Interpretation of sugar maple (Acersaccharum) ring chronologies from central and southern Ontario using a mixed linear model

1994 ◽  
Vol 24 (10) ◽  
pp. 2139-2139 ◽  
Author(s):  
D.A.J. Ryan ◽  
O.B. Allen ◽  
D.L. McLaughlin ◽  
A.M. Gordon
Keyword(s):  
Linear Model ◽  
Sugar Maple ◽  
Mixed Linear Model ◽  
Southern Ontario

not available

Interpretation of sugar maple (Acersaccharum) ring chronologies from central and southern Ontario using a mixed linear model

1994 ◽  
Vol 24 (3) ◽  
pp. 568-575 ◽  
Author(s):  
D.A.J. Ryan ◽  
O.B. Allen ◽  
D.L. McLaughlin ◽  
A.M. Gordon
Keyword(s):  
Air Pollution ◽  
Linear Model ◽  
Fixed Effects ◽  
Sugar Maple ◽  
Mixed Linear Model ◽  
Tree Age ◽  
Categorical Variables ◽  
Natural Logarithm ◽  
The Impact ◽  
Precipitation And Temperature

This study presents a new method for assessing the impact of environmental factors on the radial growth rate of trees. The natural logarithm of the specific volume increments (SVI) were fitted to a mixed linear model, which included fixed effects for tree age when the increment occurs, year, precipitation, and temperature both in the year of growth and in the preceding year, and the geographical locale. The model also incorporates stand and tree as random effects. By fitting trees of different ages, the model is able to separate year effects from age effects. Age and year were treated as categorical variables and hence no specific form of growth curve is assumed. The model was fitted to log SVI from 84 mature sugar maple (Acersaccharum Marsh.) trees from 42 uneven-aged stands in six regions of southern and central Ontario representing a known gradient of air pollution. After adjusting for age, precipitation, and temperature effects, the log SVI increased during the first half and declined during the second half of the 20th century in five of the six regions. This suggests that factors other than those included in the model have affected growth. Air pollution remains a likely causal agent in this observed decline.

Mapping QTLs with epistatic effects and QTL×environment interactions by mixed linear model approaches

1999 ◽  
Vol 99 (7-8) ◽  
pp. 1255-1264 ◽  
Author(s):  
D. L. Wang ◽  
J. Zhu ◽  
Z. K. L. Li ◽  
A. H. Paterson
Keyword(s):  
Linear Model ◽  
Mixed Linear Model ◽  
Epistatic Effects

Detecting dominance QTL in poultry pedigrees using variance component methodology

2007 ◽  
Vol 2007 ◽  
pp. 2-2
Author(s):  
S. J. Rowe ◽  
R. Pong-Wong ◽  
C.S. Haley ◽  
S.A. Knott ◽  
D.J. de Koning
Keyword(s):  
Linear Model ◽  
Variance Component ◽  
Mixed Linear Model ◽  
Variance Component Analysis ◽  
Order Effects ◽  
Empirical Power ◽  
Commercial Broiler ◽  
Underlying Mechanisms ◽  
Higher Order Effects ◽  
Qtl Effects

Methods that detect QTL within commercial populations circumvent the need for expensive experimental populations and facilitate direct application of results through marker assisted selection. Variance component analysis (VCA) uses phenotypic, pedigree and marker information within a mixed linear model to simultaneously detect QTL and estimate breeding values. The inclusion of non-additive effects has potential for greater accuracy of selection and understanding of underlying mechanisms. The linear model can be extended to include higher order effects such as dominance, however, there is little information on empirical power. Here VCA was applied to real and simulated commercial broiler data to detect additive and dominant QTL effects.

scholarly journals Mixed linear model approach adapted for genome-wide association studies

2010 ◽  
Vol 42 (4) ◽  
pp. 355-360 ◽  
Author(s):  
Zhiwu Zhang ◽  
Elhan Ersoz ◽  
Chao-Qiang Lai ◽  
Rory J Todhunter ◽  
Hemant K Tiwari ◽  
...  
Keyword(s):  
Linear Model ◽  
Association Studies ◽  
Mixed Linear Model ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Model Approach
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