Skip to main content
Dryad logo

Water uptake strategies by typical broadleaf and coniferous trees in the Loess Plateau mountain area of northern China

Citation

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 , Dryad, Dataset, 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