NCEAS Project 12504

Choosing (and making available) the right environmental layers for modeling how the environment controls the distribution and abundance of organisms

  • Brian McGill
  • Robert Guralnick
  • Walter Jetz
  • Jana McPherson

ActivityDatesFurther Information
Working Group22nd—26th March 2010Participant List  
Working Group12th—16th October 2010Participant List  
Postdoctoral Fellow29th August 2012—14th January 2014Participant List  

We seek to understand how the environment controls species distributions. Despite the fact that a great deal of work in physiology has been done on this problem and that literally thousands of niche models (regressions of distribution on environment) have been run, we know surprisingly little about basic questions. Which aspects of environment are most central in controlling the distribution and abundance of organisms? How does this change with organism? with scale? what are the mechanisms linking environment to species distributions? We propose to assemble a state-of-the-art set of environmental layers that incorporate well-known but rarely used measures that have direct links to physiological processes like frost, water stress, growing season, soil properties, drainage properties, etc. We will assemble these variables into a unified, global, gridded, high resolution data set that will be made available to the public. This will be of enormous benefit to the community. We will use this data to explore the above-mentioned basic questions about the nature of the links between the environment and the distribution of organisms.

TypeProducts of NCEAS Research
Journal Article Jetz, Walter; McPherson, Jana; Guralnick, Robert. 2012. Integrating biodiversity distribution knowledge: Toward a global map of life. Trends in Ecology and Evolution. Vol: 27. Pages 151-159. (Online version)
Journal Article Robinson, Natalie S.; Regetz, Jim; Guralnick, Robert. 2014. EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data. ISPRS Journal of Photogrammetry and Remote Sensing. Vol: 87. Pages 57-67.
Report or White Paper Schildhauer, Mark P.; Swenson, Nathan G.; Ackerly, David D.; Jetz, Walter. unknown. Botanical geospatial diversity cyberinfrastructure.
Journal Article Wilson, Adam M.; Parmentier, Benoit; Jetz, Walter. 2014. Systematic land cover bias in Collection 5 MODIS cloud mask and derived products-A global overview. Remote Sensing of Environment. Vol: 141. Pages 149-154.