A Direct Measure of Stand Density Based on Stand Growth

Author:

Dean Thomas J1ORCID,D’Amato Anthony W2ORCID,Palik Brian J3ORCID,Battaglia Mike A4,Harrington Constance A5ORCID

Affiliation:

1. School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA

2. Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT

3. USDA Forest Service, Northern Research Station, Grand Rapids, MN

4. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO

5. USDA Pacific Northwest Research Station, Olympia, WA

Abstract

Abstract Standardizing gross volume increment on periodic height increment of the dominant trees is a means of minimizing the effects of site quality and age in growth–growing-stock relations; however, volume increment per height increment contains more information than just a normalization method for fitting growth models. This study builds on previous work suggesting that the cumulative sum of the ratios between individual-tree volume increment and height increment may be a direct measure of stand density. We used data from several levels of growing-stock studies for Douglas-fir, ponderosa pine, and red pine to explore this hypothesis. Regression analysis indicated that the sum of the ratios is proportional to(Dqx⋅N), the underlying equation form of Reineke’s stand density index. Stem growth is a function of canopy dynamics, and additional analyses showed that volume added per unit of height growth was also related to canopy architecture, increasing with decreasing live-crown ratio and increasing foliage density. The linkages between growth, canopy architecture, intermediary canopy dynamics, and (Dqx⋅N) support the hypothesis that the sum of the tree ratios between volume increment and height increment is a direct measure of site occupancy due to its association between growth and corresponding resource use.

Funder

Louisiana Agricultural Experiment Station

Publisher

Oxford University Press (OUP)

Subject

Ecological Modeling,Ecology,Forestry

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