Mortality in many tree species is accelerating due to climate change, though with intraspecific variation in responses across landscapes. In order to accurately forecast and mitigate this increase in mortality, we must gain a mechanistic understanding of which trees are most at risk on the landscape, and why. Several recent lines of research have suggested that within-species variation in an organism’s response to hotter, drier conditions may be linked to its cytotype, or number of chromosome copies, a.k.a. ‘ploidy level’. The direction (i.e., whether higher ploidy levels are selected for or against in hot/dry environments) and consistency of this impact, however, is still debated. One possible mechanism may be that larger genome size, stemming from a higher cytotype, leads to a larger minimum cell size, which may then increase the minimum diameter of xylem conduits, leading to a higher probability of each conduit containing a large intermembrane pit and thus increased probability of embolism under drought conditions.
In this project, we will test how cytotype and the abiotic environment interact to influence hydraulic architecture in the stems of quaking aspen (Populus tremuloides) using dendroecological and quantitative wood anatomy techniques. We have already collected and mounted a set of tree cores (n=101) from an area spanning ~400 km2 in southwestern Colorado. We are currently working to crossdate the samples (assign a year to each annual growth ring). After crossdating the cores, the next step will be to analyze the stem xylem anatomical structure in each annual ring. Finally, we will model xylem anatomical traits as a function of cytotype and environmental variables. As within-species variation in cytotype is common in many plant species, understanding the relationship between cytotype and a plant’s hydraulic architecture is key to understanding how trees across landscapes might respond to more widespread, prolonged, and extreme droughts.
We will mentor up to two undergraduate students to specifically work on:
Preparing microsections of cores for anatomical analyses;
Imaging prepared samples and measuring anatomical traits using image processing software (ImageJ/GIMP);
Managing/organizing large datasets;
Conducting statistical analysis in R.
Students will develop skills in microscopy, imaging processing, and computational data analysis. This will also be an excellent opportunity for students to improve their independent thinking skills and to learn how to work in a collaborative environment. Additionally, students will be encouraged to participate in weekly lab meeting activities organized by the Macrosystem Ecology Lab, e.g. research presentations, paper discussions, orientation sessions, lab socials.
The student will primarily be mentored by lab PhD student Erin Carroll.
Detail-oriented and organization skills are required. Prior experience working in a wet lab environment and/or managing large datasets is not required. Academic interest in plant biology is preferred!