Dallas J
- Research Program Mentor
MS at Stony Brook University
Expertise
Marine Biology, Ornithology, Statistics, R, Programming, Data Science, Ecology, Evolution, Wildlife Biology, Spatial Ecology, movement ecology of wildlife, spatial ecology, projects that use big data to understand species distributions, habitat modeling in the marine environment
Bio
Ever since I stepped foot in a seabird colony during my undergraduate degree, I knew working with wildlife in the marine environment was what I was called to do. My passion for ocean science, and marine birds specifically, is driven by wanting to address critical questions related to conservation: where are threatened birds distributed, and what oceanographic features do they encounter during the months that they are at-sea, away from land? During my Master's degree, I developed expertise in Bayesian and frequentist data analysis in R, as well as spatial and movement ecology. Using movement modeling methods, I spend my time investigating dispersal and distributions of seabirds, using data collected by light-level geolocators and GPS tags. Leveraging these skills lets me peer into the unknown world of where birds go when they leave the mainland - it's fascinating every time the results show the far-flung places they reach. I potentially spend more time drinking specialty coffee than working on my research, and if I wasn't a marine biologist, I'd certainly open my own coffee shop. I'm passionate about all things coffee-related, and will chat to no end about my favorite roasts and roasters.Project ideas
Using large citizen science data to draw insights on how the environment impacts migration
Data collection is a perpetual problem in field biology: it is costly, both in terms of time and money. A "good" sample size for some research might involve just 7 or 8 individuals. What if we leveraged data that is already being collected-- enthusiastically collected -- by volunteers across the nation? Passionate birdwatchers across the nation collect and submit data to eBird, the largest citizen-science project to date. eBird is a repository for bird sightings and a place to share data that birders have already been collecting for decades. Even better, eBird makes sightings data publicly available in data packages, letting curious researchers draw amazing insights from distributions of birds. For this proposed project, the researcher could download the eBird basic data set and process the movements of species of interest using the R package "auk". With locations of species in hand, the researcher could conduct habitat modeling with species distribution models, using environmental covariates that the researcher thinks might impact bird distributions. The researcher could then make this species distribution model available as an R "shiny app", which is a web-based application allowing for easy input of queries to produce high quality and impactful data visualizations.