Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

Phillip J. van Mantgem, Dylan W. Schwilk

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

Original languageEnglish
Pages (from-to)116-125
Number of pages10
JournalFire Ecology
Issue number2
StatePublished - 2009


  • Forest restoration
  • Prescribed fire
  • Pseudoreplication
  • Sierra Nevada
  • Statistics


Dive into the research topics of 'Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest'. Together they form a unique fingerprint.

Cite this