Primary tabs

Assessing changes in phytochemical diversity and structural chemical similarity in plant communities across succession

Project Abstract: 
Background: Plants produce myriad compounds with various functions in growth, defense, stress tolerance, etc., and these compounds can have profound impacts on plant communities and their surrounding ecosystems. Ecological theory suggests that plant species that differ in the chemical compounds from surrounding members of the community will have a competitive advantage via avoiding consumption by similar pests and pathogens. As such, it is hypothesized that plant communities may be under selection to be more chemically different in more competitively stressful environments, such as during the period of high species richness during forest succession prior to complete canopy closure. However, changes in the chemical diversity of plant communities across successional timelines have never been investigated. Proposed Research: I propose to compare the phytochemistry of plant communities at both the intra- and inter-specific scales across the UMBS burn plots in order to answer the following specific questions: 1. How does phytochemical diversity change throughout plant community succession, both within and across species? 2. Is turnover in phytochemical diversity higher than would be expected given turnover in plant species composition? Or than expected based on turnover in plant functional traits?
Investigators: 
Status of Research Project: 
Years Active: 
2024
Research sites: 
Methods: 
Field Sampling: In order to adequately sample intra- and inter-specific variation in phytochemistry across the burn plots, I will remove 2-10 whole, undamaged leaves from 5-10 individuals of the most common plant species present within each plot. Most common species will be defined as any species with > 10 individuals within each plot according to recent plot survey data from 2019 and 2022. Additionally, life stage will be recorded for trees (i.e., sapling, juvenile, adult) and life history strategy will be recorded for all plants (e.g., annual or perennial herb, deciduous or evergreen tree, shrub, vine, etc.) for use as covariates in statistical analysis. I will flag each plant using flagging tape in case they need to be resampled. For larger trees, I will use clippers attached to long poles, to sample from as much of the canopy as possible. Leaves will be dried in silica gel and transported back to main campus where they will be stored at -20 C until chemical analysis. Chemical Analysis: Dried leaf samples from each plant will be homogenized using a tissue lyser and then extracted in methanol. Methanol-tissue solutions will be homogenized using a Vortex mixer, and then centrifuged at 14000 RPM for five minutes. After centrifugation, the supernatant will be pipetted into clean Eppendorf tubes and will serve as the raw chemical sample for that individual plant. Raw samples will then be diluted before peak separation and mass quantification are performed via ultra-high performance liquid chromatography mass spectrometry (LC-MS). LC-MS data will be processed using an R and python analysis pipeline I have created and implemented in previous work (in prep).