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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Waterlogging tolerant tree species exert a critical role in forest preservation and the associated water conservation in flood prone areas. Clarifying the patterns and drivers of water uptake by waterlogging tolerant trees is crucial for forest management in flood-prone areas, especially in the scenario of precipitation changes in the estuary delta. Here, we uploaded the values of δD and δ18O obtained from soil and xylem waters to a Bayesian mixed model (MixSIAR) to determine the water use pattern of Taxodium distichum, a waterlogging tolerant tree, following different magnitudes of rainfall events in three sites of the Yangtze River Delta, China. We further conducted variation partitioning analysis and a random forest model to discern the dominant factor driving plant water uptake. Our results indicated that T. distichum mainly absorbed soil water from shallow soil layers (0–40 cm, 43.63%–74.70%), while the percentage of water uptake from deep soil layers was lower in the Yangtze River Delta (60–100 cm, 13.43%–35.90%), whether in light, moderate, or heavy rainfall conditions. Furthermore, our results demonstrated that tree traits, such as fine root biomass, are dominantly driving plant water uptake. These findings imply that waterlogging tolerant tree species could increase the percentage of water uptake from shallow soils by changing their plant attributes, which would effectively improve the water conservation of forests in the estuary delta.

Details

Title
Disentangling the Effects of Tree and Soil Properties on the Water Uptake of a Waterlogging Tolerant Tree in the Yangtze River Delta, China
Author
Zhang, Beibei 1 ; Jiang, Jing 2 ; Xu, Qing 1 ; Gao, Deqiang 1 ; Zuo, Haijun 1   VIAFID ORCID Logo  ; Ren, Ranran 1 

 Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China; [email protected] (B.Z.); [email protected] (D.G.); [email protected] (H.Z.); [email protected] (R.R.) 
 Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; [email protected] 
First page
1547
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
19994907
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2602048339
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.