Big Data Ecology – Advancing the Study of Climate Change Vulnerability through Data Science
Measuring and predicting the consequences of modern climate change is one of the great challenges in ecology and has only been possible with the availability of “big data”. For ecologists, the most important stream of big data comes from citizen science programs that enlist the general public in collecting observations of the natural world. Citizen scientists, equipped with both old tools (binoculars) and new technologies (smartphones), regularly collect data on where species occur across unprecedented scales. Our project will leverage data from eBird, an online citizen-science program that allows volunteers to enter bird observations from anywhere in the world, along with data on weather and climate to predict bird species distributions across the conterminous United States.
Citizen science is an expanding stream of data for ecologists with programs like eBird collecting millions of observations at an unprecedented rate. Species distribution models are the most common statistical analysis approaches for predicting the responses of species to climate change, and our project seeks to advance the use of big data science and machine learning to better understand the effects of extreme weather (e.g., cold snaps, heat waves, drought) and climate on the vulnerability of species to future climate change.
Benjamin Zuckerberg, Associate Professor of Forest and Wildlife Ecology
Daniel Fink, Senior Research Associate at Cornell Lab of Ornithology