Eric R. Scott

Ph.D. Candidate, Tufts University
Orians Lab
Tea & Climate Change Collaborative

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Research Projects

Use of partial least squares regression (PLS) in ecology

PLS is a powerful multivariate regression method that has many applications for ecological data. When is it best used, what are its advantages, and how should you report your results?

Can fermentation rescue low-quality monsoon season tea?

Is microbial ripening a way for tea farmers to improve low-quality monsoon season harvests?

Climate Effects on Bug-Bitten Tea

Eastern Beauty wulong tea is only produced from tea leaves damaged by leafhoppers. The induced volatiles produced by damaged tea plants gives the finished tea a unique flavor. How will leafhopper damage change in a warming climate, and how will that impact tea quality?

Drought and plant response to herbivory

When plants experience mild or severe drought, how does that change their metabolic response to damage by insect herbivores?

Elevated CO2 and plant response to herbivory

How will elevated CO2 affect plant responses to insect herbivory? How will this interaction impact the quality of tea?

Field-Sampling Plant Volatiles

Finding a high-throughput way to collect plant volatiles in the field.

Selected Publications

We simulated herbivory on moderately and severely drought stressed tea plants. Non-volatile metabolites were unaffected by drought stress nor simulated herbivory. Most volatiles were not induced by simulated herbivory under severe drought. Methyl salicylate had greater induction by simulated herbivory under severe drought. Drought affects plant responses to biotic stress with consequences for tea quality.
EEB, 2018.

To understand plant volatile production in response to environmental stimuli, in situ sampling is necessary. Direct contact sorptive extraction (DCSE) involves placing a PDMS-coated magnetic stir bar (Twisters) in direct contact with a leaf using a magnet. In contrast to dynamic headspace sampling (DHS), this eliminates artifacts produced by enclosing plants in a chamber. We demonstrate that DCSE is more sensitive than DHS, captures a wider range of compounds, and is relatively inexpensive and simple to deploy making it ideal for in situ sampling of plant volatiles.
J Agric Food Chem, 2017.

Recent and Upcoming Presentations

More Talks

[poster] Interactive effects of drought severity and herbivory on tea (Camellia sinensis) volatile and non-volatile metabolites.
Nov 11, 2018
Can pests rescue tea quality from climate change?
Jul 20, 2018
Combined Effects of Drought and Herbivory on Tea Metabolism
Mar 2, 2018
[poster] Generating and analyzing metabolomic data from tea plant volatiles
Nov 8, 2017

Peer-Reviewed Publications

. Combined impacts of prolonged drought and warming on plant size and foliar chemistry. AOB, 2019.


. Differential Changes in Tea Quality as Influenced by Insect Herbivory. Stress Physiology of Tea in the Face of Climate Change, 2019.

Project HTML

. Interactive effects of drought severity and simulated herbivory on tea (Camellia sinensis) volatile and non-volatile metabolites. EEB, 2018.

Dataset Project HTML

. Striking changes in tea metabolites due to elevational effects. Food Chem, 2018.

Project HTML

. Exogenous melatonin alleviates cold stress by promoting antioxidant defense and redox homeostasis in Camellia sinensis L.. Molecules, 2018.


. Direct Contact Sorptive Extraction: A Robust Method for Sampling Plant Volatiles in the Field. J Agric Food Chem, 2017.

Project HTML

. Taxonomy, life history, and population sex ratios of North American Dasineura (Diptera: Cecidomyiidae) on goldenrods (Asteraceae). Annals of the Entomological Society of America, 2007.



Podcast appearances:

Invited Blog Posts:

Guest Lectures:

Outreach Talks:

  • Climate change and the quality of tea. Taste of Science Boston. April 26, 2017.

Other Activities:


I’ve been teaching biology ever since I was 12 when I became an interpretive guide at the Lindsay Wildlife Experience in my home town of Walnut Creek, CA. Since then I’ve taught science of all sorts to all ages in a variety of formats.

Selected Teaching Experience:

  • Biostatstics in R. Fall 2016–2018. Recitation section for BIO132 at Tufts University. In collaboration with Natalie Kerr in 2016 and Avalon Owens in 2018, we designed and taught this new course. Previously, BIO132 used SPSS rather than R and did not have a required recitation. Course materials available here.
  • Organisms and Populations. Spring 2015. Lab section for BIO0014 at Tufts University. I served as a graduate TA for a lab section of this course in a year when the course was being entirely redesigned. I actively participated in designing course materials and lab activities in addition to teaching my own lab section.
  • Introductory Biology. 2011 – 2014. I taught a guaranteed transfer credit lecture and lab course at Front Range Community College in Fort Collins, CO where I was an instructor. My students came from diverse age, socioeconomic, and learning backgrounds. I designed lectures and assessment materials and engaged in revising lab exercises and course materials.
  • Organismal and Evolutionary Biology. MIST section. 2007 – 2009. I was a graduate TA for IB150 at University of Illinois at Urbana Champaign as a graduate student. MIST is a program for high-achieving students from marginalized backgrounds such as small, rural schools or large, urban schools that encourages students to form peer learning groups through additional in-class time and active learning.

Recent Posts

More Posts

I woke up this morning to an email saying my first R package, holodeck, was on it’s way to CRAN! It’s a humble package, providing a framework for quickly slapping together test data with different degrees of correlation between variables and differentiation among levels of a categorical variable. # Example use of holodeck library(holodeck) library(dplyr) df <- #make a categorical variable with 10 observations and 3 groups sim_cat(n_obs = 10, n_groups = 3, name = "Treatment") %>% #add 3 variables that covary sim_covar(n_vars = 3, var = 1, cov = 0.


Have you ever pondered whether a muffin is really a breakfast food and not just an excuse to eat cake first thing in the morning? Well, you’ve come to the right blog post! In a previous post, I explained how I created a dataset of the ingredients of 269 cupcake and muffin recipes. In this installment, I’m going to use that dataset to demonstrate some of the important properties of multivariate statistics, specifically the difference between principal component analysis (PCA) and partial least squares regression (PLS).


This was my first time attending RStudio::conf, and I went primarily to explore my career options in data science. I mainly stuck to teaching and modeling related talks since that’s how I already use R. Here are my major takeaways from the conference. Shiny is the new hotness Shiny apps are interactive web apps that run on R code, and there was a big focus on Shiny development at the conference this year.


I recently gave a talk on some of my work as a PhD student on experiments manipulating densities of the tea green leafhopper (Empoasca onukii) on tea plants. What the audience liked most, I think, were my methods for finding leafhopper eggs in the field and rearing them in the lab (well, a guest room at a tea farm). You see, leafhoppers (including at least the tea green leafhopper and the small green leafhopper, Empoasca vitis) lay their eggs inside plant tissues, making them impossible to find with the naked eye.


I’m currently in Hangzhou, China at the Tea Research Institute(TRI) for my fourth and last time. It’s bitter sweet (like my favorite teas ;-) ) since I’m both glad to be nearing the end of my PhD, and sad to say goodbye to all the friends I’ve made and a city I’ve really grown to enjoy living in. Fieldwork This final summer, I’ve been focusing on a few experiments having to do with leafhoppers and their effects on tea chemistry (see the project page for more info).



  • 347 Robinson Hall, Tufts University, Medford, 02155, USA
  • Office Hours: Email for appointment