Water uptake strategies by typical broadleaf and coniferous trees in the Loess Plateau mountain area of northern China
Cite this dataset
Weiwen, Zhao; Han, Youzhi; Liang, Wenjun; Wei, Xi (2022). Water uptake strategies by typical broadleaf and coniferous trees in the Loess Plateau mountain area of northern China [Dataset]. Dryad. https://doi.org/10.5061/dryad.cz8w9gj3h
Abstract
Poor precipitation in the Loess Plateau area may significantly influence water uptake strategies of the plants growing there. The water sources of these trees have not been studied to date. We investigated the impacts of precipitation (before and after) on water uptake strategies of typical broadleaf and coniferous trees in the Loess Plateau mountain area of northern China by using hydrogen and oxygen stable isotope techniques. Our results indicated that water sources of these two tree types varied before and after rainfall. Robinia pseudoacacia, a broadleaf tree, absorbed water majorly from the 30–40 cm (57.8%) soil layer before precipitation and from the 20–30 cm (58.5%) soil layer after precipitation. However, Pinus tabuliformis, a coniferous tree, mainly absorbed water from 20–30 cm (24.9%) and 10–20 cm (21.6%) soil layers before precipitation and from 0–10 cm (39.8%) and 10–20 cm (44%) soil layers after precipitation. Moreover, the herbaceous of broadleaf plant has higher complexity of the community through filed investigation. Thus, R. pseudoacacia and P. tabuliformis exhibited peculiar difference in terms of water uptake, indicating that they are suitable to grow together as forest vegetation in arid and semi-arid areas. Overall, our results provided vital information for sustainable afforestation management in the Loess Plateau mountain area of northern China.
Methods
This dataset corresponds to experimental estimates of stable isotope of P. tabuliformisin and R. pseudoacacia in Caijiachuan. It also contains local precipitation, temperature, sampling plots' understory and stable isotope before and after precipitation.
Usage notes
There are no missing values, and column names are self-explanatory.
Funding
National Natural Science Foundation of China, Award: 31901365
National Natural Science Foundation of China, Award: 31971644
National Natural Science Foundation of China, Award: 31500523
Innovation Project of Graduate Education in Shanxi Province, Award: 2020BY048
Technological Innovation Project of Colleges and Universities in Shanxi Province*, Award: 2019l0394
Shanxi Provincial Outstanding Doctoral Program for Incentive funds for Scientific Research Projects, Award: SXYBKY2018032
Shanxi Agricultural University, Award: 2018yj09: Fund for Introduced Talents
Shanxi Agricultural University, Award: 2014yj19: Fund for Introduced Talents
Innovation Project of Graduate Education in Shanxi Province, Award: 2020BY048