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Aging mistakes and overestimation of productivity for black spruce forests

Aging mistakes and overestimation of productivity for black spruce forests
黑云杉林的老化错误和生产力高估
批准号:
445212-2012
负责人:
DesRochers, Annie
金额:
$1.95万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
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英文摘要
Characterization of forest dynamics, forest management planning and yield tables are all based on age-productivity relationships (site quality indices). However, it was previously shown that age of black spruce (Picea mariana) obtained by a ring count at ground level (commonly referred to as «the root collar») does not give the real age of trees, because of the development of adventitious roots along the base of the stem. At maturity, the root system of black spruce trees is exclusively adventitious, which means that the initial roots do not develop and disappear with time. The development of roots along the stem somewhat «hides» the true age of trees, by concealing growth rings and the root collar into the stump wood and under the roots. Since the characterization of forest dynamics and estimations of productivity mainly lie on the age of trees, when ages are wrong, those estimates are also wrong and can lead to bad decisions by managers. For example, a forest stand could be much older than it appears from a ring count at ground level, which automatically leads to productivity overestimations and erroneous management decisions. The main goal of this research project is to estimate aging mistakes of black spruce growing in different conditions, to use these estimates to quantify productivity overestimations and to develop a correction tool for yield tables and site indices. By locating the germination date (true age) concealed inside black spruce stumps, we will calculate precise age underestimations and associated productivity overestimations. On a fundamental level, we expect to determine conditions favourable to the development of adventitious roots, and hence site conditions that increase age underestimations. On an applied level, the quantification of productivity overestimations associated to aging errors will give managers better data on which to base their planning decisions.
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