar, Urška and Leos-Barajas, Vianey and Bradley, Darcy and Langrock, Roland and Weng, Kevin and Lowe, Christopher G. and Friedlander, Alan M. and Caselle, Jennifer E.}, year={2018}, month={Jun} }
 @article{papastamatiou_iosilevskii_leos-barajas_brooks_howey_chapman_watanabe_2018, title={Optimal swimming strategies and behavioral plasticity of oceanic whitetip sharks}, volume={8}, ISSN={2045-2322}, url={http://dx.doi.org/10.1038/s41598-017-18608-z}, DOI={10.1038/s41598-017-18608-z}, abstractNote={Abstract Animal behavior should optimize the difference between the energy they gain from prey and the energy they spend searching for prey. This is all the more critical for predators occupying the pelagic environment, as prey is sparse and patchily distributed. We theoretically derive two canonical swimming strategies for pelagic predators, that maximize their energy surplus while foraging. They predict that while searching, a pelagic predator should maintain small dive angles, swim at speeds near those that minimize the cost of transport, and maintain constant speed throughout the dive. Using biologging sensors, we show that oceanic whitetip shark ( Carcharhinus longimanus ) behavior matches these predictions. We estimate that daily energy requirements of an adult shark can be met by consuming approximately 1–1.5 kg of prey (1.5% body mass) per day; shark-borne video footage shows a shark encountering potential prey numbers exceeding that amount. Oceanic whitetip sharks showed incredible plasticity in their behavioral strategies, ranging from short low-energy bursts on descents, to high-speed vertical surface breaches from considerable depth. Oceanic whitetips live a life of energy speculation with minimization, very different to those of tunas and billfish.}, number={1}, journal={Scientific Reports}, publisher={Springer Nature}, author={Papastamatiou, Yannis P. and Iosilevskii, Gil and Leos-Barajas, Vianey and Brooks, Edd J. and Howey, Lucy A. and Chapman, Demian D. and Watanabe, Yuuki Y.}, year={2018}, month={Jan} }
 @article{langrock_adam_leos-barajas_mews_miller_papastamatiou_2018, title={Spline-based nonparametric inference in general state-switching models}, volume={72}, ISSN={0039-0402}, url={http://dx.doi.org/10.1111/stan.12133}, DOI={10.1111/stan.12133}, abstractNote={State‐switching models combine immense flexibility with relative mathematical simplicity and computational tractability and, as a consequence, have established themselves as general‐purpose models for time series data. In this paper, we provide an overview of ways to use penalized splines to allow for flexible nonparametric inference within state‐switching models, and provide a critical discussion of the use of corresponding classes of models. The methods are illustrated using animal acceleration data and energy price data.}, number={3}, journal={Statistica Neerlandica}, publisher={Wiley}, author={Langrock, Roland and Adam, Timo and Leos-Barajas, Vianey and Mews, Sina and Miller, David L. and Papastamatiou, Yannis P.}, year={2018}, month={Apr}, pages={179–200} }
 @article{gangloff_chow_leos-barajas_hynes_hobbs_sparkman_2017, title={Integrating behaviour into the pace-of-life continuum: Divergent levels of activity and information gathering in fast- and slow-living snakes}, volume={142}, ISSN={0376-6357}, url={http://dx.doi.org/10.1016/j.beproc.2017.06.006}, DOI={10.1016/j.beproc.2017.06.006}, abstractNote={An animal’s life history, physiology, and behaviour can be shaped by selection in a manner that favours strong associations among these aspects of an integrated phenotype. Recent work combining animal personality and life-history theory proposes that animals with faster life-history strategies (i.e., fast growth, high annual reproductive rate, short lifespan) should exhibit higher general activity levels relative to those with slower life-history strategies, but empirical tests of within-species variation in these traits are lacking. In garter snakes from ecotypes which are known to differ in ecology, life-history strategy, and physiology, we tested for differences in tongue-flick rate as a measure of information gathering and movement patterns as a measure of general activity. Tongue flicks and movement were strongly positively correlated and both behaviours were repeatable across trials. Snakes from the fast-living ecotype were more active and showed evidence of habituation. The slow-living ecotype maintained low levels of activity throughout the trials. We propose that environmental factors, such as high predation, experienced by the fast-living ecotype select for both increased information-gathering and activity levels to facilitate efficient responses to repeated challenges. Thus, we offer evidence that behaviour is an important component of co-evolved suites of traits forming a general pace-of-life continuum in this system.}, journal={Behavioural Processes}, publisher={Elsevier BV}, author={Gangloff, Eric J. and Chow, Melinda and Leos-Barajas, Vianey and Hynes, Stephanie and Hobbs, Brooke and Sparkman, Amanda M.}, year={2017}, month={Sep}, pages={156–163} }
 @article{leos-barajas_gangloff_adam_langrock_van beest_nabe-nielsen_morales_2017, title={Multi-scale Modeling of Animal Movement and General Behavior Data Using Hidden Markov Models with Hierarchical Structures}, volume={22}, ISSN={1085-7117 1537-2693}, url={http://dx.doi.org/10.1007/s13253-017-0282-9}, DOI={10.1007/s13253-017-0282-9}, abstractNote={Hidden Markov models (HMMs) are commonly used to model animal movement data and infer aspects of animal behavior. An HMM assumes that each data point from a time series of observations stems from one of N possible states. The states are loosely connected to behavioral modes that manifest themselves at the temporal resolution at which observations are made. Due to advances in tag technology and tracking with digital video recordings, data can be collected at increasingly fine temporal resolutions. Yet, inferences at time scales cruder than those at which data are collected and, which correspond to larger-scale behavioral processes, are not yet answered via HMMs. We include additional hierarchical structures to the basic HMM framework, incorporating multiple Markov chains at various time scales. The hierarchically structured HMMs allow for behavioral inferences at multiple time scales and can also serve as a means to avoid coarsening data. Our proposed framework is one of the first that models animal behavior simultaneously at multiple time scales, opening new possibilities in the area of animal movement and behavior modeling. We illustrate the application of hierarchically structured HMMs in two real-data examples: (i) vertical movements of harbor porpoises observed in the field, and (ii) garter snake movement data collected as part of an experimental design. Supplementary materials accompanying this paper appear online.}, number={3}, journal={Journal of Agricultural, Biological and Environmental Statistics}, publisher={Springer Science and Business Media LLC}, author={Leos-Barajas, Vianey and Gangloff, Eric J. and Adam, Timo and Langrock, Roland and van Beest, Floris M. and Nabe-Nielsen, Jacob and Morales, Juan M.}, year={2017}, month={May}, pages={232–248} }
 @article{leos-barajas_photopoulou_langrock_patterson_watanabe_murgatroyd_papastamatiou_2016, title={Analysis of animal accelerometer data using hidden Markov models}, volume={8}, ISSN={2041-210X}, url={http://dx.doi.org/10.1111/2041-210x.12657}, DOI={10.1111/2041-210x.12657}, abstractNote={Use of accelerometers is now widespread within animal biologging as they provide a means of measuring an animal's activity in a meaningful and quantitative way where direct observation is not possible. In sequential acceleration data, there is a natural dependence between observations of behaviour, a fact that has been largely ignored in most analyses. Analyses of acceleration data where serial dependence has been explicitly modelled have largely relied on hidden Markov models (HMMs). Depending on the aim of an analysis, an HMM can be used for state prediction or to make inferences about drivers of behaviour. For state prediction, a supervised learning approach can be applied. That is, an HMM is trained to classify unlabelled acceleration data into a finite set of pre‐specified categories. An unsupervised learning approach can be used to infer new aspects of animal behaviour when biologically meaningful response variables are used, with the caveat that the states may not map to specific behaviours. We provide the details necessary to implement and assess an HMM in both the supervised and unsupervised learning context and discuss the data requirements of each case. We outline two applications to marine and aerial systems (shark and eagle) taking the unsupervised learning approach, which is more readily applicable to animal activity measured in the field. HMMs were used to infer the effects of temporal, atmospheric and tidal inputs on animal behaviour. Animal accelerometer data allow ecologists to identify important correlates and drivers of animal activity (and hence behaviour). The HMM framework is well suited to deal with the main features commonly observed in accelerometer data and can easily be extended to suit a wide range of types of animal activity data. The ability to combine direct observations of animal activity with statistical models, which account for the features of accelerometer data, offers a new way to quantify animal behaviour and energetic expenditure and to deepen our insights into individual behaviour as a constituent of populations and ecosystems.}, number={2}, journal={Methods in Ecology and Evolution}, publisher={Wiley}, author={Leos-Barajas, Vianey and Photopoulou, Theoni and Langrock, Roland and Patterson, Toby A. and Watanabe, Yuuki Y. and Murgatroyd, Megan and Papastamatiou, Yannis P.}, editor={O'Hara, Robert B.Editor}, year={2016}, month={Oct}, pages={161–173} }
 @article{towner_leos-barajas_langrock_schick_smale_kaschke_jewell_papastamatiou_2016, title={Sex-specific and individual preferences for hunting strategies in white sharks}, volume={30}, ISSN={0269-8463}, url={http://dx.doi.org/10.1111/1365-2435.12613}, DOI={10.1111/1365-2435.12613}, abstractNote={1. Fine-scale predator movements may be driven by many factors including sex, habitat anddistribution of resources. There may also be individual preferences for certain movementstrategies within a population which can be hard to quantify.2. Within top predators, movements are also going to be directly related to the mode of hunting,for example sit-and-wait or actively searching for prey. Although there is mounting evidencethat different hunting modes can cause opposing trophic cascades, there has been littlefocus on the modes used by top predators, especially those in the marine environment.3. Adult white sharks (Carcharhodon carcharias) are well known to forage on marine mammalprey, particularly pinnipeds. Sharks primarily ambush pinnipeds on the surface, but there hasbeen less focus on the strategies they use to encounter prey.4. We applied mixed hidden Markov models to acoustic tracking data of white sharks in acoastal aggregation area in order to quantify changing movement states (area-restricted searching(ARS) vs. patrolling) and the factors that influenced them. Individuals were re-tracked overmultiple days throughout a month to see whether state-switching dynamics varied or if individualspreferred certain movement strategies.5. Sharks were more likely to use ARS movements in the morning and during periods of chummingby ecotourism operators. Furthermore, the proportion of time individuals spent in the two differentstates and the state-switching frequency, differed between the sexes and between individuals.6. Predation attempts/success on pinnipeds were observed for sharks in both ARS and patrollingmovement states and within all random effects groupings. Therefore, white sharks can use both a ‘sitand-wait’ (ARS) and ‘active searching’ (patrolling) movements to ambush pinniped prey on the surface.7. White sharks demonstrate individual preferences for fine-scale movement patterns, whichmay be related to their use of different hunting modes. Marine top predators are generallyassumed to use only one type of hunting mode, but we show that there may be a mix withinpopulations. As such, individual variability should be considered when modelling behaviouraleffects of predators on prey species.}, number={8}, journal={Functional Ecology}, publisher={Wiley}, author={Towner, Alison V. and Leos-Barajas, Vianey and Langrock, Roland and Schick, Robert S. and Smale, Malcolm J. and Kaschke, Tami and Jewell, Oliver J. D. and Papastamatiou, Yannis P.}, editor={Hopkins, WilliamEditor}, year={2016}, month={Jan}, pages={1397–1407} }