scholarly journals Parallel genomic evolution of parasite tolerance in wild honey bee populations

2018 ◽  
Author(s):  
Katarzyna Bozek ◽  
Juliana Rangel ◽  
Jatin Arora ◽  
Mandy Tin ◽  
Emily Crotteau ◽  
...  
Keyword(s):  
Honey Bee ◽  
The United States ◽  
Natural Environments ◽  
Data Sets ◽  
Strongly Correlated ◽  
Isolated Populations ◽  
Genetic Changes ◽  
Evolutionary Response ◽  
Evolutionary Trajectories ◽  
Metabolic Protein

Sudden biotic pressures, such as those from novel diseases and pathogens, require populations to respond rapidly or face potential extinction. How this response process takes place remains poorly understood, particularly in natural environments. In this study we take advantage of unique decade-long data sets of two wild honey bee (Apis mellifera) populations in the United States to reconstruct the evolution of tolerance to a novel parasite, the ectoparasitic mite Varroa destructor. Upon the arrival of Varroa, the two geographically isolated populations simultaneously suffered massive Varroa-induced mortality, but stabilized within two years. Here we sequenced and phased genomes of 465 bees sampled from both populations annually over the decade that spanned Varroa's arrival. Remarkably, we found that genetic changes were strongly correlated between the populations, suggesting parallel selective responses to Varroa parasitization. The arrival of Varroa was also correlated with an influx of genes of African origin into both populations, though surprisingly it did not substantially contribute to the overall similarity of the evolutionary response between them. Genes involved in metabolic, protein processing and developmental pathways were under particularly strong selection. It is possible that interactions among highly connected gene groups in these pathways may help channelize selective responses to novel parasites, causing completely unrelated populations to exhibit parallel evolutionary trajectories when faced with the same biotic pressure. Our analyses illustrate that ecologically relevant traits emerge from highly polygenic selection involving thousands of genes contributing to complex patterns of evolutionary change.

scholarly journals Integrating Sociological Perspectives into Obesogenic Research: Associations between Air Pollution Exposure and Obesity Prevalence across U.S. Metropolitan Statistical Areas

2018 ◽  
Vol 4 ◽  
pp. 237802311880704
Author(s):  
Jessica L. Eckhardt
Keyword(s):  
Air Pollution ◽  
The United States ◽  
Behavioral Risk ◽  
Natural Environments ◽  
Data Sets ◽  
Specific Class ◽  
Obesity Prevalence ◽  
Obesity Risk ◽  
Factor Screening ◽  
Pollution Exposure

Obesogenic theories suggests that obesity risk can be influenced by exposure to toxic chemicals present in built and natural environments. Although physical scientists have been on the forefront of obesogenic research, social science perspectives have been absent in understanding the relationship between environmental pollution and obesity risk. To address such gaps, the author uses a sociological perspective to explore the way in which exposure to a specific class of obesogens, endocrine disruptors, influences adult obesity prevalence. Using air pollution emissions data from the National Air Toxics Assessment and health data from the Behavioral Risk Factor Screening Survey, the author assesses the association between emission exposure and obesity risk across metropolitan areas in the United States. Although the nonsignificant findings do not support obesogenic hypotheses, this research demonstrates the need for obesogenic investigation using large, nationally represented data sets that can be stratified to identify inequalities in pollution exposure and associated obesity risk.

scholarly journals Insights from Fisher’s geometric model on the likelihood of speciation under different histories of environmental change

2019 ◽  
Author(s):  
Ryo Yamaguchi ◽  
Sarah P. Otto
Keyword(s):  
Environmental Change ◽  
Geometric Model ◽  
Ecological Speciation ◽  
Hybrid Speciation ◽  
Multiple Traits ◽  
Isolated Populations ◽  
Genetic Changes ◽  
Divergent Natural Selection ◽  
Species Formation ◽  
Evolutionary Trajectories

AbstractThe formation of new species via the accumulation of incompatible genetic changes is thought to result either from ecologically-based divergent natural selection or the order by which mutations happen to arise, leading to different evolutionary trajectories even under similar selection pressures. There is growing evidence in support of both ecological speciation and mutation-order speciation, but how different environmental scenarios affect the rate of species formation remains underexplored. We use a simple model of optimizing selection on multiple traits (“Fisher’s geometric model”) to determine the conditions that generate genetic incompatibilities in a changing environment. We find that incompatibilities are likely to accumulate in isolated populations adapting to different environments, consistent with ecological speciation. Incompatibilities also arise when isolated populations face a similar novel environment; these cases of mutation-order speciation are particularly likely when the environment changes rapidly and favors the accumulation of large-effect mutations. In addition, we find that homoploid hybrid speciation is likely to occur either when new environments arise in between the parental environments or when parental populations have accumulated large-effect mutations following a period of rapid adaptation. Our results indicate that periods of rapid environmental change are particularly conducive to speciation, especially mutation-order or hybrid speciation.

Asian Americans and Pacific Islanders: Employment Issues in the United States

2011 ◽  
Vol 9 (1-2) ◽  
pp. 58-69
Author(s):  
Marlene Kim
Keyword(s):  
United States ◽  
Asian Americans ◽  
The United States ◽  
Current Data ◽  
Pacific Islanders ◽  
Native Hawaiians ◽  
Data Sets ◽  
High Poverty ◽  
Unemployment Rates

Asian Americans and Pacific Islanders (AAPIs) in the United States face problems of discrimination, the glass ceiling, and very high long-term unemployment rates. As a diverse population, although some Asian Americans are more successful than average, others, like those from Southeast Asia and Native Hawaiians and Pacific Islanders (NHPIs), work in low-paying jobs and suffer from high poverty rates, high unemployment rates, and low earnings. Collecting more detailed and additional data from employers, oversampling AAPIs in current data sets, making administrative data available to researchers, providing more resources for research on AAPIs, and enforcing nondiscrimination laws and affirmative action mandates would assist this population.

Are Non-Target Honey Bees (Hymenoptera: Apidae) Exposed to Dinotefuran From Spotted Lanternfly (Hemiptera: Fulgoridae) Trap Trees?

2019 ◽  
Vol 112 (6) ◽  
pp. 2993-2996 ◽  
Author(s):  
Robyn Underwood ◽  
Brian Breeman ◽  
Joseph Benton ◽  
Jason Bielski ◽  
Julie Palkendo ◽  
...  
Keyword(s):  
Honey Bee ◽  
Honey Bees ◽  
High Performance ◽  
Host Plants ◽  
The United States ◽  
Quechers Method ◽  
Significant Damage ◽  
Lycorma Delicatula ◽  
Bee Colonies ◽  
Worker Bee

Abstract The spotted lanternfly, Lycorma delicatula, is an introduced plant hopper that causes significant damage to host plants in the United States. Because of its affinity for tree of heaven, Ailanthus altissima, control efforts have focused on the use of the systemic insecticide, dinotefuran, in designated trap trees. There is concern about exposure to this pesticide by non-target species, especially honey bees, Apis mellifera, via lanternfly honeydew. Therefore, honey bee colonies were established in areas of high densities of trap trees and samples of honey, bees, and beeswax were collected in May, July, and October of 2017 for analysis. Samples were extracted by the QuEChERS method and analyzed using high-performance liquid chromatography with tandem mass spectrometry to determine the presence and quantity of dinotefuran. Additionally, honeydew from lanternflies was analyzed for dinotefuran and informal observations of trap tree visitors were made. None of the worker bee, wax, or honey samples indicated detectable levels of dinotefuran; however, honeydew samples collected did contain dinotefuran above the detection limit with amounts ranging from 3 to 100 ng per sample. The lack of dinotefuran in honey bee products matches the general absence of honey bees at trap trees in informal observations.

Origins and Destinations – Social Security Claimant Dynamics

1998 ◽  
Vol 27 (3) ◽  
pp. 351-369 ◽  
Author(s):  
MICHAEL NOBLE ◽  
SIN YI CHEUNG ◽  
GEORGE SMITH
Keyword(s):  
The United States ◽  
Data Sets ◽  
Income Support ◽  
Data Set ◽  
Family Structures ◽  
Highly Educated ◽  
Lone Parents ◽  
Lone Mothers ◽  
Time Period ◽  
Short Time

This article briefly reviews American and British literature on welfare dynamics and examines the concepts of welfare dependency and ‘dependency culture’ with particular reference to lone parents. Using UK benefit data sets, the welfare dynamics of lone mothers are examined to explore the extent to which they inform the debates. Evidence from Housing Benefits data show that even over a relatively short time period, there is significant turnover in the benefits-dependent lone parent population with movement in and out of income support as well as movement into other family structures. Younger lone parents and owner-occupiers tend to leave the data set while older lone parents and council tenants are most likely to stay. Some owner-occupier lone parents may be relatively well off and on income support for a relatively short time between separation and a financial settlement being reached. They may also represent a more highly educated and highly skilled group with easier access to the labour market than renters. Any policy moves paralleling those in the United States to time limit benefit will disproportionately affect older lone parents.

scholarly journals Measuring the Effectiveness of Adaptive Random Forest for Handling Concept Drift in Big Data Streams

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 859
Author(s):  
Abdulaziz O. AlQabbany ◽  
Aqil M. Azmi
Keyword(s):  
Big Data ◽  
Random Forest ◽  
Real Time ◽  
Data Streams ◽  
Learning Algorithm ◽  
Concept Drift ◽  
The United States ◽  
Careful Consideration ◽  
Data Sets ◽  
Stream Data

We are living in the age of big data, a majority of which is stream data. The real-time processing of this data requires careful consideration from different perspectives. Concept drift is a change in the data’s underlying distribution, a significant issue, especially when learning from data streams. It requires learners to be adaptive to dynamic changes. Random forest is an ensemble approach that is widely used in classical non-streaming settings of machine learning applications. At the same time, the Adaptive Random Forest (ARF) is a stream learning algorithm that showed promising results in terms of its accuracy and ability to deal with various types of drift. The incoming instances’ continuity allows for their binomial distribution to be approximated to a Poisson(1) distribution. In this study, we propose a mechanism to increase such streaming algorithms’ efficiency by focusing on resampling. Our measure, resampling effectiveness (ρ), fuses the two most essential aspects in online learning; accuracy and execution time. We use six different synthetic data sets, each having a different type of drift, to empirically select the parameter λ of the Poisson distribution that yields the best value for ρ. By comparing the standard ARF with its tuned variations, we show that ARF performance can be enhanced by tackling this important aspect. Finally, we present three case studies from different contexts to test our proposed enhancement method and demonstrate its effectiveness in processing large data sets: (a) Amazon customer reviews (written in English), (b) hotel reviews (in Arabic), and (c) real-time aspect-based sentiment analysis of COVID-19-related tweets in the United States during April 2020. Results indicate that our proposed method of enhancement exhibited considerable improvement in most of the situations.

The Physiology of Body Weight Regulation: Relevance to the Etiology of Obesity in Children

PEDIATRICS ◽  
1998 ◽  
Vol 101 (Supplement_2) ◽  
pp. 525-539 ◽  
Author(s):  
Michael Rosenbaum ◽  
Rudolph L. Leibel
Keyword(s):  
United States ◽  
Body Weight ◽  
Environmental Factors ◽  
Regulatory System ◽  
The United States ◽  
Genetic Changes ◽  
Adult Body ◽  
Genes Encoding ◽  
Prevalence Of Obesity ◽  
Obesity In Children

The prevalence of obesity in children and adults in the United States has increased by more than 30% over the past decade. Recent studies of the physiology and molecular genetics of obesity in humans have provided evidence that body weight (fat) is regulated. Some of the genes encoding the molecular components of this regulatory system have been isolated from rodents. The increasing prevalence of obesity in the United States apparently represents the interaction of these genes with an environment that encourages a sedentary lifestyle and consumption of calories. The rapid increase in the prevalence of obesity emphasizes the role of environmental factors, because genetic changes could not occur at this rate. Thus, understanding of the relevant genes and how their effects are mediated by environment and development should lead to more effective prophylaxis and therapy of obesity. Although no clear environmental factors have been identified as causative of obesity, the rapid increases in the prevalence of obesity and the seeming voluntary immutability of adult body fatness can be taken as tacit evidence that the pediatric environment can be altered in a way that affects adult body weight.

Dynamic Measurement Modeling: Using Nonlinear Growth Models to Estimate Student Learning Capacity

2017 ◽  
Vol 46 (6) ◽  
pp. 284-292 ◽  
Author(s):  
Denis G. Dumas ◽  
Daniel M. McNeish
Keyword(s):  
Multiple Testing ◽  
Large Scale ◽  
Growth Models ◽  
Dynamic Assessment ◽  
The United States ◽  
Dynamic Measurement ◽  
Data Sets ◽  
Data Systems ◽  
Longitudinal Assessment ◽  
Assessment Practice

Single-timepoint educational measurement practices are capable of assessing student ability at the time of testing but are not designed to be informative of student capacity for developing in any particular academic domain, despite commonly being used in such a manner. For this reason, such measurement practice systematically underestimates the potential of students from nondominant socioeconomic or ethnic groups, who may not have had adequate opportunity to develop various academic skills but can nonetheless do so in the future. One long-standing approach to the partial rectification of this issue is dynamic assessment (DA), a technique that features multiple testing occasions integrated with learning opportunities. However, DA is extremely resource intensive to incorporate into educational assessment practice and cannot be applied to extant large-scale data sets. In this article, the authors describe a recently developed statistical technique, dynamic measurement modeling (DMM), which is capable of estimating quantities associated with DA—including student capacity for learning a particular skill—from existing large-scale longitudinal assessment data, allowing the core concepts of DA to be scaled up for use with secondary data sets such as those collected by Statewide Longitudinal Data Systems in the United States. The authors show that by considering several assessments over time, student capacity can be reliably estimated, and these capacity estimates are much less affected by student race/ethnicity, gender, and socioeconomic status than are single-timepoint assessment scores, thereby improving the consequential validity of measurement.

Incorporating Additional Tree and Environmental Variables in a Lodgepole Pine Stem Profile Model

1993 ◽  
Vol 8 (3) ◽  
pp. 86-90
Author(s):  
John C. Byrne
Keyword(s):  
Environmental Variables ◽  
Pinus Contorta ◽  
Lodgepole Pine ◽  
Linear Equations ◽  
The United States ◽  
National Forest ◽  
Data Sets ◽  
Tree Form ◽  
Northern Rocky Mountains ◽  
Profile Model

Abstract A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were obtained by fitting this model to individual national forest data sets. Other tree and environmental variables tested but found of little use in improving stem profile estimates were crown ratio, habitat series, elevation, slope percent, and aspect. West. J. Appl. For. 8(3):86-90.

scholarly journals The 2010 Structural-Demographic Forecast for the 2010–2020 Decade: A Retrospective Assessment

2020 ◽  
Author(s):  
Peter Turchin ◽  
Andrey Korotayev
Keyword(s):  
Western Europe ◽  
Time Series Data ◽  
Political Instability ◽  
The United States ◽  
Stress Index ◽  
Series Data ◽  
Strongly Correlated ◽  
Retrospective Assessment ◽  
The United Kingdom ◽  
The Usa

This article revisits the prediction, made in 2010, that the 2010–2020 decade would likely be a period of growing instability in the United States and Western Europe (Turchin 2010). This prediction was based on a computational model that quantified in the USA such structural-demographic forces for instability as popular immiseration, intraelite competition, and state weakness prior to 2010. Using these trends as inputs, the model calculated and projected forward in time the Political Stress Index, which in the past was strongly correlated with socio-political instability. Ortmans et al. (2017) conducted a similar structural-demographic study for the United Kingdom and obtained similar results. Here we use the Cross-National Time-Series Data Archive for the US, UK, and Western European countries to assess these structural-demographic predictions. We find that such measures of socio-political instability as anti-government demonstrations and riots increased dramatically during the 2010–2020 decade in all of these countries.

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