Mapping environmental variation in lowland Amazonian rainforests using remote sensing and floristic data

Abstract

This article describes a method for detailed mapping of ecological variation in a tropical rainforest based on field inventory of pteridophytes (ferns and lycophytes) and remote sensing using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery. Previously known soil cation optima of the pteridophyte species were first used in calibration, i.e. to infer soil cation concentrations for sites on the basis of their pteridophyte species composition. Multiple linear regression based on spectral reflectance values in the Landsat image was then used to derive an equation that allowed the prediction of these calibrated soil values for unvisited sites in the study area. The predictive accuracy turned out to be high: the mean absolute error, as estimated by leave-one-out cross-validation, was just 7% of the total range of calibrated soil values. This method for detailed mapping of natural environmental variability in lowland tropical rainforest has applications for land-use planning, such as wildlife management, forestry, biodiversity conservation, and payments for carbon sequestration.

Acknowledgements

During the early planning phase of the project, Anders Sirén was funded by the Academy of Finland. During further planning, as well as fieldwork and preliminary data analysis, he was funded by a postdoc grant from the Swedish International Development Authority (SIDA) and a postdoc grant from the Swedish Research Council for Environment, Agricultural Sciences, and Spatial Planning (FORMAS). During the final analyses and writing the manuscript, Sirén was funded by Akademikernas Erkända Arbetslöshetskassa, the Swedish Cultural Fund in Finland, the Oscar Öflund Foundation, and by a grant awarded to Professor Risto Kalliola by the Kone Foundation. Saul Malaver, Alex Machoa, and Angel Gualinga assisted with fieldwork. We thank the Government Council of the Sarayaku Community for facilitating fieldwork and Dra. Laura Arcos Terán, Dean of the Natural and Exact Sciences, Faculty of the Pontificia Universidad Católica del Ecuador, for institutional support to the development of the project.