This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

The University of Kansas and the University of Connecticut are awarded collaborative grants to develop software to gather, visualize and analyze large data sets of the distribution of species on continental and global scales. The proposed computational software and web services tools will gather together all available data on the geographical occurrence of any focal species from Internet sources. Once gathered, the data enter a computational pipeline to an ecological niche modeling environment that generates information on the potential distribution of individual species, which, in turn will be mapped on multi-species geographic grids. These multi-species grids are used by macroecologists for analyses of the geospatial patterning of species and for determining the ecological and evolutionary causes of current species distributions, and biodiversity spatial patterns. Macroecological analysis is also capable of analyzing the potential impacts of environmental changes on continental scales. This project, in addition to generating multi-species data grids for study, will also develop web services software tools based on the ?Spatial Analysis in Macroecology? software suite maintained at the University of Connecticut. The University of Kansas will engineer the server software architecture and computational web services for the project, building on its current species geospatial data archive and cluster-based, environmental niche modelling project ?Lifemapper."

Ultimately, the proposed software infrastructure is expected to catalyze macroecological modeling activity on important ecological and evolutionary geospatial questions by lowering the technical barriers to multispecies grid assembly and analysis. This integration is an obvious and cost-effective opportunity to accelerate research in this young, important field. The research challenges being addressed by macroecology include the most vital and insightful research predictions biologists can produce today to anticipate the biotic consequences of the changing natural environment, including global climate change.

Agency
National Science Foundation (NSF)
Institute
Emerging Frontiers (EF)
Type
Standard Grant (Standard)
Application #
0851245
Program Officer
Peter H. McCartney
Project Start
Project End
Budget Start
2009-08-01
Budget End
2012-07-31
Support Year
Fiscal Year
2008
Total Cost
$151,415
Indirect Cost
Name
University of Connecticut
Department
Type
DUNS #
City
Storrs
State
CT
Country
United States
Zip Code
06269