Easton R. WhiteEaston White Headshot
Quantitative Ecology - Data Science - Sustainability


COVID-19 pandemic and global fisheries
Marine protected areas in a changing world
Socio-ecological systems
Improving monitoring programs
Variability in ecological management outcomes
Long-term trends of marine predators
Scholarship of Teaching and Learning
Metapopulation dynamics of small mammals


Environmental variability can occur on daily to decadal time scales. This variability can include natural variation, such as changes in seasons, or anthropogenic events like oil spills. Of course, these various forms of environmental variability shape ecosystems, and, consequently, the human communities that depend on them. In addition, climate change is expected to increase variability and uncertainty of these environmental factors. My research program addresses questions that fall within the Venn diagram above:

  1. How does environmental variability, particularly rare events like heatwaves or algal blooms, affect the ecology and population dynamics of various species?
  2. How can we improve population monitoring programs given uncertainty?
  3. How can incorporating uncertainty in models help us make better decisions about fisheries and the conservation of endangered species?
  4. How are natural-human systems affected by environmental variability and how can we ensure they are robust to shocks, like the current COVID-19 pandemic?
I address these questions using a variety of mathematical and statistical tools as well as long-term field studies. I have current projects focused on socio-ecological systems, environmental variabilty and population dynamics, improving monitoring programs, and designing marine reserve networks. In addition to biology-focused work, I have also conducted research on pedagogy.

COVID-19 pandemic and global fisheries

Recent news articles on COVID-19 and fisheries
With Boats Stuck in Harbor Because of COVID-19, Will Fish Bounce Back?
COVID-19 and US recreational fishing
Covid-19: Impacts on the Blue Economy, Ocean Health, and Ocean Security
Small-scale fishermen suffering significantly from COVID-19 pandemic

Building on my work in both COVID-19 modeling and marine fisheries, I am now collaborating with several people on how COVID-19 might affect fisheries and fishing communities. The last time we experienced a reduction in fishing effort of this magnitude was during both world wars when oceans were effectively closed to fishing. In response to the COVID-19 pandemic, governments have shut down various parts of their economies to promote social distancing. Already, fishing seasons have been cut short or certain types of fishing (e.g. commercial versus recreational) have been restricted. However, these government actions vary between and within countries (White & Hébert-Dufresne 2020). This presents another natural experiment to see how fish populations and fisheries respond to management interventions. Our goal is to understand the downstream effects of these shutdowns on fisheries, fish populations, and the communities that rely on them. If you are interested in contributing to this project please send an email to Easton.White@uvm.edu. We have also built a crowd-sourced database of COVID-19 related effects on fisheries which is being updated here: https://zenodo.org/record/3866189/

Relevant publications

COVID-specific publications

Marine protected areas in a changing world

We are examining the design of marine protected areas given environmental variability. All over the world, networks of marine protected areas have been established as both a conservation and management tool (Gaines et al. 2010). However, most work to date has ignored the role that variability or uncertainty in designing these marine protected areas (but see Halpern et al. 2006). Variability is important as individual protected areas can serve as an insurance policy for one another. If a population in a particular protected area is devastated by a hurricane, then organisms from another, unaffected population can recolonize that protected area. My current work (available as a preprint below) has focused on building simple, theoretical models to include variability in the design of these protected areas.

White, Easton R., Marissa L. Baskett, and Alan Hastings. 2020. Catastrophes, connectivity, and Allee effects in the design of marine reserve networks. bioRxiv.

Socio-ecological systems

Our work on marine protected areas led to an interdisciplinary collaboration with Drs. Merrill Baker-Medard (social scientist at Middlebury College) and Elizabeth Fairchild (fisheries biologist at the University of New Hampshire).

A conceptual diagram depicting key socio-ecological processes relating to MPAs including the relationship between (1) ecological factors such as fish diversity and harvest patterns such as the type and range of species targeted, (2) fishing community engagement such as the percent of fishers who participate in MPA management and ecological factors such as fish abundance inside the MPA, and (3) harvest patterns such as the type of species targeted and community engagement such as fishers opinion about the MPA.
Our goal is to develop tools to make better decisions in highly variable Malagasy fisheries. We take a holistic approach to study the entire socio-ecological system—examining interactions between ecosystem health, poverty, and human health. This project was recently funded by the National Science Foundation Coupled Natural-Human Systems program:

(CO-PIs) Baker-Medard Merrill, White Easton R., and Elizabeth Fairchild. Socio-Ecological Feedbacks of Marine Protected Areas: Dynamics of Small-Scale Fishing Communities and Inshore Marine Ecosystems. National Science Foundation CNH2: Dynamics of Integrated Socio-Environmental Systems. $602,320. 2019-2024.

Improving monitoring for species conservation and management

Monitoring of populations is a critical aspect of making decisions about the management of species. However, monitoring is often expensive and requires a lot of people-hours. Therefore, it is essential to determine the optimal locations for monitoring, the number of samples to take, and the frequency and duration of monitoring effort.

(a) Distributions of the minimum time required for populations from four dierent biological classes. (b) Distribution of minimum time required for all populations regardless of biological class. The minimum time required calculation corresponds to a significance level of 0.05 and statistical power of 0.8

In a recent manuscript at Bioscience (available here), I determined the minimum number of years required to be confident (i.e. have enough statistical power) in a population trend. Using simulations and empirical data from 822 populations, I estimated that 15.9 years on average were required. There was, however, tremendous variation between populations, casting doubt on simple rules of thumb. In a BioScience podcast, I discuss this work and population monitoring in general.

Dr. Stephen Heard (University of New Brunswick), Dr. Auriel Fournier (Forbes Biological Station), and I recently published an article in Conservation Biology that focused on the question of sampling bias in monitoring programs.. We found that bias in the sites chosen for monitoring can lead to overestimates in the long-term population decline estimates.

In a recent preprint, Dr. Christie Bahlai and I examine the various tools available for thinking about improving species monitoring programs. We emphasize the idea of conducting "experiments" with past monitoring programs in order to improve them and design new ones.

Dr. Rosalie Bruel and I applied these techniques to study the optimal sampling requirements and approaches for detecting ecosystem change in plankton communities derived from sediment cores. This work is now available in a recent preprint.

Relevant publications

Variability in ecological management outcomes

From invasive species to fisheries, managers are always trying to determine which management strategies are most effective. However, this is often a difficult challenge. If a particular management strategy fails, was it because it was a bad strategy or because of bad luck? It is difficult to disentangle management effectiveness from luck in the field because we often only have a single observation of the system. We have built a series of mathematical models (specifically a set of stochastic discrete-time equations that include stage-structure) to show there can be large variability in management outcomes. We studied this in the context of controlling the spread of an invasive species. We tested these ideas using laboratory experiments with the flour beetle (Tribolium spp.). The experiments matched up with predictions from the mathematical models. Although the laboratory experiments were highly controlled, there was still large variability in management outcomes (see movie of time series below). This highlights the importance of carefully evaluating management successes and failures in nature. We are now building on this work to study how to make invasive species management both effective and also cost effective.

White, Easton R., Kyle Cox, Brett Melbourne, and Alan Hastings. In press. Success and failure of ecological management is highly variable in an experimental test. Proceedings of the National Academy of Sciences.

Animation of number of beetles in each patch with each frame representing one generation over the course of the experiment. Each subplot is a different combination of dispersal time (hours) and harvesting rate.

Long-term population trends of sharks and rays

Worldwide, many species of sharks and rays have seen large declines in population size. Approximently, 25% of all chondrichthyan (shark, ray, chimaeras) species around the world are threatened according to IUCN criteria (Dulvy 2014). These species are threatened from overfishing, habitat degradation and pollution. Sharks and rays act as predators and drive population dynamics of species lower in the food chain. (Heithaus et al. 2010). In response to declining populations of sharks and rays, many countries have instituted marine protected areas (MPA). An MPA is a conservation and management tool that is designed to let species recover by providing them with an area of refuge, free from fishing. However, it is not clear if MPAs are effective for large mobile predators, like sharks and rays.

We are studying sharks and rays at Cocos Island. The island is located 550km off of the mainland of Costa Rica. The island has been a marine protected area for the past two decades. We use data collected by the dive company Undersea Hunter, to get a sense of the population status of 12 shark and ray species that are commonly seen at Cocos Island. Here is the paper Shifting elasmobranch community assemblage at Cocos Island – an isolated marine protected area and here is a corresponding press release.


Shark nurseries in the Bahamas

In a related project, I studied long-term trends of lemon sharks found in the Bahamas. We developed a series of mathematical models to better understand the population of juvenile lemon sharks found in the lagoons of Bimini. We found that the variance in population size of juvenile sharks, is mostly driven by the environment. Therefore, predators and food resources may not be as important factors in driving population dynamics as once thought. I combined a mathematical model with field data to better understand a population of lemon sharks in the Bahamas. I found that a simple model could predict the long-term mean of the population size well, but it did a poor job at predicting the variance in population size (White et al. 2014). It turned out that much of the variance in population size could be explained by a few unusual years in terms of the environment.

Metapopulations dynamics of small mammals

We study the ecology and evolution of the American pika (Ochotona princeps) living on a metapopulation at Bodie State Historic Park. The metapopulation is comprised of patches made up of abandoned ore dumps. Near the end of the 19th century, pikas colonized these ore dumps creating a metapopulation of about 80 patches. Around 1990, the southern half of the study site had collapsed and few pikas have been censused there since. We developed a simulation model to better understand the dynamics of the Bodie population. We have found that spatial structure (the arrangement of the patches in the landscape) and demographic stochasticity both important aspects of the Bodie site.

These findings have recently been published in Ecology.

Here is a simulation of metapopulation dynamics at Bodie over the last 40 years. The size of the circles represents how many pikas are on a given patch in each year.

Bodie pika metapopulation

I spent a summer at the International Institute for Applied Systems Analysis in Vienna, Austria. I led a team of biologists and mathematicians to investigate the evolutionary consequences of changing seasonal regimes due to climate change. This work focused on the collared pika (Ochotona collaris) found in the Yukon, Canada. This work is available as a preprint (White et al. 2018).

Scholarship of Teaching and Learning

In addition to biology-focused work, I have also been engaged in research on pedagogy. This is often termed Scholarship of Teaching and Learning (SoTL) or sometimes Discipline-based education research (DBER). As a scientist, I view teaching as a highly scientific process. I design and implement experiments in the classroom each time I teach. I then examine the results using various assessments (e.g. pre- and post-assessments, clicker questions, online activities) and refine my teaching approach.

As part of my efforts in teaching a summer biology bridge program at UC Davis, I also assessed student outcomes. These results are being used by the department to improve the biology bridge program in the future.

I am also part of the QuEST Leadership Team at the University of Vermont. QuEST is a PhD training grant focused on quantitative skills, applied problem solving, and diversity. Part of my responsibility is to assess student learning in the core course titled, Foundations of Quantitative Reasoning. The course involves inquiry- and team-based activities as well as active learning.