Integrating fine-scale soil data into species distribution models

Integrating fine-scale soil data into species distribution models

by Matthew P. Peters

Book 122 of General technical report NRS --

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Fine-scale soil (SSURGO) data were processed at the county level for 37 states within the eastern United States, initially for use as predictor variables in a species distribution model called DISTRIB II. Values from county polygon files converted into a continuous 30-m raster grid were aggregated to 4-km cells and integrated with other environmental and site condition values for use in the DISTRIB II model. In an effort to improve the prediction accuracy of DISTRIB II over our earlier version of DISTRIB, fine-scale soil attributes replaced those derived from coarse-scale soil (STATSGO) data. The methods used to prepare and process the SSURGO data are described and geoprocessing scripts are provided.

Discussion questions for Integrating fine-scale soil data into species distribution models

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  1. 1

    How does the transition from coarse-scale (STATSGO) to fine-scale (SSURGO) soil data mirror our human tendency to seek out finer details to better understand complex systems in our own lives?

  2. 2

    In what ways does the author's meticulous methodology for processing 37 states worth of data challenge the reader to think about the invisible foundations that support broader ecosystems?

  3. 3

    If you were to apply a "species distribution model" to your own life or career path, what would serve as your foundational "soil data" or unyielding environmental variables?

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