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Article

Responses and Post-Recovery of Physiological Traits after Drought–Heatwave Combined Event in 12 Urban Woody Species

by
Yongkang Wang
1,†,
Chen Xing
1,2,†,
Yilin Gu
1,
Yang Zhou
1,
Jinyan Song
1,
Ziyi Zhou
1,
Jia Song
1,3,* and
Jun Gao
1,3
1
School of Environmental and Geographical Science, Shanghai Normal University, Shanghai 200234, China
2
College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
3
Yangtze River Delta National Observatory of Wetland Ecosystem, Shanghai Normal University, Shanghai 200234, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2023, 14(7), 1429; https://doi.org/10.3390/f14071429
Submission received: 3 June 2023 / Revised: 7 July 2023 / Accepted: 7 July 2023 / Published: 12 July 2023
(This article belongs to the Special Issue Forest Ecophysiological Responses to Climate Change)
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Abstract

:
The frequency and intensity of droughts combined with heatwave events have increased under climate change, increasing destruction in urban areas and leading to severe impacts on urban plants. These impacts remain poorly understood at the species level. Here, we investigate the effects of a drought–heatwave event on 12 urban woody species using in situ records of the dynamic changes in physiological traits in the field before, during and after the drought–heatwave event to assess resistance and resilience to hot drought. We found the following: (1) Hydraulic and photosynthesis traits showed an instantaneous decline during the hot drought event in the 12 species, with severe drought-induced xylem embolism in hydraulic systems and a high percentage loss of hydraulic conductivity (PLC). (2) The two conifer species were less resistant to hot droughts than broadleaves but capable of post-stress recovery, suggesting that conifers showed better resilience and that broadleaves showed better resistance under hot drought stress. (3) The evergreen species showed strong resistance, while three deciduous species showed strong resilience to hot drought stress. (4) The three shrubs may be more vulnerable to hot droughts than trees, as they showed lower resistance and were not able to recover the current year’s growth.

1. Introduction

Ongoing global climate change is increasing the frequency and intensity of droughts associated with high-temperature extreme weather events, and these are expected to continue increasing in the future [1,2,3,4], threatening plant growth and survival worldwide [5,6,7]. In the past few decades, many forests have exhibited declines or even death under droughts and heatwaves worldwide [8,9,10]. Drought and hot stress affect plants’ physiological processes, especially hydraulics, e.g., sap movement; leaf water potential; and photosynthesis, e.g., stomatal conductance [10,11,12,13]. Thus, accurately exploring and analyzing the response and post-recovery of plants’ physiological processes following hot drought events are critical to obtaining a better understanding of plants’ growth and survival under future climate change conditions, as well as improving the ability to predict these traits [14,15].
Indeed, the frequency and severity of extreme climate events, such as heatwaves and droughts, in urban areas are more severe under global climate change [16,17]. With the rapid development of urbanization, urban environmental conditions, such as impervious surfaces and the urban heat island effect, can locally exacerbate destructive extreme climate events [18,19,20,21,22]. Woody species growing in urban areas are the main way to maintain urban ecological services [23,24], which form green spaces in cities, increase the elasticity of the urban ecosystem, mitigate flooding and improve the quality of the urban environment [25,26,27,28]. In the context of climate change, urban woody plants are facing increasingly severe pressure and harm [11,29,30]. Therefore, more research on the responses and post-recovery of the physiological mechanisms of urban woody plants after heatwave and accompanying drought stresses is needed under the climate change scenario.
Plant physiological process traits describe multiple functional features among species and can be used to assess the effects of species-specific diversity in response to stress conditions. Heat stress directly affects plant metabolism, such as the photochemistry of photosynthesis (deactivating Rubisco activity or leading to RuBP regeneration), leading to a sudden and severe decline in tree productivity and health [10,31]. In hot weather, the water vapor content on the surface and in the air decreases, leading to a shortage of water resources on the surface and in the atmosphere [32]. Plants reduce their leaf temperature through transpiration to avoid dieback, which means that more water is needed in stomatal transpiration [33,34,35]. The xylem is an important part of long-distance water transportation in woody plants; as the duration and intensity of high temperatures increase, woody plants may experience xylem embolism when facing a large amount of water evaporation [36]. Under drought conditions, the increase in xylem tension leads to cavitation formation, which reduces the efficiency of hydraulic transportation and causes serious hydraulic dysfunction in plants [37]. Plants close their stomata to prevent hydraulic exhaustion, leading to a decrease in stomatal conductivity, reduced carbon absorption during photosynthesis and, ultimately, the depletion of carbon in the reservoir tissue. High temperatures and droughts can have residual effects on plants, damaging their physiological recovery and making them highly susceptible to secondary droughts and attacks from insects or fungal pathogens [38]. Therefore, to obtain insights into urban woody species’ vulnerability to hot drought stress, the effects of drought and high-temperature extreme weather events on hydraulics and photosynthetic physiological processes need to be tracked and recorded simultaneously.
Studies on the physiological responses of urban woody species to unpredictable hot drought under natural stress conditions in the field need to be better recorded [39,40,41,42,43,44,45,46,47]. Simulation-controlled experiments may not perform well the real outdoor environment of urban trees, and urban-specific factors can worsen the effects that the combined action of other environmental pressure factors have on plants [48,49]. Therefore, field data on hydraulic and photosynthesis-based physiological dynamic changes in urban plants as a response to hot drought events are essential and valuable for accurately evaluating vulnerability to stress among urban woody species and for validating experiments under controlled conditions [50]. In addition, investigating the changes in the critical physiological functional traits of urban plants during drought–heatwave events (resistance) and subsequent post-stress recovery (resilience) can help to better understand the response mechanisms of various urban woody species to hot drought stress. This is crucial for comprehensively assessing the impact of climate change on urban plants, as well as for urban forestry and ecological construction in urban areas against the background of climate change.
In recent years, drought and heatwave events have occurred frequently in the Yangtze River Basin of China, with severe drought events occurring in 2001, 2006, 2011 and 2013 [51]. Shanghai is located at the mouth of the Yangtze River (Figure 1), and due to factors such as rising sea levels, extreme weather events and population growth, future climate change will further exacerbate the vulnerability of the region [52]. In summer 2022, climate catastrophes brought on by high temperatures overtook the whole northern hemisphere, surpassing historical extremes and persisting for three months [53]. Heatwaves affected Europe, Asia, Africa and North America from June to August, with several locations experiencing record-breaking temperatures. The temperature in some areas of Shanghai exceeded 40 °C (Figure 2), which is much higher than the average summer temperature of 21~28 °C in previous years. This hot weather, combined with extreme drought, may have a serious impact on the water-related and photosynthesis physiological processes of plants in this area during the growing season. Research recording changes in plant physiological processes during hot drought events is urgently needed to investigate the responses that tree species have to these hot drought events (resistance), as well as investigating their post-hot-drought recovery (resilience), especially under the scenario of frequent extreme hot drought events.
In this study, we took advantage of the unprecedented hot drought event of summer 2022 in Shanghai to investigate the impairment of the hydraulic and photosynthesis traits of 12 common urban woody species growing in Qingxi Park, Shanghai (Table 1). Field measurements can record the instantaneous dynamic response process of the functional physiological traits of urban species related to hydraulic processes and photosynthesis. These measurements were taken under normal growing season conditions (before the hot drought event, June 2022), at the peak of the hot drought event (July–August 2022) and during the subsequent post-hot-drought recovery phase (late August–early September 2022). Measurements were taken, and an analysis was conducted of the dynamic changes in functional physiological traits related to hydraulic processes and photosynthesis to assess the resistance (sensitivity to hot drought events) and resilience (subsequent post-hot drought recovery rate) of these key physiological processes in these urban woody species. Specifically, we aimed to answer the following questions:
(1)
How do hydraulic and photosynthesis traits dynamically change before, during and after drought–heatwave events in the 12 urban woody species?
(2)
How do the resistance and resilience of key physiological traits to drought–heatwave events differ between the following different urban woody functional groups: evergreen vs. deciduous, broadleaved vs. coniferous and trees vs. shrubs?
The main objective of this study was to assess the key physiological functional traits of resistance and resilience to hot drought stress for urban woody species during the growing season. Furthermore, this study could expand on and update the comprehensive evaluation of urban woody species to provide necessary theoretical scientific support for the design and management of urban forestry ecological engineering under the scenario of global climate change.

2. Materials and Methods

2.1. Study Site and Plant Species

Our study was conducted in the Yangtze River Delta National Observatory of Wetland Ecosystem (Figure 1), located at Qingxi Park in the Qingpu District of Shanghai (121°12′ E, 31°15′ N). The research area is a typical urban region of eastern China, with species richness and a wide range of urban species. It is a prominent representative for the study of subtropical urban woody plants in eastern China. The climate here is mild with plenty of sunshine and four distinct seasons. In normal conditions, the annual rainfall is 1056 mm, the annual temperature is 15.5 °C, and the average annual relative humidity is 82%. The study area showed obvious drought and heatwave event climate characteristics in the summer of 2022, where temperatures above 40 °C and an air humidity below 45% were measured in the field for several continuous days, with drought conditions (Figure 2). Unlike the SPEI index curves for the summers of 2021 and 2020, or even showing contrary trends to them, it can be clearly seen that the SPEI index curve of 2022 was an inverted “Ω” type (Figure 3). Specially, the minimum values of the SPEI recorded in August 2022 were lower than −1. During the whole 2022 growing season, the SPEI value remained under −0.5, representing drought conditions during the plant growing season in the study area. As Shanghai is in a monsoon climate zone, the average SPEI index in summer tends to be above 1, and it can even reach 2 or 3, with relatively wet and mild weather. Conditions with averages of around zero, or even below −0.5, are rare.
In this study, we selected 12 urban woody species growing in Qingxi Park, Shanghai. The 12 woody species are common urban afforestation species and are widely distributed in Shanghai [54]. This is a common garden study conducted to determine the effects of drought and heatwave stress at the species level. Specifically, the 12 urban woody species studied in this research are Cinnamomum camphora (L.) Presl, Distylium racemosum Siebold and Zucc., Eucommia ulmoides Oliv., Ginkgo biloba L., Hibiscus syriacus L., Koelreuteria paniculata Laxm., Ligustrum lucidum Ait., Matasequoia glyptostroboides Hu and W.C. Cheng, Prunus cerasifera ‘Atropurpurea’, Salix babylonica L., Taxodium distichum var. Imbricatum (Nuttall) Croom and Yulania denudate (Desr.) D.L. Fu (Table 1). Ten individuals for each species were measured. Among these species, Kp, Cc, Ll, Sb, Eu, Yd, Gb, Mg and Td are tree species (Table 2); Hs, Pc and Dr are shrub species; Kp, Sb, Eu, Gb, Hs, Pc, Dr, Mg and Td are deciduous species; and Cc, Ll and Yd are evergreen species. The rest of the 12 species, except for the three gymnosperms of Gb, Mg and Td, are angiosperms (Table 2). For each species, we selected ten healthy individuals to study changes in physiological indicators. Additionally, measurements were taken before, during and after the hot drought event on 20 June 2022–25 June 2022, 28 July 2022–6 August 2022 and 29 August 2022–4 September 2022, respectively (Figure 4).

2.2. Meteorological Data Collection and Tidying

Meteorological data were collected using an observation tower and a meteorological station located in the Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station (Figure 2). These data include the temperature, precipitation (Ppt), the relative air humidity (RH), soil temperature (Ts), volumetric water content (VWC) and soil moisture (Ms) in Shanghai for 2022. To better show the year-round climate characteristics in 2022, we converted the daily data to monthly data. In order to obtain the monthly saturation vapor pressure difference (VPD), representing the dryness of the air and affecting the transpiration and photosynthesis of plants, we used the daily maximum temperature (°C) and daily RH (%) for calculation. The VPD (kPa) was calculated as follows [55]:
V P D = a × e b × T m a x . d c + T m a x . d × 1 − R H 100
In this formula, a, b and c are all constants. a = 0.6108, b = 17.27, and c = 237.3. e is a natural constant, while T m a x . d (°C) represents the maximum daily temperature, and RH (%) represents the relative air humidity.
SPEI was created by Vicente-Serrano et al. based on the Standardized Precipitation Index (SPI) [56,57]. It combines the sensitivity of the Palmer Drought Severity Index (PDSI) to changes in evaporation demand with the multitemporal nature of SPI [56]. The SPEI uses the difference between Ppt and potential evapotranspiration (PET) to characterize the degree of drought in an area, which is suitable for global drought assessments and can be applied to hydrology, ecology, agriculture and other fields [58]. In this study, we downloaded the SPEI from the following website: https://spei.csic.es/index.html (accessed on 23 May 2023). The calculation method of the SPEI has been described by Vicente-Serrano [56].

2.3. Stem Hydraulic Conductivity and the Native Embolism Measurements

To measure hydraulic conductivity, ten sun-exposed branches ~1.5 m in length, each from a different individual, were collected from each species in the early morning (4:00–5:00 a.m.). These were placed in a bucket filled with water immediately after being cut from the tree. The branches were re-cut under water (5 cm removed), and the other end of the branches was wrapped in a black plastic bag, with the cuttings being submerged in water and directly transported to the laboratory. This process avoided the tension-cutting effect, particularly the induction of embolism when cutting stems under relatively low water potentials [59]. An unbranched stem segment of ∼20 cm of angiosperm and ~7 cm of gymnosperm in length and 1 cm in diameter was sampled from each of the sampled branches for stem hydraulic conductivity (Kh) measurements. The leaves at the top of the selected branches were collected for leaf area measurements. A degassed concentration of a 20 mmol L−1 KCl solution using a 50 cm water flow pressure difference was applied to the branches for water conductivity measurements. A thin, small part of the branches was cut with a blade at both ends to prevent the bleeding liquid from blocking the conduits at both ends. After measuring the hydraulic conductivity, the sapwood area of the branch was calculated by deriving the pressure difference generated by a 0.1% methylene blue solution in a 50 cm water column down through the branch to calculate the area at which both ends of the branch were stained with the methylene blue solution [60]. The dyed branches were cross-cut at both ends using a slicer, the resulting slices were scanned with a scanner (HP Scanjet G3110, Hewlett-Packard Development Co., Beijing, China), and the sapwood area was calculated using Image J 1.48v software (US National Institutes of Health, Bethesda, MD, USA).
Hydraulic conductivity (kg m s−1 MPa−1) was calculated as follows [60,61,62]:
K h = J v ∆ P ∆ L
where Jv is the flow rate through the segment (kg s−1), and ∆ P / ∆ L is the pressure gradient across the segment (MPa m−1). The stem-specific hydraulic conductivity (Ks; kg m−1 s−1 MPa−1) was calculated as the ratio of Kh to the sapwood area.
After the initial measurement of Kh, the stem segments of angiosperm species were then flushed with a degassed filtered 20 mmol−1 KCL solution under 0.1 MPa pressure for 20 min to remove air bubbles from the xylem. For gymnosperm species, the stem segments were submerged in distilled water, and a partial vacuum was applied overnight to remove air bubbles from the xylem. The maximum hydraulic conductance (Kh-max) was then measured.
The percent loss of hydraulic conductivity (PLC) was calculated as follows:
P L C = 100 K h − m a x − K h K h − m a x

2.4. Water Potential Measurements

Water potentials were measured on consecutive sunny days with a pressure chamber (Model 1505D-EXP, PMS Instrument Co., Albany, OR, USA). Six mature, sun-exposed leaves were selected and cut from each branch at 12:00–14:00 p.m. These were then immediately placed in a self-sealing bag with a wet tissue and transported back to the laboratory in an insulated box to isolate them from the high-temperature, dry environment for water potential measurements. The period from the detachment of the experimental materials to the measurement should be completed in an hour to ensure the accuracy of the experiment [63].

2.5. Photosynthesis Measurements

Leaf stomatal conductance (gs) and the CO2 assimilation rate (Anet) were measured using a LI-6400 photosynthetic system (LI-COR lnc., Lincoln, NE, USA). For each tree species, six fully expanded, mature sunny leaves were selected from different individuals and placed under a leaf cuvette. The LI-6400 setting parameters were a temperature of 20–25 °C and a relative humidity (RH) of 50%–65%, with a CO2 concentration of 350–400 μmol mol−1. These were then measured at a quantum density of 1000–1880 μmol m−2 s−1 [63].

2.6. Leaf SPAD Value and Relative Water Content of Leaves

In this study, we used a SPAD-502 chlorophyll analyzer (SPAD-502 Plus, Minolta, Japan) to measure the chlorophyll content of the leaves [64]. Prior to the measurement, we conducted a functional test of the apparatus using the standard plate provided by the manufacturer to ensure its normal function. The leaves of each tree species were divided into left and right regions based on the leaf veins, and they were then further divided into tip, middle and base regions according to the distance between the blade’s parts and the petiole, resulting in six different leaf regions. To measure the SPAD values, we started from the right leaf base and rotated counterclockwise through each region, obtaining six SPAD values in total. The average of these six values was taken as the SPAD value for the whole leaf. At least eight leaves were taken from different individuals for each species in this study.
To determine the leaf relative water content (RWC) in this study, we first measured the fresh weight of the leaves. Next, the leaves were soaked in distilled water overnight (longer than 6 h) to ensure full saturation; then, the surface water was wiped, and the leaves were weighed to obtain the saturated weight. Lastly, the leaves were dried in an oven at 65 °C until a constant mass was reached, and then they were weighed to obtain their dry weight. The RWC of the leaves of different tree species was calculated by averaging the values obtained from six repeated measurements [65,66].
RWC was calculated as follows:
R W C % = f r e s h   w e i g h t − d r y   w e i g h t s a t u r a t e d   w e i g h t − d r y   w e i g h t × 100 %

2.7. Data Analysis

In this research project, to represent the degree of damage and the stability of different physiological indicators of different tree species under extreme climate events, we calculated the resistance and resilience indices proposed by Lloret et al. We considered the three periods before, during and after the drought–heatwave event in the same year of 2022 [67].
The calculation formula is as follows:
R e s i s t a n c e = I I P r e
R e s i l i e n c e = I P o s t I P r e
where I is defined as the mean physiological indicators of the trees during the drought–heatwave event, IPre is defined as the mean physiological indicators before the drought–heatwave event, and IPost is defined as the mean physiological indicators after the drought–heatwave event.
Comparisons of physiological traits before, during and after the hot drought event were performed using an analysis of variance (ANOVA). Tukey’s post hoc comparison test was used to test the possible significance of the hydraulic and photosynthetic traits before (under normal growing season weather conditions) and during the hot drought event, as well as the significant difference between the measurements taken during and after the hot drought event (SPSS 19.0 software package, SPSS Inc., Chicago, IL, USA). Differences in the resistance and resilience of the physiological traits to hot droughts between plant functional groups (evergreen vs. deciduous, broadleaved vs. coniferous and trees vs. shrubs) were compared using a t-test analysis. Statistical significance was accepted at the level of p < 0.05 (* = p < 0.05; ** = p < 0.01).

3. Results

3.1. Dynamic Changes in Physiological Traits throughout Drought–Heatwave Event

During the drought–heatwave event, all urban woody species but Eu showed a significant decline in Ks (Figure 5 and Figure 6; p < 0.01), and PLC significantly increased for all studied urban woody species (Figure 5). A significant decrease in Ψmidday and high PLC levels in the xylem were recorded during the hot drought, which indicates that hydraulic system dysfunction occurred under drought-induced xylem embolism. The photosynthetic physiological processes of all the urban woody species in this study sustained serious damage after the hot drought event, showed the significant decline in gs, Anet and the leaf SPAD value (Figure 5). The significance of the decrease in the leaf RWC value during droughts and high temperatures was recorded for all studied urban woody species, except for Eu.
In the post-hot-drought phase, the photosynthesis traits, i.e., gs and Anet, showed low recovery across the studied urban woody species (Figure 5). gs’s ability to recover after the hot drought events was only significant in Mg, Kp and Eu, with no significant short-term recovery recorded in the other tree species (Figure 6). Anet showed a significant inability to recover in all tree species in this study, except for in Kp. For hydraulic traits, only Kp, Sb, Gb and Mg showed a significantly strong recovery during the post-hot-drought phase, with the other species being unable to effectively recover (Figure 5 and Figure 6).

3.2. Responses to and Recovery from Hot Drought among Different Functional Groups

In general, the physiological traits of the 12 urban woody species showed a decrease (Figure 5) during the hot drought event, while the post-hot-drought recovery ability differed among species.
The Ks of Cc, Ll and Yd in evergreen broadleaf was less damaged by the effects of the drought–heatwave event compared to that of the other species with deciduous broadleaf (Figure 7), indicating that evergreen urban trees show better resistance. In the post-hot-drought phase, the evergreen broadleaf species, such as Cc and Ll, showed a lower recovery ability than the deciduous species, such as Kp (Figure 7).
Compared with the broadleaved species, Mg and Td, as coniferous fir species, showed a significant drop in Ks, gs and Anet during the hot drought but significantly recovered their hydraulic traits in the post-hot-drought phase (Figure 6).
Among the 12 urban woody species, all physiological traits studied in this research were significantly decreased in the shrub species (Hs, Pc and Dr). Furthermore, the hydraulic and photosynthesis traits of the three shrub species could not recover in the subsequent post-hot-drought phase (Figure 6 and Figure 7), suggesting that shrubs suffer a high degree of damage and have low resistance and resilience.

4. Discussion

4.1. Dynamic Changes in Hydraulic and Photosynthesis Traits under Drought–Heatwave Event

During the drought–heatwave events, plant xylem hydraulic conductivity showed an instantaneous decrease, accompanied by an increase in PLC. This indicates that urban woody species in this study experienced severe drought-induced xylem cavitation during extreme weather events, which caused a decline in xylem hydraulic efficiency. Some studies also indicated that the collapse of the hydraulic system within a short time demonstrates that plants can rapidly be pushed out of the zone of hydraulic safety during the progression of a severe drought [39]. Other research showed that well-watered plants closed their stomata and decreased stomatal conductance (gs) during a heatwave, but droughted plants did not. Urban woody species with a low gs, either due to isohydric stomatal behavior under a water deficit or an inherently low transpiration capacity, opened the stomata and increased gs under high temperatures [44]. During hot drought events, the stomata of some plants will ordinarily close to reduce the water loss caused by the high evaporation, but this also reduces the amount of CO2 that enters the plant, which indirectly impairs the photosynthetic ability [10]. However, when the hot drought event passes and the climate returns to normal, the overall recovery of the photosynthetic indices of these species is not significant. In general, isohydric species are able to maintain leaf water potential, regulate evaporative demand and mitigate the risk of hydraulic failure under drought conditions. And anisohydric species tend to show a leaf water potential decline and high stomatal conductance for continuous photosynthesis despite the high hydraulic failure risk under drought [68,69]. As an important means of control to maintain the water balance in plants, stomata have a direct effect on the water dispersion loss of plants, so the sharp decrease in stomatal conductance will also lead to a serious decline in other hydraulic indicators. Many studies found that plants can control transpiration by controlling the degree of the opening and closing of stomata and rely on evaporative cooling to reduce thermal damage. Some studies explored the influence of temperature on the stomatal conductance of vegetation through experiments [70,71,72,73,74,75,76]. Various studies have confirmed that the stomata of different tree species show typical differences in drought and temperature sensitivity, which leads to inconsistency in the stomatal response to hot drought stress. The dynamic behavior of stomata in regulating water loss determines the rate of plant dehydration when soil water availability decreases.

4.2. Response to and Recovery from Drought–Heatwave Event among Different Plant Functional Groups

The hydraulic and photosynthesis traits in the evergreen broadleaf species were less damaged by the effects of the drought–heatwave event than the deciduous broadleaf species, indicating that evergreen urban woody species have better resistance. However, the evergreen broadleaf species showed a lower recovery ability regarding their physiological traits during the post-drought–heatwave phase than the deciduous broadleaf species. This response and the recovery differences between the evergreen and deciduous species reflect their different adaptive strategies. Evergreen plants have a longer leaf lifespan, which means that these species face stressful environments over long periods of time during their growth, including drought and heatwave stress. Evergreen species generally have higher structural investments [77,78], which may mean that they are more inclined to exhibit a “conservative” strategy. This strategy is consistent with the evergreen species showing a greater resistance but lower recovery, i.e., insensitivity to stress conditions and the post-stress phase. In contrast to evergreen species, deciduous species might be more inclined to exhibit a “risk” strategy, especially during a short growing season. This strategy is associated with the higher growth efficiency of deciduous species [79], which also allows them to exhibit a low resistance to hot drought but a rapid recovery after stress conditions. In addition, with “cheap” leaf construction costs, deciduous plants may shed leaves during hot drought stress. These results suggest that there might be trade-offs between resistance to and recovery from hot drought stress among evergreen and deciduous species.
Compared with the other urban woody species, Mg and Td, as coniferous firs, are less resistant to extreme hot drought climates [80]. However, the two types of fir (Mg and Td) showed low resistance and strong resilience to hot drought stress (Figure 7). We speculate that this is related to their strong recovery ability: even if the fir is severely damaged in extreme heat and drought [81], it can be quickly restored in a short period of time when the water and temperature conditions revert back to normal. Mg and Td, as typical wetland-suitable coniferous species, also demonstrated a quicker recovery (that is, higher resilience) after the drought–heatwave events, probably caused by their greater sensitivity to water availability at those times. Furthermore, unlike coniferous firs, the broad-leaved species’ resistance to drought may be correlated with self-growth conditions and partly depend on drought events [82].
In this study, urban shrub species were less resistant to damage from drought and high-temperature events (Figure 7), showing a significant decline in hydraulic and photosynthesis traits during hot drought. This may be related to the shallow root system and relatively short morphology of shrub species [83], which means that shrub species only obtain water in the shallow soil layer. The moisture content of shallow soil is greatly affected by extreme high-temperature conditions and evaporation under high temperatures [84]. The shorter posture of shrubs makes them more vulnerable to the higher ground radiation that occurs during high-temperature and drought events. Extremely high temperatures may affect shrubs more than the loss of moisture [85]. In terms of resilience, trees have an advantage over shrubs, but they suffer some damage in terms of their photosynthetic rate.
Among all the urban species studied, Sb showed a weak resistance to hot drought stress but a relatively stronger resilience. This may be due to the fact that Sb always grows near water in urban areas with a sufficient water content. Some research showed that Sb had the lowest total damage rate and the highest heat-resisting index after drought–heatwave events [86]. Therefore, Sb showed a weak drought resistance and a high ability to recover in a short period of time after hot droughts. This may be due to the fact that Sb always grows near urban waters with a sufficient water content and has a strong dependence on water.
Overall, the trade-off between resistance to and recovery from drought–heatwaves among evergreen and deciduous species reflects two different ecological adaptation strategies. There were differences among broadleaved and coniferous species, with characteristics of “strong resistance and weak resilience” in broadleaved Kp, Eu and “weak resistance and strong resilience” in the two types of fir: Mg and Td. These are two completely different survival strategies adopted by different functional groups under the stress of external climate factors: one is to seek strong resilience through strong resistance, and the other is to seek strong resilience through a strong recovery ability. Furthermore, the effects of drought and high temperature on the photosynthesis and growth of trees are complex, and further studies on the interaction between different factors are needed.

5. Conclusions

The key physiological functional traits of the hydraulic and photosynthesis process dynamics provide a valuable reference for assessing resistance and resilience among urban woody species under drought–heatwave stress. In our study, broadleaf species showed an increased resistance to hot drought, while they had a lower recovery ability than Mg and Td with conifer leaf, which demonstrates that there are different survival strategies among species. Thus, different plant functional groups may perform various survival strategies, with a large resistance during hot drought events vs. a strong recovery ability post-hot-drought events. Future research could focus on this. Our results may allow for a better understanding of the eco-physiological functional traits of urban woody species’ response to drought–heatwave events caused by climate change, as well as contributing to urban forest management.

Author Contributions

Data curation, Y.W., Y.G., Y.Z. and J.S. (Jinyan Song); Formal analysis, Z.Z.; funding acquisition, J.S. (Jia Song); methodology, Y.W., C.X. and Y.Z.; project administration, J.S. (Jia Song); resources, J.S. (Jia Song) and J.G.; supervision, J.S. (Jia Song) and J.G.; writing—original draft, Y.W., C.X. and Y.G.; writing—review and editing, J.S. (Jia Song). All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (32101480).

Data Availability Statement

Data are available upon request to the corresponding authors.

Acknowledgments

We gratefully acknowledge the people of Yangtze River Delta Urban Wetland Ecosystem National Field Observation and Research Station for their support of the experiment.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Study area and the locations of the observation station, Meteorological tower and Meteorological station. The yellow line frame is the study area, located in Qingxi Park, Qingpu District, Shanghai, China (121°12′ E, 31°15′ N). The yellow star characterizes the Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station. The red dot represents the Meteorological tower, while the blue dot represents the Meteorological station. The base map is available at https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer (accessed on 30 April 2023). The shapefiles of the traffic network and administrative area of Shanghai and Qingpu District are from https://www.webmap.cn (accessed on 6 February 2023).
Figure 1. Study area and the locations of the observation station, Meteorological tower and Meteorological station. The yellow line frame is the study area, located in Qingxi Park, Qingpu District, Shanghai, China (121°12′ E, 31°15′ N). The yellow star characterizes the Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station. The red dot represents the Meteorological tower, while the blue dot represents the Meteorological station. The base map is available at https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer (accessed on 30 April 2023). The shapefiles of the traffic network and administrative area of Shanghai and Qingpu District are from https://www.webmap.cn (accessed on 6 February 2023).
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Figure 2. Monthly meteorological data statistics of the study area in 2022. In (a), the black curve characterizes the monthly soil temperature (Ts), while the bar graph characterizes the monthly mean temperature (T). In (b), the bar graph shows the relative humidity of air (RH), while (c) shows the water vapor pressure deficit (VPD). In (d), the bar graph shows the soil moisture (Ms). In (e), the bar graph represents the volumetric water content of soil (VWC), while (f) represents the precipitation (Ppt). The gray rectangular area highlights the drought–heatwave event. All abbreviations are shown in Table 1.
Figure 2. Monthly meteorological data statistics of the study area in 2022. In (a), the black curve characterizes the monthly soil temperature (Ts), while the bar graph characterizes the monthly mean temperature (T). In (b), the bar graph shows the relative humidity of air (RH), while (c) shows the water vapor pressure deficit (VPD). In (d), the bar graph shows the soil moisture (Ms). In (e), the bar graph represents the volumetric water content of soil (VWC), while (f) represents the precipitation (Ppt). The gray rectangular area highlights the drought–heatwave event. All abbreviations are shown in Table 1.
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Figure 3. Comparison of the Standardized Precipitation–Evapotranspiration Index (SPEI) of Shanghai between 2022 and other years (2021, 2020) without extreme drought–heatwave events. The red curve in the graph represents the monthly SPEI in 2022, while the other curves represent the monthly SPEI in some normal years. The value of SPEI is based on 0; the higher the value, the wetter it is, while the lower the value, the drier it is. The drought event has an SPEI value under −0.5. The gray rectangular area highlights the period of drought–heatwave event. All abbreviations are shown in Table 1.
Figure 3. Comparison of the Standardized Precipitation–Evapotranspiration Index (SPEI) of Shanghai between 2022 and other years (2021, 2020) without extreme drought–heatwave events. The red curve in the graph represents the monthly SPEI in 2022, while the other curves represent the monthly SPEI in some normal years. The value of SPEI is based on 0; the higher the value, the wetter it is, while the lower the value, the drier it is. The drought event has an SPEI value under −0.5. The gray rectangular area highlights the period of drought–heatwave event. All abbreviations are shown in Table 1.
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Forests 14 01429 g004 550
Figure 4. Photographs of four urban woody species (Ligustrum lucidum Ait., Yulania denudata (Desr.) D. L. Fu, Salix babylonica L., Prunus cerasifera ‘Atropurpurea’) and leaf surface temperatures. In August 2022, some urban woody plants in Shanghai withered, and leaves turned yellow or even dropped off due to the influence of drought and heatwave events. Photo credits: Jia Song.
Figure 4. Photographs of four urban woody species (Ligustrum lucidum Ait., Yulania denudata (Desr.) D. L. Fu, Salix babylonica L., Prunus cerasifera ‘Atropurpurea’) and leaf surface temperatures. In August 2022, some urban woody plants in Shanghai withered, and leaves turned yellow or even dropped off due to the influence of drought and heatwave events. Photo credits: Jia Song.
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Forests 14 01429 g005 550
Figure 5. Dynamic changes in physiological indicators for 12 urban woody species before, during and after drought–heatwave event (D-H event). All abbreviations are shown in Table 1.
Figure 5. Dynamic changes in physiological indicators for 12 urban woody species before, during and after drought–heatwave event (D-H event). All abbreviations are shown in Table 1.
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Figure 6. Significance of decline (during hot drought event vs. before hot drought event) and recovery (post-hot-drought event vs. during hot drought event) in the hydraulic- and photosynthesis-related physiological traits (Ks, Ψmidday, PLC, RWC, SPAD, gs, Anet) of 12 species (Kp, Cc, Ll, Sb, Eu, Yd, Gb, Hs, Pc, Dr, Mg, Td) under hot drought events. ** = p < 0.01 (red color), * = p < 0.05 (orange color), and blue color indicates little to no significance. All abbreviations are shown in Table 1.
Figure 6. Significance of decline (during hot drought event vs. before hot drought event) and recovery (post-hot-drought event vs. during hot drought event) in the hydraulic- and photosynthesis-related physiological traits (Ks, Ψmidday, PLC, RWC, SPAD, gs, Anet) of 12 species (Kp, Cc, Ll, Sb, Eu, Yd, Gb, Hs, Pc, Dr, Mg, Td) under hot drought events. ** = p < 0.01 (red color), * = p < 0.05 (orange color), and blue color indicates little to no significance. All abbreviations are shown in Table 1.
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Figure 7. Radar charts (a–l) are used to represent the resistance and resilience of different indicators of the same tree species before and after drought–heatwave event. The larger the red area, the less severely damaged the tree and the stronger the resilience. The larger the blue area, the higher and stronger the resistance ability of the tree. All abbreviations are shown in Table 1.
Figure 7. Radar charts (a–l) are used to represent the resistance and resilience of different indicators of the same tree species before and after drought–heatwave event. The larger the red area, the less severely damaged the tree and the stronger the resilience. The larger the blue area, the higher and stronger the resistance ability of the tree. All abbreviations are shown in Table 1.
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Table
Table 1. Abbreviations and descriptions of climate, physiological traits and species in this study.
Table 1. Abbreviations and descriptions of climate, physiological traits and species in this study.
AbbreviationDescription/Scientific NameUnit
Climate variablesTAir temperature(°C)
RHRelative air humidity(%)
VPDVapor pressure deficit(kPa)
TsSoil temperature(°C)
MsSoil moisture content(%)
VWCVolumetric water content(m3/m3)
PptPrecipitation(mm)
SPEIStandardized Precipitation–Evapotranspiration Index-
Leaf traitsRWCLeaf relative water content(%)
SPADRelative value of chlorophyll content-
gsStomatal conductance(mol−1 m−2 s−1)
AnetLeaf net CO2 assimilation rateμmol m−2 s−1
Hydraulic traitsKsStem hydraulic conductivity(kg m s−1 MPa−1)
ΨmiddayMidday water potential(MPa)
PLCPercent loss of hydraulic conductivity(%)
SpeciesCcCinnamomum camphora (L.) Presl-
DrDistylium racemosum Siebold and Zucc.-
EuEucommia ulmoides Oliv.-
GbGinkgo biloba L.-
HsHibiscus syriacus L.-
KpKoelreuteria paniculata Laxm.-
LlLigustrum lucidum Ait.-
MgMatasequoia glyptostroboides Hu and W.C. Cheng-
PcPrunus cerasifera ‘Atropurpurea’-
SbSalix babylonica L.-
TdTaxodium distichum var. Imbricatum (Nuttall)Croom-
YdYulania denudate (Desr.) D.L. Fu-
The different background colors in the table are used to distinguish different data types.
Table
Table 2. Growth and type information of the 12 urban woody species, including the scientific name, diameter at breast height, height, crown width and plant functional types.
Table 2. Growth and type information of the 12 urban woody species, including the scientific name, diameter at breast height, height, crown width and plant functional types.
SpeciesDiameter at Breast Height (cm)Height (m)Crown Width (m)Type
Cinnamomum camphora (L.) Presl14.2 ± 0.514.3 ± 0.78.6 ± 0.8AngiospermTreeEvergreenBroadleaf
Ligustrum lucidum Ait.7.6 ± 0.47.8 ± 0.73.8 ± 0.5Angiosperm
Yulania denudata (Desr.) D. L. Fu18.4 ± 1.115.6 ± 1.27.2 ± 1.1Angiosperm
Eucommia ulmoides Oliv.9.1 ± 0.59.5 ± 0.66.7 ± 0.8AngiospermDeciduous
Koelreuteria paniculata Laxm.15.4 ± 0.711 ± 0.37.5 ± 0.6Angiosperm
Ginkgo biloba L.6.5 ± 0.87.2 ± 0.65.3 ± 0.7Gymnosperm
Salix babylonica L.14.8 ± 0.614.9 ± 0.58.9 ± 0.9Angiosperm
Distylium racemosum Siebold and Zucc.5.3 ± 0.65.3 ± 0.93.8 ± 0.8AngiospermShrub
Hibiscus syriacus L.6.2 ± 0.46.2 ± 0.94.8 ± 0.5Angiosperm
Prunus cerasifera ‘Atropurpurea’8.1 ± 0.85.7 ± 0.75.9 ± 0.9Angiosperm
Metasequoia glyptostroboides Hu and W. C. Cheng15.7 ± 0.715.2 ± 1.36.8 ± 0.7GymnospermTreeConiferous
Taxodium distichum var. imbricatum (Nuttall) Croom12.6 ± 0.411.7 ± 0.86.1 ± 0.6Gymnosperm
The different background colors in the table are used to distinguish different plant functional types.
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MDPI and ACS Style

Wang, Y.; Xing, C.; Gu, Y.; Zhou, Y.; Song, J.; Zhou, Z.; Song, J.; Gao, J. Responses and Post-Recovery of Physiological Traits after Drought–Heatwave Combined Event in 12 Urban Woody Species. Forests 2023, 14, 1429. https://doi.org/10.3390/f14071429

AMA Style

Wang Y, Xing C, Gu Y, Zhou Y, Song J, Zhou Z, Song J, Gao J. Responses and Post-Recovery of Physiological Traits after Drought–Heatwave Combined Event in 12 Urban Woody Species. Forests. 2023; 14(7):1429. https://doi.org/10.3390/f14071429

Chicago/Turabian Style

Wang, Yongkang, Chen Xing, Yilin Gu, Yang Zhou, Jinyan Song, Ziyi Zhou, Jia Song, and Jun Gao. 2023. "Responses and Post-Recovery of Physiological Traits after Drought–Heatwave Combined Event in 12 Urban Woody Species" Forests 14, no. 7: 1429. https://doi.org/10.3390/f14071429

APA Style

Wang, Y., Xing, C., Gu, Y., Zhou, Y., Song, J., Zhou, Z., Song, J., & Gao, J. (2023). Responses and Post-Recovery of Physiological Traits after Drought–Heatwave Combined Event in 12 Urban Woody Species. Forests, 14(7), 1429. https://doi.org/10.3390/f14071429

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