scholarly journals Greater wealth inequality, less polygyny: rethinking the polygyny threshold model

2018 ◽  
Vol 15 (144) ◽  
pp. 20180035 ◽  
Author(s):  
Cody T. Ross ◽  
Monique Borgerhoff Mulder ◽  
Seung-Yun Oh ◽  
Samuel Bowles ◽  
Bret Beheim ◽  
...  
Keyword(s):  
Choice Model ◽  
Threshold Model ◽  
Population Level ◽  
Wealth Inequality ◽  
Human Populations ◽  
Individual Level ◽  
Level Data ◽  
Mutual Mate Choice ◽  
Polygynous Marriage ◽  
Human Mating

Monogamy appears to have become the predominant human mating system with the emergence of highly unequal agricultural populations that replaced relatively egalitarian horticultural populations, challenging the conventional idea—based on the polygyny threshold model—that polygyny should be positively associated with wealth inequality. To address this polygyny paradox, we generalize the standard polygyny threshold model to a mutual mate choice model predicting the fraction of women married polygynously. We then demonstrate two conditions that are jointly sufficient to make monogamy the predominant marriage form, even in highly unequal societies. We assess if these conditions are satisfied using individual-level data from 29 human populations. Our analysis shows that with the shift to stratified agricultural economies: (i) the population frequency of relatively poor individuals increased, increasing wealth inequality, but decreasing the frequency of individuals with sufficient wealth to secure polygynous marriage, and (ii) diminishing marginal fitness returns to additional wives prevent extremely wealthy men from obtaining as many wives as their relative wealth would otherwise predict. These conditions jointly lead to a high population-level frequency of monogamy.

scholarly journals Do we need demographic data to forecast plant population dynamics?

2015 ◽  
Author(s):  
Andrew T. Tredennick ◽  
Mevin B. Hooten ◽  
Peter B. Adler
Keyword(s):  
Environmental Change ◽  
Forecast Accuracy ◽  
Population Level ◽  
Population Models ◽  
Demographic Model ◽  
Percent Cover ◽  
Climate Effects ◽  
Individual Level ◽  
Level Data ◽  
Significant Difference

1. Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts. 2. Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction. 3. In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types. 4. In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.

scholarly journals In search of opportunity and community: Internal migration of refugees in the United States

2020 ◽  
Vol 6 (32) ◽  
pp. eabb0295
Author(s):  
Nadwa Mossaad ◽  
Jeremy Ferwerda ◽  
Duncan Lawrence ◽  
Jeremy Weinstein ◽  
Jens Hainmueller
Keyword(s):  
United States ◽  
Population Level ◽  
The United States ◽  
Retention Rates ◽  
State Governments ◽  
Individual Level ◽  
Welfare Benefits ◽  
Level Data ◽  
Immigrant And Refugee ◽  
National Networks

At a time of heightened anxiety surrounding immigration, state governments have increasingly sought to manage immigrant and refugee flows. Yet the factors that influence where immigrants choose to settle after arrival remain unclear. We bring evidence to this question by analyzing population-level data for refugees resettled within the United States. Unlike other immigrants, refugees are assigned to initial locations across the country but are free to relocate and select another residence after arrival. Drawing on individual-level administrative data for adult refugees resettled between 2000 and 2014 (N = 447,747), we examine the relative desirability of locations by examining how retention rates and patterns of secondary migration differ across states. We find no discernible evidence that refugees’ locational choices are strongly influenced by state partisanship or the generosity of welfare benefits. Instead, we find that refugees prioritize locations with employment opportunities and existing co-national networks.

scholarly journals Hurricane-induced demographic changes in a non-human primate population

2020 ◽  
Vol 7 (8) ◽  
pp. 200173
Author(s):  
Dana O. Morcillo ◽  
Ulrich K. Steiner ◽  
Kristine L. Grayson ◽  
Angelina V. Ruiz-Lambides ◽  
Raisa Hernández-Pacheco
Keyword(s):  
Population Level ◽  
Matrix Population Models ◽  
Individual Level ◽  
Animal Populations ◽  
Level Data ◽  
Climatic Event ◽  
Free Ranging ◽  
Human Primate ◽  
Population Fitness

Major disturbance events can have large impacts on the demography and dynamics of animal populations. Hurricanes are one example of an extreme climatic event, predicted to increase in frequency due to climate change, and thus expected to be a considerable threat to population viability. However, little is understood about the underlying demographic mechanisms shaping population response following these extreme disturbances. Here, we analyse 45 years of the most comprehensive free-ranging non-human primate demographic dataset to determine the effects of major hurricanes on the variability and maintenance of long-term population fitness. For this, we use individual-level data to build matrix population models and perform perturbation analyses. Despite reductions in population growth rate mediated through reduced fertility, our study reveals a demographic buffering during hurricane years. As long as survival does not decrease, our study shows that hurricanes do not result in detrimental effects at the population level, demonstrating the unbalanced contribution of survival and fertility to population fitness in long-lived animal populations.

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

2019 ◽  
Vol 116 (42) ◽  
pp. 20923-20929 ◽  
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.

scholarly journals The 1968 Influenza Pandemic and COVID-19 Outcomes

2021 ◽  
Author(s):  
Charles A Taylor ◽  
Christopher Boulos ◽  
Matthew J Memoli
Keyword(s):  
Influenza Pandemic ◽  
Population Level ◽  
Related Factors ◽  
Death Rates ◽  
Individual Level ◽  
Age Cohorts ◽  
Differential Outcomes ◽  
Level Data ◽  
The Us ◽  
Before And After

Past pandemic experience at an individual or population level may affect health outcomes in future pandemics. In this study, we focus on how the influenza pandemic of 1968 (H3N2), which killed up to 100,000 people in the US, may have produced differential COVID-19 (SARS-CoV-2) outcomes. Our analysis finds that areas with high influenza-related mortality in 1968 experienced 1-2% lower COVID-19 death rates. We employ an identification strategy that isolates variation in COVID-19 rates across age cohorts born before and after 1968. Locales in the US with high 1968 influenza mortality have lower COVID-19 death rates among older cohorts relative to younger ones. The relationship holds using county-level and patient-level data, as well as data from hospitals and nursing homes. Results do not appear to be driven by systemic or policy-related factors that would affect a population, but instead suggest a potential individual-level response to prior influenza pandemic exposure. The findings merit substantial further investigation into potential biological, immunological, or other mechanisms that can account for these differential outcomes.

scholarly journals Multimethod, multidataset analysis reveals paradoxical relationships between sociodemographic factors, Hispanic ethnicity and diabetes

2020 ◽  
Vol 8 (2) ◽  
pp. e001725
Author(s):  
Gabriel M Knight ◽  
Gabriela Spencer-Bonilla ◽  
David M Maahs ◽  
Manuel R Blum ◽  
Areli Valencia ◽  
...  
Keyword(s):  
Census Data ◽  
Characteristic Curve ◽  
Population Level ◽  
Sociodemographic Factors ◽  
Robert Wood Johnson Foundation ◽  
County Level ◽  
Ethnic Density ◽  
Hispanic Ethnicity ◽  
Individual Level ◽  
Level Data

IntroductionPopulation-level and individual-level analyses have strengths and limitations as do ‘blackbox’ machine learning (ML) and traditional, interpretable models. Diabetes mellitus (DM) is a leading cause of morbidity and mortality with complex sociodemographic dynamics that have not been analyzed in a way that leverages population-level and individual-level data as well as traditional epidemiological and ML models. We analyzed complementary individual-level and county-level datasets with both regression and ML methods to study the association between sociodemographic factors and DM.Research design and methodsCounty-level DM prevalence, demographics, and socioeconomic status (SES) factors were extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings and merged with US Census data. Analogous individual-level data were extracted from 2007 to 2016 National Health and Nutrition Examination Survey studies and corrected for oversampling with survey weights. We used multivariate linear (logistic) regression and ML regression (classification) models for county (individual) data. Regression and ML models were compared using measures of explained variation (area under the receiver operating characteristic curve (AUC) and R2).ResultsAmong the 3138 counties assessed, the mean DM prevalence was 11.4% (range: 3.0%–21.1%). Among the 12 824 individuals assessed, 1688 met DM criteria (13.2% unweighted; 10.2% weighted). Age, gender, race/ethnicity, income, and education were associated with DM at the county and individual levels. Higher county Hispanic ethnic density was negatively associated with county DM prevalence, while Hispanic ethnicity was positively associated with individual DM. ML outperformed regression in both datasets (mean R2 of 0.679 vs 0.610, respectively (p<0.001) for county-level data; mean AUC of 0.737 vs 0.727 (p<0.0427) for individual-level data).ConclusionsHispanic individuals are at higher risk of DM, while counties with larger Hispanic populations have lower DM prevalence. Analyses of population-level and individual-level data with multiple methods may afford more confidence in results and identify areas for further study.

scholarly journals Population frequencies of vkorc1 c1173t polymorphism, which determining the organism sensitivity to warfarin, in forest nenets and nganasans of northern siberia

2020 ◽  
pp. 35-42
Author(s):  
Р.П. Тийс ◽  
Л.П. Осипова ◽  
Е.Н. Воронина ◽  
М.Л. Филипенко
Keyword(s):  
Population Level ◽  
Indigenous Populations ◽  
Human Populations ◽  
Similar Distribution ◽  
Taimyr Peninsula ◽  
Key Factors ◽  
Single Nucleotide ◽  
Individual Level ◽  
Vkorc1 Gene ◽  
Similar Distribution Pattern

Полиморфизм C1173T гена VKORC1 является одним из ключевых факторов, определяющих как этнические, так и индивидуальные различия в чувствительности к антикоагулянту варфарину и его поддерживающей дозе у пациентов при лечении тромбозозависимых заболеваний. В связи с этим, на популяционном уровне проведено исследование полиморфизма VKORC1 C1173T среди коренных представителей лесных ненцев Ямало-Ненецкого автономного округа и нганасан полуострова Таймыр Красноярского края. Генотипирование однонуклеотидных замен в гене VKORC1 проводилось в режиме реального времени с использованием конкурирующих TaqMan-зондов. Выявлено, что вариант VKORC1 1173T встречается с высокой частотой в изученных популяциях: 67% у лесных ненцев и 94% у нганасан. Этот показатель существенно и статистически значимо выше, чем у европейцев, и имеет схожий характер распространения с таковым у азиатов Китая и Японии. Результаты нашего исследования расширяют знания о полиморфизме гена VKORC1 в человеческих популяциях, а также способствуют развитию персонализированной медицины по отношению к коренным жителям Сибири, так как генетический статус человека, имеющего вариант 1173T, может учитываться в целях достижения максимально безопасной и эффективной терапии варфарином при тромбозозависимых заболеваниях. Polymorphism C1173T of the VKORC1 gene is one of the key factors determining both ethnic and individual differences in the sensitivity to the anticoagulant warfarin and its maintenance dose in patients in the treatment of thrombosis-dependent diseases. In this regard, at the population level the VKORC1 C1173T polymorphism was studied in indigenous populations of the Forest Nenets (the Yamal-Nenets Autonomous Okrug) and Nganasans (the Taimyr Peninsula of the Krasnoyarsk region). Genotyping of C1173T single nucleotide substitution in the VKORC1 gene was carried out in real time using competing TaqMan probes. It was revealed that the variant VKORC1 1173T occurs with a high frequency in the studied populations: 67% in Forest Nenets and 94% in Nganasans. This indicator is significantly higher than that of Europeans, and has a similar distribution pattern with that of Asians. The results of our study expand knowledge about VKORC1 gene polymorphism in human populations, and also promote the development of personalized medicine in relation to indigenous people of Siberia, since the genetic status of a person with variant 1173T can be taken into account at an individual level in order to achieve the most safe and effective warfarin therapy of thrombosis-dependent diseases.

scholarly journals Key data for outbreak evaluation: building on the Ebola experience

2017 ◽  
Vol 372 (1721) ◽  
pp. 20160371 ◽  
Author(s):  
Anne Cori ◽  
Christl A. Donnelly ◽  
Ilaria Dorigatti ◽  
Neil M. Ferguson ◽  
Christophe Fraser ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Outbreaks ◽  
Population Level ◽  
West African ◽  
Public Health Response ◽  
The West ◽  
Individual Level ◽  
Infectious Disease Outbreaks ◽  
Exposure Data ◽  
Level Data

Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

scholarly journals Strategic Social Learning and the Population Dynamics of Human Behavior: The Game of Go

2014 ◽  
Author(s):  
Bret A Beheim ◽  
Calvin Thigpen ◽  
Richard McElreath
Keyword(s):  
Population Dynamics ◽  
Social Learning ◽  
Learning Strategies ◽  
Evolutionary Dynamics ◽  
Human Cognition ◽  
Human Populations ◽  
Cultural Dynamics ◽  
Individual Level ◽  
Level Data ◽  
Social Learning Processes

Human culture is widely believed to undergo evolution, via mechanisms rooted in the nature of human cognition. A number of theories predict the kinds of human learning strategies, as well as the population dynamics that result from their action. There is little work, however, that quantitatively examines the evidence for these strategies and resulting cultural evolution within human populations. One of the obstacles is the lack of individual-level data with which to link transmission events to larger cultural dynamics. Here, we address this problem with a rich quantitative database from the East Asian board game known as Go. We draw from a large archive of Go games spanning the last six decades of professional play, and find evidence that the evolutionary dynamics of particular cultural variants are driven by a mix of individual and social learning processes. Particular players vary dramatically in their sensitivity to population knowledge, which also varies by age and nationality. The dynamic patterns of opening Go moves are consistent with an ancient, ongoing arms race within the game itself.

Political Attitudes and Behaviour in a Non-Partisan Environment: Toronto 2014

2016 ◽  
Vol 49 (2) ◽  
pp. 311-333 ◽  
Author(s):  
R. Michael McGregor ◽  
Aaron A. Moore ◽  
Laura B. Stephenson
Keyword(s):  
Choice Model ◽  
Vote Choice ◽  
Valuable Insight ◽  
Individual Level ◽  
Voter Preferences ◽  
Multi Stage ◽  
Mayoral Election ◽  
Level Data ◽  
Municipal Level ◽  
Insight Into

AbstractVoting behaviour in municipal elections is understudied in Canada. Existing research is limited by the type of data (aggregate instead of individual-level) and the cases evaluated (partisan when most contests are non-partisan). The objective of this study is to contribute to this literature by using individual-level data about a non-partisan election. To do so, we use data from the Toronto Election Study, conducted during the 2014 election. Our research goals are to evaluate whether a standard approach to understanding vote choice (the multi-stage explanatory model) is applicable in a non-partisan, municipal-level contest, and to determine the correlates of vote choice in the 2014 Toronto mayoral election in particular. Our analysis reveals that, although it was a formally non-partisan contest, voters tended to view the mayoral candidates in both ideological and partisan terms. We also find that a standard vote choice model provides valuable insight into voter preferences at the municipal level.

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