Genecology and seed zones for tapertip onion in the US Great Basin

Botany ◽  
2013 ◽  
Vol 91 (10) ◽  
pp. 686-694 ◽  
Author(s):  
R.C. Johnson ◽  
Barbara C. Hellier ◽  
Ken W. Vance-Borland
Keyword(s):  
Great Basin ◽  
Plant Traits ◽  
Principal Component ◽  
Common Garden ◽  
The United States ◽  
Production Traits ◽  
Seed Transfer ◽  
Common Gardens ◽  
Seed Zones ◽  
Surrounding Areas

The choice of germplasm is critical for sustainable restoration, yet seed transfer guidelines are lacking for all but a few herbaceous species. Seed transfer zones based on genetic variability and climate were developed using tapertip onion (Allium acuminatum Hook.) collected in the Great Basin and surrounding areas in the United States. Bulbs from 53 locations were established at two common garden sites and morphological (such as leaf and scape dimensions), phenological (such as bolting date and flowering), and production traits (such as emergence and seeds per plant) were measured. Differences among source locations for plant traits within both common gardens were strong (P < 0.001), indicating genetic variation. Principal component 1 (PC 1) for phenological traits, with R2 = 0.59, and PC 1 for production traits, with R2 = 0.65, were consistently correlated with annual, maximum, minimum, and average temperature, annual precipitation, and frost-free days at source locations (P < 0.05). Regression of PC 1 phenology and PC 1 production scores with source location climates resulted in models with R2 values of 0.73 and 0.52, respectively. Using a geographic information system, maps of these models were overlaid to develop proposed seed zones to guide the choice of germplasm for conservation and restoration of tapertip onion across the collection region.

Mapping genetic variation and seed zones for Bromus carinatus in the Blue Mountains of eastern Oregon, USAIn this article, mention of companies or trade names does not constitute an endorsement of any product or procedure.

Botany ◽  
2010 ◽  
Vol 88 (8) ◽  
pp. 725-736 ◽  
Author(s):  
R. C. Johnson ◽  
Vicky J. Erickson ◽  
Nancy L. Mandel ◽  
J. Bradley St Clair ◽  
Kenneth W. Vance-Borland
Keyword(s):  
Environmental Variables ◽  
Regression Models ◽  
Plant Traits ◽  
Seed Source ◽  
Maximum Temperature ◽  
Blue Mountains ◽  
Seed Transfer ◽  
Bromus Carinatus ◽  
Seed Zones ◽  
Transfer Zones

Seed transfer zones ensure that germplasm selected for restoration is suitable and sustainable in diverse environments. In this study, seed zones were developed for mountain brome ( Bromus carinatus Hook. & Arn.) in the Blue Mountains of northeastern Oregon and adjoining Washington. Plants from 148 Blue Mountain seed source locations were evaluated in common-garden studies at two contrasting test sites. Data on phenology, morphology, and production were collected over two growing seasons. Plant traits varied significantly and were frequently correlated with annual precipitation and annual maximum temperature at seed source locations (P < 0.05). Plants from warmer locations generally had higher dry matter production, longer leaves, wider crowns, denser foliage, and greater plant height than those from cooler locations. Regression models of environmental variables with the first two principal components (PC 1 and PC 2) explained 46% and 40% of the total variation, respectively. Maps of PC 1 and PC 2 generally corresponded to elevation, temperature, and precipitation gradients. The regression models developed from PC 1 and PC 2 and environmental variables were used to map seed transfer zones. These maps will be useful in selecting mountain brome seed sources for habitat restoration in the Blue Mountains.

A model of genetic variation for Pinus ponderosa in the Inland Northwest (U.S.A.): applications in gene resource management

1991 ◽  
Vol 21 (10) ◽  
pp. 1491-1500 ◽  
Author(s):  
G. E. Rehfeldt
Keyword(s):  
Genetic Variation ◽  
Pinus Ponderosa ◽  
Regression Models ◽  
Common Garden ◽  
Shoot Elongation ◽  
The United States ◽  
Independent Data ◽  
Gene Conservation ◽  
Seed Transfer ◽  
Inland Northwest

Models were developed to describe genetic variation among 201 seedling populations ofPinusponderosa var. ponderosa in the Inland Northwest of the United States. Common-garden studies provided three variables that reflected growth and development in field environments and three principal components of six variables that reflected patterns of shoot elongation. Regression models were developed for describing genetic variation across the landscape. Using functions of latitude, longitude, and elevation as descriptors, these models produced values of R2 that were as large as 0.66, while averaging 0.39. The models described genetic variation as occurring along relatively steep elevational clines and gentle geographic (i.e., latitudinal and longitudinal) clines. An exercise at validating the models with independent data supported their veracity. Predictions made by the models are applied to limiting seed transfer, designing breeding zones, planning gene conservation programs, interpreting phenotypic variation, and predicting the effects of environmental change on the adaptedness of populations.

scholarly journals Detecting Adaptive Differentiation in Structured Populations with Genomic Data and Common Gardens

Genetics ◽  
2019 ◽  
Vol 211 (3) ◽  
pp. 989-1004 ◽  
Author(s):  
Emily B. Josephs ◽  
Jeremy J. Berg ◽  
Jeffrey Ross-Ibarra ◽  
Graham Coop
Keyword(s):  
Quantitative Traits ◽  
Genomic Data ◽  
Common Garden ◽  
The United States ◽  
Structured Populations ◽  
Human Populations ◽  
United States Department ◽  
Department Of Agriculture ◽  
Common Gardens ◽  
Polygenic Adaptation

Adaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci—a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the relatedness matrix to detect excess divergence consistent with polygenic adaptation, and using a conditional test to control for confounding effects due to population structure. We apply these methods to inbred maize lines from the United States Department of Agriculture germplasm pool and maize landraces from Europe. Ultimately, these methods can be applied to additional domesticated and wild species to give us a broader picture of the specific traits that contribute to adaptation and the overall importance of polygenic adaptation in shaping quantitative trait variation.

Landscape patterns of phenotypic variation and population structuring in a selfing grass, Elymus glaucus (blue wildrye)

2004 ◽  
Vol 82 (12) ◽  
pp. 1776-1789 ◽  
Author(s):  
Vicky J Erickson ◽  
Nancy L Mandel ◽  
Frank C Sorensen
Keyword(s):  
Genetic Variation ◽  
Principal Component ◽  
Common Garden ◽  
Primary Objective ◽  
Landscape Patterns ◽  
Clinal Variation ◽  
Phenotypic Variance ◽  
Seed Transfer ◽  
Wide Range ◽  
Elymus Glaucus

Source-related phenotypic variance was investigated in a common garden study of populations of Elymus glaucus Buckley (blue wildrye) from the Blue Mountain Ecological Province of northeastern Oregon and adjoining Washington. The primary objective of this study was to assess geographic patterns of potentially adaptive differentiation in this self-fertile allotetraploid grass, and use this information to develop a framework for guiding seed movement and preserving adaptive patterns of genetic variation in ongoing restoration work. Progeny of 188 families were grown for 3 years under two moisture treatments and measured for a wide range of traits involving growth, morphology, fecundity, and phenology. Variation among seed sources was analyzed in relation to physiographic and climatic trends, and to various spatial stratifications such as ecoregions, watersheds, edaphic classifications, etc. Principal component (PC) analysis extracted four primary PCs that together accounted for 67% of the variance in measured traits. Regression and cluster analyses revealed predominantly ecotypic or stepped-clinal distribution of genetic variation. Three distinct geographic groups of locations accounted for over 84% of the variation in PC-1 and PC-2 scores; group differences were best described by longitude and ecoregion. Clinal variation in PC-3 and PC-4 scores was present in the largest geographic group. Four geographic subdivisions were proposed for delimiting E. glaucus seed transfer in the Blue Mountains.Key words: Elymus glaucus, morphological variation, local adaptation, seed transfer, seed zones, polyploid.

Statistical Analsysis to Evaluate Heavy Metal Pollution in the Air Obatained by Moss Technique in Hanoi and its Surrounding Region

2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Statistical Analysis ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Five Factors ◽  
Heavy Metal Elements ◽  
Surrounding Areas ◽  
Potential Pollution

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.

scholarly journals Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States

2021 ◽  
Vol 18 (9) ◽  
pp. 4560
Author(s):  
Mostafa Abbas ◽  
Thomas B. Morland ◽  
Eric S. Hall ◽  
Yasser EL-Manzalawy
Keyword(s):  
Functional Data ◽  
Time Series Data ◽  
Principal Component ◽  
State Level ◽  
The United States ◽  
Functional Principal Component Analysis ◽  
Series Data ◽  
Dynamic Correlation ◽  
The Us ◽  
Google Search

We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19-related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.

scholarly journals Dietary patterns related to total mortality and cancer mortality in the United States

2021 ◽  
Author(s):  
Marcela R. Entwistle ◽  
Donald Schweizer ◽  
Ricardo Cisneros
Keyword(s):  
United States ◽  
Dietary Patterns ◽  
Cancer Mortality ◽  
Cox Regression ◽  
Total Mortality ◽  
Principal Component ◽  
The United States ◽  
Red Meat ◽  
Increased Risk ◽  
All Cause Mortality

Abstract Purpose This study investigated the association between dietary patterns, total mortality, and cancer mortality in the United States. Methods We identified the four major dietary patterns at baseline from 13,466 participants of the NHANES III cohort using principal component analysis (PCA). Dietary patterns were categorized into ‘prudent’ (fruits and vegetables), ‘western’ (red meat, sweets, pastries, oils), ‘traditional’ (red meat, legumes, potatoes, bread), and ‘fish and alcohol’. We estimated hazard ratios for total mortality, and cancer mortality using Cox regression models. Results A total of 4,963 deaths were documented after a mean follow-up of 19.59 years. Higher adherence to the ‘prudent’ pattern was associated with the lowest risk of total mortality (5th vs. 1st quintile HR 0.90, 95% CI 0.82–0.98), with evidence that all-cause mortality decreased as consumption of the pattern increased. No evidence was found that the ‘prudent’ pattern reduced cancer mortality. The ‘western’ and the ‘traditional’ patterns were associated with up to 22% and 16% increased risk for total mortality (5th vs. 1st quintile HR 1.22, 95% CI 1.11–1.34; and 5th vs. 1st quintile HR 1.16, 95% CI 1.06–1.27, respectively), and up to 33% and 15% increased risk for cancer mortality (5th vs. 1st quintile HR 1.33, 95% CI 1.10–1.62; and 5th vs. 1st quintile HR 1.15, 95% CI 1.06–1.24, respectively). The associations between adherence to the ‘fish and alcohol’ pattern and total mortality, and cancer mortality were not statistically significant. Conclusion Higher adherence to the ‘prudent’ diet decreased the risk of all-cause mortality but did not affect cancer mortality. Greater adherence to the ‘western’ and ‘traditional’ diet increased the risk of total mortality and mortality due to cancer.

Assessing Potential Seed Transfer Zones for Five Forb Species from the Great Basin Floristic Region, USA

2015 ◽  
Vol 35 (1) ◽  
pp. 174-188 ◽  
Author(s):  
Andrea T. Kramer ◽  
Daniel J. Larkin ◽  
Jeremie B. Fant
Keyword(s):  
Great Basin ◽  
Seed Transfer ◽  
Transfer Zones
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