Patterns in Bird Migration Phenology Explored through Data Intensive Analysis and Visualization
Steven
Kelling, Cornell Lab of Ornithology, stk2@cornell.edu
Daniel
Fink, Cornell Lab of Ornithology, df36@cornell.edu
Kevin
Webb, Cornell Lab of Ornithology, kfw4@cornell.edu
Suresh
SanthanaVannan, Oak Ridge National Laboratory, santhanavans@ornl.gov
Robert
Cook, Oak Ridge National Laboratory, cookrb@ornl.gov
(Presenting)
Assessing, and mitigating threats to biodiversity must overcome three challenges: 1) species’ distributions vary through time and space; 2) sufficient data are seldom available; 3) conventional analyses are not effective for facilitating pattern discovery. The goal of our Scientific Exploration, Visualization, and Analysis (EVA) project is to advance data intensive science by developing new techniques that describe the broad-scale dynamics of continent-scale bird migration.
First, we developed a data warehouse where locations of bird observations made through eBird (http://www.ebird.org) are linked to environmental covariates such as weather, habitat (land cover, land use change, soils, human population, urbanization), and vegetation phenology (MODIS land products) from multiple sources. At present, more than 300,000 bird observation locations have been linked to over 500 environmental variables. Next, we employed novel semi-parametric spatiotemporal models to analyze dynamic patterns of species occurrence and identify predictors of habitat suitability. The model produces highly accurate simulations of intra-annual bird migrations. Finally, VisTrails (http://www.vistrails.org/) scientific workflow software is used to provide a systematic means to organize, document, explore, and visualize data and results from these analyses. Encapsulating this research in a workflow environment allows others to efficiently reproduce and validate results and use this data and methodology for other applications.
By interpreting and analyzing these models, novel patterns “born from the data” provide valuable insight into the underlying ecological processes of bird migration. Our EVA techniques allow scientists to analyze bigger and more complex systems efficiently, and complement more traditional scientific processes of hypothesis generation and experimental testing for a better understanding of the natural world.
Presentation Type: Poster
Poster Session: Ecosystems Science
NASA TE Funded Awards Represented:
NONE: Related Activity or Previously Funded TE Award