unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison

Habitat occupancy of Rusty Blackbirds (Euphagus carolinus) breeding in northern New England, USA

The Rusty Blackbird (Euphagus carolinus), an uncommon songbird often associated with northern coniferous wetlands, has experienced a precipitous population decline since at least the early 20th century. Here, we provide the first analysis of breeding-habitat occupancy at the wetland scale and make recommendations for streamlined monitoring. We modeled occupancy and detectability as a function of site (i.e. habitat-based) and sampling (i.e. visit-specific) variables collected at 546 wetlands in northern New England, USA. Wetland occupancy (mean 6 SE ¼ 0.07 6 0.02 in randomly selected wetlands, and 0.12 6 0.02 in all wetlands surveyed) was best explained by variables describing Rusty Blackbird foraging habitat (PUDDLES: a proxy for shallow water), nesting habitat (coniferous adjacent uplands), and evidence of beavers. In contrast to Rusty Blackbirds’ selection of pole-stage conifers at the nest-site scale, stand age did not affect occupancy at the wetland scale. It appears that most wetlands in northern coniferous forest landscapes, regardless of stand age, offer dense conifer patches nearby and provide suitable breeding habitat if quality foraging sites (e.g., areas of shallow water) also are available. Detectability (0.29 6 0.04) decreased with increasing wind speed, and decreased about fourfold over the course of the breeding season. Rusty Blackbirds responded to broadcast of conspecific vocalizations by flying toward the observer and perching more often than prior to broadcast, demonstrating that broadcasts can be a useful tool to enhance visual detectability. Given our results, observers can now focus site selection on wetlands and sampling conditions most likely to maximize detections of Rusty Blackbirds

Positive and negative well-being and objectively measured sedentary behaviour in older adults: evidence from three cohorts

Background: Sedentary behaviour is related to poorer health independently of time spent in moderate to vigorous physical activity. The aim of this study was to investigate whether wellbeing or symptoms of anxiety or depression predict sedentary behaviour in older adults. Method: Participants were drawn from the Lothian Birth Cohort 1936 (LBC1936) (n = 271), and the West of Scotland Twenty-07 1950s (n = 309) and 1930s (n = 118) cohorts. Sedentary outcomes, sedentary time, and number of sit-to-stand transitions, were measured with a three-dimensional accelerometer (activPAL activity monitor) worn for 7 days. In the Twenty-07 cohorts, symptoms of anxiety and depression were assessed in 2008 and sedentary outcomes were assessed ~ 8 years later in 2015 and 2016. In the LBC1936 cohort, wellbeing and symptoms of anxiety and depression were assessed concurrently with sedentary behaviour in 2015 and 2016. We tested for an association between wellbeing, anxiety or depression and the sedentary outcomes using multivariate regression analysis. Results: We observed no association between wellbeing or symptoms of anxiety and the sedentary outcomes. Symptoms of depression were positively associated with sedentary time in the LBC1936 and Twenty-07 1950s cohort, and negatively associated with number of sit-to-stand transitions in the LBC1936. Meta-analytic estimates of the association between depressive symptoms and sedentary time or number of sit-to-stand transitions, adjusted for age, sex, BMI, long-standing illness, and education, were β = 0.11 (95% CI = 0.03, 0.18) and β = − 0.11 (95% CI = − 0.19, −0.03) respectively. Conclusion: Our findings indicate that depressive symptoms are positively associated with sedentary behavior. Future studies should investigate the causal direction of this association

Effects of Sample Size on Estimates of Population Growth Rates Calculated with Matrix Models

BACKGROUND: Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. METHODOLOGY/PRINCIPAL FINDINGS: Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. CONCLUSIONS/SIGNIFICANCE: We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities

Moving beyond fan typologies: The impact of social integration on team loyalty in football

The purpose of this paper is to develop detailed insight into loyalty among football fans of Hibernian FC, moving beyond typologies to a more socially grounded approach. Issues explored include patterns of consumption, distinctions between fan groups, and antecedents of loyalty. The origins and development of the club are evaluated, and consumer fanaticism, football fan loyalty, consumption behaviour, and the sociological impact of fan communities are discussed. Data were collected using a variety of methods, including participant observation, in-depth interviews, and analysis of websites and fan forums. Key findings relate to the impact of family and community influences on loyalty, initial experiences of developing associations with the club, through to the impact of socialisation, and the lived experience of being a supporter. A supporter matrix is constructed as a portrayal of the loyalty found at the club. A range of theoretical implications is considered, and the matrix promoted as a tool for understanding loyalty in clubs with similar social structures and community connections

Leaders' sensemaking under crises:emerging cognitive consensus over time within management teams

When facing a crisis, leaders' sensemaking can take a considerable amount of time due to the need to develop consensus in how to deal with it so that vision formation and sensegiving can take place. However, research into emerging cognitive consensus when leaders deal with a crisis over time is lacking. This is limiting a detailed understanding of how organizations respond to crises. The findings, based on a longitudinal analysis of cognitive maps within three management teams at a single organization, highlight considerable individual differences in cognitive content when starting to make sense of a crisis. Evidence for an emerging viable prescriptive mental model for the future was found, but not so much in the management as a whole. Instead, the findings highlight increasing cognitive consensus based on similarities in objectives and cause-effect beliefs within well-defined management teams over time

Patterns and associates of cognitive function, psychosocial wellbeing and health in the Lothian Birth Cohort 1936

BACKGROUND: Cognitive function, psychosocial wellbeing and health are important domains of function. Consistencies and inconsistencies in patterns of wellbeing across these domains may be informative about wellbeing in old age and the ways it is manifested amongst individuals. In this study we investigated whether there were groups of individuals with different profiles of scores across these domains. We also aimed to identify characteristics of any evident groups by comparing them on variables that were not used in identifying the groups. METHODS: The sample was the Lothian Birth Cohort 1936, which included 1091 participants born in 1936. They are a community-dwelling, narrow-age-range sample of 70-year-olds. Most had taken part in the Scottish Mental Survey 1947 at an average age of 11, making available a measure of childhood intelligence. We used latent class analysis (LCA) to explore possible profiles using 9 variables indicating cognitive functioning, psychosocial wellbeing and health status. Demographic, personality, and lifestyle variables – none of which were used in the LCA – were used to characterize the resulting profile groups. RESULTS: We accepted a 3-group solution, which we labeled High Wellbeing (65.3%), Low Cognition (20.3%), and Low Bio-Psychosocial (14.5%). Notably, the High Wellbeing group had significantly higher childhood IQ, lower Neuroticism scores, and a lower percentage of current smokers than the other 2 groups. CONCLUSION: The majority of individuals were functioning generally well; however, there was evidence of the presence of groups with different profiles, which may be explained in part in terms of cognitive ability differences. Results suggested that higher life-long intelligence, personality traits associated with less mental distress, and basic health practices such as avoiding smoking are important associates of wellbeing in old age

Virtual Morality: Transitioning from Moral Judgment to Moral Action?

The nature of moral action versus moral judgment has been extensively debated in numerous disciplines. We introduce Virtual Reality (VR) moral paradigms examining the action individuals take in a high emotionally arousing, direct action-focused, moral scenario. In two studies involving qualitatively different populations, we found a greater endorsement of utilitarian responses–killing one in order to save many others–when action was required in moral virtual dilemmas compared to their judgment counterparts. Heart rate in virtual moral dilemmas was significantly increased when compared to both judgment counterparts and control virtual tasks. Our research suggests that moral action may be viewed as an independent construct to moral judgment, with VR methods delivering new prospects for investigating and assessing moral behaviour

Alternative spatial sampling in studies of plant demography: Consequences for estimates of population growth rate

Ecologists commonly use matrix models to study the population dynamics of plants. Most studies of plant demography use plot-based methods to collect data, in part, because mapped individuals are easier to relocate in subsequent surveys and survey methods can be standardized among sites. However, there is tremendous variation among studies, both in terms of plot arrangement and the total area sampled. In addition, there has been little discussion of how alternative sampling arrangements influence estimates of population growth rates (λ) calculated with matrix models. We surveyed the literature to determine what sampling designs are most used in studies of plant demography using matrix models. We then used simulations of three common sampling techniques-using a single randomly placed plot, multiple randomly placed plots, and systematically distributed plots-to evaluate how these alternative strategies influenced the precision of estimates of λ. These simulations were based on long-term demographic data collected on 13 populations of the Amazonian understory herb Heliconia acuminate (Heliconiaceae). We found that the method used to collect data did not affect the bias or precision of estimates in our system-a surprising result, since the advantage in efficiency that is gained from systematic sampling is a well-known result from sampling theory. Because the statistical advantage of systematic sampling is most evident when there is spatial structure in demographic vital rates, we attribute this result to the lack of spatially structured vital rates in our focal populations. Given the likelihood of spatial autocorrelation in most ecological systems, we advocate sampling with a systematic grid of plots in each study site, as well as that researchers ensure that enough area is sampled-both within and across sites-to encompass the range of spatial variation in plant survival, growth, and reproduction. © Springer Science+Business Media B.V. 2009