The synthesis and modeling of ecological processes at bring together investigators, ideas, and data for the purpose of locally validating the National Aeronautics and multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This ar-Space Administration Earth Observation System-era global data sets (Running et al., 1999, this issue). This ticle describes a data and information system model that facilitates assembling, managing, and sharing diverse coordinated exercise proposes to study the effect of scaling from a fine grain to a coarse grain on estimates of data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain important biosphere variables from a range of biome conditions. Using standardized methods that incorporate working groups coordinate the development of data associated with their particular scientific working group, inextensive ground data sets, ecosystem models, and remotely sensed imagery, sites will develop local maps of cluding decisions about data requirements, data to be compiled, data formats, derived data products, and land cover class (LCC), leaf area index (LAI), and aboveground net primary productivity (NPP). This article de-schedules across the sites. The Web-based data and information system consists of nodes for each working group scribes a data and information system (DIS) model that would facilitate assembling, managing, and sharing di-plus a central node that provides data access, project information, data query, and other functionality. The apverse data from multiple disciplines, scales, and sites to support integrated ecological studies, such as the Big-proach incorporates scientists and computer experts in the working groups and provides incentives for individu-Foot project. als to submit documented data to the data and information system. Published by Elsevier Science Inc.
Integrated, Multisite Projects
Projects that entail the synthesis and modeling of ecological phenomena over regions require multidiscipline data