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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Implications of allometric model selection for county-level biomass mapping.

Laura Duncanson1,2, Wenli Huang3, Kristofer Johnson4

  • 1Biosciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, USA. laura.i.duncanson@nasa.gov.

Carbon Balance and Management
|October 20, 2017
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Summary

Choosing the right forest allometric model significantly impacts biomass mapping accuracy. Differences of up to 20% were observed between models, highlighting the need for better understanding of allometric model errors in forest carbon accounting.

Keywords:
AllometryCarbon accountingForest biomassLidar

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Area of Science:

  • Forestry
  • Ecology
  • Remote Sensing

Background:

  • Forest aboveground biomass (AGB) estimation is crucial for global carbon cycle understanding and forest management.
  • Current AGB mapping accuracy is limited by uncertainties in field-based allometric models.
  • Allometric models often have unknown uncertainties beyond their development scope.

Purpose of the Study:

  • To evaluate the impact of selecting different allometric models on county-level AGB mapping.
  • To compare the performance of three popular allometric models: Jenkins et al., Chojnacky et al., and the Component Ratio Method (CRM).

Main Methods:

  • Tested three allometric models (Jenkins et al., Chojnacky et al., CRM) for field biomass estimation.
  • Applied these models for county-level biomass mapping in Sonoma County, California.
  • Analyzed discrepancies in biomass estimates based on forest characteristics like height and canopy cover.

Main Results:

  • Jenkins and Chojnacky models showed comparable results, but differed by ~20% from CRM estimates.
  • Discrepancies were larger in areas with high biomass, high canopy cover, and moderate heights (25-45m).
  • CRM models estimated higher biomass in the tallest forests (>60m), while Jenkins models estimated higher biomass in shorter forests (<50m).

Conclusions:

  • Allometric model selection significantly influences AGB map accuracy and estimates.
  • Allometric model errors are not well understood and are not solely driven by forest height.
  • Improved understanding of allometric model errors, especially in high biomass forests, is vital for accurate AGB mapping.