Introduction

Shell ridges are unique beach ridge landforms near the high tide line that forms from the accumulation of residual shells from dead mollusks and their fragments, which are transported by waves. The shell ridges in the Yellow River Delta compose one of the three largest groups of ancient shell ridges in the world, and this group is the only one composed of both new and old shell ridges. Owing to its close proximity to a muddy coastal zone, the groundwater below these shell ridges is relatively shallow and is easily affected by natural factors, e.g., tides and high evaporation-precipitation ratios1. The soil in the beach ridge area of the shell ridges, which sits at a relatively high altitude, undergoes frequent dry/wet cycles but has been experiencing an increasing frequency of severe drought stress events. The soil in the beach ridge area of the shell ridges has a high porosity, a low capacity to store and retain water, and low capillary action. These properties have led to a lack of freshwater resources in the shell sand habitat. Soil water content is a key factor that limits plant growth and community succession in shell sand habitats2. Periploca sepium Bunge is a dominant shrub species on the shell ridges of the Yellow River Delta. Owing to its exceptional capability to disrupt wind, hold sand, resist drought, and retain water, P. sepium Bunge has become a primary tree species studied for its ability to persist under drought conditions3,4. During drought stress, the soil water content substantial affects plants in terms of their physiological, biochemical, and photosynthesis characteristics as well as their water-related physiological processes. Dominant plants can withstand stress by regulating their metabolic rhythm2,5. Therefore, studying the physiological and ecological characteristics of the dominant shrubs in shell sand on the Yellow River Delta under drought stress is of great importance for elucidating the mechanism through which xerophytic vegetation in the beach ridge area of shell ridges adapts to drought stress.

Plants adapt to stress conditions by continuously varying and adjusting their photosynthesis, water transport, physiological and biochemical characteristics. The light-compensation point (LCP), light-saturation point (LSP), and maximum net photosynthesis rate (Pmax) of plant leaves are the primary parameters used for measuring photosynthesis physiological processes in response to stress conditions1,6. Specifically, the initial fluorescence (F0), photochemical yield of photosystem II (ΦPSII), and nonphotochemical quenching coefficient (NPQ) are essential parameters for evaluating the photosynthesis regulatory mechanism of plants7,8. Enzyme activity is also a factor that can indicate changes in plant physiological activity9,10. Drought stress can cause increased activity of enzymes such as superoxide dismutase (SOD) and peroxidase (POD)11. Under suitable water conditions on shell ridges, Tamarix chinensis exhibited relatively high photosynthesis efficiency, although waterlogging and drought stress affected its photosynthesis efficiency by affecting leaf gas exchange12. Under mild drought stress, plants close there stomata. This action not only prevents the loss of water required for vital activities but also prevents atmospheric carbon dioxide (CO2) entering the leaves, resulting in a decrease in intercellular CO2 concentration; because of the deficiency in raw materials, photosynthesis is inhibited13. As drought stress increases, the photosynthesis organs in plants start to sustain damage. Additionally, the electron transport chain in photosystem II (PSII) can become damaged or even disrupted, resulting in a rapid decrease in photosynthesis efficiency and a sharp increase in the intercellular CO2 concentration. As a result, the stomatal function is also severely affected13. Therefore, the physiological regulatory mechanisms that plants use to adapt to drought stress can vary substantially depending on the soil texture, water conditions, and plant species.

In recent years, researchers have investigated the photosynthesis characteristics, water physiology, and physiological and biochemical processes of plants. However, most of these studies evaluated the effects of drought stress on individual physiological indices of xerophytes and focused primarily on the effects of drought stress on the photosynthesis parameters and physiological variations of typical xerophytic plants or crop species14,15,16,17. Vieira et al. reported that drought stress led to a decrease in the net photosynthesis rate (Pn) and stomatal conductance (Gs) of Vateria macrocarpa and an increase in its SOD, ascorbate peroxidase, and catalase activities. Additionally, the authors reported that these parameters recovered to control levels after rehydration14. Liu et al. reported that severe drought stress damaged or even disrupted the photosynthetic electron transport chain in maize, significantly decreasing the photosynthesis activity15. Similarly, Ou et al. reported a significant decrease in the Pmax and dark respiration rate (Rd) of Excentrodendron hsienmu and a significant increase in its osmotic adjustment substance and malondialdehyde (MDA) contents in a simulated arid karst habitat16. Xin et al. discovered that the stem sap flow rate and average daily stem sap flow of two Populus species from the Tibetan region are significantly lower during the dry season than during the rainy season and that the stem sap flow dynamics shift mostly from a multimodal pattern during the rainy season to a unimodal pattern during the dry season17. Plants suffer from photoinhibition caused by photosynthesis carbon assimilation and unbalanced water loss during drought stress1,18. Additionally, drought stress can also easily lead to the formation of reactive oxygen species and can disrupt the scavenging equilibrium in plants, resulting in membrane lipid peroxidation19,20. With respect to the relationships between the physiological and ecological characteristics of plants and water, there are generally two primary types of water treatment methods. One type focuses on water adaptability under mild, moderate, and severe stress. These methods address the patterns of plant adaptations to long-term drought stress by evaluating their physiological photosynthesis parameters and relevant mechanisms21. By using a serial, short-term, multilevel water gradient, the other method involves investigating the threshold effect of the soil water content on the physiological photosynthesis parameters of plants1,5,12. Physiological and ecological changes in plants under drought stress in shell sand habitats are less frequently studied. How changes in the water contents of shell sand affect the photosynthesis, water transport, and physiological and biochemical processes of the dominant species P. sepium Bunge along the shell ridges in the Yellow River Delta as well as the tolerance and adaptability of P. sepium Bunge to drought stress in shell sand remain unknown. Few studies have investigated the comprehensive photosynthesis efficiency, water physiology, and physiological and biochemical processes of P. sepium Bunge in shell sand habitats. The physiological and ecological regulatory mechanisms through which P. sepium Bunge adapts to drought stress in shell sand remain unclear. These factors somewhat hinder water management and the selection of habitats with suitable soil water contents, both of which are vital for guiding the planting of P. sepium Bunge in the degraded ecosystem of the shell ridges along the Yellow River Delta.

Hence, this study investigated four-year-old seedlings of P. sepium Bunge, a typical xerophytic shrub species that grows along the shell ridges in the Yellow River Delta, on four simulated shell sand habitats whose water conditions differ. Several P. sepium Bunge indices and parameters were measured, including leaf photosynthesis physiological indices and chlorophyll fluorescence parameters, stem sap flow parameters, and primary physiological and biochemical indices. The effects of drought stress on the physiological and ecological characteristics of P. sepium Bunge in shell sand habitats were evaluated. This study aimed to provide a reference for the water management of plant resources in dry shell sand habitats.

Results

Light responses according to the physiological photosynthesis indices

As demonstrated in Fig. 1a, the rectangular hyperbolic correction model had a high goodness of fit with the Pn–PAR response process in the leaves of P. sepium Bunge from the four shell sand habitats whose water conditions differed. The fitted correlation coefficients for the control (CK), T1, T2, and T3 groups were 0.998, 0.999, 0.995, and 0.932, respectively. As the drought stress increased, the Pn of P. sepium Bunge decreased significantly (P < 0.05). When the PAR was 1200 µmol∙m−2 ∙ s−1, the Pn values of P. sepium Bunge in the T1, T2, and T3 groups were 23.50%, 42.44%, and 95.12% lower than that in the CK, respectively. Figure 1b shows that as the drought stress increased, the Gs of the leaves decreased significantly (P < 0.05). When the PAR was 1200 µmol∙m−2 ∙ s−1, the Gs of the leaves in the CK was the greatest, at 243.56 mmol∙m−2∙s−1, and the Gs values in the T1, T2, and T3 groups were 41.42%, 30.88%, and 6.89% of that in the CK, respectively.

Figure 1
figure 1

Light response of net photosynthesis rate (a) and stomatal conductance (b) of P. sepium leaves under various drought stress conditions.

Full size image

Light-response parameters of photosynthesis

As the drought stress increased, the LCP of the leaves from P. sepium Bunge increased significantly (P < 0.05) (Table 1). The LCP values for the T1, T2, and T3 groups were 1.72%, 87.93%, and 67.24% greater than that for the CK, respectively. The LSP values of the leaves from the CK, T2, and T3 groups were 20.68%, 32.28%, and 63.64% lower than that from the T1 group, respectively. As the drought stress increased, both the apparent quantum yield (AQY) and Rd of the leaves decreased significantly (P < 0.05). The leaf Pmax was the greatest in the CK, followed by the T1, T2, and T3 groups. The Pmax values of the leaves in the T1, T2, and T3 groups were 78.68%, 54.86%, and 9.95% of the value in the CK, respectively.

Table 1 Light-compensation point (LCP), light-saturation point (LSP), apparent quantum yield (AQY), dark respiration rate (Rd) and light-saturated net photosynthesis rate (Pmax) of P. sepium leaves under various drought stress conditions.
Full size table

Chlorophyll fluorescence characteristics

As the drought stress level increased, the Fv/Fm ratio of the P. sepium Bunge leaves decreased significantly (P < 0.05). However, there was no significant difference in the Fv/Fm ratio between the CK, T1, and T2 groups (P > 0.05) (Fig. 2). The NPQ values of the leaves in the T1, T2, and T3 groups were 40.10%, 61.44%, and 119.88% greater than that in the CK, respectively. The effects of drought stress on the ETR and ΦPSII of the leaves exhibited the same pattern. As the drought stress increased, there was a significant decrease in the leaf ETR (P < 0.05). The ETRs in the leaves in the T1, T2, and T3 groups were 27.84%, 32.14%, and 57.65% lower than that in the CK, respectively.

Figure 2
figure 2

Potential photochemical efficiency and nonphotochemical quenching coefficient (a) as well as the actual photochemical efficiency and noncyclic photosynthetic electron transport rate (b) of leaves of P. sepium under various drought stress conditions.

Full size image

Physiological and biochemical characteristics

As the drought stress increased, the SOD activity first increased but then decreased, and the POD activity increased (Fig. 3a). The POD activity in the T1, T2, and T3 groups was 2.80, 3.01, and 4.19 times that in the CK, respectively. As the drought stress increased, there was a significant increase in both the proline (Pro) and soluble sugar (Ss) (two types of osmotic adjustment substances) contents in the leaves (P < 0.05) (Fig. 3b). The MDA contents in the T1, T2, and T3 groups were 1.50, 2.02, and 1.80 times that in the CK, respectively (Fig. 3c).

Figure 3
figure 3

Superoxide dismutase and peroxidase activity (a), proline and soluble sugar contents (b) and malondialdehyde content (c) of leaves of P. sepium under various drought stress conditions.

Full size image

Changes in stem sap flow

There was a significant difference in the daily stem sap flow rate dynamics in P. sepium Bunge under the different water treatments (P < 0.05) (Fig. 4a). Under mild drought stress, the stem sap flow activity in P. sepium Bunge occurred primarily between 4:30 and 19:00. Under the other water conditions, stem sap flow activity occurred throughout the day. As the drought stress increased, the stem sap flow rate decreased overall. The daily cumulative stem sap flow was the greatest in the CK, followed by the T1, T2, and T3 groups (Fig. 4b). The daily cumulative stem sap flow rates in the T1, T2, and T3 groups were 23.98%, 33.3%, and 63.94% lower than that (205.21 g·d−1) in the CK, respectively. The daily cumulative stem sap flow in the T3 group increased slowly and linearly. The slope of the daily cumulative stem sap flow curve for the T2 group decreased over time, and the curve exhibited an inverted “Z” shape; the daily cumulative stem sap flow exhibited a typical “S”-shaped pattern in the CK and T1 groups.

Figure 4
figure 4

Daily stem sap flow rate dynamics (a) and daily cumulative stem sap flow (b) in P. sepium under various drought stress conditions.

Full size image

Changes in the T r and WUE

There was a significant difference in the Tr values of the P. sepium Bunge leaves under different drought stress levels (P < 0.05). The Tr was the greatest in the CK, followed by the T1, T2, and T3 groups (Fig. 5). When the PAR was 1200 µmol∙m−2∙s−1, the Tr results for the T1, T2, and T3 groups were 50.82%, 37.16%, and 10.11% of that (3.66 mmol∙m−2∙s−1) in the CK. As the drought stress increased, the water-use efficiency (WUE) of the leaves first increased but then decreased significantly (P < 0.05). The WUE remained at a relatively high level in the T1 and T2 groups but was the lowest in the T3 group. When the PAR was 1200 µmol∙m−2∙s−1, the WUE values of the leaves in the T1 and T2 groups were 37.87% and 38.09% greater than that in the CK, respectively, whereas the WUE of the leaves in the T3 group was 59.84% lower than that in the CK.

Figure 5
figure 5

Transpiration rate and water-use efficiency of leaves of P. sepium under various drought stress conditions.

Full size image

Discussion

There was a significant difference in the extent of the decreases in the Pn and Gs between the P. sepium leaves in the shell sand habitats under different drought stress conditions. The decrease in the photosynthesis efficiency of the leaves is related to their stomatal state12. Research has shown a significant decrease in both the Pn and Gs of Populus × euramericana ‘Neva’ and Phaseolus vulgaris L., a difference in the stomatal limitation mechanism between these two species, and a significant positive correlation between the Pn and Gs under various water stress conditions22,23. These findings are similar to those of the present study. The leaves of P. sepium Bunge adapt to drought stress in shell sand via stomatal regulation. This mechanism varies significantly with the drought stress level. As the drought stress level increased, the Pn of the leaves of the four-year-old P. sepium Bunge seedlings decreased significantly, whereas the Pn of the leaves of one-year-old P. sepium Bunge seedlings first increased but then decreased24. This may be because young P. sepium Bunge seedlings are more sensitive to drought stress. The response of the low-intensity light-use efficiency (LUE) of the leaves to drought stress is nonsignificant. However, the low-intensity LUE of the leaves can decrease significantly under severe drought stress. Under natural conditions, the AQY of plant leaves ranges from 0.03 to 0.05 mol·mol−125. In the present study, the AQY of the leaves from the shell sand habitats was significantly lower than this range. This result suggests that the photosynthesis capability of P. sepium Bunge is relatively weak under low-intensity light. The difference between the LSP and LCP of the leaves under severe drought stress was only 40.10% of that in the CK. This finding indicates that drought stress can significantly reduce the LUE and light ecological amplitude of leaves during photosynthesis. Consistent changes in the Rd and AOY of the P. sepium Bunge leaves under drought stress were detected. This finding suggests that leaves can adapt to drought stress by decreasing respiration. Waterlogging and drought stress resulted in a significant decrease in the AQY, Pmax, and LSP of leaves of T. chinensis growing in a shell sand habitat, and there was a significant increase in their LCP12. These findings are similar to those of the present study. The AQY and Rd of Aralia elata first increased but then decreased as drought stress increased, and both of its AQY-drought stress and Rd-drought stress curves exhibited an “n” shape26. While the AQY and Rd of A. elata26 start to decrease at a lower water stress level than did those of P. sepium Bunge on shell sand ridges, the AQY and Rd of A. elata decrease more sharply as the water stress level increases. Thus, P. sepium Bunge exhibits a greater LUE under drought stress than under no drought stress.

A significant decrease in the Fv/Fm ratios of leaves of P. sepium Bunge growing in the shell sand habitat under severe drought stress was detected. This finding suggests that under these conditions, there was a decrease in the photochemical quantum yield of PSII in the electron transport chain in the leaves, and the photosynthesis process suffered from severe photoinhibition21,27. Under severe drought stress, the leaves suffered from severe photoinhibition, and there was a significant decrease in the number of electrons for the light reactions or CO2 assimilation and a decrease in photosynthesis efficiency21,28. A significant positive correlation was detected between the changes in the ETR and ΦPSII28. Under mild drought stress (relative water content (RWC) > 40%), there was a relatively insignificant decrease in the NPQ of the leaves, which had a relatively low heat dissipation capacity. Drought stress at this level did not cause damage to the photosynthesis organs of the leaves. Under mild drought stress, the leaf photosynthesis activity was relatively insignificantly inhibited and could be restored by measures such as rehydration12,29. Under severe drought stress (RWC ≤ 40%), there was a significant decrease in the NPQ of the leaves and a significant increase in their heat dissipation. Additionally, under severe drought stress, the photosynthesis ability of the leaves could be easily inhibited and could not be restored12,29. The Pn of the leaves was extremely and significantly negatively correlated with the NPQ values but significantly positively correlated with ФPSII, ETR, and Rd (Table 2). This finding suggests that orderly electron transport along the electron transport chain is the determinant for photosynthesis output and that light energy dissipation is a key protective mechanism of photosynthesis under stress conditions27,28. In addition, respiration also regulates normal photosynthesis output to a certain extent. A decrease in the soil water content led to a significant decrease in the Fv/Fm ratio, ΦPSII, and ETR of four wolfberry species and a significant increase in their NPQ30. However, compared with that of P. sepium Bunge, the decrease in the Fv/Fm ratio of these four wolfberry species was more pronounced. Silva et al. reported that, under various water stress conditions, there was no significant difference in the Fv/Fm ratio of Jatropha curcas, a significant decrease in its ETR, and a significant increase in its NPQ31. Cecilia et al.32 reported that, increasing in excessive electron transport and non-photochemical quenching was shown on Celtis australis due to photosynthesis and gas exchange processes inhibited, and C. australis showed conserved water utilization behavior and was sensitive to drought stress32. These changes are consistent with those observed in this study. The effects of drought stress on the physiological photosynthesis processes of various plant species across various habitats can evidently differ relatively significantly.

Table 2 Correlation coefficients of photosynthesis and physiological water indices of P. sepium.
Full size table

Under moderate drought stress, the SOD activity in the P. sepium Bunge leaves was relatively highly adaptable and adjustable. However, as the drought stress level increased, the ability to alter the SOD activity in the leaves was inhibited. As a result, there was a decrease in SOD activity. In comparison, there was a significant increase in POD activity. P. sepium Bunge evidently eliminates drought stress-induced peroxide stress primarily by increasing POD activity31,33. Studies have indicated that there is a significant increase in SOD, POD, and catalase activities in the leaves of Haloxylon ammodendron34 and peanut seedlings35 under various drought conditions. This finding suggests that, under drought stress, changes in the activities of plant protective enzymes are closely related to the habitat and drought resistance of the plants. As drought stress increases, the activities of protective antioxidant enzymes in plants increase or first increase but then decrease33,36. However, under severe drought stress, the ability of plants to alter their enzyme activities is limited, and consequently, their enzyme activities mostly decrease33,36.

Lü et al. reported a significant increase in the Pro and Ss contents in H. ammodendron under various drought stress conditions, although the Ss content increased to a greater extent than did the Pro content34. Similarly, Schimpl et al. reported a significant increase in the Ss content of Bertholletia excelsa under drought stress37. In the present study, as the drought stress increased, the Pro content in the leaves increased to a significantly greater extent than did the Pro content. This finding suggests that P. sepium Bunge is more capable of improving its osmotic adjustability by altering the Pro content than the Ss content. Under drought stress, plants can reduce their osmotic potential by accumulating solutes such as Pro and Ss to improve the osmotic adjustability of their cells to ensure proper osmotic balance inside and outside their cells37,38,39. In the present study, in the leaves, the Pro content was extremely significantly negatively correlated with the Pn; significantly negatively correlated with the ETR, ФPSII, and Rd; and significantly positively correlated with the NPQ. Additionally, in the leaves, the Ss content was significantly negatively correlated with the Pn and Rd; significantly positively correlated with the NPQ; and extremely significantly positively correlated with the Pro and Ss contents (Table 2). These findings suggest that, by secreting osmotic adjustment substances, P. sepium Bunge can adjust the osmotic pressure on both sides of the plasma membrane, and ensuring orderly physiological activity37,38, thereby affecting its photosynthetic electron transport ability. In the present study, as the drought stress increased, there was an increase in the contents of osmotic adjustment substances (e.g., Pro and Ss) in the P. sepium Bunge leaves as well as an increase in the activities of their antioxidant enzymes (SOD and POD). This trend may be the cause of the decrease in the MDA content40,41, which led to a reduction in cell membrane lipid peroxidation36. Abida et al.42 reported that two different varieties of maize resisted effectively drought stress by increasing antioxidant enzyme activity, reducing cell membrane lipid peroxidation efficiency and accumulating osmotic adjustive substances. As a result, the toxic effects of cell membrane lipid peroxidation diminished under severe drought stress.

As the drought stress level increased, the time at which the stem sap flow in P. sepium Bunge peaked was delayed or advanced, and the sap flow activity diminished during the day and increased during the night. To adapt to drought stress, P. sepium Bunge improved its WUE by reducing its transpiration intensity and duration. Furthermore, P. sepium Bunge exhibited relatively high adaptive plasticity to the dry soil environment. Bhusal et al. reported a significant decrease in instantaneous sap flow rate under drought stress43. Similarly, Liu et al. reported, that under drought stress, there was a decrease in the instantaneous sap flow rate of several dominant species in a Quercus liaotungensis community in a hilly loess region, a significant decrease in their maximum sap flow rates, and an advance or delay in the time at which the sap flow process started44. Clearly, drought stress obstructs the water transport process in plants and reduces their usable water content. In the present study, the Pn of the P. sepium Bunge leaves was extremely significantly positively correlated with the cumulative sap flow; the Tr was extremely significantly positively correlated with Gs, significantly positively correlated with the cumulative sap flow, and significantly negatively correlated with the NPQ; and Gs was significantly positively correlated with the ФPSII, ETR, and cumulative sap flow (Table 2). These results suggest that transpiration is closely related to the state of stomata. The photosynthetic electron transport and light energy dissipation processes also affected the Tr and Gs while protecting the photosynthesis organs, thereby intervening in the water-related physiological processes of P. sepium Bunge. Mengesha et al.45 reported that decreasing net photosynthetic rate and being limited gas exchange were shown on two types of wheat with different genotypes, which result in declining water transport and evapotranspiration rate, but improving significantly water use efficiency. Water transport and use in plants also affects their normal photosynthesis output. Certain relationships evidently exist between photosynthesis and water-related physiological processes in plants.

Under mild and moderate drought stress (RWC > 40%), there was a significant decrease in the Tr and Pn of the leaves (P < 0.05) (the Pn decreased to a smaller extent than did the Tr) and an increase in their WUE. As the drought stress increased (RWC ≤ 40%), the Tr and Pn decreased to extremely low levels and were not significantly different (P > 0.05). Additionally, as the drought stress increased (RWC ≤ 40%), there was also a significant decrease in WUE (P < 0.05). Therefore, increasing its peroxidase activity and secreting more osmotic adjustment, the leaves of P. sepium Bunge exhibited a relatively high WUE. A decrease in Gs reduces the water consumption of plants due to transpiration, obstructs water transport and use processes, and inhibits water-related physiological activities. A decrease in WUE leads to a decrease in the amount of raw materials for photosynthesis, thereby reducing photosynthesis. Liang et al. reported a significant decrease in the Tr, Pn, and WUE of Populus × euramericana ‘Neva’ as the drought stress level increased22. Similarly, Xia et al. reported that, as the drought stress level increased, the Tr and Pn of T. chinensis in a shell sand habitat decreased, whereas its WUE first increased but then decreased46. These findings are consistent with those of this study. Drought stress results in a significant decrease in the WUE and transpiration-related water consumption of plants, thereby inhibiting their water-related physiological processes. This trend ensures that plants will be able to use limited water efficiently to survive drought stress.

Conclusions

Drought stress on shell sand can significantly affect the photosynthesis, water consumption, and physiological and biochemical processes of P. sepium Bunge. As the degree of drought in shell sand area increased, a significant decrease in the Pn, Tr, Gs, and light energy for photosynthesis of P. sepium Bunge leaves occurred, and an increased amount of light energy was dissipated as heat. Moderate drought stress significantly improved the WUE, and severe drought stress led to severe photoinhibition and obstructed the water transport of P. sepium Bunge. Drought stress leads to a decrease in the amount of water available for other physiological activities. The decrease in photosynthesis is an important photoprotection mechanism that enables P. sepium Bunge to adapt to drought stress on shell sand. Moreover, P. sepium Bunge counteracts lipid peroxidation by increasing the contents of osmotic adjustment substances (Pro and Ss) and activities of antioxidant enzymes (SOD and POD) under severe drought stress on shell sand and adapts to drought stress through interactions and interregulatory activity between photosynthesis, water-related physiological activities, and physiological and biochemical processes. By reducing its photosynthesis output and WUE, P. sepium Bunge can reduce its photosynthetic electron transport efficiency, increase heat dissipation, increase both the activities of its protective enzymes and the content of its lipid peroxide molecules, and improve the osmotic adjustability of its cell membranes to withstand and adapt to drought stress on shell sand.

Methods

Experimental materials

Four-year-old seedlings of P. sepium Bunge, a dominant shrub species that grows on the shell ridges of the Yellow River Delta, were selected as experimental materials. The P. sepium Bunge seedlings were uniformly cut to prepare samples that had a height of 1.18 ± 0.13 m, a rhizome thickness of 1.25 ± 0.06 cm and a root depth of 11.2 ± 0.3 cm. The seedling samples were subsequently trimmed such that the canopy size was 0.4 m (east–west) × 0.4 m (south–north).

Experimental design

This experiment was conducted in the Scientific Research Greenhouse (SRG) of the Shandong Key Laboratory of Eco-Environmental Science for the Yellow River Delta. Shell sand was collected from the area of the P. sepium Bunge community in the Binzhou National Shell Ridge and Wetland Nature Reserve. The collected shell sand was sieved through a 2.0 mm mesh and was subsequently transferred to a pot (diameter of the top, 40 cm; height, 50 cm). The basic chemical and physical properties of the shell sand were as follows: field capacity, 18.31%; bulk density, 1.29 g·cm−3; particle size, 0.2–2.0 mm; pH, 7.40; and salt content, 0.1%–0.4%. The primary environmental conditions of the SRG included the following: illumination intensity, 80%–84% of the natural external light intensity relative air humidity, 45%–65%; temperature, 20–35 °C; and atmospheric CO2 concentration, 350–370 μmol·mol−1.

The seedlings were planted in a total of 24 pots (three seedlings per pot) in the SRG on March 13, 2018, after which they were subjected to normal plant management practices for approximately 90 d. On June 15, 2018, the seedlings received one of four water treatments. The seedlings were randomly divided into four groups, with each group comprising six pots of seedlings. One of the four groups was selected as a CK (RWC of the shell sand: 77.72%). The remaining three groups were subjected to mild (RWC of the shell sand: 58.16%), moderate (RWC of the shell sand: 42.98%), or severe (RWC of the shell sand: 32.39%) drought stress treatments, which are referred to as the T1, T2, and T3 groups, respectively. The pots in the CK, T1, and T2 groups were watered once every 3 days with 4, 2, and 1 L of water, respectively. The pots in the T3 group were not watered. The RWC of the shell sand was calculated as the ratio of the water content of the shell sand to its field capacity, by weight. The RWC of the shell sand was monitored and controlled by weighing the pot and drying. A tray was placed underneath each pot to prevent water loss, thereby controlling the designed water treatment and ensuring experimental accuracy. Each group of seedlings was allowed to adapt to the water treatment for approximately 30 d. Afterward, from July 16 to July 23, 2018, the P. sepium Bunge seedlings were measured to determine the physiological photosynthesis indices and the chlorophyll fluorescence parameters of their leaves as well as their physiological and biochemical indices and stem sap flow parameters.

Measurement of physiological photosynthesis indices

The experiment was conducted from 9:00 to 11:30 on a sunny day. Three pots of P. sepium Bunge seedlings were randomly selected from each group as experimental samples. Three healthy, mature leaves were then selected from the middle-upper section of the seedlings in each pot. An LI-6400XT portable photosynthesis system (LI-COR, Inc., Lincoln, NE, USA) was used to measure the light response of the plants. A standard 6400-02B red and blue light-source leaf chamber was used. Photosynthetically active radiation (PAR) was subsequently applied at 0, 40, 80, 100, 150, 200, 400, 600, 800, 1000, and 1200 µmol∙m−2 ∙ s−1, for a total of 11 illumination intensities. During the measurements, the PAR was decreased from the greatest level to the lowest level, with each level maintained for 120 s; these measurements were repeated three times. The instrument automatically recorded and calculated various physiological photosynthesis indices, such as the Pn, transpiration rate (Tr), Gs, and WUE (WUE = Pn/Tr).

Measurements of chlorophyll fluorescence parameters

An FMS-2 portable pulse-modulated fluorometer (Hansatech Instruments, Ltd., UK) was used to measure the chlorophyll fluorescence parameters of the P. sepium Bunge leaf samples as well as their photosynthesis indices. After the leaves were dark adapted for 30 min, the F0 and the maximum fluorescence (Fm) of each leaf were measured. Subsequently, after each leaf was dark adapted to natural light for 50 min, it was measured to determine its steady-state and maximum fluorescence under light-adapted conditions (Fs and Fm′). Additionally, the potential photochemical efficiency (Fv/Fm = (Fm − F0)/Fm), actual photochemical efficiency (ΦPSII = (Fm′ − Fs)/Fm′), noncyclic photosynthetic electron transport rate (ETR = ΦPSII × PAR × 0.5 × 0.84, where 0.5 is the partition coefficient between the two photosystems and 0.84 is the proportion of the amount of light absorbed by the leaf to the amount of incident light), and NPQ ((Fm − Fm′)/Fm′) were calculated47.

Measurements of physiological and biochemical indices

To measure physiological and biochemical indices, five to seven leaves were collected from the same section of each seedling from which the leaves were collected to measure and analyze the photosynthesis parameters48. The SOD activity was measured via nitro blue tetrazolium photoreduction, and the POD activity was measured via guaiacol colorimetry. In addition, the Pro content was determined via ninhydrin colorimetry, and the Ss content was determined according to the anthrone coloration method. Last, the MDA content was measured via thiobarbituric acid colorimetry.

Measurements of stem sap flow parameters

A Flow 32 heat-balance stem sap flow measurement system (Dynamax, Houston, TX, USA) was used to measure the P. sepium Bunge seedling stem sap flow rate and daily stem sap flow continuously. On the basis of the stem thickness for each P. sepium Bunge seedling selected for testing, an SGA-5 sensor with a suitable diameter (5–7 mm) was selected. The stem sap flow measurement system was installed according to the standard instructions provided by Dynamax. A Delta-T Logger data acquisition system was used to collect and record the instantaneous stem sap flow rates automatically at 30 min intervals.

Statistical analysis

A rectangular hyperbolic correction model49 was used to simulate the PAR–Pn photosynthesis light-response process. Equation (1) shows the expression of the model as follows:

$${P}_{n}=\alpha \frac{1-\beta I}{1+\gamma I}(I-{I}_{c})$$
(1)

Here, Pn is the net photosynthesis rate; I is the PAR; Ic is the LCP; and α, β, and γ are three coefficients unrelated to the light intensity (α is the initial slope of the light-response curve when the PAR is 0, which is considered the AQY, and β and γ are biological important photoinhibition and photosaturation terms, respectively).

On the basis of Eq. (1), three photosynthesis parameters, namely, Rd, LSP, and Pmax, can be derived, as shown in Eqs. (2)–(4).

$${{R}}_{{d}}={P}({I}=0)=-\,\alpha {{I}}_{{c}}$$
(2)
$${I}_{m}=\frac{-1+\sqrt{\frac{(\beta +\gamma )(1+\gamma {I}_{c})}{\beta }}}{\gamma }$$
(3)

where Im is the LSP.

$${P}_{n}({I}_{m})=\alpha \frac{1-\beta {I}_{m}}{1+\gamma {I}_{m}}({I}_{m}-{I}_{C})$$
(4)

where Pn(Im) is equal to Pmax.

The data were processed and plotted in Microsoft Excel 2016. Correlation analysis, analysis of variance, and multiple comparisons of the data were performed by SPSS 19.0.