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Gradient analysis, the next generation: Towards more plant-relevant explanatory variables

Publication ,  Journal Article
Lookingbill, TR; Urban, DL
Published in: Canadian Journal of Forest Research
July 1, 2005

The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. This model is unsatisfying in that elevation is not directly relevant to plants and the ubiquitous "elevation gradient" is composed of multiple intertwined environmental factors. We offer an approach to landscape-scale vegetation analysis that disentangles the elevation gradient into its constituent parts through focused field sampling and statistical analysis. We illustrate the approach for an old-growth watershed in the Oregon Western Cascades. Our initial model of this system supports the common observation that forest community types are highly associated with specific elevation bands. By replacing elevation and other crude environmental proxy variables with estimates of more direct and resource gradients (radiation, temperature, and soil moisture), we create a vegetative model with stronger explanatory power than the proxy model in both cross-validation analysis and validation using an independent data set. The resulting model is also more biologically interpretable, which provides more meaningful insight into potential forest response to environmental change (e.g., global climate change scenarios). Acquiring a better mechanistic understanding of the relationship between plant communities and environmental predictor variables presents the next great challenge to community ecologists conducting gradient studies at landscape scales. © 2005 NRC.

Duke Scholars

Published In

Canadian Journal of Forest Research

DOI

ISSN

0045-5067

Publication Date

July 1, 2005

Volume

35

Issue

7

Start / End Page

1744 / 1753

Related Subject Headings

  • Forestry
  • 41 Environmental sciences
  • 37 Earth sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 05 Environmental Sciences
  • 04 Earth Sciences
 

Citation

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Lookingbill, T. R., & Urban, D. L. (2005). Gradient analysis, the next generation: Towards more plant-relevant explanatory variables. Canadian Journal of Forest Research, 35(7), 1744–1753. https://doi.org/10.1139/x05-109
Lookingbill, T. R., and D. L. Urban. “Gradient analysis, the next generation: Towards more plant-relevant explanatory variables.” Canadian Journal of Forest Research 35, no. 7 (July 1, 2005): 1744–53. https://doi.org/10.1139/x05-109.
Lookingbill TR, Urban DL. Gradient analysis, the next generation: Towards more plant-relevant explanatory variables. Canadian Journal of Forest Research. 2005 Jul 1;35(7):1744–53.
Lookingbill, T. R., and D. L. Urban. “Gradient analysis, the next generation: Towards more plant-relevant explanatory variables.” Canadian Journal of Forest Research, vol. 35, no. 7, July 2005, pp. 1744–53. Scopus, doi:10.1139/x05-109.
Lookingbill TR, Urban DL. Gradient analysis, the next generation: Towards more plant-relevant explanatory variables. Canadian Journal of Forest Research. 2005 Jul 1;35(7):1744–1753.

Published In

Canadian Journal of Forest Research

DOI

ISSN

0045-5067

Publication Date

July 1, 2005

Volume

35

Issue

7

Start / End Page

1744 / 1753

Related Subject Headings

  • Forestry
  • 41 Environmental sciences
  • 37 Earth sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 05 Environmental Sciences
  • 04 Earth Sciences