Quantifying Uncertainty in Net Primary Production Measurements

Mark E. Harmon, Donald L. Phillips, John J. Battles, Andrew Rassweiler, Robert O. Hall, William K. Lauenroth

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

28 Scopus citations


Because primary production usually is estimated from several variables that are themselves subject to error in measurement, these errors propagate as the variables are combined mathematically. Following a brief overview of the various sources of error and bias associated with primary production measurements, this chapter provides a detailed description of approaches for quantifying propagation of error in productivity calculations. Monte Carlo simulation approaches are described and the problem of compounding of errors are examined. Several explicit examples are provided to illustrate uncertainty quantification in a variety of biomes.

Original languageEnglish
Title of host publicationPrinciples and Standards for Measuring Primary Production
PublisherOxford University Press
ISBN (Electronic)9780199790128
ISBN (Print)9780195168662
StatePublished - Aug 1 2007


  • Bias
  • Compounding error
  • Error propagation
  • Measurement error
  • Monte carlo simulation

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