PinnoPareGuindonEtAl2009

Reference

Pinno, B.D., Pare, D., Guindon, L., Belanger, N. (2009) Predicting productivity of trembling aspen in the Boreal Shield ecozone of Quebec using different sources of soil and site information. Forest Ecology and Management, 257(3):782-789. (Scopus )

Abstract

Site quality index (SQI) of trembling aspen (Populus tremuloides Michx) in the Boreal Shield of Quebec was predicted using two sources of information: (1) mappable permanent site variables derived from permanent sampling plots and other sources and (2) measured soil and site properties including both biological and permanent site variables. General mappable information did not produce reasonable relationships (R<sup>2</sup> < 0.25) with SQI while measured variables were able to explain much of trembling aspen SQI variability. For the two parent material types found in our study, i.e. fluvial and till, there was no difference between median SQI values between groups. However, different soil and site variables were better at predicting trembling aspen productivity for the individual parent material types. As much as 60% of the variability in trembling aspen productivity was explained when both biological and permanent site variables were considered in stepwise regression models. When treated individually, models developed for fluvial sites better explained trembling aspen productivity compared to models developed for till sites. Moreover, the ability of the model to predict trembling aspen productivity on till sites when using permanent site variables alone, e.g. soil texture, elemental chemistry and elevation was decreased (R<sup>2</sup> < 0.3). This indicates that the inclusion of biological site variables such as overstory species composition and forest floor properties provide a major contribution to SQI prediction and are necessary to yield high R<sup>2</sup>. Overall, the data indicate that the traditional mapping of landscape attributes such as drainage and deposit as well as inferred soil geochemistry do not contribute much to explaining SQI. At present, field measurements are needed to predict SQI with a reasonable degree of precision within a forest management unit. © 2008 Elsevier B.V. All rights reserved.

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@ARTICLE { PinnoPareGuindonEtAl2009,
    AUTHOR = { Pinno, B.D. and Pare, D. and Guindon, L. and Belanger, N. },
    TITLE = { Predicting productivity of trembling aspen in the Boreal Shield ecozone of Quebec using different sources of soil and site information },
    JOURNAL = { Forest Ecology and Management },
    YEAR = { 2009 },
    VOLUME = { 257 },
    PAGES = { 782-789 },
    NUMBER = { 3 },
    ABSTRACT = { Site quality index (SQI) of trembling aspen (Populus tremuloides Michx) in the Boreal Shield of Quebec was predicted using two sources of information: (1) mappable permanent site variables derived from permanent sampling plots and other sources and (2) measured soil and site properties including both biological and permanent site variables. General mappable information did not produce reasonable relationships (R<sup>2</sup> < 0.25) with SQI while measured variables were able to explain much of trembling aspen SQI variability. For the two parent material types found in our study, i.e. fluvial and till, there was no difference between median SQI values between groups. However, different soil and site variables were better at predicting trembling aspen productivity for the individual parent material types. As much as 60% of the variability in trembling aspen productivity was explained when both biological and permanent site variables were considered in stepwise regression models. When treated individually, models developed for fluvial sites better explained trembling aspen productivity compared to models developed for till sites. Moreover, the ability of the model to predict trembling aspen productivity on till sites when using permanent site variables alone, e.g. soil texture, elemental chemistry and elevation was decreased (R<sup>2</sup> < 0.3). This indicates that the inclusion of biological site variables such as overstory species composition and forest floor properties provide a major contribution to SQI prediction and are necessary to yield high R<sup>2</sup>. Overall, the data indicate that the traditional mapping of landscape attributes such as drainage and deposit as well as inferred soil geochemistry do not contribute much to explaining SQI. At present, field measurements are needed to predict SQI with a reasonable degree of precision within a forest management unit. © 2008 Elsevier B.V. All rights reserved. },
    COMMENT = { Export Date: 10 February 2010 Source: Scopus CODEN: FECMD doi: 10.1016/j.foreco.2008.09.058 },
    ISSN = { 03781127 (ISSN) },
    KEYWORDS = { Populus tremuloides, Site quality, Soil properties, Stand composition, Forecasting, Forestry, Productivity, Regression analysis, Soils, Degree of precisions, Field measurements, Forest floors, Forest management units, Landscape attributes, Parent materials, Populus tremuloides, Site informations, Site quality, Soil geochemistries, Soil properties, Soil textures, Species compositions, Stand composition, Stepwise regressions, Trembling aspens, Two sources, Geologic models, deciduous forest, forest management, geochemistry, overstory, parent material, soil chemistry, soil property, Drainage, Forecasts, Forest Management, Forestry, Geochemistry, Geology, Measurement, Models, Populus, Populus Tremuloides, Productivity, Regression Analysis, Soil, Boreal Shield, Canada, North America, Populus tremuloides },
    OWNER = { Luc },
    TIMESTAMP = { 2010.02.10 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-58149289696&partnerID=40&md5=77f682d3a5f93e0317cdc73aa63e94b0 },
}

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