Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects

Ecology and Evolution
Gabriel Massaine MoulatletHanna Tuomisto

Abstract

Amazonia combines semi-continental size with difficult access, so both current ranges of species and their ability to cope with environmental change have to be inferred from sparse field data. Although efficient techniques for modeling species distributions on the basis of a small number of species occurrences exist, their success depends on the availability of relevant environmental data layers. Soil data are important in this context, because soil properties have been found to determine plant occurrence patterns in Amazonian lowlands at all spatial scales. Here we evaluate the potential for this purpose of three digital soil maps that are freely available online: SOTERLAC, HWSD, and SoilGrids. We first tested how well they reflect local soil cation concentration as documented with 1,500 widely distributed soil samples. We found that measured soil cation concentration differed by up to two orders of magnitude between sites mapped into the same soil class. The best map-based predictor of local soil cation concentration was obtained with a regression model combining soil classes from HWSD with cation exchange capacity (CEC) from SoilGrids. Next, we evaluated to what degree the known edaphic affinities of thirteen plant species (...Continue Reading

Associated Datasets

References

May 23, 2000·Nature·C R Margules, R L Pressey
Jan 11, 2003·Science·Hanna TuomistoMarkku Yli-Halla
Jan 17, 2012·Journal of Biogeography·Mark A HigginsMatti Räsänen
Aug 30, 2014·PloS One·Tomislav HenglMaria Ruiperez Gonzalez
Jul 14, 2016·Scientific Reports·Hans Ter SteegeRafael P Salomão
Jan 5, 2017·Proceedings of the National Academy of Sciences of the United States of America·Crystal N H McMichaelKenneth J Feeley
Feb 17, 2017·PloS One·Tomislav HenglBas Kempen

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Software Mentioned

rgdal
SOTERLAC
Soilgrids
rioja
maptools
SOTER
WorldClim
HWDS
R
ggplot2

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