Exploring similarities among many species distributions
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Abstract
Collecting species presence data and then building models to predict species distribution has been long practiced in the field of ecology for the purpose of improving our understanding of species relationships with each other and with the environment. Due to limitations of computing power as well as limited means of using modeling software on HPC facilities, past species distribution studies have been unable to fully explore diverse data sets. We build a system that can, for the first time to our knowledge, leverage HPC to support effective exploration of species similarities in distribution as well as their dependencies on common environmental conditions. Our system can also compute and reveal uncertainties in the modeling results enabling domain experts to make informed judgments about the data. Our work was motivated by and centered around data collection efforts within the Great Smoky Mountains National Park that date back to the 1940s. Our findings present new research opportunities in ecology and produce actionable field-work items for biodiversity management personnel to include in their planning of daily management activities.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Exploring similarities among many species distributions |
| DOI | 10.1145/2335755.2335835 |
| Year Published | 2012 |
| Language | English |
| Publisher | ACM |
| Contributing office(s) | Coop Res Unit Atlanta |
| Description | art38 |
| Larger Work Type | Conference Paper |
| Larger Work Subtype | Conference Paper |
| Larger Work Title | Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond |
| Conference Title | 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond |
| Conference Location | Chicago, IL |
| Conference Date | July 16-20, 2012 |
| Online Only (Y/N) | N |
| Additional Online Files (Y/N) | N |
| Google Analytic Metrics | Metrics page |