Direct evidence of poison-driven widespread population decline in a wild vertebrate

Toxicants such as organochlorine insecticides, lead ammunition, and veterinary drugs have caused severe wildlife poisoning, pushing the populations of several apex species to the edge of extinction. These prime cases epitomize the serious threat that wildlife poisoning poses to biodiversity. Much of the evidence on population effects of wildlife poisoning rests on assessments conducted at an individual level, from which population-level effects are inferred. Contrastingly, we demonstrate a straightforward relationship between poison-induced individual mortality and population changes in the threatened red kite (Milvus milvus). By linking field data of 1,075 poisoned red kites to changes in occupancy and abundance across 274 sites (10 × 10-km squares) over a 20-y time frame, we show a clear relationship between red kite poisoning and the decline of its breeding population in Spain, including local extinctions. Our results further support the species listing as endangered, after a breeding population decline of 31% to 43% in two decades of this once-abundant raptor. Given that poisoning threatens the global populations of more than 2,600 animal species worldwide, a greater understanding of its population-level effects may aid biodiversity conservation through increased regulatory control of chemical substances. Our results illustrate the great potential of long-term and large-scale on-ground monitoring to assist in this task.

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Population- and Individual-Level Dynamics of the Intestinal Microbiota of a Small Primate

Applied and Environmental Microbiology ◽

10.1128/aem.00559-16 ◽

2016 ◽

Vol 82 (12) ◽

pp. 3537-3545 ◽

Cited By ~ 27

Author(s):

Tuomas Aivelo ◽

Juha Laakkonen ◽

Jukka Jernvall

Keyword(s):

Intestinal Microbiota ◽

Large Scale ◽

Small Body ◽

Bacterial Community Composition ◽

Temporal Trends ◽

Population Level ◽

Microbiota Composition ◽

Individual Level ◽

Mouse Lemurs ◽

Free Ranging

ABSTRACTLongitudinal sampling for intestinal microbiota in wild animals is difficult, leading to a lack of information on bacterial dynamics occurring in nature. We studied how the composition of microbiota communities changed temporally in free-ranging small primates, rufous mouse lemurs (Microcebus rufus). We marked and recaptured mouse lemurs during their mating season in Ranomafana National Park in southeastern mountainous rainforests of Madagascar for 2 years and determined the fecal microbiota compositions of these mouse lemurs with MiSeq sequencing. We collected 160 fecal samples from 71 animals and had two or more samples from 39 individuals. We found small, but statistically significant, effects of site and age on microbiota richness and diversity and effects of sex, year, and site on microbiota composition, while the within-year temporal trends were less clear. Within-host microbiota showed pervasive variation in intestinal bacterial community composition, especially during the second study year. We hypothesize that the biological properties of mouse lemurs, including their small body size and fast metabolism, may contribute to the temporal intraindividual-level variation, something that should be testable with more-extensive sampling regimes.IMPORTANCEWhile microbiome research has blossomed in recent years, there is a lack of longitudinal studies on microbiome dynamics on free-ranging hosts. To fill this gap, we followed mouse lemurs, which are small heterothermic primates, for 2 years. Most studied animals have shown microbiota to be stable over the life span of host individuals, but some previous research also found ample within-host variation in microbiota composition. Our study used a larger sample size than previous studies and a study setting well suited to track within-host variation in free-ranging mammals. Despite the overall microbiota stability at the population level, the microbiota of individual mouse lemurs can show large-scale changes in composition in time periods as short as 2 days, suggesting caution in inferring individual-level patterns from population-level data.

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Impact of increasing vegetarian availability on meal selection and sales in cafeterias

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1907207116 ◽

2019 ◽

Vol 116 (42) ◽

pp. 20923-20929 ◽

Cited By ~ 19

Author(s):

Emma E. Garnett ◽

Andrew Balmford ◽

Chris Sandbrook ◽

Mark A. Pilling ◽

Theresa M. Marteau

Keyword(s):

Large Scale ◽

Population Level ◽

Field Studies ◽

Individual Level ◽

Rebound Effects ◽

Percentage Points ◽

Physical Environments ◽

Meat Meal ◽

Level Data ◽

The Impact

Shifting people in higher income countries toward more plant-based diets would protect the natural environment and improve population health. Research in other domains suggests altering the physical environments in which people make decisions (“nudging”) holds promise for achieving socially desirable behavior change. Here, we examine the impact of attempting to nudge meal selection by increasing the proportion of vegetarian meals offered in a year-long large-scale series of observational and experimental field studies. Anonymized individual-level data from 94,644 meals purchased in 2017 were collected from 3 cafeterias at an English university. Doubling the proportion of vegetarian meals available from 25 to 50% (e.g., from 1 in 4 to 2 in 4 options) increased vegetarian meal sales (and decreased meat meal sales) by 14.9 and 14.5 percentage points in the observational study (2 cafeterias) and by 7.8 percentage points in the experimental study (1 cafeteria), equivalent to proportional increases in vegetarian meal sales of 61.8%, 78.8%, and 40.8%, respectively. Linking sales data to participants’ previous meal purchases revealed that the largest effects were found in the quartile of diners with the lowest prior levels of vegetarian meal selection. Moreover, serving more vegetarian options had little impact on overall sales and did not lead to detectable rebound effects: Vegetarian sales were not lower at other mealtimes. These results provide robust evidence to support the potential for simple changes to catering practices to make an important contribution to achieving more sustainable diets at the population level.

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A difference that matters: comparisons of structured and semi-structured psychiatric diagnostic interviews in the general population

Psychological Medicine ◽

10.1017/s0033291799008880 ◽

1999 ◽

Vol 29 (5) ◽

pp. 1013-1020 ◽

Cited By ~ 77

Author(s):

T. S. BRUGHA ◽

P. E. BEBBINGTON ◽

R. JENKINS

Keyword(s):

General Population ◽

Psychiatric Disorders ◽

Large Scale ◽

Population Level ◽

Individual Level ◽

Case Identification ◽

Diagnostic Interviews ◽

Health Project ◽

The Individual ◽

General Populations

Psychiatric case-identification in general populations allows us to study both individuals with functional psychiatric disorders and the populations from which they come. The individual level of analysis permits disorders to be related to factors of potential aetiological significance and the study of attributes of the disorders that need to be assessed in non-referred populations (an initially scientific endeavour). At the population level valid case identification can be used to evaluate needs for treatment and the utilization of service resources (a public health project). Thus, prevalence is of interest both to scientists and to those responsible for commissioning and planning services (Brugha et al. 1997; Regier et al. 1998). The quality of case identification techniques and of estimates of prevalence is thus of general concern (Bartlett & Coles, 1998).Structured diagnostic interviews were introduced into general population surveys in the 1970s as a method ‘to enable interviewers to obtain psychiatric diagnoses comparable to those a psychiatrist would obtain’ (Robins et al. 1981). The need to develop reliable standardized measures was partly driven by an earlier generation of prevalence surveys showing rates ranging widely from 10·9% (Pasamanick et al. 1956) to 55% (Leighton et al. 1963) in urban and rural North American communities respectively. If the success of large scale psychiatric epidemiological enquiries using structured diagnostic interviews and standardized classifications is measured in terms of citation rates it would seem difficult to question. But the development of standardized interviews of functional psychiatric disorders has not solved this problem of variability: the current generation of large scale surveys, using structured diagnostic interviews and serving strictly defined classification rules, have generated, for example, 12-month prevalence rates of major depression in the US of 4·2% (Robins & Regier, 1991) and 10·1% (Kessler et al. 1994). This calls into question the validity of the assessments, such that we must reopen the question of what they should be measuring and how they should do it.

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Shared and unique brain network features predict cognition, personality and mental health in childhood

10.1101/2020.06.24.168724 ◽

2020 ◽

Cited By ~ 3

Author(s):

Jianzhong Chen ◽

Angela Tam ◽

Valeria Kebets ◽

Csaba Orban ◽

Leon Qi Rong Ooi ◽

...

Keyword(s):

Mental Health ◽

Individual Differences ◽

Large Scale ◽

Population Level ◽

Brain Network ◽

Behavioral Variability ◽

Network Organization ◽

Individual Level ◽

And Task ◽

Behavioral Domains

AbstractThe manner through which individual differences in brain network organization track population-level behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, the focus of most studies on single behavioral traits has come at the expense of capturing broader relationships across behaviors. Here, we utilized a large-scale dataset of 1858 typically developing children to estimate whole-brain functional network organization that is predictive of individual differences in cognition, impulsivity-related personality, and mental health during rest and task states. Predictive network features were distinct across the broad behavioral domains: cognition, personality and mental health. On the other hand, traits within each behavioral domain were predicted by highly similar network features. This is surprising given decades of research emphasizing that distinct brain networks support different mental processes. Although tasks are known to modulate the functional connectome, we found that predictive network features were similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood, yet are unique to different behavioral domains.

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Conformity bias in the cultural transmission of music sampling traditions

Royal Society Open Science ◽

10.1098/rsos.191149 ◽

2019 ◽

Vol 6 (9) ◽

pp. 191149 ◽

Cited By ~ 2

Author(s):

Mason Youngblood

Keyword(s):

Cultural Transmission ◽

Large Scale ◽

Scale Up ◽

Population Level ◽

Neutral Evolution ◽

Individual Level ◽

Online Databases ◽

Approximate Bayesian ◽

Cultural Evolutionary ◽

Turn Over

One of the fundamental questions of cultural evolutionary research is how individual-level processes scale up to generate population-level patterns. Previous studies in music have revealed that frequency-based bias (e.g. conformity and novelty) drives large-scale cultural diversity in different ways across domains and levels of analysis. Music sampling is an ideal research model for this process because samples are known to be culturally transmitted between collaborating artists, and sampling events are reliably documented in online databases. The aim of the current study was to determine whether frequency-based bias has played a role in the cultural transmission of music sampling traditions, using a longitudinal dataset of sampling events across three decades. Firstly, we assessed whether turn-over rates of popular samples differ from those expected under neutral evolution. Next, we used agent-based simulations in an approximate Bayesian computation framework to infer what level of frequency-based bias likely generated the observed data. Despite anecdotal evidence of novelty bias, we found that sampling patterns at the population-level are most consistent with conformity bias. We conclude with a discussion of how counter-dominance signalling may reconcile individual cases of novelty bias with population-level conformity.

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SARS-CoV-2 serology across scales: a framework for unbiased seroprevalence estimation incorporating antibody kinetics and epidemic recency

10.1101/2021.09.09.21263139 ◽

2021 ◽

Author(s):

Saki Takahashi ◽

Michael J Peluso ◽

Jill Hakim ◽

Keirstinne Turcios ◽

Owen Janson ◽

...

Keyword(s):

Large Scale ◽

Statistical Approach ◽

Population Level ◽

Individual Level ◽

Antibody Titers ◽

Severe Infections ◽

Study Designs ◽

Antibody Levels ◽

Antibody Kinetics ◽

Parameter Values

Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

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Zeitstrukturen im Jazz

Zeitschrift für Ästhetik und Allgemeine Kunstwissenschaft ◽

10.28937/1000106230 ◽

2014 ◽

Vol 59 (1) ◽

pp. 79-92

Author(s):

Alexander Becker

Keyword(s):

Large Scale ◽

Large Scale Structure ◽

Time Frame ◽

Scale Structure ◽

Classical Form ◽

Jazz Music ◽

The Moment

Wie erlebt der Hörer Jazz? Bei dieser Frage geht es unter anderem um die Art und Weise, wie Jazz die Zeit des Hörens gestaltet. Ein an klassischer Musik geschultes Ohr erwartet von musikalischer Zeitgestaltung, den zeitlichen Rahmen, der durch Anfang und Ende gesetzt ist, von innen heraus zu strukturieren und neu zu konstituieren. Doch das ist keine Erwartung, die dem Jazz gerecht wird. Im Jazz wird der Moment nicht im Hinblick auf ein Ziel gestaltet, das von einer übergeordneten Struktur bereitgestellt wird, sondern so, dass er den Bewegungsimpuls zum nächsten Moment weiterträgt. Wie wirkt sich dieses Prinzip der Zeitgestaltung auf die musikalische Form im Großen aus? Der Aufsatz untersucht diese Frage anhand von Beispielen, an denen sich der Weg der Transformation von einer klassischen zu einer dem Jazz angemessenen Form gut nachverfolgen lässt.<br><br>How do listeners experience Jazz? This is a question also about how Jazz music organizes the listening time. A classically educated listener expects a piece of music to structure, unify and thereby re-constitute the externally given time frame. Such an expectation is foreign to Jazz music which doesn’t relate the moment to a goal provided by a large scale structure. Rather, one moment is carried on to the next, preserving the stimulus potentially ad infinitum. How does such an organization of time affect the large scale form? The paper tries to answer this question by analyzing two examples which permit to trace the transformation of a classical form into a form germane to Jazz music.

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The Green New Deal

10.31228/osf.io/zakfb ◽

2019 ◽

Author(s):

Robert C. Hockett

Keyword(s):

New Deal ◽

Large Scale ◽

Public Investment ◽

Climate Science ◽

Time Frame ◽

White Paper ◽

Good News ◽

Carbon Neutrality ◽

The One ◽

In Virtue Of

This white paper lays out the guiding vision behind the Green New Deal Resolution proposed to the U.S. Congress by Representative Alexandria Ocasio-Cortez and Senator Bill Markey in February of 2019. It explains the senses in which the Green New Deal is 'green' on the one hand, and a new 'New Deal' on the other hand. It also 'makes the case' for a shamelessly ambitious, not a low-ball or slow-walked, Green New Deal agenda. At the core of the paper's argument lies the observation that only a true national mobilization on the scale of those associated with the original New Deal and the Second World War will be up to the task of comprehensively revitalizing the nation's economy, justly growing our middle class, and expeditiously achieving carbon-neutrality within the twelve-year time-frame that climate science tells us we have before reaching an environmental 'tipping point.' But this is actually good news, the paper argues. For, paradoxically, an ambitious Green New Deal also will be the most 'affordable' Green New Deal, in virtue of the enormous productivity, widespread prosperity, and attendant public revenue benefits that large-scale public investment will bring. In effect, the Green New Deal will amount to that very transformative stimulus which the nation has awaited since the crash of 2008 and its debt-deflationary sequel.

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Blood Pressure Trajectories Across the Life Course

American Journal of Hypertension ◽

10.1093/ajh/hpab009 ◽

2021 ◽

Vol 34 (3) ◽

pp. 234-241

Author(s):

Norrina B Allen ◽

Sadiya S Khan

Keyword(s):

Blood Pressure ◽

Measurement Errors ◽

Clinical Care ◽

Population Level ◽

Cumulative Exposure ◽

Older Adulthood ◽

Individual Level ◽

The Life Course ◽

Level Group ◽

Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

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Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Sustainability ◽

10.3390/su13010368 ◽

2021 ◽

Vol 13 (1) ◽

pp. 368

Author(s):

Dillon T. Fitch ◽

Hossain Mohiuddin ◽

Susan L. Handy

Keyword(s):

Travel Behavior ◽

Regression Models ◽

Population Level ◽

Panel Survey ◽

Multilevel Regression ◽

Combine Data ◽

Cross Sectional ◽

Individual Level ◽

Before And After ◽

Bike Share

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

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