Department of Soil and Water Conservation and Desertification Combating, College of Environmental Science and Engineering, Liaoning Technical University, Fuxin, Liaoning, People's Republic of China.
Liaoning Institute of Sandy Land Control and Utilization, Fuxin, Liaoning, People's Republic of China.
PLoS One. 2019 Mar 11;14(3):e0213509. doi: 10.1371/journal.pone.0213509. eCollection 2019.
Tree height growth is sensitive to climate change; therefore, incorporating climate factors into tree height prediction models can improve our understanding of this relationship and provide a scientific basis for plantation management under climate change conditions. Mongolian pine (Pinus sylvestris var. mongolica) is one of the most important afforestation species in Three-North Regions in China. Yet our knowledge on the relationship between height growth and climate for Mongolian pine is limited. Based on survey data for the dominant height of Mongolian pine and climate data from meteorological station, a mixed-effects Chapman-Richards model (including climate factors and random parameters) was used to study the effects of climate factors on the height growth of Mongolian pine in Zhanggutai sandy land, Northeast China. The results showed that precipitation had a delayed effect on the tree height growth. Generally, tree heights increased with increasing mean temperature in May and precipitation from October to April and decreased with increasing precipitation in the previous growing season. The model could effectively predict the dominant height growth of Mongolian pine under varying climate, which could help in further understanding the relationship between climate and height growth of Mongolian pine in semiarid areas of China.
树木的高度生长对气候变化很敏感；因此，将气候因素纳入树木高度预测模型可以帮助我们更好地理解这种关系，并为气候变化条件下的造林管理提供科学依据。樟子松（Pinus sylvestris var. mongolica）是中国三北地区最重要的造林树种之一。然而，我们对樟子松高度生长与气候之间的关系的了解有限。本研究基于樟子松优势高的调查数据和气象站的气候数据，利用包含气候因子和随机参数的混合效应 Chapman-Richards 模型，研究了气候因子对中国东北章古台沙地樟子松高度生长的影响。结果表明，降水对树木高度生长有滞后效应。一般来说，树木的高度随着 5 月份平均温度和 10 月至 4 月降水的增加而增加，随着上一季降水的增加而减少。该模型可以有效地预测不同气候条件下樟子松的优势高度生长，有助于进一步了解中国半干旱地区樟子松的气候与高度生长之间的关系。
