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广西桂林植物园尾巨桉树干液流径向变化数据集（2021）
The data set of radical variation of sap flow density of Eucalyptus urophylla × Eucalyptus Grandis in Guilin Botanical Garden, Guangxi 2021
秦佳双，倪隆康(广西壮族自治区中国科学院广西植物研究所)
发布时间：2023/11/15 15:46:37
摘要
树干液流密度的径向变化是准确估算树木整树水分利用的前提，忽略这种径向变化将导致树木水分消耗估算的较大误差。基于热扩散探针技术，我们于2021年生长季在桂林植物园对11龄尾巨桉0～2cm、2～4cm、4～6cm深度树干液流密度进行了1个月的连续监测。发现尾巨桉液流密度径向分布格局为递减型， 日变化格局均为单峰型。 中等径级尾巨桉液流密度具有明显的径向变化特征，如不考虑这种径向变化将会导致中等径级桉树整树蒸腾估算的较大误差。该数据集可为分析桉树液流密度径向变化、比较不同树种的液流密度径向变化格局差异提供基础数据支撑。
The radial variation of sap flow density is a prerequisite for accurate estimation of whole tree water use and ignoring this radial variation will lead to considerable error in estimation of tree water consumption. Based on the thermal diffusion probe method, the sap flow density of 11-aged Eucalyptus urophylla × Eucalyptus Grandis was continuously monitored at the sapwood depth of 0 ~ 2cm, 2 ~ 4cm and 4 ~ 6cm in Guilin Botanical Garden for 32 days during the growing season in 2021. The results showed that the diurnal variation of sap flow density in each sapwood depth showed a single-peak pattern, and the sap flow density decreased with the increase of sapwood depth. The apparent radial variation of sap flow density appeared in Eucalyptus urophylla × Eucalyptus Grandis with middle-class diameter, and it will lead to a large error in estimating whole-tree transpiration if not considering this radial variation. The data set can provide basic data support for analyzing the radial variation of sap flow density of eucalyptus and comparing the difference in the radial variation pattern of sap flow density among various tree species.
关键词
桉树，热扩散探针，液流密度，径向变化
数据集信息
数据引用
| 必引文献: |
秦佳双,顾大形,倪隆康,何文,林芙蓉,周翠鸣.桉树液流径向变化及其对整树蒸腾估算的影响[J].林业科学研究,2022,35(06):170-176. |
| 数据引用: |
数据来源于：广西桂林植物园尾巨桉树干液流径向变化数据集（2021）,秦佳双，倪隆康(广西壮族自治区中国科学院广西植物研究所), 2023, 中国科学院植物科学数据中心, DOI:10.12282/plantdata.1421, CSTR:34735.11.PLANTDATA.1421
Normative references：The data set of radical variation of sap flow density of Eucalyptus urophylla × Eucalyptus Grandis in Guilin Botanical Garden, Guangxi 2021, 2023, Plant Data Center of Chinese Academy of Sciences, DOI:10.12282/plantdata.1421, CSTR:34735.11.PLANTDATA.1421 |
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中文致谢方式：
感谢中国科学院植物科学数据中心(Plant Data Center of Chinese Academy of Sciences, https://www.plantplus.cn) 提供数据支撑。
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Acknowledgements：
Acknowledgement for the data support from Plant Data Center of Chinese Academy of Sciences (https://www.plantplus.cn).
