ZhangPengDang2004

Référence

Zhang, L., Peng, C., Dang, Q. (2004) Individual-tree basal area growth models for jack pine and black spruce in northern Ontario. Forestry Chronicle, 80(3):366-374. (Scopus )

Résumé

Individual-tree models of five-year basal area growth were developed for jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) in northern Ontario. Tree growth data were collected from long-term permanent plots of pure and mixed stands of the two species. The models were fitted using mixed model methods due to correlated remeasurements of tree growth over time. Since the data covered a wide range of stand ages, stand conditions and tree sizes, serious heterogeneous variances existed in the data. Therefore, the coefficients of the final models were obtained using weighted regression techniques. The models for the two species were evaluated across 4-cm diameter classes using independent data. The results indicated (1) the models of jack pine and black spruce produced similar prediction errors and biases for intermediate-sized trees (12-28 cm in tree diameter), (2) both models yielded relatively large errors and biases for larger trees (> 28 cm) than those for smaller trees, and (3) the jack pine model produced much larger errors and biases for small-sized trees (< 12 cm) than did the black spruce model.

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@ARTICLE { ZhangPengDang2004,
    AUTHOR = { Zhang, L. and Peng, C. and Dang, Q. },
    TITLE = { Individual-tree basal area growth models for jack pine and black spruce in northern Ontario },
    JOURNAL = { Forestry Chronicle },
    YEAR = { 2004 },
    VOLUME = { 80 },
    PAGES = { 366-374 },
    NUMBER = { 3 },
    ABSTRACT = { Individual-tree models of five-year basal area growth were developed for jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) in northern Ontario. Tree growth data were collected from long-term permanent plots of pure and mixed stands of the two species. The models were fitted using mixed model methods due to correlated remeasurements of tree growth over time. Since the data covered a wide range of stand ages, stand conditions and tree sizes, serious heterogeneous variances existed in the data. Therefore, the coefficients of the final models were obtained using weighted regression techniques. The models for the two species were evaluated across 4-cm diameter classes using independent data. The results indicated (1) the models of jack pine and black spruce produced similar prediction errors and biases for intermediate-sized trees (12-28 cm in tree diameter), (2) both models yielded relatively large errors and biases for larger trees (> 28 cm) than those for smaller trees, and (3) the jack pine model produced much larger errors and biases for small-sized trees (< 12 cm) than did the black spruce model. },
    COMMENT = { Cited By (since 1996): 11 Export Date: 14 May 2012 Source: Scopus CODEN: FRCRA },
    ISSN = { 00157546 (ISSN) },
    KEYWORDS = { Mixed models, Model validation, Repeated measures, Error analysis, Mathematical models, Regression analysis, Tree growth, Forestry, coniferous forest, error analysis, growth modeling, model validation, Canada, North America, Ontario, lamb, Paragnetina, Picea, Picea mariana, Pinus banksiana },
    OWNER = { Luc },
    TIMESTAMP = { 2012.05.14 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-3242776377&partnerID=40&md5=10c52185064d8cffe60f4ffc4d5e2cbc },
}

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