Productivity Index Grid (conterminous U.S.) GIS Data
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Author: Bradley Miller
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The Productivity Index (PI) maps the inherent, long-term capacity of soils across the lower 48 states to support plant growth. It is an ordinal scale from 0 (least productive) to 19 (most productive) derived from family-level Soil Taxonomy attributes rather than short-term management effects. PI uses interpretations of taxonomic features that are consistently associated with lower or higher natural productivity and expresses them as a gridded surface for landscape analysis.
Applied Relevance
PI provides a stable, data-light indicator of potential productivity for regional planning, policy analysis, forestry and rangeland assessments, and ecological modeling. Because it reflects soil formation and morphology rather than current fertilization or tillage, it is well suited for comparing capability across counties, watersheds, and ecoregions and for screening areas where management or conservation investments are likely to yield the greatest return.
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Data and method
Values originate from a Michigan State University–U.S. Forest Service framework. Base ranks are assigned by soil order using traits linked to fertility potential, then adjusted within suborders, great groups, and subgroups to reflect systematic differences implied by taxonomy. Family-level texture is used to modify the rank for coarse versus fine materials, and additional adjustments consider properties such as organic matter, cation-exchange capacity, and clay mineralogy. These ranks are joined to digital soil maps and rendered as a raster for spatial analysis. Because the scale is ordinal, differences should be interpreted as relative rather than absolute magnitudes.
Metadata – Sources – Limitations
PI represents inherent potential under natural conditions; it does not measure current yield, management level, irrigation, drainage, or recent land disturbance. Map-unit inclusions, taxonomic updates, and local variability can produce mismatches at fine scales. Use PI for screening and comparison, and confirm site-level expectations with field data.
Schaetzl, R.J., Krist, F.J. Jr., and Miller, B.A. 2012. A Taxonomically Based, Ordinal Estimate of Soil Productivity for Landscape-Scale Analyses. Soil Science 177:288–299.