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Modeling Species Distribution and Change Using Random Forest

  • Jeffrey S. Evans
  • Melanie A. Murphy
  • Zachary A. Holden
  • Samuel A. Cushman
Chapter

Abstract

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.

Keywords

Minority Class Niche Model Random Forest Model Random Forest Algorithm Climate Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Funding for this research was provided by the USDA Forest Service, Rocky Mountain Research Station and The Nature Conservancy. The authors would like to thank G. Rehfeldt, A. Hudak, N. Crookston, L. Iverson, and A. Cutler for valuable discussion on Random Forest and species distribution modeling and A. Prasad, J. Kiesecker and two anonymous reviewers for comments that strengthened this chapter. Additionally we would like to thank the editors for their patience and perseverance in seeing this book published.

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Copyright information

© Springer Science+BUsiness Media, LLC 2011

Authors and Affiliations

  • Jeffrey S. Evans
    • 1
  • Melanie A. Murphy
  • Zachary A. Holden
  • Samuel A. Cushman
  1. 1.The Nature Conservancy, North America ScienceFort CollinsUSA

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