Gradient analysis of remnant True and Upper Coastal Prairie grasslands of North America

1988 ◽  
Vol 66 (11) ◽  
pp. 2152-2161 ◽  
Author(s):  
David D. Diamond ◽  
Fred E. Smeins

Sixty-three upland True and Upper Coastal Prairie grasslands were sampled for vegetation composition and soil variables. The first axis from principal components analysis produced a south to north arrangement of stands along which temperature and precipitation decrease and soil organic matter increases (P < 0.0001). The second principal components analysis axis was related to a soils gradient, primarily within Texas communities, which had more varied soils than grasslands to the north. Species response curves against the first axis showed a continual replacement from north to south, with Schizachyrium scoparium and Paspalum plicatulum dominants in the south, Andropogon gerardii more important in central and northern communities, and Stipa spartea and Sporobolus heterolepis important in the north. The C3/C4 ratio of grasses increased rapidly northward from Nebraska. Species diversity and richness did not vary greatly and showed nonsignificant correlations with environmental variables across this latitudinal gradient. Stand relationships from cluster analysis corresponded with the results of principal components analysis, and based on these analyses, plus a review of the literature, seven community types were recognized. Five form a continuum, across which Andropogon gerardii increases northward and Schizachyrium scoparium increases southward, while two are limited to high-precipitation areas of north Texas.


1988 ◽  
Vol 66 (12) ◽  
pp. 2436-2444 ◽  
Author(s):  
Jerrold I. Davis

The contributions of genetic and environmental variation to multivariate patterns in morphology were investigated in a comparative analysis of two samples of plants representing the Puccinellia nuttalliana complex (Poaceae). The first sample is a series of individuals (genotypes) collected live, vegetatively divided, and grown under controlled environmental conditions. Phenotypic variation in this sample, in individual characters and in multivariate factors, can be apportioned between genetic (among genotype) and environmental (among treatment) causes. The second sample consists of field-collected individuals from throughout the North American range of the complex. Variation in this sample, as in most field-collected samples, cannot be assigned directly to its underlying causes. Multivariate patterns in the two samples were analyzed by identical principal-components analyses of 48 morphological characters. The strongest factor identified by the greenhouse principal-components analysis correlates with the strongest of the field principal-components analysis; they are similar in character makeup, both reflecting spikelet size and plant scabrousness. These factors have a genetic component and no environmental component and appear to differentiate Puccinellia distans from the rest of the complex. The second strongest factor of the greenhouse principal-components analysis correlates with the second of the field principal-components analysis. These axes reflect general vegetative stature; they have genetic and plastic components. The overall analysis indicates that multivariate patterns in phenotype can reflect both genetic and environmental effects, in varying proportions; patterns of genetic affinity therefore may be difficult to dissociate from those reflecting plasticity.



2005 ◽  
pp. 54-75 ◽  
Author(s):  
S. Baranov ◽  
T. Skufina

The article proposes methods for quantitative analysis of interregional differentiation structure and construction of regional ratings based on principal components analysis. Results of computations and analysis of interregional differentiation structure for all Russia, the North zone, and Russia without the North zone are provided. For computations data for 1998-2003 and their forecasting values for 2004-2005 were used. Ratings of socioeconomic development of Russian regions for 1998-2005 are also provided in the paper.



1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.



Sign in / Sign up

Export Citation Format

Share Document