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| Main Author: | |
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| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2017
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.879542 |
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Table of Contents:
- Maps of soil cation concentration as modelled using direct and plant-derived soil data together as input data: -KrigeSoill_fernRcropNEW.tif - covering the whole Amazonian sensu latissimo. One single interpolation without wetlands claasification. -KrigeAvg_MaskWETfern_Soil.tif - Two krigings were run separately for wetlands and uplands and ovelaped to compose a single map (map extent limited to the area covered by the available wetlands map). -KrigeSoill_fernERRORNEW.tif - degree of uncertainty in predicted values as quantified by the Kriging variance associated with map KrigeSoill_fern.tif. To obtain a standard deviation map use the variance map to the power of 2 (KrigeSoill_fernERRORNEW.tif ^2). -KrigeAvg_WETLANDfern_SoilERROR.tif - degree of uncertainty in predicted values as quantified by the Kriging variance associated with map KrigeAvg_MaskWETfern_Soil.tif. To obtain a standard deviation map use the variance map to the power of 2 (KrigeAvg_WETLANDfern_SoilERROR.tif ^ 2). Methods in brief: We defined fern species optima using compiled data from 1,353 quantitative fern and lycophyte inventory plots across Amazonia that also provided locally measured soil cation concentration. We obtained and cleaned species occurrence records from the Global Biodiversity Information Facility (GBIF; http://www.gbif.org) and SpeciesLink (http://www.splink.org.br) and assigned a soil value to each of the georeferenced records according to the exchangeable cation concentration optima estimated for the species (hereafter fern-derived soil points). We combined the fern-derived soil points with soil points provided by Harmonized World Soil Database v1.2 (HWSD) (Nachtergaele et al. 2012) and Brazilian National database (BND) (Cooper et al. 2005). We generated exchangeable cation concentration maps using both direct and indirect environmental data as input points for interpolation using ordinary Kriging. We validated the maps using external soil information from 194 plots of the Amazon Forest Inventory Network (RAINFOR). -- The files are in .tif format and consist of digital spatial layers that can be opened in QGIS, R and other GIS or spatial analysis programs.