Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help
 

Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (1.0 MB byte)

Title: Modeling species distribution and change using random forest [Chapter 8]

Author: Evans, Jeffrey S.; Murphy, Melanie A.; Holden, Zachary A.; Cushman, Samuel A.;

Date: 2011

Source: In: Drew, A. C.; Wiersma, Y.; Huettmann, F., eds. Predictive Species and Habitat Modeling in Landscape Ecology. New York, NY: Springer. p.139-159.

Publication Series: Book Chapter

Description:

Although inference is a critical component in ecological modeling, the balance between accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; De’ath 2007). Practical applications of ecology in conservation planning, ecosystem assessment, and bio-diversity are highly dependent on very accurate spatial predictions of ecological process and spatial patterns (Millar et al. 2007). However, the complex nature of ecological systems hinders our ability to generate accurate models using the traditional frequentist data model (Breiman 2001a; Austin 2007). Well-defined issues in ecological modeling, such as complex non-linear interactions, spatial autocorrelation, high-dimensionality, non-stationary, historic signal, anisotropy, and scale contribute to problems that the frequentist data model has difficulty addressing (Olden et al. 2008). When one critically evaluates data used in ecological models, rarely do the data meet assumptions of independence, homoscedasticity, and multivariate normality (Breiman 2001a). This has caused constant reevaluation of modeling approaches and the effects of reoccurring issues such as spatial autocorrelation. Model misspecification problems such as the modifiable aerial unit (MAUP) (Cressie 1996; Dungan et al. 2002) and ecological fallacy (Robinson 1950) have also arisen as clearly defined challenges to ecological modeling and inference.

Keywords: ecological modeling, species distribution, conservation planning

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.
  • You may send email to rmrspubrequest@fs.fed.us to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)

XML: View XML

Citation:


Evans, Jeffrey S.; Murphy, Melanie A.; Holden, Zachary A.; Cushman, Samuel A. 2011. Modeling species distribution and change using random forest [Chapter 8]. In: Drew, A. C.; Wiersma, Y.; Huettmann, F., eds. Predictive Species and Habitat Modeling in Landscape Ecology. New York, NY: Springer. p.139-159.

 


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

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.