Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)

Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines for the relevant component traits are frequently observed for species that have a north-south distribution, but these relationships do...

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Main Author: Oubida, Regis Wendpouire
Other Authors: Forest Resources and Environmental Conservation
Format: Others
Published: Virginia Tech 2015
Subjects:
Online Access:http://hdl.handle.net/10919/56619
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-566192020-09-29T05:48:33Z Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa) Oubida, Regis Wendpouire Forest Resources and Environmental Conservation Holliday, Jason A. Nilsen, Erik T. Seiler, John R. Brunner, Amy M. Populus trichocarpa common garden adaptive traits trait variation pattern population differentiation Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines for the relevant component traits are frequently observed for species that have a north-south distribution, but these relationships do not account for climatic variation within a given latitudinal band, which may be reflected in adaptive traits. We used black cottonwood (Populus trichocarpa) as a model to characterize the interplay between geography, climate, and adaptation to abiotic factors. Twelve traits (height, diameter, volume index, crown diameter, number of branches, number of sylleptic branches, relative number of branches, Relative canopy depth, Bud set, Bud flush, cold index of injury, carbon isotope ratio) were measured in a range-wide sample of 124 P. trichocarpa genotypes grown in a common garden. Heritability's were moderate to high (0.24 to 0.55) and significant population differentiation (QST > 0.3) suggested adaptive divergence. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, aridity (Eref) explained the most variation, with subsequent splits grouping individuals according to mean temperature of the warmest month, frost-free period (FFP), and mean annual precipitation (MAP). This grouping matches relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref) had the lowest growth performance, and the highest cold hardiness. The groups spanning the south of British Columbia (low Eref and intermediate temperatures) displayed an average growth and cold hardiness. The group from the coast of California and Oregon (high Eref and FFP) had the best growth performance and the lowest cold hardiness. The southernmost and high-elevated group (with High Eref and low FFP) performed poorly, had a low cold hardiness and a significantly lower WUE. Master of Science 2015-09-21T12:31:32Z 2015-09-21T12:31:32Z 2014-03-04 Thesis vt_gsexam:2307 http://hdl.handle.net/10919/56619 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic Populus trichocarpa
common garden
adaptive traits
trait variation pattern
population differentiation
spellingShingle Populus trichocarpa
common garden
adaptive traits
trait variation pattern
population differentiation
Oubida, Regis Wendpouire
Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
description Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines for the relevant component traits are frequently observed for species that have a north-south distribution, but these relationships do not account for climatic variation within a given latitudinal band, which may be reflected in adaptive traits. We used black cottonwood (Populus trichocarpa) as a model to characterize the interplay between geography, climate, and adaptation to abiotic factors. Twelve traits (height, diameter, volume index, crown diameter, number of branches, number of sylleptic branches, relative number of branches, Relative canopy depth, Bud set, Bud flush, cold index of injury, carbon isotope ratio) were measured in a range-wide sample of 124 P. trichocarpa genotypes grown in a common garden. Heritability's were moderate to high (0.24 to 0.55) and significant population differentiation (QST > 0.3) suggested adaptive divergence. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, aridity (Eref) explained the most variation, with subsequent splits grouping individuals according to mean temperature of the warmest month, frost-free period (FFP), and mean annual precipitation (MAP). This grouping matches relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref) had the lowest growth performance, and the highest cold hardiness. The groups spanning the south of British Columbia (low Eref and intermediate temperatures) displayed an average growth and cold hardiness. The group from the coast of California and Oregon (high Eref and FFP) had the best growth performance and the lowest cold hardiness. The southernmost and high-elevated group (with High Eref and low FFP) performed poorly, had a low cold hardiness and a significantly lower WUE. === Master of Science
author2 Forest Resources and Environmental Conservation
author_facet Forest Resources and Environmental Conservation
Oubida, Regis Wendpouire
author Oubida, Regis Wendpouire
author_sort Oubida, Regis Wendpouire
title Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
title_short Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
title_full Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
title_fullStr Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
title_full_unstemmed Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa)
title_sort partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (populus trichocarpa)
publisher Virginia Tech
publishDate 2015
url http://hdl.handle.net/10919/56619
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