在环境和竞争的联合影响下,区域相容的个体树木生长模型
Wenjie Zhang1,2,3, Baoguo Wu1,4, Yi Ren5
1School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China.
Plants (Basel, Switzerland)
|July 29, 2023
概括
竞争和环境因素对中国树的生长有很大影响 (直径与乳房高度和高度). 随机森林模型在预测树木生长方面表现出卓越的准确性,为森林管理提供了宝贵的见解.
科学领域:
- 林业科学 林业科学
- 生态建模 生态建模
- 量化林业 量化林业是什么
背景情况:
- 了解影响树木生长的因素对于可持续森林管理至关重要.
- 中国 (Cunninghamia lanceolata) 是中国重要的木材物种,需要准确的生长预测模型.
研究的目的:
- 开发和比较中国树的单个树木生长模型,结合竞争,地点和气候变量.
- 确定影响树直径至胸高 (DBH) 和高度 (H) 的最有影响力的环境和竞争因素.
主要方法:
- 利用来自福建省 (1993-2018) 的连续森林库存 (CFI) 数据.
- 使用重新参数化 (RP),BP神经网络 (BP) 和随机森林 (RF) 方法构建了DBH和H模型.
- 对比了不同建模方法的预测准确度.
主要成果:
- 竞争和环境因素显著提高了模型预测的准确性.
- 斜坡位置 (PW),高度 (HB) 和斜坡方面 (PX) 是关键的地点因素;超过18°C的度日 (DD18),平均年降水 (MAP) 和哈格里夫斯参考蒸发 (Eref) 是关键的气候因素.
- 随机森林 (RF) 模型表现最好,DBH的R2值为0.849,H的R2值为0.845.
结论:
- 开发的基于射频的模型对环境敏感,在统计学上可靠,并且有效地预测了中国树的增长.
- 结果为明智的管理决策和混合不均年龄森林的收获预测提供了理论基础.
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