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Partitioning tree water usage into storage and transpiration in a mixed forest

Partitioning tree water usage into storage and transpiration in a mixed forest Background: Water migration and use are important processes in trees. However, it is possible to overestimate transpiration by equating the water absorbed through the plant roots to that diffused back to the atmosphere through stomatal transpiration. Therefore, it is necessary to quantify the water transpired and stored in plants. 2 18 Method: The δ H/δ O technique and heat ratio method were used to explore the water usage of coniferous and broad-leaved tree species, including the proportions of water used for transpiration and water storage. Results: Platycladus orientalis and Quercus variabilis had strong plasticity in their water usage from different sources. Platycladus orientalis primarily used groundwater (30.5%) and the 60–100-cm soil layer (21.6%) throughout the experimental period and was sensitive to precipitation, absorbing water from the 0–20-cm layer (26.6%) during the rainy season. Quercus variabilis absorbed water from all sources (15.7%–36.5%) except from the 40–60-cm soil layer during the dry season. In addition, it did not change its water source but increased its groundwater uptake during − 1 the rainy season. The annual mean water fluxes of P. orientalis and Q. variabilis were 374.69 and 469.50 mm·year , with 93.49% and 93.91% of the water used for transpiration, respectively. However, nocturnal sap flow in P. orientalis and Q. variabilis was mainly used for water storage in the trunk rather than transpiration, which effectively alleviated drought stress and facilitated the transport of nutrients. Conclusions: The water stored in both species comprised 6%–7% of the total water fluxes and, therefore, should be considered in water balance models. Keywords: Water migration, Water uptake, Nocturnal sap flow, Transpiration Introduction plants. This technology solves the challenge of quan- Water is a key factor affecting the circulation of ma- tifying plants’ absorption ratio from each water terials and plant growth in forest ecosystems source (Wang et al. 2017). Since there is no isotopic (Nadezhdina et al. 2020). Plants absorb water from fractionation in hydrogen and oxygen isotopes dur- the soil through their roots and store it in their ing water uptake and transportation from xylem to xylem, use it during photosynthesis, or lose it leaves (Ehleringer et al. 1991), the hydrogen and through evaporation through the stomata in their oxygen isotopes in the xylem and water source can leaves (Weatherley 1982; Buckley et al. 2020;Barbeta be compared based on the isotopic mass conserva- et al. 2015; Huang et al. 2017; Molina et al. 2019). tion law. Linear mixed models (Iso-Source) and Stable hydrogen and oxygen isotope technology is a Bayesian mixed models, including MixSIAR, MixSIR, new technique for exploring the source of water in and SIAR, have been used to quantify the ratio of water used by the plants from each water source (Phillips et al. 2005). Dawson and Ehleringer (1991) * Correspondence: yuxinxiao1111@126.com explored the use of stable hydrogen and oxygen iso- Key Laboratory of Soil and Water Conservation and Desertification Combating of Ministry of Education, Beijing Forestry University, Beijing tope technology to distinguish between the water 100083, China sources of plants and revealed that tree species that Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Liu et al. Forest Ecosystems (2021) 8:72 Page 2 of 13 grew by the riverside did not use river water but in- et al. (2017) suggested that night transpiration can stead used soil water along the riverside. Since then, drive the supplementation of water. there have been several reports on the source of Currently, there is no adequate technology for water utilized by plants in China and throughout the quantifying night transpiration and water supple- world (Moreno-Gutiérrez et al. 2012;Pocaetal. mentation owing to their simultaneous occurrence. 2019; Liu et al. 2020). Previous research has focused However, based on the response relationship be- on comparing the differences in water sources tween transpiration and the vapor pressure deficit among different plants or the variation in water (VPD), transpiration and water supplementation can usage by the same plant across different seasons be distinguished (Resco de Dios et al. 2016; Siddiq (Nie et al. 2011;Yangetal. 2015;Pocaetal. 2019). et al. 2017;Dietal. 2019a, 2019b) since the main However, very few studies have focused on the water factor causing nocturnal transpiration is VPD. usage and symbiotic mechanism in coniferous and Therefore, when the VPD approaches zero, if sap broad-leaved mixed forests under seasonal drought flow still occurs, it supplements the stem water. in rocky mountainous regions characterized by thin However, if sap flow has a good fitting relationship soils and high gravel content. Moreover, with inci- with the large VPD, the sap flow is primarily used dences of seasonal drought becoming rampant and for transpiration. more intense in these regions owing to global cli- Numerous studies have explored daytime transpir- mate change, the adaptations of species in these ation and quantified the amount of water that tran- mixed forests to this heterogeneous change with spired (Fu et al. 2016;Wuetal. 2019; McCormick changing water sources remain unclear. et al. 2021). However, the amount of nocturnal Several studies have investigated the proportion of water supplementation has largely been ignored. water absorbed from each source and quantified the Consequently, substantial errors may occur when diurnal transpiration (Palacio et al. 2014;Wu et al. calculating the water balance in an ecosystem, 2016; Liu et al. 2020). Although previous studies impacting the development of management strat- have established that stomata are closed at night, egies. Therefore, if the amounts of each water frac- and there is no sap flow during this period (Zeppel tion used for transpiration and nocturnal sap flow et al. 2014; Zhang et al. 2020), with the develop- were accurately quantified, existing formulae or ment and improvement in technologies, nocturnal models for calculating water balance could be re- sap flow has been confirmed in plants in different vised. Therefore, it is paramount to quantitatively habitats (Hentschel et al. 2013;Siddiqand Cao distinguish the flux and proportion of water 2018;Chenetal. 2020). Nocturnal sap flow has absorbed, transported and transpired in a mixed for- been rarely considered in traditional models owing est. In this study, we employed the isotope (δ H to the small proportion of nocturnal sap flow com- and δ O) technique and heat ratio method to i) de- pared to the overall sap flow. However, for some termine the water absorption ratio from the differ- plant species, nocturnal sap flow comprises a large ent water sources and the symbiotic mechanism of proportion of the overall sap flow (Alvarado-Bar- the mixed forest; ii) quantify the amount of water rientos et al. 2015;Dietal. 2019a, 2019b; Flo et al. that flows in the nocturnal sap and quantify the 2019). For example, Barbeta et al. (2012) established proportions of water transpired and stored in plants. that Quercus ilex (holly oak) growing in the Medi- Our results will provide a scientific reference for terranean climate with annual precipitation of 350 further research on the underlying mechanisms of mm had a nocturnal sap flow of 40% of the overall water cycling in forest ecosystems. flow. In addition, the nocturnal sap flow in Q. oleoides in the central USA increased from 8% dur- Materials and methods ing the rainy season to 20% during the dry season Site description (Cavender-Bares et al. 2007). Based on these find- The study was conducted at the Forest Ecosystem ings, nocturnal sap flow cannot be neglected. Noc- Positioning Research Station in Beijing (40°03′ N, turnal sap flow effectively improves the leaf and 116°05′ E). The station lies at an elevation of 240 m stem water potential before dawn and reduces above sea level with a warm temperate semi-humid embolisms in the xylem (Forster 2014). However, monsoon climate. The annual average precipitation nocturnal sap flow is not equivalent to nocturnal and potential evapotranspiration were 630 and 1800 transpiration (Binks et al. 2020). During the night, mm, respectively. June to September precipitation some sap is transpired through the stomata (30%– comprised 70% of the annual precipitation. The 60%), and some is used to supplement the stem average annual temperature was 11.6 °C with 2662 h water (40%–70%) (Gribovszki et al. 2015). Huang of sunshine. The primary forest vegetation includes Liu et al. Forest Ecosystems (2021) 8:72 Page 3 of 13 Platycladus orientalis and Quercus variabilis planta- Spring (40°03′ N, 116°05′ E) 310 m southwest of the tions established after the 1960s. Broussonetia plots. papyrifera, Vitex negundo, Lespedeza bicolor,and other shrubs are underneath the canopy. The soil Stable isotope analysis type is leached cinnamon with a thickness of 80– The isotopic ratios in the samples were determined at 100 cm, the humus content is high, and the deep the Ecohydrological Processes and Mechanisms Labora- soil primarily consists of gravel. tory, Beijing Forestry University, China. The water in the soil and branches samples was extracted by low- 2 18 Experimental design temperature vacuum condensation, and δ H/δ O was Three plots measuring 20 m × 20 m each were estab- analyzed using a liquid water isotope analyzer (LGR 2 18 lished at the study area. Six P. orientalis and Q. var- DLI-100, USA). The ratio of H and O was recorded in iabilis with average height, diameter at breast height parts per thousand of the “standard average ocean (DBH), and crown width were randomly selected water” with a precision of determination of 0.3‰ and from each plot (Table 1). In each plot, three ECH O 0.1‰, respectively, and expressed as follows: soil moisture sensors (Decagon Devices, Pullman, WA, USA) were installed at three sampling points R −R sample standard to measure the soil water content (SWC) at 0–20, δXðÞ ‰ ¼  1000 ð1Þ standard 20–40, 40–60, 60–80, and 80–100 cm. The ECH O sensors were connected to a Em50/R data collection box (Decagon Devices, Pullman, WA, USA), which The ratio of water absorption by trees recorded data every 30 min and simultaneously The isotopic ratios of water in the branches carry the stored it in a computer. The data for precipitation, isotopic information of all the water sources since water radiation, atmospheric temperature, and relative hu- is absorbed through the roots. Owing to this, the Mix- midity in the study area were collected from a for- SIAR model was used to quantify the water absorption est weather station HOBO (U30-NRC; Onset, ratio of trees (Phillips et al. 2005) using the following Bourne, MA USA) located 1 km away from the ex- equations: perimental plots. δX ¼ c1δX1 þ c2δX2 þ c3δX3 þ c4δX4 Quantification of the water amounts used for þ c5δX5 ð2Þ physiological processes Determination of the water source: branches, soil, and c1 þ c2 þ c3 þ c4 þ c5 ¼ 1 ð3Þ groundwater sampling 2 18 In each plot, three trees with good vigor and similar where, X is the H/ O value of tree branch water (‰); 2 18 height/DBH were randomly selected, and their annual X , X , X , X , and X are the H/ O values of soil water 1 2 3 4 5 non-green branches (0.3–0.6 cm in diameter) were col- at 0–20, 20–40, 40–60, 60–100 cm, and groundwater lected at the same height (5 and 6 m for P. orientalis and levels, respectively; and c , c , c , c , and c represent the 1 2 3 4 5 Q. variabilis, respectively) from the ground. The bark of absorption ratio of trees for soil water from 0 to 20, 20– the branches was removed to obtain the xylem. Three 40, 40–60, 60–100 cm, and groundwater levels, samples were collected per tree. respectively. Three soil samples were collected from 0 to 20, 20–40, 40–60, 60–80, and 80–100 cm within a radius of 0.5 to Quantification of the amount of water for migration (Q) 1 m from the sampled trees using an auger with a diam- Three P. orientalis and Q. variabilis tree species eter of 3.5 cm and a length of 120 cm. The sampled with an average tree height and DBH were selected branches and soil were immediately placed into a 50-mL at each observation point, which were the same sampling bottle, sealed with Parafilm®, and stored at − points for the isotope sample collection in the plot. 4 °C until the isotopes were determined. Three sap flow meters (SFM , HRM 30, ICT Inter- Simultaneously, three spring water samples (represent- national PTY, Armidale, Australia) were installed at ing groundwater) were collected from the Miaolingshan a height of roughly 1.35 m on the three selected Table 1 Basic information about the tree species measured Tree species Number Average height (m) Diameter at breast height (cm) Platycladus orientalis 37 7.16 ± 1.53 7.60 ± 2.83 Quercus variabilis 43 9.18 ± 1.15 11.59 ± 3.91 Liu et al. Forest Ecosystems (2021) 8:72 Page 4 of 13 trees to monitor the sap flow rate. The SFM flow- correlation analysis was conducted on the data after meter has three probes, which simultaneously meas- dislocation. The dislocation time corresponding to ure two-way flows. Three cores were taken from the maximum correlation coefficient was the storage each tree at roughly 1.35 m using a borer with 5 time (The results of correlation analysis after dis- mm increments, and the radii of cross-sections and location are shown in the Supplemental Table S1). heartwood were measured with a ruler. Three cylin- The migration flux during this time is the stored drical probes were inserted into the sapwood water. The VPD was calculated as through the drilled holes. The device was wrapped and sealed with insulated and radiation-proof 17:27T aluminum foil to prevent rainwater from entering Taþ237:3 VPD ¼ 0:61078  e ðÞ 1−RH ð7Þ and protect against direct solar radiation. The data acquisition interval of the SFM flowmeter was set where T and RH are atmospheric temperature (°) and 1 a at 10 min, and the water that migrated through the relative humidity (%), respectively. tree was calculated using the following equations (Allen et al. 2011): Quantification of water used for transpiration (Q ) Tr Sap flow during the stomatal opening represents the rate of transpiration in a plant. Therefore, the water used for Q ¼ V A ¼ V A þ V A ð4Þ s s ot 1 in 2 transpiration was quantified by determining the stomatal opening time via the VPD and radiation. The Q was Tr V ρðÞ c þ m c h W c s V ¼ ð5Þ s determined by calculating the difference between the ρ c overall sap flow and water storage. k t V ¼ ln  3600 ð6Þ Data analysis x t The statistical analyses were performed using SPSS Here, Q is the total migration (mL); V is the sap flow 16.0 (SPSS, Inc., Chicago, IL, USA). Descriptive sta- − 1 2 velocity (cm·s ); A is the sapwood area (cm ); V and tistics were applied to calculate the means and s ot V are the sap flow velocities of the thermocouple inside standard deviations for each set of replicates. First, in − 1 and outside the temperature probe (cm·s ), respect- a one-way analysis of variance (ANOVA) was per- ively; A and A are the areas of the outer ring and the formed to test the effect of tree species on the mi- 1 2 inner ring, respectively (cm ); V is the heat pulse rate gration flux, transpiration, and storage. A two-way − 1 (cm·s ); k is the thermal diffusion coefficient of fresh ANOVA was then performed to analyze the differ- wood; x is the distance between the thermal probe and ences in SWC, isotopic composition, season, and the temperature probe; t and t are the variation in soil depth as independent factors. In addition, a 1 2 temperature in the upward and downward directions, re- three-way ANOVA was used to analyze the differ- − 3 spectively; ρ is the wood density (g·cm ); c and c are ences in water source using the soil depth, tree spe- b w s − 1 the specific heat capacities of fresh wood (1200 J·kg ·° cies, and season as independent factors. − 1 C , 20 °C) and specific heat capacity of liquid flow − 1 − 1 (4182 J·kg ·°C , 20 °C), respectively; m and ρ are the Results c s moisture content and density of fresh wood, Variation in soil water content and meteorological respectively. conditions The annual precipitation totals in 2015 and 2016 Quantification of the water used for migration were 580.0 and 649.8 mm, respectively (Fig. 1), with The water migrating through the trees can be divided the precipitation in June to September comprising into the water used in transpiration and storage. 79.0% and 80.5% of the total annual precipitation in 2015 and 2016, respectively. June to September is Quantification of the used for water storage (Q ) the rainy season, while October to May comprises The amount of water stored at night depends on the dry seasons. During the dry season, the average the storage time as determined by the dislocation SWC in the 0–20-, 20–40-, 40–60-, 60–80-, and correlation method (Maherali and DeLucia 2001). 80–100-cm layers were 11.6%, 12.6%, 11.9%, 9.8%, The data series of sap flow velocity and the corre- and 9.2%, respectively. However, the SWC in the sponding VPD/radiation were established according five soil layers increased at different degrees after it to the observation time sequence. The sap flow vel- rained, followed by a decrease. The average SWC in ocity and VPD/radiation based on dislocation were the five layers during the rainy season was 16.5%, successively recorded every half hour, and a 17.0%, 17.6%, 14.0%, and 11.2%, respectively, 42.2%, Liu et al. Forest Ecosystems (2021) 8:72 Page 5 of 13 Fig. 1 Variation in precipitation and mean soil water content in the Forest Ecosystem Positioning Research Station, north China, during the study period. The blue shading corresponds to the dry season, while the white region corresponds to the rainy season 35.0%, 39.7%, 17.5%, and 13.9% higher than those in 0–20-cm layer were − 32% and − 2.13‰,which were the dry season. After approximately 10 mm of pre- 19.50%, 26.29%, 38.19%, and 53.59% higher than cipitation, the SWC increased by 64.22% in the 0– those in the 20–40-, 40–60-, 60–80-, and 80–100-cm 20-cm layer, but no significant changes were ob- layers, respectively (P < 0.05). However, the δ Hand served in the other layers (P > 0.05). After > 50 mm δ Ointhe 80–100-cm layer were significantly lower precipitation, the SWC increased in all the five soil than those of the other layers (P < 0.05). Neverthe- 2 18 layers, with a lag time effect in the deeper layers. less, the δ Hand δ O in each layer decreased grad- The total solar radiation (TR) and VPD had a ually during the rainy season, with 96.93%, 46.84%, similar trend, with an initial increase and a subse- 38.76%, 25.92%, and 15.49% decreases, respectively quent decrease (Fig. 2). The peak VPD appeared 0– across the five soil layers. 3h later compared to TR. The TR was 0 and VPD> Branch water in P. orientalis ranged from − 0 Kpa from 19:00 to 06:00 at night. In January, 105.63‰ to − 37.82‰ for δ Hand − 14.09‰ to − mean and peak TR values were 87.1 and 174.6 0.19‰ for δ O, with more extreme values than − 2 W·m , respectively, while those of VPD values those of Q. variabilis (− 99.89‰ to − 36.24‰ for 2 18 were 0.35 and 0.59 Kpa, respectively. The TR and δ Hand − 13.58‰ to − 2.61‰ for δ O). The mean 2 18 VPD values gradually increased with seasonal vari- values of δ Hand δ O in the branch water in P. ation from January to July and decreased from Au- orientalis during the dry season were − 56.53‰ and gust to December. The mean and peak TR values − 4.99‰, which were 28.56% and 54.30% higher than − 2 2 reached 176.2 and 491.6 W·m in July, which were those of Q. variabilis.Additionally,the δ Hand 2.0- and 2.8-fold higher than the mean and peak δ O in the branch water in P. orientalis during the values in January, respectively. In addition, the mean rainy season were 45.67% and 69.93% higher than and peak values of VPD reached 2.57 and 6.84 Kpa those in the dry season, while in Q. variabilis they in July, which was 7.3- and 11.6-fold higher than were 6.31% and 9.53% higher, respectively. those in January, respectively. However, there were The water absorption by P. orientalis and Q. varia- no significant differences in TR and VPD between bilis from the different water sources fluctuated with January and December. the season (Fig. 5). The two species absorbed water from the groundwater from the 60–100-cm layer, al- Water absorption by trees though Q. variabilis also absorbed water from the 2 18 The δ Hand δ O in soil and branch water of P. 0–20-cm (21.7%) and 20–40-cm (19.9%) layers dur- orientalis and Q. variabilis significantly fluctuated ing the dry season. In the rainy season, P. orientalis across the different seasons (Figs. 3 and 4). The δ H used groundwater (30.5%) and water from the 60– and δ O in soil water were higher in the dry season 100-cm soil layer (21.6%) and 0–20-cm layer (26.6%). than in the rainy season (P < 0.05), implying that the The absorption ratio of water from the 20–40-cm isotope fractionation effect in soil water in the dry layer used by Q. variabilis during the rainy season season was more pronounced than in the rainy sea- was 47.4% lower than during the dry season, but the 2 18 son. During the dry season, the δ Hand δ Ointhe absorption ratio of groundwater increased by 68.2%. Liu et al. Forest Ecosystems (2021) 8:72 Page 6 of 13 Fig. 2 Variation in total solar radiation (TR) and vapor pressure deficit (VPD) in the Forest Ecosystem Positioning Research Station, North China, during the study period. The figure shows the observation data of TR and VPD randomly selected for 10 consecutive days each month P. orientalis used less water from the 20–40-cm and The proportions of water used in transpiration and water 40–60-cm soil layers, whereas Q. variabilis used less storage water from the 40–60-cm soil layer throughout the The annual mean water fluxes in P. orientalis and Q. − 1 experimental period. variabilis were 374.69 and 469.50 mm·year , respect- ively (Fig. 7). The average sap flux in P. orientalis was 20.19% lower than that of Q. variabilis. The amounts of Water migration of P. orientalis and Q. variabilis water used by P. orientalis for transpiration and storage − 1 The sap flow rate (SFR) of P. orientalis during the were 350.3 and 24.41 mm·year , respectively, account- dry season were bimodal over the observation ing for 93.49% and 6.51% of the sap flow, respectively. period (Fig. 6). SFR gradually increased, reaching its Moreover, the amounts of water used by Q. variabilis maximum at 11:00 and 14:30, respectively, followed for transpiration and storage were 440.85 and 28.65 − 1 by a decrease. In contrast, the variation in SFR of mm·year , respectively, accounting for 93.91% and Q. variabilis showed no peak during the dry season 6.09% of the sap flow, respectively, which implies that but had a single peak during the wet season. The the plants used most of the water for transpiration. − 1 mean SFR in P. orientalis (0.0008 cm·s )was four However, there was no significant difference in water times higher than that of Q. variabilis,and the used by P. orientalis and Q. variabilis for transpiration − 1 maximum SFR in P. orientalis (0.0022 cm·s )was and storage (P > 0.05). 4.4 times higher than that of Q. variabilis during the dry season. Additionally, the mean SFR in Q. Discussion variabilis during the wet season was 6.5 times that Water absorption by trees in the dry season, while the mean SFR of P. orienta- P. orientalis and Q. variabilis showed different water lis during the wet season was not significantly dif- usage in the same habitat, related to their root distribution ferent from that in the dry season (P > 0.05). and water conditions. More than 50% of the P. orientalis Liu et al. Forest Ecosystems (2021) 8:72 Page 7 of 13 Fig. 3 Variation in mean (± SD) isotopic values of soil water in the Forest Ecosystem Positioning Research Station, North China during the study period root biomass is distributed in the 0–20-cm layer (Liu et al. In contrast to P. orientalis, 79.2% of the main root 2019), and its highly developed surface root system of P. system of Q. variabilis is highly developed and uni- orientalis is more sensitive to precipitation. Therefore, P. formly distributed in different soil layers (Liu et al. orientalis used water from the 0–20-cm layer following 2019); hence, it can use multiple water sources. precipitation, consistent with findings of Jia et al. (2017), However, it uses a higher surface soil water ratio who established that P. orientalis primarily absorbed water during thedry season,possiblyowing to theshort from the surface soil during the rainy season to maintain transport distance of surface soil water and the normal physiological activities and then switched its water lower energy consumption. This suggests that Q. source to deep soil layers during the dry season. This variabilis prefers surface soil water during the dry phenomenon is known as a “dimorphic” structural feature season, consistent with previous findings, which of the root system (Evaristo et al. 2016; Cuneo et al. 2018; established that plants with uniform root distribu- Poca et al. 2019). Previous studies have also established tions preferentially absorb water from surface soil variation in water usage from different sources in Q. pub- layers (Fan et al. 2017; Cai et al. 2018; Cuneo et al. escens, Populus, Robinia pseudoacacia,and Pinus tabulae- 2018). However, Q. variabilis absorbs water from formis (Gebauer and Ehleringer 2000; Liu et al. 2020; the deep soil layers via its highly developed root Ripullone et al. 2020). system to maintain a high transpiration rate during Liu et al. Forest Ecosystems (2021) 8:72 Page 8 of 13 Fig. 4 Typical diurnal variation in mean (± SD) isotopic values in Platycladus orientalis and Quercus variabilis branch water in the Forest Ecosystem Positioning Research Station, North China during the study period the rainy season. Wang et al. (2017)and Peddinti Water migration and use et al. (2020) have demonstrated that several plants We observed significant differences in water usage can take up deep soil water and groundwater and distribution between the two tree species, which through their developed roots throughout the grow- could be related to their characteristics. Molina et al. ing season, ensuring a stable water supply. The (2019) established that the aboveground biomass and threshold value of the root system response to SWC defoliation cycle are the main factors affecting SFR. is one of the key factors affecting water usage In our study, the SFR of P. orientalis was higher (Cuneo et al. 2018). In our study, the P. orientalis than that of Q. variabilis during the dormant period, root system was more sensitive to precipitation than probably because Q. variabilis is a broad-leaved de- that of Q. variabilis. These water uptake patterns in ciduous species, which had already shed its leaves, P. orientalis and Q. variabilis from different water while P. orientalis retained its leaves. In addition, sources result from long-term adaptation to seasonal the xylem vessel diameter and the crown width of Q. arid environments. Such strategies help reduce com- variabilis were greater than those of P. orientalis, petition for water with other tree species and im- which significantly improved the efficiency of water prove symbiotic ability among community species migration. In addition, Q. variabilis had more sto- (Yang et al. 2015; Jia et al. 2017; Liu et al. 2019). mata per leaf area than P. orientalis,and therateof Liu et al. Forest Ecosystems (2021) 8:72 Page 9 of 13 Fig. 5 Mean (± SD) absorption ratios of Platycladus orientalis and Quercus variabilis from different water sources in the Forest Ecosystem Positioning Research Station, North China during the study period water diffusion was higher, resulting in a higher SFR. capacity of trees depends on the trunk volume and Nocturnal sap flow does not necessarily represent the water pressure difference between the tree vol- nocturnal transpiration since there is a time lag ef- ume and root cap (Huang et al. 2017). This is con- fect in sap flow and stomatal aperture at night (Phil- sistent with the tree capacity, nocturnal water lips et al. 2003). A positive correlation between storage, and transpiration during the day in Q. var- nocturnal sap flow and the VPD indicates water used iabilis being significantly higher than in P. orientalis. for transpiration by the trees at night (Green et al. Nocturnal water storage alleviates drought stress and 1989;Hogg and Hurdle 1997; Fisher et al. 2007). helps plants overcome intense evaporation in the dry Otherwise, this water will be stored in the trunk at season (Huang et al. 2017). Nocturnal sap flow also night. However, in this study, the correlation be- facilitates oxygen and nutrient transport. For ex- tween sap flow rate and VPD was weak, implying ample, in Betula, it provides sufficient oxygen to that the sap flow at night was used for water storage sapwood parenteral cells (Daley and Phillipa 2006). in the trunk but not for nocturnal transpiration. The In addition, the phenomenon of hydraulic redistri- presence of nocturnal fluid flow comprising 5%–6% bution in P. orientalis was previously established in of total sap flow has been confirmed in both P. our study area (Liu et al. 2019). Nocturnal sap flow orientalis and Q. variabilis, which is consistent with reduces the water potential in plant leaves, negatively the findings in previous studies (Forster 2014; Siddiq affecting the hydraulic redistribution (Yu et al. 2018; and Cao 2018;Chenetal. 2020). The water storage Howard et al. 2009). Moreover, the findings in our Liu et al. Forest Ecosystems (2021) 8:72 Page 10 of 13 Fig. 6 Typical diurnal variation in sap flow rates in Platycladus orientalis and Quercus variabilis in the Forest Ecosystem Positioning Research Station, North China during the study period. The figure shows the observed sap flow rates randomly selected for 10 consecutive days in each month study suggest that nocturnal sap flow and root hy- orientalis and Q. variabilis comprised 6%–7% of the draulic redistribution can occur simultaneously, con- total water quantity, which cannot be ignored. sistent with previous findings, which demonstrated hydraulic redistribution contributes to the occur- Conclusions rence of nocturnal sap flow (Matimati et al. 2014;Fu We used an isotope technique and the heat ratio et al. 2018;Hafneretal. 2020). The root hydraulic method to quantify the utilization ratio of water redistribution in P. orientalis effectively alleviates the source and sap flow and determine the proportion of spatial heterogeneity of soil water that meets its water used in transpiration and storage. The results water requirement and neighboring trees (Matimati indicated that P. orientalis and Q. variabilis uptake et al. 2014; Fan et al. 2017). P. orientalis water usage water from multiple sources simultaneously and facilitates water sharing, which is conducive to the showed strong plasticity to water sources. P. orienta- coexistence of different species. Although the sap lis was sensitive to the variation in SWC and quickly flow and diurnal transpiration in P. orientalis were absorbed surface soil water during the rainy season. lower than those of Q. variabilis, the proportion of Q. variabilis absorbed water from sources with water stored was higher in P. orientalis, implying higher and stable water content and did not change that P. orientalis balances the water deficit better its sources, but did increase its uptake of ground- than Q. variabilis. This also explains why P. orienta- water during the rainy season. The sap flow in P. lis is widely distributed as a pioneer tree species in orientalis and Q. variabilis was mainly used for tran- North China. The amount of water stored in P. spiration, and 6%–7% of the water was used for Liu et al. Forest Ecosystems (2021) 8:72 Page 11 of 13 Fig. 7 Schematic representation of water uptake, migration, and use in Platycladus orientalis and Quercus variabilis. The blue font in the yellow box indicates the absorption ratio of trees from each water source during the dry and wet seasons. The numbers that are light blue indicate the migration flux in trees throughout the year, while the pink arrow indicates the water usage process in trees storage in the trunk. However, a long-term survey of Availability of data and materials Available on request. plant water movement partitioning is needed to pro- vide more insights on the partitioning of tree water Declarations usage into storage and transpiration in such mixed Ethics approval and consent to participate forest systems. Not applicable. Abbreviations Consent for publication VPD: Vapor pressure deficit; DBH: Diameter at breast height; SWC: Soil water Not Applicable. content; S: Water storage; Q : Quantification of the water used for Tr transpiration; SFR: Sap flow rates; TR: Total solar radiation Competing interests The authors declare no competing interests. Supplementary Information Author details The online version contains supplementary material available at https://doi. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing org/10.1186/s40663-021-00353-5. Forestry University, Nanjing 210037, China. Key Laboratory of Soil and Water Conservation and Desertification Combating of Ministry of Education, Beijing Forestry University, Beijing 100083, China. Additional file 1. Received: 16 July 2021 Accepted: 20 October 2021 Acknowledgments We thank Huan Zhang and Weiwei Lu for their help with fieldwork. 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Partitioning tree water usage into storage and transpiration in a mixed forest

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Abstract

Background: Water migration and use are important processes in trees. However, it is possible to overestimate transpiration by equating the water absorbed through the plant roots to that diffused back to the atmosphere through stomatal transpiration. Therefore, it is necessary to quantify the water transpired and stored in plants. 2 18 Method: The δ H/δ O technique and heat ratio method were used to explore the water usage of coniferous and broad-leaved tree species, including the proportions of water used for transpiration and water storage. Results: Platycladus orientalis and Quercus variabilis had strong plasticity in their water usage from different sources. Platycladus orientalis primarily used groundwater (30.5%) and the 60–100-cm soil layer (21.6%) throughout the experimental period and was sensitive to precipitation, absorbing water from the 0–20-cm layer (26.6%) during the rainy season. Quercus variabilis absorbed water from all sources (15.7%–36.5%) except from the 40–60-cm soil layer during the dry season. In addition, it did not change its water source but increased its groundwater uptake during − 1 the rainy season. The annual mean water fluxes of P. orientalis and Q. variabilis were 374.69 and 469.50 mm·year , with 93.49% and 93.91% of the water used for transpiration, respectively. However, nocturnal sap flow in P. orientalis and Q. variabilis was mainly used for water storage in the trunk rather than transpiration, which effectively alleviated drought stress and facilitated the transport of nutrients. Conclusions: The water stored in both species comprised 6%–7% of the total water fluxes and, therefore, should be considered in water balance models. Keywords: Water migration, Water uptake, Nocturnal sap flow, Transpiration Introduction plants. This technology solves the challenge of quan- Water is a key factor affecting the circulation of ma- tifying plants’ absorption ratio from each water terials and plant growth in forest ecosystems source (Wang et al. 2017). Since there is no isotopic (Nadezhdina et al. 2020). Plants absorb water from fractionation in hydrogen and oxygen isotopes dur- the soil through their roots and store it in their ing water uptake and transportation from xylem to xylem, use it during photosynthesis, or lose it leaves (Ehleringer et al. 1991), the hydrogen and through evaporation through the stomata in their oxygen isotopes in the xylem and water source can leaves (Weatherley 1982; Buckley et al. 2020;Barbeta be compared based on the isotopic mass conserva- et al. 2015; Huang et al. 2017; Molina et al. 2019). tion law. Linear mixed models (Iso-Source) and Stable hydrogen and oxygen isotope technology is a Bayesian mixed models, including MixSIAR, MixSIR, new technique for exploring the source of water in and SIAR, have been used to quantify the ratio of water used by the plants from each water source (Phillips et al. 2005). Dawson and Ehleringer (1991) * Correspondence: yuxinxiao1111@126.com explored the use of stable hydrogen and oxygen iso- Key Laboratory of Soil and Water Conservation and Desertification Combating of Ministry of Education, Beijing Forestry University, Beijing tope technology to distinguish between the water 100083, China sources of plants and revealed that tree species that Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Liu et al. Forest Ecosystems (2021) 8:72 Page 2 of 13 grew by the riverside did not use river water but in- et al. (2017) suggested that night transpiration can stead used soil water along the riverside. Since then, drive the supplementation of water. there have been several reports on the source of Currently, there is no adequate technology for water utilized by plants in China and throughout the quantifying night transpiration and water supple- world (Moreno-Gutiérrez et al. 2012;Pocaetal. mentation owing to their simultaneous occurrence. 2019; Liu et al. 2020). Previous research has focused However, based on the response relationship be- on comparing the differences in water sources tween transpiration and the vapor pressure deficit among different plants or the variation in water (VPD), transpiration and water supplementation can usage by the same plant across different seasons be distinguished (Resco de Dios et al. 2016; Siddiq (Nie et al. 2011;Yangetal. 2015;Pocaetal. 2019). et al. 2017;Dietal. 2019a, 2019b) since the main However, very few studies have focused on the water factor causing nocturnal transpiration is VPD. usage and symbiotic mechanism in coniferous and Therefore, when the VPD approaches zero, if sap broad-leaved mixed forests under seasonal drought flow still occurs, it supplements the stem water. in rocky mountainous regions characterized by thin However, if sap flow has a good fitting relationship soils and high gravel content. Moreover, with inci- with the large VPD, the sap flow is primarily used dences of seasonal drought becoming rampant and for transpiration. more intense in these regions owing to global cli- Numerous studies have explored daytime transpir- mate change, the adaptations of species in these ation and quantified the amount of water that tran- mixed forests to this heterogeneous change with spired (Fu et al. 2016;Wuetal. 2019; McCormick changing water sources remain unclear. et al. 2021). However, the amount of nocturnal Several studies have investigated the proportion of water supplementation has largely been ignored. water absorbed from each source and quantified the Consequently, substantial errors may occur when diurnal transpiration (Palacio et al. 2014;Wu et al. calculating the water balance in an ecosystem, 2016; Liu et al. 2020). Although previous studies impacting the development of management strat- have established that stomata are closed at night, egies. Therefore, if the amounts of each water frac- and there is no sap flow during this period (Zeppel tion used for transpiration and nocturnal sap flow et al. 2014; Zhang et al. 2020), with the develop- were accurately quantified, existing formulae or ment and improvement in technologies, nocturnal models for calculating water balance could be re- sap flow has been confirmed in plants in different vised. Therefore, it is paramount to quantitatively habitats (Hentschel et al. 2013;Siddiqand Cao distinguish the flux and proportion of water 2018;Chenetal. 2020). Nocturnal sap flow has absorbed, transported and transpired in a mixed for- been rarely considered in traditional models owing est. In this study, we employed the isotope (δ H to the small proportion of nocturnal sap flow com- and δ O) technique and heat ratio method to i) de- pared to the overall sap flow. However, for some termine the water absorption ratio from the differ- plant species, nocturnal sap flow comprises a large ent water sources and the symbiotic mechanism of proportion of the overall sap flow (Alvarado-Bar- the mixed forest; ii) quantify the amount of water rientos et al. 2015;Dietal. 2019a, 2019b; Flo et al. that flows in the nocturnal sap and quantify the 2019). For example, Barbeta et al. (2012) established proportions of water transpired and stored in plants. that Quercus ilex (holly oak) growing in the Medi- Our results will provide a scientific reference for terranean climate with annual precipitation of 350 further research on the underlying mechanisms of mm had a nocturnal sap flow of 40% of the overall water cycling in forest ecosystems. flow. In addition, the nocturnal sap flow in Q. oleoides in the central USA increased from 8% dur- Materials and methods ing the rainy season to 20% during the dry season Site description (Cavender-Bares et al. 2007). Based on these find- The study was conducted at the Forest Ecosystem ings, nocturnal sap flow cannot be neglected. Noc- Positioning Research Station in Beijing (40°03′ N, turnal sap flow effectively improves the leaf and 116°05′ E). The station lies at an elevation of 240 m stem water potential before dawn and reduces above sea level with a warm temperate semi-humid embolisms in the xylem (Forster 2014). However, monsoon climate. The annual average precipitation nocturnal sap flow is not equivalent to nocturnal and potential evapotranspiration were 630 and 1800 transpiration (Binks et al. 2020). During the night, mm, respectively. June to September precipitation some sap is transpired through the stomata (30%– comprised 70% of the annual precipitation. The 60%), and some is used to supplement the stem average annual temperature was 11.6 °C with 2662 h water (40%–70%) (Gribovszki et al. 2015). Huang of sunshine. The primary forest vegetation includes Liu et al. Forest Ecosystems (2021) 8:72 Page 3 of 13 Platycladus orientalis and Quercus variabilis planta- Spring (40°03′ N, 116°05′ E) 310 m southwest of the tions established after the 1960s. Broussonetia plots. papyrifera, Vitex negundo, Lespedeza bicolor,and other shrubs are underneath the canopy. The soil Stable isotope analysis type is leached cinnamon with a thickness of 80– The isotopic ratios in the samples were determined at 100 cm, the humus content is high, and the deep the Ecohydrological Processes and Mechanisms Labora- soil primarily consists of gravel. tory, Beijing Forestry University, China. The water in the soil and branches samples was extracted by low- 2 18 Experimental design temperature vacuum condensation, and δ H/δ O was Three plots measuring 20 m × 20 m each were estab- analyzed using a liquid water isotope analyzer (LGR 2 18 lished at the study area. Six P. orientalis and Q. var- DLI-100, USA). The ratio of H and O was recorded in iabilis with average height, diameter at breast height parts per thousand of the “standard average ocean (DBH), and crown width were randomly selected water” with a precision of determination of 0.3‰ and from each plot (Table 1). In each plot, three ECH O 0.1‰, respectively, and expressed as follows: soil moisture sensors (Decagon Devices, Pullman, WA, USA) were installed at three sampling points R −R sample standard to measure the soil water content (SWC) at 0–20, δXðÞ ‰ ¼  1000 ð1Þ standard 20–40, 40–60, 60–80, and 80–100 cm. The ECH O sensors were connected to a Em50/R data collection box (Decagon Devices, Pullman, WA, USA), which The ratio of water absorption by trees recorded data every 30 min and simultaneously The isotopic ratios of water in the branches carry the stored it in a computer. The data for precipitation, isotopic information of all the water sources since water radiation, atmospheric temperature, and relative hu- is absorbed through the roots. Owing to this, the Mix- midity in the study area were collected from a for- SIAR model was used to quantify the water absorption est weather station HOBO (U30-NRC; Onset, ratio of trees (Phillips et al. 2005) using the following Bourne, MA USA) located 1 km away from the ex- equations: perimental plots. δX ¼ c1δX1 þ c2δX2 þ c3δX3 þ c4δX4 Quantification of the water amounts used for þ c5δX5 ð2Þ physiological processes Determination of the water source: branches, soil, and c1 þ c2 þ c3 þ c4 þ c5 ¼ 1 ð3Þ groundwater sampling 2 18 In each plot, three trees with good vigor and similar where, X is the H/ O value of tree branch water (‰); 2 18 height/DBH were randomly selected, and their annual X , X , X , X , and X are the H/ O values of soil water 1 2 3 4 5 non-green branches (0.3–0.6 cm in diameter) were col- at 0–20, 20–40, 40–60, 60–100 cm, and groundwater lected at the same height (5 and 6 m for P. orientalis and levels, respectively; and c , c , c , c , and c represent the 1 2 3 4 5 Q. variabilis, respectively) from the ground. The bark of absorption ratio of trees for soil water from 0 to 20, 20– the branches was removed to obtain the xylem. Three 40, 40–60, 60–100 cm, and groundwater levels, samples were collected per tree. respectively. Three soil samples were collected from 0 to 20, 20–40, 40–60, 60–80, and 80–100 cm within a radius of 0.5 to Quantification of the amount of water for migration (Q) 1 m from the sampled trees using an auger with a diam- Three P. orientalis and Q. variabilis tree species eter of 3.5 cm and a length of 120 cm. The sampled with an average tree height and DBH were selected branches and soil were immediately placed into a 50-mL at each observation point, which were the same sampling bottle, sealed with Parafilm®, and stored at − points for the isotope sample collection in the plot. 4 °C until the isotopes were determined. Three sap flow meters (SFM , HRM 30, ICT Inter- Simultaneously, three spring water samples (represent- national PTY, Armidale, Australia) were installed at ing groundwater) were collected from the Miaolingshan a height of roughly 1.35 m on the three selected Table 1 Basic information about the tree species measured Tree species Number Average height (m) Diameter at breast height (cm) Platycladus orientalis 37 7.16 ± 1.53 7.60 ± 2.83 Quercus variabilis 43 9.18 ± 1.15 11.59 ± 3.91 Liu et al. Forest Ecosystems (2021) 8:72 Page 4 of 13 trees to monitor the sap flow rate. The SFM flow- correlation analysis was conducted on the data after meter has three probes, which simultaneously meas- dislocation. The dislocation time corresponding to ure two-way flows. Three cores were taken from the maximum correlation coefficient was the storage each tree at roughly 1.35 m using a borer with 5 time (The results of correlation analysis after dis- mm increments, and the radii of cross-sections and location are shown in the Supplemental Table S1). heartwood were measured with a ruler. Three cylin- The migration flux during this time is the stored drical probes were inserted into the sapwood water. The VPD was calculated as through the drilled holes. The device was wrapped and sealed with insulated and radiation-proof 17:27T aluminum foil to prevent rainwater from entering Taþ237:3 VPD ¼ 0:61078  e ðÞ 1−RH ð7Þ and protect against direct solar radiation. The data acquisition interval of the SFM flowmeter was set where T and RH are atmospheric temperature (°) and 1 a at 10 min, and the water that migrated through the relative humidity (%), respectively. tree was calculated using the following equations (Allen et al. 2011): Quantification of water used for transpiration (Q ) Tr Sap flow during the stomatal opening represents the rate of transpiration in a plant. Therefore, the water used for Q ¼ V A ¼ V A þ V A ð4Þ s s ot 1 in 2 transpiration was quantified by determining the stomatal opening time via the VPD and radiation. The Q was Tr V ρðÞ c þ m c h W c s V ¼ ð5Þ s determined by calculating the difference between the ρ c overall sap flow and water storage. k t V ¼ ln  3600 ð6Þ Data analysis x t The statistical analyses were performed using SPSS Here, Q is the total migration (mL); V is the sap flow 16.0 (SPSS, Inc., Chicago, IL, USA). Descriptive sta- − 1 2 velocity (cm·s ); A is the sapwood area (cm ); V and tistics were applied to calculate the means and s ot V are the sap flow velocities of the thermocouple inside standard deviations for each set of replicates. First, in − 1 and outside the temperature probe (cm·s ), respect- a one-way analysis of variance (ANOVA) was per- ively; A and A are the areas of the outer ring and the formed to test the effect of tree species on the mi- 1 2 inner ring, respectively (cm ); V is the heat pulse rate gration flux, transpiration, and storage. A two-way − 1 (cm·s ); k is the thermal diffusion coefficient of fresh ANOVA was then performed to analyze the differ- wood; x is the distance between the thermal probe and ences in SWC, isotopic composition, season, and the temperature probe; t and t are the variation in soil depth as independent factors. In addition, a 1 2 temperature in the upward and downward directions, re- three-way ANOVA was used to analyze the differ- − 3 spectively; ρ is the wood density (g·cm ); c and c are ences in water source using the soil depth, tree spe- b w s − 1 the specific heat capacities of fresh wood (1200 J·kg ·° cies, and season as independent factors. − 1 C , 20 °C) and specific heat capacity of liquid flow − 1 − 1 (4182 J·kg ·°C , 20 °C), respectively; m and ρ are the Results c s moisture content and density of fresh wood, Variation in soil water content and meteorological respectively. conditions The annual precipitation totals in 2015 and 2016 Quantification of the water used for migration were 580.0 and 649.8 mm, respectively (Fig. 1), with The water migrating through the trees can be divided the precipitation in June to September comprising into the water used in transpiration and storage. 79.0% and 80.5% of the total annual precipitation in 2015 and 2016, respectively. June to September is Quantification of the used for water storage (Q ) the rainy season, while October to May comprises The amount of water stored at night depends on the dry seasons. During the dry season, the average the storage time as determined by the dislocation SWC in the 0–20-, 20–40-, 40–60-, 60–80-, and correlation method (Maherali and DeLucia 2001). 80–100-cm layers were 11.6%, 12.6%, 11.9%, 9.8%, The data series of sap flow velocity and the corre- and 9.2%, respectively. However, the SWC in the sponding VPD/radiation were established according five soil layers increased at different degrees after it to the observation time sequence. The sap flow vel- rained, followed by a decrease. The average SWC in ocity and VPD/radiation based on dislocation were the five layers during the rainy season was 16.5%, successively recorded every half hour, and a 17.0%, 17.6%, 14.0%, and 11.2%, respectively, 42.2%, Liu et al. Forest Ecosystems (2021) 8:72 Page 5 of 13 Fig. 1 Variation in precipitation and mean soil water content in the Forest Ecosystem Positioning Research Station, north China, during the study period. The blue shading corresponds to the dry season, while the white region corresponds to the rainy season 35.0%, 39.7%, 17.5%, and 13.9% higher than those in 0–20-cm layer were − 32% and − 2.13‰,which were the dry season. After approximately 10 mm of pre- 19.50%, 26.29%, 38.19%, and 53.59% higher than cipitation, the SWC increased by 64.22% in the 0– those in the 20–40-, 40–60-, 60–80-, and 80–100-cm 20-cm layer, but no significant changes were ob- layers, respectively (P < 0.05). However, the δ Hand served in the other layers (P > 0.05). After > 50 mm δ Ointhe 80–100-cm layer were significantly lower precipitation, the SWC increased in all the five soil than those of the other layers (P < 0.05). Neverthe- 2 18 layers, with a lag time effect in the deeper layers. less, the δ Hand δ O in each layer decreased grad- The total solar radiation (TR) and VPD had a ually during the rainy season, with 96.93%, 46.84%, similar trend, with an initial increase and a subse- 38.76%, 25.92%, and 15.49% decreases, respectively quent decrease (Fig. 2). The peak VPD appeared 0– across the five soil layers. 3h later compared to TR. The TR was 0 and VPD> Branch water in P. orientalis ranged from − 0 Kpa from 19:00 to 06:00 at night. In January, 105.63‰ to − 37.82‰ for δ Hand − 14.09‰ to − mean and peak TR values were 87.1 and 174.6 0.19‰ for δ O, with more extreme values than − 2 W·m , respectively, while those of VPD values those of Q. variabilis (− 99.89‰ to − 36.24‰ for 2 18 were 0.35 and 0.59 Kpa, respectively. The TR and δ Hand − 13.58‰ to − 2.61‰ for δ O). The mean 2 18 VPD values gradually increased with seasonal vari- values of δ Hand δ O in the branch water in P. ation from January to July and decreased from Au- orientalis during the dry season were − 56.53‰ and gust to December. The mean and peak TR values − 4.99‰, which were 28.56% and 54.30% higher than − 2 2 reached 176.2 and 491.6 W·m in July, which were those of Q. variabilis.Additionally,the δ Hand 2.0- and 2.8-fold higher than the mean and peak δ O in the branch water in P. orientalis during the values in January, respectively. In addition, the mean rainy season were 45.67% and 69.93% higher than and peak values of VPD reached 2.57 and 6.84 Kpa those in the dry season, while in Q. variabilis they in July, which was 7.3- and 11.6-fold higher than were 6.31% and 9.53% higher, respectively. those in January, respectively. However, there were The water absorption by P. orientalis and Q. varia- no significant differences in TR and VPD between bilis from the different water sources fluctuated with January and December. the season (Fig. 5). The two species absorbed water from the groundwater from the 60–100-cm layer, al- Water absorption by trees though Q. variabilis also absorbed water from the 2 18 The δ Hand δ O in soil and branch water of P. 0–20-cm (21.7%) and 20–40-cm (19.9%) layers dur- orientalis and Q. variabilis significantly fluctuated ing the dry season. In the rainy season, P. orientalis across the different seasons (Figs. 3 and 4). The δ H used groundwater (30.5%) and water from the 60– and δ O in soil water were higher in the dry season 100-cm soil layer (21.6%) and 0–20-cm layer (26.6%). than in the rainy season (P < 0.05), implying that the The absorption ratio of water from the 20–40-cm isotope fractionation effect in soil water in the dry layer used by Q. variabilis during the rainy season season was more pronounced than in the rainy sea- was 47.4% lower than during the dry season, but the 2 18 son. During the dry season, the δ Hand δ Ointhe absorption ratio of groundwater increased by 68.2%. Liu et al. Forest Ecosystems (2021) 8:72 Page 6 of 13 Fig. 2 Variation in total solar radiation (TR) and vapor pressure deficit (VPD) in the Forest Ecosystem Positioning Research Station, North China, during the study period. The figure shows the observation data of TR and VPD randomly selected for 10 consecutive days each month P. orientalis used less water from the 20–40-cm and The proportions of water used in transpiration and water 40–60-cm soil layers, whereas Q. variabilis used less storage water from the 40–60-cm soil layer throughout the The annual mean water fluxes in P. orientalis and Q. − 1 experimental period. variabilis were 374.69 and 469.50 mm·year , respect- ively (Fig. 7). The average sap flux in P. orientalis was 20.19% lower than that of Q. variabilis. The amounts of Water migration of P. orientalis and Q. variabilis water used by P. orientalis for transpiration and storage − 1 The sap flow rate (SFR) of P. orientalis during the were 350.3 and 24.41 mm·year , respectively, account- dry season were bimodal over the observation ing for 93.49% and 6.51% of the sap flow, respectively. period (Fig. 6). SFR gradually increased, reaching its Moreover, the amounts of water used by Q. variabilis maximum at 11:00 and 14:30, respectively, followed for transpiration and storage were 440.85 and 28.65 − 1 by a decrease. In contrast, the variation in SFR of mm·year , respectively, accounting for 93.91% and Q. variabilis showed no peak during the dry season 6.09% of the sap flow, respectively, which implies that but had a single peak during the wet season. The the plants used most of the water for transpiration. − 1 mean SFR in P. orientalis (0.0008 cm·s )was four However, there was no significant difference in water times higher than that of Q. variabilis,and the used by P. orientalis and Q. variabilis for transpiration − 1 maximum SFR in P. orientalis (0.0022 cm·s )was and storage (P > 0.05). 4.4 times higher than that of Q. variabilis during the dry season. Additionally, the mean SFR in Q. Discussion variabilis during the wet season was 6.5 times that Water absorption by trees in the dry season, while the mean SFR of P. orienta- P. orientalis and Q. variabilis showed different water lis during the wet season was not significantly dif- usage in the same habitat, related to their root distribution ferent from that in the dry season (P > 0.05). and water conditions. More than 50% of the P. orientalis Liu et al. Forest Ecosystems (2021) 8:72 Page 7 of 13 Fig. 3 Variation in mean (± SD) isotopic values of soil water in the Forest Ecosystem Positioning Research Station, North China during the study period root biomass is distributed in the 0–20-cm layer (Liu et al. In contrast to P. orientalis, 79.2% of the main root 2019), and its highly developed surface root system of P. system of Q. variabilis is highly developed and uni- orientalis is more sensitive to precipitation. Therefore, P. formly distributed in different soil layers (Liu et al. orientalis used water from the 0–20-cm layer following 2019); hence, it can use multiple water sources. precipitation, consistent with findings of Jia et al. (2017), However, it uses a higher surface soil water ratio who established that P. orientalis primarily absorbed water during thedry season,possiblyowing to theshort from the surface soil during the rainy season to maintain transport distance of surface soil water and the normal physiological activities and then switched its water lower energy consumption. This suggests that Q. source to deep soil layers during the dry season. This variabilis prefers surface soil water during the dry phenomenon is known as a “dimorphic” structural feature season, consistent with previous findings, which of the root system (Evaristo et al. 2016; Cuneo et al. 2018; established that plants with uniform root distribu- Poca et al. 2019). Previous studies have also established tions preferentially absorb water from surface soil variation in water usage from different sources in Q. pub- layers (Fan et al. 2017; Cai et al. 2018; Cuneo et al. escens, Populus, Robinia pseudoacacia,and Pinus tabulae- 2018). However, Q. variabilis absorbs water from formis (Gebauer and Ehleringer 2000; Liu et al. 2020; the deep soil layers via its highly developed root Ripullone et al. 2020). system to maintain a high transpiration rate during Liu et al. Forest Ecosystems (2021) 8:72 Page 8 of 13 Fig. 4 Typical diurnal variation in mean (± SD) isotopic values in Platycladus orientalis and Quercus variabilis branch water in the Forest Ecosystem Positioning Research Station, North China during the study period the rainy season. Wang et al. (2017)and Peddinti Water migration and use et al. (2020) have demonstrated that several plants We observed significant differences in water usage can take up deep soil water and groundwater and distribution between the two tree species, which through their developed roots throughout the grow- could be related to their characteristics. Molina et al. ing season, ensuring a stable water supply. The (2019) established that the aboveground biomass and threshold value of the root system response to SWC defoliation cycle are the main factors affecting SFR. is one of the key factors affecting water usage In our study, the SFR of P. orientalis was higher (Cuneo et al. 2018). In our study, the P. orientalis than that of Q. variabilis during the dormant period, root system was more sensitive to precipitation than probably because Q. variabilis is a broad-leaved de- that of Q. variabilis. These water uptake patterns in ciduous species, which had already shed its leaves, P. orientalis and Q. variabilis from different water while P. orientalis retained its leaves. In addition, sources result from long-term adaptation to seasonal the xylem vessel diameter and the crown width of Q. arid environments. Such strategies help reduce com- variabilis were greater than those of P. orientalis, petition for water with other tree species and im- which significantly improved the efficiency of water prove symbiotic ability among community species migration. In addition, Q. variabilis had more sto- (Yang et al. 2015; Jia et al. 2017; Liu et al. 2019). mata per leaf area than P. orientalis,and therateof Liu et al. Forest Ecosystems (2021) 8:72 Page 9 of 13 Fig. 5 Mean (± SD) absorption ratios of Platycladus orientalis and Quercus variabilis from different water sources in the Forest Ecosystem Positioning Research Station, North China during the study period water diffusion was higher, resulting in a higher SFR. capacity of trees depends on the trunk volume and Nocturnal sap flow does not necessarily represent the water pressure difference between the tree vol- nocturnal transpiration since there is a time lag ef- ume and root cap (Huang et al. 2017). This is con- fect in sap flow and stomatal aperture at night (Phil- sistent with the tree capacity, nocturnal water lips et al. 2003). A positive correlation between storage, and transpiration during the day in Q. var- nocturnal sap flow and the VPD indicates water used iabilis being significantly higher than in P. orientalis. for transpiration by the trees at night (Green et al. Nocturnal water storage alleviates drought stress and 1989;Hogg and Hurdle 1997; Fisher et al. 2007). helps plants overcome intense evaporation in the dry Otherwise, this water will be stored in the trunk at season (Huang et al. 2017). Nocturnal sap flow also night. However, in this study, the correlation be- facilitates oxygen and nutrient transport. For ex- tween sap flow rate and VPD was weak, implying ample, in Betula, it provides sufficient oxygen to that the sap flow at night was used for water storage sapwood parenteral cells (Daley and Phillipa 2006). in the trunk but not for nocturnal transpiration. The In addition, the phenomenon of hydraulic redistri- presence of nocturnal fluid flow comprising 5%–6% bution in P. orientalis was previously established in of total sap flow has been confirmed in both P. our study area (Liu et al. 2019). Nocturnal sap flow orientalis and Q. variabilis, which is consistent with reduces the water potential in plant leaves, negatively the findings in previous studies (Forster 2014; Siddiq affecting the hydraulic redistribution (Yu et al. 2018; and Cao 2018;Chenetal. 2020). The water storage Howard et al. 2009). Moreover, the findings in our Liu et al. Forest Ecosystems (2021) 8:72 Page 10 of 13 Fig. 6 Typical diurnal variation in sap flow rates in Platycladus orientalis and Quercus variabilis in the Forest Ecosystem Positioning Research Station, North China during the study period. The figure shows the observed sap flow rates randomly selected for 10 consecutive days in each month study suggest that nocturnal sap flow and root hy- orientalis and Q. variabilis comprised 6%–7% of the draulic redistribution can occur simultaneously, con- total water quantity, which cannot be ignored. sistent with previous findings, which demonstrated hydraulic redistribution contributes to the occur- Conclusions rence of nocturnal sap flow (Matimati et al. 2014;Fu We used an isotope technique and the heat ratio et al. 2018;Hafneretal. 2020). The root hydraulic method to quantify the utilization ratio of water redistribution in P. orientalis effectively alleviates the source and sap flow and determine the proportion of spatial heterogeneity of soil water that meets its water used in transpiration and storage. The results water requirement and neighboring trees (Matimati indicated that P. orientalis and Q. variabilis uptake et al. 2014; Fan et al. 2017). P. orientalis water usage water from multiple sources simultaneously and facilitates water sharing, which is conducive to the showed strong plasticity to water sources. P. orienta- coexistence of different species. Although the sap lis was sensitive to the variation in SWC and quickly flow and diurnal transpiration in P. orientalis were absorbed surface soil water during the rainy season. lower than those of Q. variabilis, the proportion of Q. variabilis absorbed water from sources with water stored was higher in P. orientalis, implying higher and stable water content and did not change that P. orientalis balances the water deficit better its sources, but did increase its uptake of ground- than Q. variabilis. This also explains why P. orienta- water during the rainy season. The sap flow in P. lis is widely distributed as a pioneer tree species in orientalis and Q. variabilis was mainly used for tran- North China. The amount of water stored in P. spiration, and 6%–7% of the water was used for Liu et al. Forest Ecosystems (2021) 8:72 Page 11 of 13 Fig. 7 Schematic representation of water uptake, migration, and use in Platycladus orientalis and Quercus variabilis. The blue font in the yellow box indicates the absorption ratio of trees from each water source during the dry and wet seasons. The numbers that are light blue indicate the migration flux in trees throughout the year, while the pink arrow indicates the water usage process in trees storage in the trunk. However, a long-term survey of Availability of data and materials Available on request. plant water movement partitioning is needed to pro- vide more insights on the partitioning of tree water Declarations usage into storage and transpiration in such mixed Ethics approval and consent to participate forest systems. Not applicable. Abbreviations Consent for publication VPD: Vapor pressure deficit; DBH: Diameter at breast height; SWC: Soil water Not Applicable. content; S: Water storage; Q : Quantification of the water used for Tr transpiration; SFR: Sap flow rates; TR: Total solar radiation Competing interests The authors declare no competing interests. Supplementary Information Author details The online version contains supplementary material available at https://doi. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing org/10.1186/s40663-021-00353-5. Forestry University, Nanjing 210037, China. Key Laboratory of Soil and Water Conservation and Desertification Combating of Ministry of Education, Beijing Forestry University, Beijing 100083, China. Additional file 1. Received: 16 July 2021 Accepted: 20 October 2021 Acknowledgments We thank Huan Zhang and Weiwei Lu for their help with fieldwork. 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Journal

"Forest Ecosystems" – Springer Journals

Published: Nov 18, 2021

Keywords: Water migration; Water uptake; Nocturnal sap flow; Transpiration

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