Southern Research Station

Title: A Nonparametric Geostatistical Method For Estimating Species Importance

Author: Lister, Andrew J.; Riemann, Rachel; Hoppus, Michael

Date: 2001

Source: In: Reams, Gregory A.; McRoberts, Ronald E.; Van Deusen, Paul C., eds. 2001. Proceedings of the second annual Forest Inventory and Analysis symposium; 2000 October 17-18; Salt Lake City, UT. Gen. Tech. Rep. SRS-47. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 52-59

Description: Parametric statistical methods are not always appropriate for conducting spatial analyses of forest inventory data. Parametric geostatistical methods such as variography and kriging are essentially averaging procedures, and thus can be affected by extreme values. Furthermore, non normal distributions violate the assumptions of analyses in which test statistics are generated and compared to a theoretical distribution, such as analysis of variance or stepwise multiple linear regression. Here, we offer guidelines and an example of the use of the indicator approach for dealing with nonparametric data distributions, using data from a study conducted in northern Vermont and New Hampshire.

Keywords: 

View and Print this Publication (387 KB)

Publication Notes: 

• We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
• This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

 Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

Citation

Lister, Andrew J.; Riemann, Rachel; Hoppus, Michael  2001.  A Nonparametric Geostatistical Method For Estimating Species Importance.   In: Reams, Gregory A.; McRoberts, Ronald E.; Van Deusen, Paul C., eds. 2001. Proceedings of the second annual Forest Inventory and Analysis symposium; 2000 October 17-18; Salt Lake City, UT. Gen. Tech. Rep. SRS-47. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 52-59