An individual-based growth and competition model for coastal redwood forest restoration
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Abstract
Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | An individual-based growth and competition model for coastal redwood forest restoration |
Series title | Canadian Journal of Forest Research |
DOI | 10.1139/cjfr-2014-0143 |
Volume | 44 |
Issue | 9 |
Year Published | 2014 |
Language | English |
Publisher | NRC Research Press |
Contributing office(s) | Western Ecological Research Center |
Description | 7 p. |
First page | 1051 |
Last page | 1057 |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |