Abstract
We tested the effectiveness of ponderosa pine forest restoration by comparing forest restoration treatments to untreated forest and to reconstructed forest structure in 1870 (date of Euro-American settlement) using an experimental block design at the Grand Canyon-Parashant National Monument in northwestern Arizona. Forest tree density averaged more than 20 times the historical tree density, and basal area was 4 to 6 times higher in contemporary forests than in historical forests. Restoration treatments consisted of thinning young trees to emulate the forest density, tree composition, and spatial distribution in 1870, followed by prescribed burning. Following restoration treatment, tree density was significantly reduced but remained 6 times higher than historical forests. Basal area in restored forests was still 2.5 times greater than reconstructed basal area values. Ponderosa pine dominance changed little from pretreatment data across the four blocks, averaging 60% of stems and 87% of the basal area prior to treatment and 56% of stems and 85% of the basal area following treatment. Ninety-eight percent of contemporary forest trees were less than 100 yr old prior to restoration treatment; this proportion was reduced to 82% following treatment. Restoration treatment also significantly reduced canopy cover and increased total tree regeneration. However, treatment effects on forest fuels were highly variable. Litter and duff fuel layers were significantly reduced by prescribed fire but woody debris increased. Overall forest structural diversity following treatment implies that fire behavior, wildlife habitats, and other ecological attributes will vary relatively widely in the future landscape.
Original language | English (US) |
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Pages (from-to) | 885-900 |
Number of pages | 16 |
Journal | Forest Science |
Volume | 49 |
Issue number | 6 |
State | Published - Dec 2003 |
Keywords
- Canopy cover
- Fuels
- Pinus ponderosa
- Presettlement
- Reference conditions
- Regeneration
ASJC Scopus subject areas
- Forestry
- Ecology
- Ecological Modeling