Birds are excellent indicators of ecosystem health. New Big Data approaches, which employ global networks of volunteers to gather data, and novel approaches to model and visualize species distributions over enormous spatial and temporal scales represent a game-changing opportunity for the conservation of bird populations and overall environmental health. The objective of this proposal is to build the foundation of our existing work, thus Modeling Broad-scale Species distributions with Fine-scale Spatial and Temporal Resolution across the entire Western Hemisphere. To accomplish this we will build a workflow to gather new sources of data describing environment, and to develop new species distribution analyses to model not just distribution but also abundance. With these new tools in hand, we will be able to identify critical concentrations of birds anywhere in the western hemisphere, as well as being able to extrapolate distributions to novel environmental conditions such as those that will occur under variety of climate change scenarios. Ultimately, our goal is to improve the effectiveness of conservation actions at a hemispheric scale by stabilizing and reversing negative population trends and identifying critical areas for protection at the local scale. The potential is enormous because for the first time we can implement conservation priorities hemisphere-wide, and throughout the entire life-cycle of many migratory bird populations. We will provide the tools to allow us to prioritize conservation areas anywhere, and devise management actions that will deliver the biggest impact in terms of bird populations protection in return on conservation resources invested. First year funding will allow us to further develop and refine the spatial temporal exploratory models that are currently being employed throughout the conterminous United States. This will allow us to provide decision support tools to be employed in out-years by The Nature Conservancy to conserve migratory bird populations throughout the Western Hemisphere.