Using climatically based random forests to downscale coarse-grained potential natural vegetation maps in tropical Mexico
Authors: Vaca, R.A., Golicher, D.J. and Cayuela, L.
Journal: Applied Vegetation Science
Volume: 14
Issue: 3
Pages: 388-401
eISSN: 1654-109X
ISSN: 1402-2001
DOI: 10.1111/j.1654-109X.2011.01132.x
Abstract:Questions: Can the accuracy of coarse resolution potential vegetation maps be improved through downscaling to finer resolution climatic grids? Can output from random forests produce new insight into the climatic characteristics that are associated with the structural characteristics of the vegetation? Location: Southern Mexico. Methods: A potential vegetation map (National Atlas of Mexico) at a 1:4000000 scale, was downscaled to a 1km2 grid resolution using climatically based random forests models. The resulting map was then evaluated against 256 inventory plots sampled at the transition between different vegetation types in Southern Mexico. Results: Downscaling increased accuracy up to 0.40, as measured by the Kappa Index of Agreement. Multivariate analysis of the results allowed the association between Rzedowski's classification and climatic variation to be explored. This confirmed that many of the structural aspects of the vegetation that are used by the Rzedowski classification are closely associated with climate, but it also revealed weaknesses in the underlying basis of this classification system. Conclusions: Rzedowski's scheme for vegetation classification may require further modification in order to be an effective tool for research into vegetation-climate relationships. © 2011 International Association for Vegetation Science.
Source: Scopus
Preferred by: Duncan Golicher
Using climatically based random forests to downscale coarse-grained potential natural vegetation maps in tropical Mexico
Authors: Vaca, R.A., Golicher, D.J. and Cayuela, L.
Journal: APPLIED VEGETATION SCIENCE
Volume: 14
Issue: 3
Pages: 388-401
eISSN: 1654-109X
ISSN: 1402-2001
DOI: 10.1111/j.1654-109X.2011.01132.x
Source: Web of Science (Lite)