Skip to main content

A Mixed-Effects Heterogeneous Negative Binomial Model for Postfire Conifer Regeneration in Northeastern California, USA

Buy Article:

$21.50 plus tax (Refund Policy)

Many western USA fire regimes are typified by mixed-severity fire, which compounds the variability inherent to natural regeneration densities in associated forests. Tree regeneration data are often discrete and nonnegative; accordingly, we fit a series of Poisson and negative binomial variation models to conifer seedling counts across four distinct burn severities and three forest types 10 years after the 23,000-ha Storrie Fire, a large mixed-severity fire in northern California. Despite the accessibility and power of the zero-inflated negative binomial mixture model, a flexible heterogeneous negative binomial model offered a superior fit. Incorporation of a random stand effect further improved model performance. A parametric bootstrap analysis was conducted to examine seedling distributions and stand stocking. Mean simulated seedling densities had an expansive range (272‐29,257 ha−1). Stocking analyses suggest a high probability of deficient conifer coverage in the majority of lower-elevation high-severity burn stands. In addition, models were fit to fir and pine seedling counts. Only a minority of postfire stands were likely to be stocked in the pine-only analysis. These models will help land managers prioritize limited resources for artificial reforestation in mixed-severity burned landscapes.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Keywords: Storrie Fire; burn severity; natural regeneration; ponderosa pine; stocking analysis; white fir; zero-inflated negative binomial

Document Type: Research Article

Publication date: 2014-04-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more