Enhancing resiliency and restoring ecological attributes in second-growth ponderosa pine stands in Northern New Mexico, USA

Zachary Thomas, Kristen M. Waring

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

In the past 150 years, southwestern ponderosa pine forests have become less resilient with altered ecological traits, such as higher tree densities, greater crown fire hazard, and lower understory cover. Treatments consisting of density reductions and/or prescribed burning have been implemented with increasing frequency to counteract the effects of these changes. The objectives of this study were to investigate the effects of these treatments on resiliency and ecological attributes in second-growth ponderosa pine stands located on Vermejo Park Ranch, northern New Mexico. More specifically, this study examined how stand-level treatments affected overstory structure, diameter growth, growth maintenance during drought and growth recovery from drought, fire hazard, understory regeneration success and plant cover, and ungulate utilization. Treated stands had fewer trees of larger average size with significantly higher recent rates of growth and biomass accretion compared to untreated stands. These stands also had greater growth maintenance during drought and growth recovery from drought in overstory trees, increased establishment of ponderosa pine regeneration, and lower fire hazard. Treated stands had more herbaceous understory productivity and were being used more by deer and elk. Our results illustrate how thinning and prescribed burning treatments can be used to meet a variety of ecological management objectives, while shifting stand structure to a more resilient state.

Original languageEnglish (US)
Pages (from-to)93-104
Number of pages12
JournalForest Science
Volume61
Issue number1
DOIs
StatePublished - 2015

Keywords

  • Drought
  • Fire
  • Pinus ponderosa
  • Resiliency
  • Restoration
  • Understory production

ASJC Scopus subject areas

  • Forestry
  • Ecology
  • Ecological Modeling

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