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Long-Term Thinning Effects on the Leaf Area of Pinus strobus L. as Estimated from Litterfall and Individual-Tree Allometric Models

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Canopy leaf area index (LAI) is important for predicting stand growth response to silviculture, but it is difficult to quantify because of high variability, time constraints, and limitations of nondestructive techniques. We used an uninterrupted 17-year record of litterfall in a 60-year-old Pinus strobus L. plantation in central Maine to quantify LAI in response to both B-line and low-density thinning and to evaluate individual-tree allometric leaf area prediction models fitted to data from 51 destructively sampled trees. Allometric model performance was inconsistent between the tree and stand levels; the most robust model at both scales predicted leaf area from sapwood basal area and crown length. The LAI of the control treatment declined gradually from 4.5 to 4, with interannual variability associated with disturbances to the canopy. Thinning reduced LAIs but not in proportion to the number of trees removed by thinning because LAIs were similar between the B-line and low-density treatments. At the tree level, differences between the treatments were substantial, with low-density tree leaf area increasing nearly fivefold over the study period, twice the response of comparable B-line trees. These results demonstrate the dynamic nature of leaf area, the difficulty in predicting it accurately, and the influence of silvicultural activities.
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Keywords: eastern white pine; nonlinear least squares; nonlinear mixed effects; weighted models

Document Type: Research Article

Publication date: 2012-02-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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