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Short Paper: A signal-to-noise index to quantify the potential for peak detection in sediment–charcoal records

Published online by Cambridge University Press:  20 January 2017

Ryan F. Kelly ,
Philip E. Higuera ,
Carolyn M. Barrett  and
Feng Sheng Hu
Ryan F. Kelly*
Affiliation:
Department of Plant Biology, University of Illinois, Urbana, IL, USA
Philip E. Higuera
Affiliation:
Department of Forest Ecology and Biogeosciences, University of Idaho, Moscow, ID, USA
Carolyn M. Barrett
Affiliation:
Program in Ecology, Evolution, and Conservation Biology, University of Illinois, Urbana, IL, USA
Feng Sheng Hu
Affiliation:
Department of Plant Biology, University of Illinois, Urbana, IL, USA Program in Ecology, Evolution, and Conservation Biology, University of Illinois, Urbana, IL, USA
*
⁎Corresponding author.
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Abstract

Charcoal peaks in lake-sediment records are commonly used to reconstruct fire histories spanning thousands of years, but quantitative methods for evaluating the suitability of records for peak detection are largely lacking. We present a signal-to-noise index (SNI) that quantifies the separation of charcoal peaks (signal) from other variability in a record (noise). We validate the SNI with simulated and empirical charcoal records and show that an SNI > 3 consistently identifies records appropriate for peak detection. The SNI thus offers a means to evaluate the suitability of sediment–charcoal records for reconstructing local fires. MATLAB and R functions for calculating SNI are provided.

Keywords

Signal-to-noise index (SNI)Charcoal analysisFire historyLake sedimentPaleoecology
Type
Research Article
Information
Quaternary Research , Volume 75 , Issue 1 , January 2011 , pp. 11 - 17
Copyright
University of Washington

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