About Me

Professional Background

I graduated from the University of California, Santa Barbara in 2022 with a B.S. in Zoology. During that time, I contributed to a meta-analysis, extracting data on ungulate diets to better understand how specific functional traits of ungulates influence plant biodiversity. After graduating, I held various positions within the public sector, working for the National Parks Service and the California Department of Food and Agriculture.

I went on to receive my Master of Environmental Data Science at the UC Santa Barbara, Bren School of Environmental Science & Management. I am currently completing a manuscript that evaluates the effectiveness of machine learning methods for predicting species distributions, using long-term data on the Black-Bellied Slender Salamander (Batrachoseps nigriventris).

Education

Master of Environmental Data Science - University of California, Santa Barbara (2024)

B.S. Zoology - University of California, Santa Barbara (2022)

Bird Watching

One of my favorite undergraduate classes was my vertebrate lab. I had the opportunity to visit sites across Santa Barbara to go bird watching, and learn about wildlife surveying techniques. I have continued to bird watch ever since, and keep track of my sightings using the Merlin and eBird apps, which are maintained by the Cornell Lab of Ornithology.

I thought it would be fun to visualize my personal bird sightings using a leaflet map:

View Code

# add CRS to lat/long points
birds <- birds %>%   
  st_as_sf(coords = c('longitude', 'latitude'), crs = 'EPSG:4236')

# create map
birds %>% 
  leaflet() %>% 
  addProviderTiles(providers$Jawg.Streets,
                   options = providerTileOptions(accessToken = token)) %>% 
  addMarkers(label = birds$common_name,
             popup = paste0(birds$common_name, ' (',
                            birds$scientific_name, ')'),
             clusterOptions = markerClusterOptions(),
             icon = makeIcon(iconUrl = iconpath,
                             iconWidth = 32, iconHeight = 32))