中国冷杉种植园的林分和林木生长建模

IF 1.7 3区 农林科学 Q2 FORESTRY Canadian Journal of Forest Research Pub Date : 2024-05-03 DOI:10.1139/cjfr-2023-0195
Hanyue Chen, Quang V. Cao, Yihang Jiang, Yuxin Hu, Jianguo Zhang, Xiongqing Zhang
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引用次数: 0

摘要

生长和产量系统是加强森林管理决策的重要工具。本研究系统地评估了三个林分级模型和两种数据类型,用于预测中国南方冷杉人工林的林分存活率和基部面积。第一个模型通过自伐概念将成活率和直径联系起来。第二个模型结合了林分直径、前一年的直径和林分存活率,而第三个模型仅将林分存活率和直径视为林分年龄的相互独立函数。模型 2 在短期预测(2-4 年)中表现最佳,而模型 3 则在较长预测期(6-10 年)中表现出色。尽管模型 3 对林木存活率和直径的预测是独立的,但它在长期预测中密切跟踪了观察到的自稀疏轨迹。由模型 2 和模型 3 得出的树木生长模型分别在短期和长期树木生长预测中表现最佳。虽然这项研究仅限于四个实验点,但它为杉木人工林的生长和产量建模奠定了理论基础。
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Modeling stand- and tree-level growth of Chinese fir plantations
Growth and yield systems are essential tools for enhancing forest management decision-making. This study systematically evaluated three stand-level models and two data types for predicting stand survival and basal area of Chinese fir ( Cunning lanceolate (Lamb.) Hook.) plantations in southern China. The first model links survival and diameter through the self-thinning concept. The second model incorporates stand diameter, the previous year’s diameter, and stand survival, while the third model treats stand survival and diameter as mutually independent functions of only stand age. Model 2 was the best performer for short-term prediction (2–4 years), whereas Model 3 excelled in longer projection periods (6–10 years). Despite the independent predictions of stand survival and diameter in Model 3, it closely tracked observed self-thinning trajectories in long-term predictions. Tree-level model growth derived from Models 2 and 3 performed optimally for short-term and long-term tree-level predictions, respectively. While limited to four experimental sites, this research contributes theoretical groundwork to growth and yield modeling for Chinese fir plantations.
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来源期刊
CiteScore
4.20
自引率
9.10%
发文量
109
审稿时长
3 months
期刊介绍: Published since 1971, the Canadian Journal of Forest Research is a monthly journal that features articles, reviews, notes and concept papers on a broad spectrum of forest sciences, including biometrics, conservation, disturbances, ecology, economics, entomology, genetics, hydrology, management, nutrient cycling, pathology, physiology, remote sensing, silviculture, social sciences, soils, stand dynamics, and wood science, all in relation to the understanding or management of ecosystem services. It also publishes special issues dedicated to a topic of current interest.
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