Estimating Species Distributions-Across Space, Through Time, and with Features of the Environment

Steve Kelling, Daniel Fink, Wesley Hochachka, Ken Rosenberg, Robert Cook, Theodoros Damoulas, Claudio Silva, William Michener

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Determining the patterns of species occurrence through time and space and understanding their links with features of the environment are central themes in ecology. Using data-intensive approaches, scientists can analyze larger and more complex systems efficiently and complement more traditional scientific processes of hypothesis generation and experimental testing, and in so doing refine our understanding of the natural world. Over the past year, a working group consisting of computer scientists, domain researchers, programmers, and analysts met to identify and develop data-intensive procedures. This chapter reports the results of this working group. For this project, the dynamic habitat relationships of hundreds of species of birds across North America are identified through the assembly, exploration, analysis, and visualization of data using examples based on the synthesis and modeling of large datasets collected across multiple scientific domains.

Original languageEnglish (US)
Title of host publicationThe DATA Bonanza
Subtitle of host publicationImproving Knowledge Discovery in Science, Engineering, and Business
PublisherJohn Wiley and Sons
Pages441-458
Number of pages18
ISBN (Print)9781118398647
DOIs
StatePublished - Apr 9 2013

Keywords

  • Biological databases
  • Data access
  • Data discovery
  • Data products
  • Data synthesis
  • Data-intensive approaches
  • Environment
  • Species distributions

ASJC Scopus subject areas

  • Mathematics(all)

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  • Cite this

    Kelling, S., Fink, D., Hochachka, W., Rosenberg, K., Cook, R., Damoulas, T., Silva, C., & Michener, W. (2013). Estimating Species Distributions-Across Space, Through Time, and with Features of the Environment. In The DATA Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business (pp. 441-458). John Wiley and Sons. https://doi.org/10.1002/9781118540343.ch22