A comparison of water use strategies between pure and mixed forests on the Chinese Loess Plateau
Data files
Oct 21, 2025 version files 27.39 KB
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doi-10.5061dryad.pvmcvdp00.zip
23.45 KB
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README.md
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Abstract
To elucidate how pure and mixed forests adjust their water use strategies under interannual precipitation variability, we conducted a systematic investigation of root architecture, water dynamics, and physiological regulation in pure Pinus tabuliformis, pure Robinia pseudoacacia, and their mixed forests on the Chinese Loess Plateau during a wet year (2022) and a normal year (2023). By analyzing fine root vertical distribution, root length density, soil moisture, stand transpiration, stable isotope-based water sources, and stomatal behavior, we found that mixed forests accumulated higher fine root biomass than either pure forest type, while exhibiting intermediate root length density. Seasonal fluctuations in soil water content and stand transpiration were more pronounced in mixed forests than in pure P. tabuliformis stands, though less variable than in pure R. pseudoacacia stands. Transpiration dynamics closely tracked root length density patterns and responded strongly to environmental drivers such as air temperature, net radiation, and vapor pressure deficit. Importantly, as conditions shifted from the wet to the normal year, all forests reduced surface water use, but mixed forests showed a markedly greater shift toward deep soil water extraction compared to pure stands. Stomatal conductance analysis further indicated that mixed forests adopted more stringent stomatal regulation, reflecting a more conservative water use approach relative to pure forests. These results demonstrate that mixed forests develop a more efficient and conservative water-use strategy by optimizing root distribution for deep-water access and enhancing stomatal control. Our findings offer key physiological and ecological insights for predicting the stability and adaptability of plantation ecosystems under future climate variability on the Loess Plateau.
Dataset DOI: 10.5061/dryad.pvmcvdp00
Description of the data and file structure
This dataset (doi-10.5061dryad.pvmcvdp00.zip)includes eight data sheets for statistical analyses.
Files and variables
File: Dataset1-Environmentaldata.csv
Description: This data table contains the precipitation (P), vapor pressure deficit (VDP), air temperature (Ta), relative humidity in air (RH) during the tree growing seasons of 2022 and 2023, as well as the relative extractable water of pure Pinus tabuliformis forest (PT), pure Robinia pseudoacacia forest (RP), and Pinus tabuliformis * Robinia pseudoacacia forest (PT*RP).
Variables
- Variables-2022/2023: Variables in 2022 or in 2023
- DOY: Day of year
- P: Precipitation (mm)
- Ta: Air temperature (°C)
- VPD: Vapor pressure deficit (kPa)
- RH: Relative humidity (%)
- REW: Relative extractable soil water
- PT: Pinus tabuliformis forest
- RP: Robinia pseudoacacia forest
- PT*RP: Pinus tabuliformis * Robinia pseudoacacia forest
File: Dataset2-Fineroots.csv
Description: This data sheet contains the dry fine root biomass and fine root length density of each forest at different soil depths.
Variables
- Depth: Soil depth (cm)
- DB: Dry biomass (kg m -3)
- RLD: Root length density (cm cm -3)
- PT-PTRP: PT trees in the PTRP forest
- RP-PTRP: RP trees in the PTRP forest
File: Dataset3-Soilwatercontent.csv
Description: This data sheet contains data on soil water content for each forest at different soil layers.
Variables
- Variables-2022/2023: Variables in 2022 or in 2023
- Surface: Soil water content in surface layer (cm3 cm -3)
- Middle: Soil water content in the middle layer (cm3 cm -3)
- Deep: Soil water content in the deep layer (cm3 cm -3)
File: Dataset4-Isotope.csv
Description: This data sheet contains isotopic data of soil water for each forest.
Variables
- Depth: Soil depth (cm)
- 2H: δ2H value (‰)
- 18O: δ18O value (‰)
- 17O: δ17O value (‰)
File: Dataset5-Plantisotope.csv
Description: This data sheet contains isotopic data of plant xylem samples for each forest.
Variables
- Plants: Plant xylem samples
- 2H: δ2H value (‰)
- 18O: δ18O value (‰)
- 17O: δ17O value (‰)
File: Dataset6-Watersources.csv
Description: This data sheet contains data on soil water resources from different soil layers for each forest.
Variables
- Forests: Forest types
- Surface: Surface layer contribution (%)
- Middle: Middle layer contribution (%)
- Deep: Deep layer contribution (%)
File: Dataset7-Dailytranspiration.csv
Description: This data sheet contains data on daily transpiration for each forest in 2022 and 2023.
Variables
- DOY-2022(2023): Day of year in 2022 or in 2023
- PT-2022(2023): Daily transpiration in PT in 2022 or in 2023 (mm)
- RP-2022(2023): Daily transpiration in RP in 2022 or in 2023 (mm)
- PT-PTRP-2022(2023): Daily transpiration for PT trees in PTRP forest in 2022 or in 2023 (mm)
- RP-PTRP-2022(2023): Daily transpiration for RP trees in PTRP forest in 2022 or in 2023 (mm)
File: Dataset8-Canopyconductance.csv
Description: This data sheet contains data on canopy stomatal conductance for each forest in 2022 and 2023.
Variables
- DOY-2022(2023): Day of year in 2022 or in 2023
- PT-2022(2023): Canopy stomatal conductance for PT in 2022 or in 2023 (mm s-1)
- RP-2022(2023): Canopy stomatal conductance for RP in 2022 or in 2023 (mm s-1)
- PT-PTRP-2022(2023): Canopy stomatal conductance for PT trees in PTRP forest in 2022 or in 2023 (mm s-1)
- RP-PTRP-2022(2023): Canopy stomatal conductance for RP trees in PTRP forest in 2022 or in 2023 (mm s-1)
Code/software
All the analyses were done in SPSS 22.0 (SPSS Inc., Chicago, USA), and all figures were produced using Origin 2018 (OriginLab Corporation, USA).
