Improving methods in gap ecology: revisiting size and shape distributions using a model selection approach
Article first published online: 1 OCT 2012
© 2012 International Association for Vegetation Science
Journal of Vegetation Science
Volume 24, Issue 3, pages 484–495, May 2013
How to Cite
de Lima, R. A. F., Prado, P. I., Martini, A. M. Z., Fonseca, L. J., Gandolfi, S., Rodrigues, R. R. (2013), Improving methods in gap ecology: revisiting size and shape distributions using a model selection approach. Journal of Vegetation Science, 24: 484–495. doi: 10.1111/j.1654-1103.2012.01483.x
- Issue published online: 2 APR 2013
- Article first published online: 1 OCT 2012
- Manuscript Accepted: 29 AUG 2012
- Manuscript Received: 22 DEC 2010
- Diversidade, dinâmica e conservação em florestas do Estado de São Paulo: 40 ha de parcelas permanentes. Grant Number: 99/09635-0
- CNPq. Grant Number: 132.938/2005-7
- FAPESP. Grant Number: 04/09554-0
- CNPq. Grant Number: 303878/2008-8
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Appendix S1. Maximum likelihood methods used during the gap size and shape analyses.
Appendix S2. Basic R codes and functions used during the gap size and shape analyses.
Appendix S3. Overall results of the gap size comparison between plots (Table S1), gap type (Table S2) and gap age (Table S3).
Appendix S4. Power-law function describing the relationship between CG and EG sizes.
Appendix S5. Results of CG and EG shape comparison between plots, and between classes of gap size and age.
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Appendix S6. Data set used to run the R codes given in Appendix S2.
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