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

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 (as documented with field data from 1,200 of the soil sample sites) can be inferred from the soil maps. The species segregated clearly along the soil cation concentration gradient in the field, but only partially along the model‐estimated cation concentration gradient, and hardly at all along the mapped CEC gradient. The main problems reducing the predictive ability of the soil maps were insufficient spatial resolution and/or georeferencing errors combined with thematic inaccuracy and absence of the most relevant edaphic variables. Addressing these problems would provide better models of the edaphic environment for ecological studies in Amazonia.

Using remote sensing to model tree species distribution in Peruvian lowland Amazonia

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Global fern and lycophyte richness explained: How regional and local factors shape plot richness

“…However, when soil properties have not been measured at the site but their impact needs to be inferred from soil type data derived from digital soil maps, their direct impact is not easy to quantify. This is partly due to accuracy problems and georeferencing errors in the available digital soil data, which themselves have been derived from scant field data (Moulatlet et al, 2017).…”

Discovering floristic and geoecological gradients across Amazonia

“…Although digital soil maps exist (Hengl et al, 2017), they do not provide layers of soil base cation concentration. The digitally available variables, such as soil type and cation exchange capacity have had only weak relationships with field-measured base cation concentration (Moulatlet et al, 2017). Therefore, we used Landsat imagery as a surrogate, since earlier studies at the landscape extent have found them useful for identifying spatial heterogeneity in soils and soil-related floristic patterns (Higgins et al, 2012(Higgins et al, , 2011Salovaara et al, 2005;Tuomisto, Poulsen, et al, 2003;Tuomisto, Ruokolainen, Aguilar, et al, 2003).…”