Modeling browse impacts on sapling and tree recruitment across forests in the northern United States

Matthew B. Russell, James A. Westfall, Christopher W. Woodall

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Understanding the patterns of tree recruitment is essential to quantifying the future health and productivity of forest ecosystems. Using national forest inventory information, we incorporated browse impact measurements into models of sapling (2.5-12.7 cm diameter at breast height (DBH)) and overstory tree (≥12.7 cm DBH) ingrowth across the northern United States. Ingrowth was modeled with standard and zero-inflated techniques using discrete Poisson and negative binomial distributions. Zero-inflated models using stand attributes and browse impacts provided the best fit statistics for modeling the occurrence and frequency of ingrowth over a 5-year time period. Results indicate that stands with very high browse impact would contain 50.0% fewer ingrowth saplings compared with stands with no browse impact. Greater browse impacts similarly yielded a negative effect on overstory tree ingrowth, but to a lesser degree than saplings. Despite the stochastic nature of ingrowth observations, incorporating browse impacts may be essential in determining accurate levels of ingrowth in forests where herbivory constrains forest regeneration objectives.

Original languageEnglish (US)
Pages (from-to)1474-1481
Number of pages8
JournalCanadian Journal of Forest Research
Issue number11
StatePublished - 2017

Bibliographical note

Funding Information:
This work was supported by the U.S. Department of Agriculture Forest Service Northern Research Station and the Minnesota Agricultural Experiment Station. We thank Lance Vickers, Arun Bose, the Associate Editor, and anonymous reviewers for their comments that improved this manuscript.

Publisher Copyright:
© Her Majesty the Queen in right of Canada 2017.


  • Forest inventory and analysis
  • Herbivory
  • Ingrowth
  • Regeneration
  • White-tailed deer


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