Does climate play a more important role than competition in modeling height to crown base of Larix principis-rupprechtii in northern China?

竞赛(生物学) 牙冠(牙科) 中国 基础(拓扑) 生态学 植物 环境科学 地理 生物 数学 医学 牙科 数学分析 考古
作者
Jingning Shi,Xianzhao Liu,Wei Xiang
出处
期刊:Forest Ecology and Management [Elsevier BV]
卷期号:526: 120564-120564 被引量:1
标识
DOI:10.1016/j.foreco.2022.120564
摘要

• A climate-sensitive mixed-effects height to crown base (HCB) model was developed. • The logistic model form showed the best prediction performance and biological reasonability. • The relative contribution of climate was larger than inter-tree competition at a large spatial scale. • Compared to current-year precipitation, variables reflecting average precipitation of the recent five years performed better in modeling HCB. Competition is the major factor influencing crown recession rates and therefore plays an important role in height to crown base (HCB) modeling. However, few studies have directly investigated the effects of climate on HCB modeling. In this study, a climate-sensitive individual tree HCB model was developed using measurements from a total of 9902 Rupprecht larch ( Larix principis-rupprechtii Mayr) trees on 156 sample plots located in northern China. The impacts of tree height, inter-tree competition, site condition, and climate on HCB modeling were assessed using the mixed-effects modeling approach. Results showed that HCB increased with tree height and competition intensity. The inclusion of climate variables significantly improved model performance. HCB was negatively associated with mean temperature of the coldest month and positively associated with autumn precipitation averaged over the previous five years. According to hierarchical partitioning analysis, tree height is the most important factor affecting HCB (relative contribution 50.03%), followed by climate (22.51%), inter-tree competition (20.17%), and site condition (6.06%). Our findings highlighted the importance of considering regional climate differences in improving HCB predictions at a large spatial scale. Disentangling different sources of variations in HCB will help advance our understanding of the factors driving crown recession and reduce uncertainty in predicting crown characteristics under changing climates.
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