Ecological modeling is becoming an increasingly important tool for uniting biological observations with remote sensing and ground-based data networks to develop predictive tools for resource management and human health. The availability of over three petabytes of data from the NASA Earth Observing System Data and Information System (EOSDIS) alone provides an unprecedented opportunity to develop Earth science applications for decision support. In combination with data networks such as the U.S. National Oceanic and Atmospheric Administration's National Climate Data Center, the nonprofit NatureServe's network of biological inventories, the National Environmental Public Health Tracking Network of the U.S. Centers for Disease Control and Prevention, and many others, there is a vast wealth of Earth observation data on parameters as diverse as land cover, sea surface temperature, precipitation, species distribution, and disease occurrence.