Date of Completion


Document Type

Honors College Thesis


Plant Biology

Thesis Type

College of Arts and Science Honors, Honors College

First Advisor

Stephen Keller


local adaptation, parallel evolution, Populus balsamifera


Local adaptation to climate provides strong evidence for the operation of natural selection. When climate gradients are shared, there is a potential for parallelism of local adaptation. By studying this potential parallelism, we gain insight into the balance between natural selection and gene flow operating within a given system. Here, I explore the idea of potential parallel evolution of local adaptation between a broad spatial scale and a fine spatial scale within Populus balsamifera. To do this, we grew trees from both spatial scales in a common garden and measured selected bud phenology traits (growing season length, bud set, bud flush, and leaf flush). These traits were first analyzed with linear mixed models to determine if there were significant clinal relationships between traits and source climate. Then the models of broad spatial scale individuals were used to predict trait values for the fine spatial scale individuals to determine if broad-scale relationships can accurately predict those of the fine scale. The results showed significant clinal relationships for the broad scale, but not for the fine scale. These broad-scale relationships successfully estimated the trait values of the fine scale but often left considerable variation unexplained. These results suggest that at the broad scale, there is a clinal relationship between phenology and source climate. The fine-scale individuals fall within this trend; however, they show no relationship of their own. Thus, selection is able to overcome the homogenizing effects of gene flow at broad spatial scales, but at fine spatial scales, the strength of gene flow cannot be overcome by selection. This study provides new insight into the evolutionary drivers operating at these spatial scales within P. balsamifera.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.