红松间距试验中早期选择茎量的效率和选择大小分布的预测

IF 1.5 4区 农林科学 Q2 FORESTRY
Steen Magnussen
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引用次数: 0

摘要

在 10 到 34 岁之间的红松间距试验中,对 34 岁时的优良茎量进行了模拟表型选择。随着选择年龄的增长和初始间距的减小,选择效率呈指数增长。间距、年龄和选择强度之间的相互作用改变了早期选择的总体效率。当初始间距小于 2.1 米时,一棵树在 2 年或 4 年期间保持在特定相对大小等级的概率随着年龄的增长而增加。在马尔可夫链(过渡概率矩阵)的帮助下,根据最多 4 年的生长信息,对 10 树龄时因优越树形而被选中的树木的未来大小等级分布进行了真实预测。以年龄、间距和选择强度(%-select)为自变量的二次响应面可以估算出早期选择的 34 树龄标准化平均值,误差不超过 2%。就育种而言,10龄期的选育结果似乎比晚期选育结果更具吸引力。根据这些马尔可夫链对 10 到 34 岁茎秆体积相关性的预测,对种植间距为 3.0 米或更近的种植园产生了现实的结果。For.科学》37(2):593-612。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficiency of Early Selections for Stem Volume and Predictions of Size Distributions of Selections in a Red Pine Spacing Trial
Simulated phenotypic selections for superior stem volume at age 34 were carried out in a red pine spacing trial between age 10 and age 34. The efficiency of selections increased exponentially with selection age and with diminishing initial spacing. Interactions between spacing, age, and the intensity of selection modified the overall efficiency of early selections. The probability that a tree would remain in a given relative size class during a 2-or 4-year-period increased with age when the initial spacing was less than 2.1 m. Wider spacings induced a decline in these probabilities. Realistic predictions of future size class distributions of trees selected for superior size at age 10 were generated from a maximum of 4 years growth information with the help of Markov chains (transition probability matrices). Age 34 standardized means of early selections could be estimated within 2% from a quadratic response surface with age, spacing, and selection intensity (%-select) as independent variables. For breeding purposes, selections at age 10 appeared more attractive than later selections. Predictions of age 10 to age 34 years correlations of stem volume based on these Markov chains produced realistic results for plantations planted at a 3.0 m square spacing and closer. For. Sci. 37(2):593-612.
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来源期刊
Forest Science
Forest Science 农林科学-林学
CiteScore
2.80
自引率
7.10%
发文量
45
审稿时长
3 months
期刊介绍: 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.
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