环境和冠层结构对华北落叶松林树干液流的影响

准确量化环境和冠层结构变化对树干液流的影响,对于深入理解变化环境下的树木水分利用机制具有重要意义。在六盘山香水河小流域于2019年6—9月利用热扩散式探针监测了华北落叶松林的树干液流,同步观测林外气象、林内根系层土壤含水量和冠层结构动态,分析树干液流速率与潜在蒸散(PET)、土壤相对可利用水分(REW)和林冠层叶面积指数(LAI)的关系,并量化各因素对树干液流速率的相对贡献。结果表明: 树干液流速率对PET的响应符合二项式函数,对LAI的响应符合线性增长函数,对REW的响应符合趋于饱和的指数增长函数。将树干液流速率与PET、REW和LAI的单因子响应关系以连乘形式耦合得到多因素影响的树干液流模型,具有较好的模拟精度。基于该模型得到,PET是导致不同天气下树干液流速率差异的主导因素,其平均贡献率在晴天(40.3%)、多云(4.3%)和雨天(-26.3%)下有较大不同;PET和LAI是影响树干液流速率月份变化的主导因素,其在各月贡献率范围分别为-23.1%~16.8%和-12.3%~11.0%。本研究构建的多因素影响的树干液流模型可用于评估和预测树干液流速率,亦可用于量化各主导因素影响,将有潜力成为分析变化环境下树木水分利用的有效工具。

Effects of environment and canopy structure on stem sap flow in a Larix principis-rupprechtii plantation.

Accurately quantifying the impacts of environmental factors and canopy structure on stem sap flow is of great significance for deeply understanding water use strategies of trees in changing environment. The stem sap flow of Larix principis-rupprechtii plantation was observed using thermal diffusion probes from June to September of 2019 in the Xiangshuihe small watershed of Liupan Mountains, with the meteorological conditions, root-zone soil water content and canopy structure being simultaneously recorded. We first analyzed the relationships of sap flow rate (J_c) to potential evapotranspiration (PET), relative extract water (REW) and canopy leaf area index (LAI), and then quantified their relative contribution to J_c. The results showed that the response of J_c to PET, LAI, and REW conformed to binomial, linearly increase and saturated exponential function, respectively. The J_c model coupling multiple factors was established as a continuous multiplication of the response functions of J_c to PET, REW and LAI, which had good simulation precision. PET was the main factor leading to the difference of J_c in different weather conditions. The average contribution rate of PET had obvious difference in sunny (with a contribution rate of 40.3%), cloudy (4.3%), and rainy days (-26.3%). PET and LAI were the leading factors affecting the J_c variation among months. The ranges of the contribution rates of PET and LAI were from -23.1% to 16.8% and from -12.3% to 11.0%, respectively. The J_c model coupling the multi-factor effect developed in this study could be used to predict J_c, and quantify the impacts of each leading factor, which had the potential to be an effective tool to analyze the water use of trees in the changing environment.