Document


Title

Peak detection in sediment-charcoal records: impacts of alternative data analysis methods on fire-history interpretations
Document Type: Journal Article
Author(s): Philip E. Higuera; Daniel G. Gavin; Patrick J. Bartlein; Douglas J. Hallett
Publication Year: 2010

Cataloging Information

Keyword(s):
  • bias
  • British Columbia
  • Canada
  • charcoal
  • charcoal analysis
  • data analysis
  • decomposition
  • fire management
  • forest management
  • fuel accumulation
  • paleoecology
  • sediment
  • sedimentation
  • sensitivity
  • size classes
  • statistical analysis
Record Maintained By:
Record Last Modified: October 14, 2019
FRAMES Record Number: 49418
Tall Timbers Record Number: 25799
TTRS Location Status: In-file
TTRS Call Number: Journals - I
TTRS Abstract Status: Fair use, Okay, Reproduced by permission

This bibliographic record was either created or modified by the Tall Timbers Research Station and Land Conservancy and is provided without charge to promote research and education in Fire Ecology. The E.V. Komarek Fire Ecology Database is the intellectual property of the Tall Timbers Research Station and Land Conservancy.

Description

Over the past several decades, high-resolution sediment-charcoal records have been increasingly used to reconstruct local fire history. Data analysis methods usually involve a decomposition that detrends a charcoal series and then applies a threshold value to isolate individual peaks, which are interpreted as fire episodes. Despite the proliferation of these studies, methods have evolved largely in the absence of a thorough statistical framework. We describe eight alternative decomposition models (four detrending methods used with two threshold-determination methods) and evaluate their sensitivity to a set of known parameters integrated into simulated charcoal records. Results indicate that the combination of a globally defined threshold with specific detrending methods can produce strongly biased results, depending on whether or not variance in a charcoal record is stationary through time. These biases are largely eliminated by using a locally defined threshold, which adapts to changes in variability throughout a charcoal record. Applying the alternative decomposition methods on three previously published charcoal records largely supports our conclusions from simulated records. We also present a minimum-count test for empirical records, which reduces the likelihood of false positives when charcoal counts are low. We conclude by discussing how to evaluate when peak detection methods are warranted with a given sediment-charcoal record.

Online Link(s):
Citation:
Higuera, Philip E.; Gavin, Daniel G.; Bartlein, Patrick J.; Hallett, Douglas J. 2010. Peak detection in sediment-charcoal records: impacts of alternative data analysis methods on fire-history interpretations. International Journal of Wildland Fire 19(8):996-1014.