COS 104-4
Global ecological land units and ecoinformatics

Thursday, August 13, 2015: 9:00 AM
324, Baltimore Convention Center
Roger Sayre, USGS, Reston, VA
Dawn J. Wright, Environmental Systems Research Institute, Redlands, CA
Charlie Frye, Esri, Redlands, CA
Peter Aniello, Environmental Systems Research Institute, Redlands, CA
Randy Vaughan, Environmental Systems Research Institute, Redlands, CA
Sean Breyer, Environmental Systems Research Institute, Redlands, CA

The development of standardized concepts for identifying and characterizing ecological entities, and the development of  associated data models, is a fundamental element of ecoinformatics. We have developed a new global ecological land units (ELUs) datalayer at a 250 m spatial resolution for use in a variety of applications including climate change impacts studies, assessments of economic and social value of ecosystem goods and services, biodiversity conservation planning, scientific research, and resource management.


We mapped 3,923 ELUs as unique combinations of bioclimate, landform, lithology, and land cover. Unlike existing ecoregionalizations of the planet which are largely interpretive (expert-derived), the ELUs were derived from data, are largely objective (repeatable), and are highly systematic. They allow for cross-region and cross-continent comparisons of the ecological settings which control biotic distributions. We present a standardized conceptual framework for defining ecological land systems based on a contemplation of the major elements of terrestrial ecosystem structure. We describe a data model for representing these ELUs, and discuss the ecoinformatics dimension associated with the access, use, and dissemination of the data. Produced in a public/private collaboration between the U.S. Geological Survey and Esri, the ELUs represent an increasingly popular “ mixed”  ecoinformatics approach which contemplates hosting of authorized data as Living Atlas content in Esri’s ArcGIS Online web-based GIS resource. The data architecture, data serving, and data curation aspects of our ecoinformatics approach are presented.