Modeling the simulated soil warming and water stress on foliar Nutrients allocation of Cunninghamia lanceolata

Modeling the simulated soil warming and water stress on foliar Nutrients allocation of Cunninghamia lanceolata | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Modeling the simulated soil warming and water stress on foliar Nutrients allocation of Cunninghamia lanceolata Xuan Fang, Hui Chen, Yueling Li, Jinmao Zhu, Jian Wang, Yusheng Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9358268/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aims Global climate change may influence nutrient allocation strategies in subtropical trees. We aimed to understand the changes in nutrient allocation and the growth adaptability situation of plant leaves under conditions of continuous warming and water stress. Methods In 2014, the experiments were established in 30 mini-plots (2 ×2 m) with the following treatments:control, soil warming (W, + 5°C), rainfall exclusion (D, 50% reduction in precipitation) and warming+rainfall exclusion. We sampled the leaf of Cunninghamia lanceolata to assess their morphological change, lemental and stoichiometric variables and photosynthetic nutrient-use efficiency under all four conditions. Results Warming increased leaf area and length, decreased leaf mass per area (LMA), and enhanced photosynthetic nitrogen and phosphorus use efficiencies (PNUE, PPUE). Water stress increased leaf N, reduced C:N, raised N:P, and decreased PNUE.Under the combined effects of warming and water stress, more P was allocated to structural components, with less to metabolic and nucleic acid P, alongside increased leaf area. Conclusions Findings indicate that warming promoted N allocation to Rubisco rather than cell walls, supporting growth and resource efficiency. In contrast, drought shifted N toward cell walls, enhancing leaf toughness but limiting N use and slowing growth. Combined warming and drought conditions induced a preferential allocation of phosphorus to membrane phospholipids, thereby enhancing plant stress tolerance. In tandem, investment in key metabolic processes such as photosynthesis was reduced, and leaf toughness was further augmented. This integrated physiological and structural adjustment collectively reflects an adaptive trade-off between growth and survival under climate change. simulated soil warming water stress nutrients allocation photosynthesis foliar morphology Cunninghamia lanceolata Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The Intergovernmental Panel on Climate Change (IPCC) reported that the global surface temperature was 1.09°C higher during 2011–2020 than during 1850–1900, and it is projected that the globe will have warmed by 4–5℃ by 2100 (IPCC 2021 ). Human activities have likely influenced global soil moisture patterns during the 20th century. The combination of a higher temperature, lower relative humidity, and greater net radiation has increased atmospheric evaporative demand, which, in turn, has enhanced water evaporation and dispersion, resulting in a global trend toward drought (IPCC 2021 ). Consequently, the probability of co-occurring high temperature and water stress is increasing. Most plant species are adapted to grow within specific temperature and moisture ranges, consequently, climate change will have a significant impact on plant ecosystems. (Kang et al., 2021 ), though they will likely adapt to higher temperatures and water stress by modifying their growth and development or by shifting leaf function (i.e., nutrient allocation and photosynthesis) and/or size (Christie et al., 2022 , Lynn et al., 2021 , Guittar et al., 2016 ). Not only do the alteration of nitrogen (N) and phosphorus (P) elements reflect global climate change, but they also play a crucial part in plant photosynthesis (Luo et al., 2021 , Sterner and Elser 2002 ). Studies on the effects of warming and water stress on N and P concentrations are now prevalent, with findings showing that warming treatments either reduce leaf N and P concentrations(Zhang et al., 2017 , Tian et al., 2019 ), increase, or generate no change (Sardans et al., 2008 ). Similarly, studies examing the effect of water stress on plant nutrients have found that the impacts on plant N and P concentrations are inconclusive, either decreasing (Farooq et al., 2012 ) or increasing (Gargallo-Garriga et al., 2014 ). Furthermore, few studies have focused on the mechanisms governing N and P partitioning in leaves under combined warming and water stress. Photosynthetic nutrient-use efficiency (PNUE/PPUE) is the ratio of photosynthetic rate to leaf N or P concentration, respectively. It serves as a critical parameter for characterizing plants’ leaf nutrient allocation patterns, physiological traits, and survival strategies (Yang et al., 2011 , Tang et al., 2019 ). The photosynthetic nitrogen-use efficiency (PNUE) and photosynthetic phosphorus-use efficiency (PPUE) are significantly influenced by foliar N and P concentrations, respectively, and studies have further demonstrated that optimizing the functional allocation of N and P within leaves is critical, as the distribution of these nutrients directly modulte PNUE and PPUE (Pao et al., 2019 ). PNUE represents the physiological relationship between the N content and photosynthetic capacity in leaves, with the proportion of leaf N allocated to the photosynthetic apparatus being a key factor in determining PNUE (Minjee et al., 2019 ). Owing to constraints imposed by its physical structure and physiological function, a leaf cannot simultaneously maximize both PNUE and toughness (quantified by leaf mass per area (LMA)), consequently, a trade-off exists between N allocated to cell wall and that allocated to Rubisco (Harrison et al., 2009 , Tang et al., 2018 ). While plants PNUE are known to influenced by environment factors (Tang et al., 2019 ), but how do plants balance PNUE and toughness (LMA) under increased temperature and water stress is unknown. P deficiency is one of the major factors limiting plant productivity (Koutika 2019 ). Studies have demonstrated that while many of plant species grown in highly weathered, P-deficient environments, they still maintain high PPUE via to preferential allocation of P to mesophyll cells (Hayes et al., 2018 ). The present study partitioned plant foliar P into four fractions: structural P, metabolic P, nucleic acid P, and residual P (i.e., the uncharacterized residual fraction, which primarily contains P-containing proteins) (Hidaka and Kitayama 2011 ). Under foliage P limitation, a trade-off must occur among these four fractions to sustain a high PPUE (Hidaka and Kitayama 2009 ). Maintaining photosynthetic rates requires the allocation of more P to metabolic P (Pereira et al., 2018 ), whereas higher plant growth rates demand increased P allocation to nucleic acid P (Sterner and Elser, 2002 ; Han et al., 2021 ). Tree species with slower growth rates and reduced leaf turnover (i.e., higher LMA)exhibit greater structural P content (Villar and Merino 2001 ). Studies have shown that a high PPUE can be achieved via a relatively high investment of P in metabolic P and a reduced investment in structural P (Hidaka and Kitayama 2013 ). However, how are foliar P fractions allocated when plants are exposed to warming and water stress? Do plants continue to maintain a high PPUE, or do they allocate more P to structural P to adapt to environmental stresses—thereby slowing growth? These questions remain unresolved. In addition, the PNUE and PPUE can indirectly indicate plant adaptations to climate change. Leaf morphological traits—leaf length, width, and area—intuitively reflect plant advantages (e.g., adaptability and performance) under global climate change (Liu, Zheng, and Qi 2020 ). For instance, leaf width in the shrub species Dodonaea viscosa subsp. angustissima decreased by 2 mm with increasing temperature (Guerin, Wen, and Lowe 2012 ). Often, the leaf size increases with rising precipitation and temperature (Li et al., 2020a , Li et al., 2020b ). Recent studies have demonstrated that leaf size is significantly influenced by hydrothermal interactions (Wright et al., 2017 ). Accordingly, LMA is one of the key indicators forinvestigating plant response to climate change. LMA is often closely related to plant growth and survival strategies (Lin et al., 2021 ), which can reflect plant adaptive characteristics across different habitats. LMA is also significantly influenced by temperature and moisture (Yang et al., 2016 , Wright et al., 2017 ). Furthermore, LMA correlates with physiological traits: on average, species withlower LMA tend to have higher leaf N concentration and higher PNUE (Wright et al., 2005 , Hikosaka 2004 ). Hidaka and Kitayama ( 2009 ) observed that plants growing in P-impoverished tropical soils exhibit increased LMA and PPUE. Looking ahead, what will be the relationship between LMA, PNUE, and PPUE when plants are exposed to both warming and water stress? In summary, existing research has established that warming and drought (or water stress) can exert both positive and negative effects on plant leaf size, PNUE, and PPUE. However, the mechanisms through which warming and water stress drive changes in nutrient allocation strategies—and thereby induce changes in PNUE and PPUE—remain poorly understood. Cunninghamia lanceolata is a fast-growing evergreen conifer widely distributed in the subtropical regions of China (Yang et al., 2016 ). It constitutes 6.5% of the world's planted forests (Piao et al., 2009 ). Previous studies have demonstrated that warming and water stress significantly affect the physiological and metabolic processes of C. lanceolata (Guo et al., 2020 ; Zhang et al., 2019 ; Yu et al., 2016 ; Fang et al., 2022 ). However, no studies have investigated N and P in C. lanceolata leaves under the elevated temperature and water deficit. This study used C. lanceolata as the research subject and aimed to address the following questions: (1) How will future warming and water stress affect C. lanceolata leaf morphology and photosynthetic traits? (2) How are N and P (especially the latter) optimally allocated in C. lanceolata leaves under warming and water stress? (3) How do changes in N and P allocation driven by warming and water stress affect C. lanceolata growth? Resolving these uncertainties is critical for predicting the impacts of climate change on the physiology and ecology of tropical woody plants—knowledge that will enhance our understanding of anticipated climate change effects on terrestrial ecosystems functioning and efficiency. Materials and methods Study site and experiment design The experiment was conducted at the Fujian Sanming Forest Ecosystem National Observation and Research Station (26°19′ N, 117°36′ E) in China (Fig. 1 ). The climate is characterized as subtropical monsoon. The study site has a mean annual rainfall of 1749 mm (predominantly occurring from March to August), and a mean annual temperature and evaporation of 19.1℃ and 1585 mm, respectively, besides a mean relative humidity of 81%. The station is located at an elevation of 300 m above sea level (a. s. l). The soil is classified as a Typic Hapludult (USDA Soil Taxonomy) with clay texture, gibbsite-rich composition, and thermal regime. In April 2017, soil analysis revealed significant differences in pH, soil moisture, soil temperature, NH 4 + -N. and NO 3 − -N across the experimental four treatments (p < 0.05). Specifically, soil moisture was significantly lower in the warming treatment and the combined warming and drought treatment than in the CT, whereas soil temperature was significantly higher in these two treatments than in CT (p < 0.05, Table S1 ). The experiment had a randomized complete-block factorial design, with warming and precipitation exclusion as fixed factors. There were four treatments (with five replicates): (1) no warming and no precipitation exclusion (CT); (2) warmed with no precipitation exclusion (W, with a 5°C increase in temperature); (3) no warming but precipitation exclusion (D, with a 50% decrease in precipitation); (4) warmed and with precipitation exclusion (WD). The area of the tested mini-plot was 2 × 2 m. Around the test plot, four PVC pipes (200 cm width, 70 cm depth) were buried. In November 2013, 80 healthy, uniform C. lanceolata seedlings were selected based on their plant basal diameter, height, and fresh weight. Four seedlings were randomly transplanted into each mini-plot. In March 2014, artificial soil warming and precipitation exclusion began. A heating cable was installed under the soil in October 2013 (all cells had the same cable), buried in a spiral pattern 10 cm below the ground. Five months after planting, transparent U-shaped tubes of 0.05 x 5 m were placed at the height of the plot to isolate 50% of the rainfall (the total precipitation during the experiment was 1994.2 mm). Sampling and processing The light-saturated photosynthetic rate per leaf area (Aarea) was measured between 09:00 and 11:30 h on sunny days (Zhao, Zhao, and Gao 2013 ) using a portable open gas-exchange system (LI-6400, LiCor, Lincoln, NE, USA) in July 2017. Healthy intact leaves free of pests and diseases were selected for testing. The photosynthetic photon flux density, relative humidity, and leaf temperature in the leaf chamber were set at 1500 µmol m –2 s –1 , 60–70%, and 25 ± 0.5°C. The ambient CO 2 concentration was 390 ± 10 µmol mol − 1 . The three values per tree were averaged as the trait value of the individual. The light-saturated photosynthetic rate per unit of dry mass (Amass) was calculated as the Aarea/LMA, the PNUE was calculated as the ratio of Amass to the total leaf N content per unit of leaf dry mass (Nmass) and the PPUE was calculated as the ratio of Pmass to the total leaf P content per unit of leaf dry mass (Pmass) (Hidaka and Kitayama 2009 ). Samples were collected in July 2017. The leaves were sampled as follows: We chose branches with fully expanded leaves at 1.3 meters and facing south in the test plot, and 80 mature leaves were taken from each treatment (used to determine Aarea) and put in a marked envelope. Then, we used a digital scanner (Epson scanner) to scan the leaves. After the scan was completed, we used WinRHIZO (Pro 2005b) image analysis software to analyze the scanned images to determine the length, width, and surface area of the leaves. Next, we divided the sample in two: Half was oven-dried at 65°C for 72 h. Dried samples were ground to a powdered form using a mortar and pestle and passed through a 0.149 mm sieve before we measured the dry matter mass of C, N, and P. The foliar C and N concentrations were measured using a CN auto-analyzer (Vario Max CN, Elementar, Langenselbold, Germany). Foliar P concentrations were measured by first digesting the samples with H 2 SO 4 and HClO 4 (ratio 4:1) (Xu et al., 2017 ) and then using a continuous flow analyzer (Skalar san++, Netherlands). The other half was freeze-dried, crushed, and passed through a 0.149 mm sieve to determine the P fractions. P fractions include structural P, metabolic P, nucleic acid P, and residual P; refer to Hidaka and Kitayama ( 2011 ) for the determination method of P fractions. Statistical analyses Leaf functional traits, foliar C, N, P stoichiometry, foliar P fractions, PNUEand PPUE were analyzed using one-way ANOVA in different treatments. The effects of warming and water stress on leaf functional traits, foliar C, N, P stoichiometry, foliar P fractions. PNUE, and PPUE were analyzed within treatments using a two-way ANOVA and Tukey’s HSD post hoc test; p-values < 0.05 were considered to be statistically significant. The data were organized and statistically analyzed using SPSS 22.0 software (Statistical Graphics Corp., Princeton, USA). The surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions were subjected to Pearson correlation analysis, and the results were presented in the form of heat maps. And we also ran separate linear regressions between LMA and PNUE or PPUE. The charts were drawn using Microsoft Excel software, and the diagrams were drawn using Origin 9.0 and GraphPad Prism 8.0 software. Results Effects of warming and water stress on surface morphology of leaves The W and D treatments did not have a significant effect on the dry weight and width of the leaves (Table 1). The leaf length was highly significantly increased by 51.1% under the W treatment compared with CT, resulting in a highly significant increase in leaf area by 44.9% (Table 1, p < 0.01). At the same time, the LMA significantly decreased by 23.3% under the W treatment (Table 1, p < 0.05), indicating that the main influencer of leaf morphology traits is the temperature. Table 1 Morphological changes of leaves under different treatments in C. lanceolata. Treatment Dry mass (g) Length (mm) Width (mm) Area (mm 2 ) LMA (g m -2 ) CT 0.01±0.0016 A 33.14±4.13 B 2.62±0.09 A 2.76±0.41 B 50.54±2.90 AB W 0.02±0.0018 A 50.06±2.96 A 2.56±0.07 A 4.00±0.16 A 38.73±6.00 B D 0.02±0.0009 A 35.83±2.77 B 2.58±0.13 A 2.94±0.37 AB 60.02±7.39 A WD 0.02±0.0005 A 41.65±2.72 AB 2.68±0.09 A 3.49±0.17 AB 46.26±1.86 AB W F 0.124 12.644 0.061 8.917 6.384 p 0.729 0.003 0.807 0.009 0.022 D F 2.305 0.798 0.217 0.304 2.826 p 0.148 0.385 0.648 0.589 0.112 W×D F 0.791 3.016 0.768 1.331 0.037 p 0.387 0.102 0.394 0.266 0.850 Notes: Values are shown as mean±SD (n = 5). Data with different capital letters refer to significant differences in different treatments at the 0.05 level. Treatment: control (CT), warming (W), water stress (D), and warming and water stress (WD). Bold numbers indicate significant differences. Effects of warming and water stress on nutrient stoichiometry of leaves There was no significant difference in the C concentration among the four treatments (Fig. 2a). The N concentration was highly significantly increased by 24.1% under D treatment compared to CT ( p < 0.01, Fig. 2b), resulting in a significant decrease in the C:N ratio by 19.8% under the D treatment ( p < 0.05, Fig. 2d). The P concentration was significantly different under the interaction of warming and water stress, and the P concentrations were reduced by 13.3% and 19.3%, respectively, under W and D treatments compared with CT ( p < 0.05, Fig. 2c). As a result, the ratios of C:P and N:P were found to be significantly different under the interaction of warming and water stress, where C:P increased by 14% and 20.2% under W and D treatments, respectively, while the N:P ratio increased significantly by 51.7% under the D treatment ( p < 0.05, Fig. 2e, f). Effects of warming and water stress on photosynthetic nutrient-use efficiency of leaves The PNUE was significantly increased by 35.6% ( p < 0.05) under the W treatment (Fig. 3a) and was highly significantly decreased by 35.7% ( p < 0.01) under the D treatment. The PPUE was not changed significantly under either the W or D treatment, but the PPUE of W was greater than for the other three treatments (Fig. 3b). Through regression analysis, the photosynthetic nutrient-use efficiency and leaf LMA were significantly negatively correlated (Fig. 4, p structural P > nucleic acid P > residual P (Fig. 5). However, in the W and WD treatments, the ratio of the P fractions was structural P > metabolic P > nucleic acid P > residual P (Fig. 5), indicating that the changes in structural P and metabolic P were related to the change in temperature. Through our analysis, we found that only the metabolic P significantly differed under the interaction of warming and water stress (Fig. 5, p < 0.05). Through further analyses, we found that under the W treatment, metabolic P was significantly reduced by 32.5% compared with CT ( p < 0.05). Under D treatment, meanwhile, it was significantly reduced by 32.1%, compared with CT ( p < 0.05). As such, we assert that the metabolic P is greatly affected by temperature and moisture. By analyzing the proportions of four P fractions, we found that metabolic P accounted for the largest proportion in all the four treatments, followed by structural P (Fig. 5). In addition, W, D, and WD treatments can increase the proportion of structural P and decrease the proportion of metabolic P (Fig. 5). Through the analysis of the relationship between the four P fractions, it was found that the proportion of metabolic P was inversely proportional to the proportion of structural P and nucleic acid P, respectively, indicating that the proportion of structural P and nucleic acid P decreased with the increase of the proportion of metabolic P in the P fractions distribution of leaves (Fig. 6). The correlation between the surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions of different treatment leaves The analysis results show that N and C:N ratios and P and C:P ratios were significantly negatively correlated in the four treatments ( p < 0.01). Under CT treatment, length was positively correlated with dry mass, area was positively correlated with dry mass and length, LMA was positively correlated with length and area, and PNUE was positively correlated with length, area, and LMA. Structural P was significantly positively correlated with C and P and negatively correlated with N/P and C/P, metabolic P was significantly positively correlated with P and width, and nucleic acid P was significantly negatively correlated with C/N and PPUE. Residual P was negatively correlated with N/P (Fig. 7a, p < 0.05). Under W treatment, length is negatively correlated with C:P ratios. Width is negatively correlated with P and positively correlated with C/P. Area and width are positively correlated. There is a significant positive correlation between LMA and dry mass. PNUE was positively correlated with length and area. PPUE was positively correlated with PNUE. Structural P was negatively correlated with N/P. Metabolic P was positively correlated with P, length, area, and PNUE, and negatively correlated with C:P ratios. Residual P was significantly negatively correlated with N:P ratios (Fig. 7b, p < 0.05). Under D treatment, area was positively correlated with length and width ( p < 0.01). LMA is negatively correlated with length. P was positively correlated with the four P fractions. And three P fractions negatively correlated with C:P ratios, except metabolic P. The nucleic acid P was positively correlated with structural P and residual P (Fig. 7c, p < 0.05). Under WD treatment, width is negatively correlated with length. LMA was negatively correlated with N and positively correlated with N:P ratios. Structural P was negatively correlated with C:P ratios. The nucleic acid P was negatively correlated with PPUE. Residual P was significantly negatively correlated with C:P ratios, and residual P was significantly positively correlated with structural P and nucleic acid P (Fig. 7d, p < 0.05). Discussion Effect of warming and drought on leaf functional traits Temperature is an important factor affecting plant growth. Warming will directly affect the physiological characteristics and morphology of plants (Peppe et al., 2011 ; Yu et al., 2022 ; Seth and Sebastian, 2024 ; Liu et al., 2024 ; Jiang et al., 2023 ). In this study, we noted leaf trait responses, such as an increasing leaf area, leaf length, and lower LMA under experimental warming. Different from the results of this study, some studies have found that the leaf size decreases with increasing temperature (Kang et al., 2021 ). However, Ren et al. ( 2021 ) measured the leaf size of a total of 1192 grassland species in the Tibetan Plateau, Loess Plateau, and Mongolian Platea; they found that the leaf size increases with temperature (Ren et al., 2021 ). The plants can adjust their leaf length to add to the intercepting surface area for light (Yang et al., 2011 ), which also allows leaves to fix more CO 2 . And some researchers also found that warming reduced the LMA of leaves (Yu et al., 2022 ; Huang et al., 2022 ; Liu et al., 2021 ); a decrease in LMA indicates that the ability of plants to capture light energy is enhanced (Scoffoni et al., 2011 ; Houminer et al., 2022 ). Both of them are beneficial to leaf photosynthesis. Water stress, one of the major abiotic stresses, changes plant growth by affecting various physiological and biochemical processes (Chiappero et al., 2019 , Zhang et al., 2022 ). In this study, a leaf accumulated more N when exposed to water stress, resulting in low C:N and high N:P ratios. It has also been reported that drought-increased N is likely used for photosynthesis, given 50% of ribulose-1, 5-bisphosphate carboxylase/oxygenase, the major enzyme for C fixation in photosynthesis, consists of soluble proteins in C. lanceolata (Feller, Anders and Mae 2008 , Shaw and Cheung 2021 ). However, Orians et al. ( 2019 ) found foliar N was reduced under drought in a Boston area climate experiment (Orians et al., 2019 ). Such a finding is notably different from our results, which may be explained by the fact that the object of this study was woody plants in subtropical regions, while the object of study for Orians et al. ( 2019 ) was herbaceous plants in temperate regions. Regardless, it can be seen that the response of the plant N concentration to water is closely related to the experimental area and experimental material. Changes in leaf C:N ratios can help us predict how plant productivity will respond to future climate change scenarios (Yue et al., 2017 ). In this area, plants will increase their N utilization efficiency while reducing their N consumption in the leaves to maintain basic metabolic activities, resulting in a decrease in C:N to adapt to a relatively drought-ridden environment under water stress. Higher temperatures reduce relative humidity and soil moisture (Ren et al., 2022 ), which can have a negative effect on photosynthesis and plant stoichiometry (Olivera Viciedo et al., 2019 , Huang et al., 2018 ). In this study, the P concentration and C:P and N:P ratios were significantly affected by the combined effects of warming and water stress. Both warming and drought conditions decreased P concentration. A plant’s nutrient status response to warming was strongly dependent on its impact on soil moisture, given warming can simultaneously exacerbate water and nutrient limitation in dry lands via its negative effects on soil moisture (Ji et al., 2022 , Peñuelas et al., 2004 , Sardans and Peñuelas 2012 ). This is due to water stress, which can reduce the absorption, transportation, and redistribution of P by plants (Rouphael et al., 2012 ). The C:P ratio can reflect the speed of plant growth (Sterner and Elser 2002 ). Since carbon is relatively constant, the C:P ratio was determined by the P concentration. The N and P allocation strategies in leaves under warming and drought conditions Environmental changes will induce adaptive modifications in the allocation of N and P, thereby adjusting the survival strategies of organisms (Tang et al., 2019 ; Liu et al., 2020 ). Our analysis suggested that C. lanceolata may have good potential for fast growth and high resource-use efficiency in a warmer climate in the future. This was evidenced by the increase in the PNUE and PPUE in the W treatment. The PNUE was increased with warming in our study, in line with the results of Yang et al. ( 2011 ), who found that K. pygmaea leaves exhibited a higher PNUE under experimental warming, indicating advanced physiological activity (Yang et al., 2011 ). The proportion of N in plant leaves involved in photosynthesis has also been noted to affect the PNUE (Hikosaka 2004 ). The higher the PNUE, the higher the N utilization rate of leaves, indicating that the plant can make better use of the N element under an increased temperature. In this way, plants adapt to the warming environment by decreasing their investment in cell wall N to reduce LMA, while increasing their N investment in Rubisco to increase the PNUE. On the contrary, under water stress treatment, PNUE significantly decreased while LMA increased. This indicates that C. lanceolata allocates more N to the cell wall in order to enhance leaf toughness and cope with water shortage conditions. Simultaneously, water stress restricts N utilization, leading to reduced plant growth in N-restricted areas. Besides, in the present study, we found the PNUE and PPUE were negatively correlated with LMA (Fig. 4 .). The relationship between PNUE and LMA was found to be consistent with the results of previous studies (Hidaka and Kitayama 2009 , Hidaka and Kitayama 2011 ). The PNUE likely decreased due to these physiological and anatomical changes. Increased LMA causes a decline in photosynthetic rates via higher resistance to CO 2 diffusion (Earles et al., 2017 ) and via smaller N allocation to the metabolic fraction (e.g., ribulose-1,5-bisphosphate carboxylase/oxygenase) as a result of greater N allocation to the structural fraction (i.e., cell walls) (Onoda, Hikosaka, and Hirose 2004 ; Takashima, Hikosaka, and Hirose 2004 ). Organisms need to constantly recalibrate development and physiology in response to changes in warming and drought (Li et al., 2023 ; Seth and Sebastian, 2024 ). In this article, the combined effects of warming and water stress caused significant changes to the metabolic P and foliar P. Under warming and water stress treatments, the metabolic P was smaller than CT. P-containing metabolites play key roles in the Calvin–Benson cycle, and insufficient metabolic P could limit the maximum photosynthetic rates (Ågren, Wetterstedt, and Billberger 2012 ). On the other hand, through analysis, we found that compared with CT, W, and WD treatment, structure P all increased, but because D significantly reduced foliage P, structure P also decreased under D treatment, indicating that water has a great influence on P. Meanwhile, metabolic P and nucleic acid P decreased under W, D, and WD treatment. Han et al. ( 2021 ) found that faster-growing trees allocated more foliage P to nucleic acid P than slower-growing trees (Han et al., 2021 ). The assignment of leaf phosphorus fractions may be related to subsistence requirements, as these fractions are functionally related to growth and reproduction (Han et al., 2021 ; Gao et al., 2022 ). Presumably, C. lanceolata in this study may have increased investment in leaf epidermal cells and decreased investment in mesophyll cells and ribosomal RNA, increasing the toughness and area of the leaves, slowing growth rates, and reducing photosynthetic efficiency to resist warming and water stress (Lambers et al., 2022 ). Furthermore, the research results of this study regarding PPUN and LMA are different from those of Hidaka and Kitayama ( 2009 ). They suggested that there is not a negative correlation between PPUE and LMA. This study concluded that any negative correlation between PPUE and LMA may be caused by a significant decrease in leaf P due to a temperature increase and water stress, along with the N limitation of this sample site. To survive under conditions of low nutrient supply, drought, and high temperatures, leaves are expected to exhibit high LMA values relative to those of the species in more favorable environments. Thus, plants under warming and water stress need to invest more P in structural P to maintain a higher LMA, and plants with higher LMA usually exhibit slower growth and a longer leaf lifespan (Villar et al., 2006 ; Houminer et al., 2022 ). Yuki Tsujii et al. ( 2024 ) suggest that lower PPUE correlates with higher LMA, indicating a shift in ecological strategy toward greater investment in the structure of leaf P as LMA increases (Tsujii et al., 2024 ). The results of this study show that structural P-ratios and nucleic acid P-ratios are inversely proportional to metabolic P-ratios (Fig. 6 .), indicating that with the increase in LMA, the concentration of metabolic P decreases, leading to a decrease in the photosynthetic rate due to higher resistance to CO 2 diffusion (Earles et al., 2017 ), which causes a decrease in PPUE. In addition, the leaf area and leaf length increase for the W, D, and WD treatments, confirming our conjecture that C. lanceolata faces climate change by slowing down its growth rate in the environment of warming and water stress. The correlation between the surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions of different treatment leaves If the climate changes, plants shift the distribution of phosphorus between the phosphorus fractions of the leaf surface, which may increase their fitness under prevailing conditions. Through analysis, we discovered a significant positive correlation between total P and all four fractions in water stress treatment. This is due to the fact that low total P levels are associated with lower concentrations of structural P and metabolic P because under low phosphorus conditions, phosphorus storage in the vacuole is reduced and rRNA levels are reduced (Tsujii et al., 2024 ). In this study, it was found that structure P, nucleic acid P, and residual P were significantly positively correlated. Residual P plays a role in protein phosphorylation (Lambers 2022 ). While nucleic acid P plays a role in protein synthesis and turnover, structure P is closely related to the endoplasmic reticulum, and they coordinate to influence the form of proteins. In addition, this study found that in warming and water stress NP was negatively correlated with all except nucleic acid P, which was the same as that of Yuki Tsujii (2024) (Tsujii et al., 2024 ). They suggested that nitrogen is positively correlated with the concentration of other P fractions, resulting in a negative correlation between structure P and nitrogen or the ratio of N:P. Residual P is negatively correlated with the ratio of N:P, reflecting a relatively small allocation of protein phosphorylation. In this study, a significant negative correlation between nucleic acid P and PPUE was found, indicating that when PPUE increased, the portion of P assigned to nucleic acid P decreased, and lower input of nucleic acid P was associated with a slower relative growth rate (Han et al., 2021 ). This is also related to the fact that C. lanceolata is an evergreen coniferous plant, and fewer leaves will wither and fall. Overall, C. lanceolata leaves adapt to the adverse environment by slowing down growth in the environment of temperature increase and water stress (Fig. 8 ). Conclusions Studies on C. lanceolata under warming and water stress found that C. lanceolata had a larger leaf area and smaller LMA under warming treatment, indicating the plant's potential for rapid growth and high resource-use efficiency under future warming. When studied under a warming treatment, a high PNUE is explained by a relatively greater investment of N in N-containing Rubisco and a relatively lesser investment in the cell wall. On the contrary, PNUE significantly decreased and LMA increased under water stress treatments, suggesting that more N is invested into the cell wall to increase leaf toughness and adapt to water deficit. Warming and drought treatments alone did not significantly affect P partitioning in C. lanceolata leaves. In the final analysis, the combined effects of warming and water stress were assessed. Through our analysis of P fractions and PPUE, we found that water stress has a greater impact on the P concentration in the area, significantly reducing the foliar P concentration and restricting the PPUE, resulting in a greater LMA and lower PPUE. The analysis suggests that C. lanceolata may increase investment in leaf epidermal cells, decrease investment in mesophyll cells and ribosomal RNA, increase leaf toughness and area, slow growth rate, and decrease photosynthetic efficiency to resist warming and water stress. Unexpectedly, our research results found that in this area, the N limitation on plant growth was alleviated by water stress, but leaves’ P utilization was limited. In future research, we will set up restrictions on N and P for different degrees of water stress to determine the acceptable condition for each. Our study examined the allocation strategies of C. lanceolata leaves in response to warming and drought conditions. The findings provide a valuable reference for understanding the growth adaptability strategies of leaves in the context of global climate change. Declarations Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflcit of interest. Fundings This research was funded by the National Natural Science Foundation of China (31930071) and the Natural Science Foundation of Fujian Province (2021J01146). Acknowledgments We thank the School of Geographical Sciences, Fujian Normal University, and Fujian Sanming Forest Ecosystem National Observation and Research Station for providing us with experimental plots and experimental tools in the field. And thank you to all the teachers and staff at the field station. Finally, we thank anonymous reviewers and the editors for their work on this manuscript. References Ågren GI, Wetterstedt JÅM, Billberger MFK (2012) Nutrient limitation on terrestrial plant growth - modeling the interaction between nitrogen and phosphorus. 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Photosynthetica 51:245–251. https://doi.org/10.1007/s11099-013-0016-3 Supplementary Files Originaldata.xlsx SupplementaryMaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9358268","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624592186,"identity":"b16585a0-13d4-44f1-b5bb-82780a645e76","order_by":0,"name":"Xuan Fang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBAC9gYQaWAjx8/e2PjwAzFaeA6AyII0Y8mew83GEsRr+XA4ccON9DYBHqK0SOQYfi4wOJzYcPNhG4MEg52cbgMhLTxnjKVnGKQbN85ObHtQwJBsbHaAgBZ79h4DaR4Da9lm6cR2AwmGA4nbCGnhYeYx/s1jwMzYJnmwTYKHKC3sPWZAW5wVeyQYidXCc6zMmscgzViCJxEYyAZE+IVHInnzbZ4/NnL2x48/fPihwk6OoBY0YECa8lEwCkbBKBgFOAAAkXI9XH8P7o4AAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0005-6201-2554","institution":"Fujian Teachers University: Fujian Normal University","correspondingAuthor":true,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Fang","suffix":""},{"id":624592187,"identity":"7ca44761-f356-4278-9120-e1dda974a1c3","order_by":1,"name":"Hui Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Chen","suffix":""},{"id":624592188,"identity":"67f8d4f4-a349-4897-8998-c5bcb03b6063","order_by":2,"name":"Yueling Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yueling","middleName":"","lastName":"Li","suffix":""},{"id":624592189,"identity":"75976d2c-99ab-4ae5-8c03-c52ab76c47f9","order_by":3,"name":"Jinmao Zhu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jinmao","middleName":"","lastName":"Zhu","suffix":""},{"id":624592190,"identity":"571483d3-2e5a-401f-b34d-090d8de5bf6b","order_by":4,"name":"Jian Wang","email":"","orcid":"https://orcid.org/0000-0003-0448-1027","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Wang","suffix":""},{"id":624592191,"identity":"9a4d818e-8c50-44d7-bb16-f4e14581e46a","order_by":5,"name":"Yusheng Yang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yusheng","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2026-04-08 14:26:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9358268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9358268/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107869407,"identity":"3dd7ac14-7269-4825-b1af-20691192d6c7","added_by":"auto","created_at":"2026-04-27 07:37:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":519458,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area.\u003c/p\u003e\n\u003cp\u003e(a) The geographical location diagram of the sample site. (b) The actual diagram of the sample site. (c) The rainfall and temperature of the sample site from January 2016 to July 2017\u003c/p\u003e\n\u003cp\u003eNotes: ★ is the specific location of the field station.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/f3da0b27dadad679cc00284c.png"},{"id":107869264,"identity":"89aa8174-2ff5-42a1-8c78-6aa0e55fb92a","added_by":"auto","created_at":"2026-04-27 07:36:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":240420,"visible":true,"origin":"","legend":"\u003cp\u003eC, N, and P stoichiometry characteristics of leaves under different treatments in \u003cem\u003eC. lanceolata.\u003c/em\u003e (a) C concentration of leaves under different treatments, (b) N concentration of leaves under different treatments, (c) P concentration of leaves under different treatments, (d) the ratio of C to N in leaves under different treatments, (e) the ratio of C to P in leaves under different treatments, (f) the ratio of N to P in leaves under different treatments.\u003c/p\u003e\n\u003cp\u003eNotes: Treatment: control (CT), warming (W), water stress (D), and warming plus water stress (WD). Values are mean ± SD (n=5), and treatment in the combination is expressed as W: warming effect; D: water stress effect; W×D: interactive effect of warming and water stress; *: significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **: highly significant effect at \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01; and ns: no significant effect at\u003cem\u003e p \u003c/em\u003e\u0026gt; 0.05. The bars with different capital letters are significantly different from each other (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). Values are mean ± SD (n=5).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/b1b390c551d2c7700930e872.png"},{"id":107869268,"identity":"add92e06-7ba4-459b-8f66-7f7c77b63256","added_by":"auto","created_at":"2026-04-27 07:36:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88265,"visible":true,"origin":"","legend":"\u003cp\u003ePhotosynthetic nutrient-use efficiency of leaves under different treatments in \u003cem\u003eCunninghamia lanceolata.\u003c/em\u003e (a) Photosynthetic N-use efficiency of leaves under different treatments, (b) photosynthetic P-use efficiency of leaves under different treatments.\u003c/p\u003e\n\u003cp\u003eNotes: Treatment: control (CT), warming (W), water stress (D), and warming plus water stress (WD). Values are mean ± SD (n=5); treatment in the combination is expressed as W: warming effect, D: water stress effect, W×D: interactive effect of warming and water stress, *: significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **: highly significant effect at \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01; ns: no significant effect at\u003cem\u003e p \u003c/em\u003e\u0026gt; 0.05.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/1eaf0fe1dfd74a3dc2ca2bb7.png"},{"id":107730712,"identity":"9495912e-a206-4569-9d42-4bc41e23523f","added_by":"auto","created_at":"2026-04-24 13:04:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139812,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between photosynthetic nutrient-use efficiency of leaves and LMA in \u003cem\u003eC. lanceolata\u003c/em\u003e. (a) Relationships between photosynthetic N-use efficiency of leaves and LMA, (b) Relationships between photosynthetic P-use efficiency of leaves and LMA.\u003c/p\u003e\n\u003cp\u003eNotes: r\u003csup\u003e2\u003c/sup\u003e is the fitting coefficient, and r is the correlation coefficient, with a highly significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ns: no significant effect at\u003cem\u003e p \u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/27fe4ca4387d05850b373159.png"},{"id":107869646,"identity":"c2ca3252-0acb-473f-890e-243ac615cb6e","added_by":"auto","created_at":"2026-04-27 07:37:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":158886,"visible":true,"origin":"","legend":"\u003cp\u003eP fractions and their proportion of leaves under different treatments in \u003cem\u003eC. lanceolata. \u003c/em\u003eTreatment: control (CT), warming (W), water stress (D), and warming plus water stress (WD). Values are mean ± SD (n=5). Treatment in the combination is expressed as W: warming effect, D: water stress effect, W×D: interactive effect of warming and water stress, *: significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **: highly significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ns: no significant effect at\u003cem\u003e p \u003c/em\u003e\u0026gt; 0.05.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/9e378008b78dd3bb2f3a74f1.png"},{"id":107868842,"identity":"37d700b3-758a-4dda-92df-fe904615107b","added_by":"auto","created_at":"2026-04-27 07:34:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":132886,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between the proportions of the four P fractions in \u003cem\u003eC. lanceolata\u003c/em\u003e. (a) Relationship between metabolic P proportion and structural P proportion. (b) Relationship between metabolic P proportion and nucleic P proportion. r\u003csup\u003e2\u003c/sup\u003e is the fitting coefficient, and r is the correlation coefficient, with a highly significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ns: no significant effect at\u003cem\u003e p \u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/f3c979aebe2da05097735cf3.png"},{"id":107730715,"identity":"454e8cf1-cf0d-45b1-94f9-ca6a1526e647","added_by":"auto","created_at":"2026-04-24 13:04:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":270330,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between the surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions of different treatment leaves. (a) CT treatment.(b) W treatment. (c) D treatment. (d) WD treatment.\u003c/p\u003e\n\u003cp\u003eNotes: Significant effect at\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05; highly significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/236162520890e5d3ed1f22cd.png"},{"id":107730716,"identity":"b5aabc7e-b4c5-489d-9a86-712cf031d96a","added_by":"auto","created_at":"2026-04-24 13:04:15","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":140975,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrams summarizing foliar traits affecting growth strategy for \u003cem\u003eC. lanceolata \u003c/em\u003eunder warming and water stress conditions.\u003c/p\u003e\n\u003cp\u003eNotes: solid lines indicate connections between factors; dashed arrows indicate factors that affect another factor; the orange dashed arrow indicates that the factor affects the relative growth rate. P: phosphorus; LMA: leaf mass per area; PNUE: photosynthetic N use efficiency; PPUE: photosynthetic P use efficiency.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/57c73f481a716b03592c9873.png"},{"id":109500659,"identity":"d3fe0e45-7892-45ca-8f57-14de4e9238d3","added_by":"auto","created_at":"2026-05-18 22:11:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1768210,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/ec34cba7-1c18-435c-96e1-864f97daba18.pdf"},{"id":107730708,"identity":"9bdf058e-ca14-4356-874d-21618479eb66","added_by":"auto","created_at":"2026-04-24 13:04:15","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3339521,"visible":true,"origin":"","legend":"","description":"","filename":"Originaldata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/917a8030faf82c046cde9dfd.xlsx"},{"id":107730710,"identity":"b140ddc9-0be1-4257-8878-e34c00479b51","added_by":"auto","created_at":"2026-04-24 13:04:15","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15589,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9358268/v1/ecaaad261d9d6d521ca5ac17.docx"}],"financialInterests":"","formattedTitle":"Modeling the simulated soil warming and water stress on foliar Nutrients allocation of Cunninghamia lanceolata","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Intergovernmental Panel on Climate Change (IPCC) reported that the global surface temperature was 1.09\u0026deg;C higher during 2011\u0026ndash;2020 than during 1850\u0026ndash;1900, and it is projected that the globe will have warmed by 4\u0026ndash;5℃ by 2100 (IPCC \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Human activities have likely influenced global soil moisture patterns during the 20th century. The combination of a higher temperature, lower relative humidity, and greater net radiation has increased atmospheric evaporative demand, which, in turn, has enhanced water evaporation and dispersion, resulting in a global trend toward drought (IPCC \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, the probability of co-occurring high temperature and water stress is increasing. Most plant species are adapted to grow within specific temperature and moisture ranges, consequently, climate change will have a significant impact on plant ecosystems. (Kang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), though they will likely adapt to higher temperatures and water stress by modifying their growth and development or by shifting leaf function (i.e., nutrient allocation and photosynthesis) and/or size (Christie et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Lynn et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Guittar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNot only do the alteration of nitrogen (N) and phosphorus (P) elements reflect global climate change, but they also play a crucial part in plant photosynthesis (Luo et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Sterner and Elser \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Studies on the effects of warming and water stress on N and P concentrations are now prevalent, with findings showing that warming treatments either reduce leaf N and P concentrations(Zhang et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Tian et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), increase, or generate no change (Sardans et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Similarly, studies examing the effect of water stress on plant nutrients have found that the impacts on plant N and P concentrations are inconclusive, either decreasing (Farooq et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) or increasing (Gargallo-Garriga et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Furthermore, few studies have focused on the mechanisms governing N and P partitioning in leaves under combined warming and water stress.\u003c/p\u003e \u003cp\u003ePhotosynthetic nutrient-use efficiency (PNUE/PPUE) is the ratio of photosynthetic rate to leaf N or P concentration, respectively. It serves as a critical parameter for characterizing plants\u0026rsquo; leaf nutrient allocation patterns, physiological traits, and survival strategies (Yang et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Tang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The photosynthetic nitrogen-use efficiency (PNUE) and photosynthetic phosphorus-use efficiency (PPUE) are significantly influenced by foliar N and P concentrations, respectively, and studies have further demonstrated that optimizing the functional allocation of N and P within leaves is critical, as the distribution of these nutrients directly modulte PNUE and PPUE (Pao et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). PNUE represents the physiological relationship between the N content and photosynthetic capacity in leaves, with the proportion of leaf N allocated to the photosynthetic apparatus being a key factor in determining PNUE (Minjee et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Owing to constraints imposed by its physical structure and physiological function, a leaf cannot simultaneously maximize both PNUE and toughness (quantified by leaf mass per area (LMA)), consequently, a trade-off exists between N allocated to cell wall and that allocated to Rubisco (Harrison et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Tang et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While plants PNUE are known to influenced by environment factors (Tang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but how do plants balance PNUE and toughness (LMA) under increased temperature and water stress is unknown.\u003c/p\u003e \u003cp\u003eP deficiency is one of the major factors limiting plant productivity (Koutika \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies have demonstrated that while many of plant species grown in highly weathered, P-deficient environments, they still maintain high PPUE via to preferential allocation of P to mesophyll cells (Hayes et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The present study partitioned plant foliar P into four fractions: structural P, metabolic P, nucleic acid P, and residual P (i.e., the uncharacterized residual fraction, which primarily contains P-containing proteins) (Hidaka and Kitayama \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Under foliage P limitation, a trade-off must occur among these four fractions to sustain a high PPUE (Hidaka and Kitayama \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Maintaining photosynthetic rates requires the allocation of more P to metabolic P (Pereira et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), whereas higher plant growth rates demand increased P allocation to nucleic acid P (Sterner and Elser, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Han et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Tree species with slower growth rates and reduced leaf turnover (i.e., higher LMA)exhibit greater structural P content (Villar and Merino \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Studies have shown that a high PPUE can be achieved via a relatively high investment of P in metabolic P and a reduced investment in structural P (Hidaka and Kitayama \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, how are foliar P fractions allocated when plants are exposed to warming and water stress? Do plants continue to maintain a high PPUE, or do they allocate more P to structural P to adapt to environmental stresses\u0026mdash;thereby slowing growth? These questions remain unresolved.\u003c/p\u003e \u003cp\u003eIn addition, the PNUE and PPUE can indirectly indicate plant adaptations to climate change. Leaf morphological traits\u0026mdash;leaf length, width, and area\u0026mdash;intuitively reflect plant advantages (e.g., adaptability and performance) under global climate change (Liu, Zheng, and Qi \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For instance, leaf width in the shrub species \u003cem\u003eDodonaea viscosa\u003c/em\u003e subsp. \u003cem\u003eangustissima\u003c/em\u003e decreased by 2 mm with increasing temperature (Guerin, Wen, and Lowe \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Often, the leaf size increases with rising precipitation and temperature (Li et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, Li et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). Recent studies have demonstrated that leaf size is significantly influenced by hydrothermal interactions (Wright et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Accordingly, LMA is one of the key indicators forinvestigating plant response to climate change. LMA is often closely related to plant growth and survival strategies (Lin et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which can reflect plant adaptive characteristics across different habitats. LMA is also significantly influenced by temperature and moisture (Yang et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Wright et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, LMA correlates with physiological traits: on average, species withlower LMA tend to have higher leaf N concentration and higher PNUE (Wright et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, Hikosaka \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Hidaka and Kitayama (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) observed that plants growing in P-impoverished tropical soils exhibit increased LMA and PPUE. Looking ahead, what will be the relationship between LMA, PNUE, and PPUE when plants are exposed to both warming and water stress?\u003c/p\u003e \u003cp\u003eIn summary, existing research has established that warming and drought (or water stress) can exert both positive and negative effects on plant leaf size, PNUE, and PPUE. However, the mechanisms through which warming and water stress drive changes in nutrient allocation strategies\u0026mdash;and thereby induce changes in PNUE and PPUE\u0026mdash;remain poorly understood. \u003cem\u003eCunninghamia lanceolata\u003c/em\u003e is a fast-growing evergreen conifer widely distributed in the subtropical regions of China (Yang et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It constitutes 6.5% of the world's planted forests (Piao et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Previous studies have demonstrated that warming and water stress significantly affect the physiological and metabolic processes of \u003cem\u003eC. lanceolata\u003c/em\u003e (Guo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fang et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, no studies have investigated N and P in \u003cem\u003eC. lanceolata\u003c/em\u003e leaves under the elevated temperature and water deficit. This study used \u003cem\u003eC. lanceolata\u003c/em\u003e as the research subject and aimed to address the following questions: (1) How will future warming and water stress affect \u003cem\u003eC. lanceolata\u003c/em\u003e leaf morphology and photosynthetic traits? (2) How are N and P (especially the latter) optimally allocated in \u003cem\u003eC. lanceolata\u003c/em\u003e leaves under warming and water stress? (3) How do changes in N and P allocation driven by warming and water stress affect \u003cem\u003eC. lanceolata\u003c/em\u003e growth? Resolving these uncertainties is critical for predicting the impacts of climate change on the physiology and ecology of tropical woody plants\u0026mdash;knowledge that will enhance our understanding of anticipated climate change effects on terrestrial ecosystems functioning and efficiency.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site and experiment design\u003c/h2\u003e \u003cp\u003eThe experiment was conducted at the Fujian Sanming Forest Ecosystem National Observation and Research Station (26\u0026deg;19\u0026prime; N, 117\u0026deg;36\u0026prime; E) in China (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The climate is characterized as subtropical monsoon. The study site has a mean annual rainfall of 1749 mm (predominantly occurring from March to August), and a mean annual temperature and evaporation of 19.1℃ and 1585 mm, respectively, besides a mean relative humidity of 81%. The station is located at an elevation of 300 m above sea level (a. s. l). The soil is classified as a Typic Hapludult (USDA Soil Taxonomy) with clay texture, gibbsite-rich composition, and thermal regime. In April 2017, soil analysis revealed significant differences in pH, soil moisture, soil temperature, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N. and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N across the experimental four treatments (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, soil moisture was significantly lower in the warming treatment and the combined warming and drought treatment than in the CT, whereas soil temperature was significantly higher in these two treatments than in CT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe experiment had a randomized complete-block factorial design, with warming and precipitation exclusion as fixed factors. There were four treatments (with five replicates): (1) no warming and no precipitation exclusion (CT); (2) warmed with no precipitation exclusion (W, with a 5\u0026deg;C increase in temperature); (3) no warming but precipitation exclusion (D, with a 50% decrease in precipitation); (4) warmed and with precipitation exclusion (WD). The area of the tested mini-plot was 2 \u0026times; 2 m. Around the test plot, four PVC pipes (200 cm width, 70 cm depth) were buried. In November 2013, 80 healthy, uniform \u003cem\u003eC. lanceolata\u003c/em\u003e seedlings were selected based on their plant basal diameter, height, and fresh weight. Four seedlings were randomly transplanted into each mini-plot.\u003c/p\u003e \u003cp\u003eIn March 2014, artificial soil warming and precipitation exclusion began. A heating cable was installed under the soil in October 2013 (all cells had the same cable), buried in a spiral pattern 10 cm below the ground. Five months after planting, transparent U-shaped tubes of 0.05 x 5 m were placed at the height of the plot to isolate 50% of the rainfall (the total precipitation during the experiment was 1994.2 mm).\u003c/p\u003e\n\u003ch3\u003eSampling and processing\u003c/h3\u003e\n\u003cp\u003eThe light-saturated photosynthetic rate per leaf area (Aarea) was measured between 09:00 and 11:30 h on sunny days (Zhao, Zhao, and Gao \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) using a portable open gas-exchange system (LI-6400, LiCor, Lincoln, NE, USA) in July 2017. Healthy intact leaves free of pests and diseases were selected for testing. The photosynthetic photon flux density, relative humidity, and leaf temperature in the leaf chamber were set at 1500 \u0026micro;mol m\u003csup\u003e\u0026ndash;2\u003c/sup\u003e s\u003csup\u003e\u0026ndash;1\u003c/sup\u003e, 60\u0026ndash;70%, and 25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C. The ambient CO\u003csub\u003e2\u003c/sub\u003e concentration was 390\u0026thinsp;\u0026plusmn;\u0026thinsp;10 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The three values per tree were averaged as the trait value of the individual. The light-saturated photosynthetic rate per unit of dry mass (Amass) was calculated as the Aarea/LMA, the PNUE was calculated as the ratio of Amass to the total leaf N content per unit of leaf dry mass (Nmass) and the PPUE was calculated as the ratio of Pmass to the total leaf P content per unit of leaf dry mass (Pmass) (Hidaka and Kitayama \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSamples were collected in July 2017. The leaves were sampled as follows: We chose branches with fully expanded leaves at 1.3 meters and facing south in the test plot, and 80 mature leaves were taken from each treatment (used to determine Aarea) and put in a marked envelope. Then, we used a digital scanner (Epson scanner) to scan the leaves. After the scan was completed, we used WinRHIZO (Pro 2005b) image analysis software to analyze the scanned images to determine the length, width, and surface area of the leaves. Next, we divided the sample in two: Half was oven-dried at 65\u0026deg;C for 72 h. Dried samples were ground to a powdered form using a mortar and pestle and passed through a 0.149 mm sieve before we measured the dry matter mass of C, N, and P. The foliar C and N concentrations were measured using a CN auto-analyzer (Vario Max CN, Elementar, Langenselbold, Germany). Foliar P concentrations were measured by first digesting the samples with H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e and HClO\u003csub\u003e4\u003c/sub\u003e (ratio 4:1) (Xu et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and then using a continuous flow analyzer (Skalar san++, Netherlands). The other half was freeze-dried, crushed, and passed through a 0.149 mm sieve to determine the P fractions. P fractions include structural P, metabolic P, nucleic acid P, and residual P; refer to Hidaka and Kitayama (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) for the determination method of P fractions.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eLeaf functional traits, foliar C, N, P stoichiometry, foliar P fractions, PNUEand PPUE were analyzed using one-way ANOVA in different treatments. The effects of warming and water stress on leaf functional traits, foliar C, N, P stoichiometry, foliar P fractions. PNUE, and PPUE were analyzed within treatments using a two-way ANOVA and Tukey\u0026rsquo;s HSD post hoc test; p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be statistically significant. The data were organized and statistically analyzed using SPSS 22.0 software (Statistical Graphics Corp., Princeton, USA). The surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions were subjected to Pearson correlation analysis, and the results were presented in the form of heat maps. And we also ran separate linear regressions between LMA and PNUE or PPUE. The charts were drawn using Microsoft Excel software, and the diagrams were drawn using Origin 9.0 and GraphPad Prism 8.0 software.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eEffects of warming and water stress on\u0026nbsp;surface morphology of leaves\u003c/p\u003e\n\u003cp\u003eThe W and D treatments did not have a significant effect on the dry weight and width of the leaves (Table 1). The leaf length was highly significantly increased by 51.1% under the W treatment compared with CT, resulting in a highly significant increase in leaf area by 44.9% (Table 1, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). At the same time, the LMA significantly decreased by 23.3% under the W treatment (Table 1, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05), indicating that the main influencer of leaf morphology traits is the temperature.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Morphological changes of leaves under different treatments in \u003cem\u003eC. lanceolata.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"104%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDry mass\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWidth\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mm\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLMA\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g m\u003csup\u003e-2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.0016 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e33.14\u0026plusmn;4.13 B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2.62\u0026plusmn;0.09 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e2.76\u0026plusmn;0.41 B\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e50.54\u0026plusmn;2.90 AB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.02\u0026plusmn;0.0018 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e50.06\u0026plusmn;2.96 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2.56\u0026plusmn;0.07 A\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e4.00\u0026plusmn;0.16 A\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e38.73\u0026plusmn;6.00 B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.02\u0026plusmn;0.0009 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e35.83\u0026plusmn;2.77 B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2.58\u0026plusmn;0.13 A\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e2.94\u0026plusmn;0.37 AB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e60.02\u0026plusmn;7.39 A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eWD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.02\u0026plusmn;0.0005 A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e41.65\u0026plusmn;2.72 AB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2.68\u0026plusmn;0.09 A\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e3.49\u0026plusmn;0.17 AB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e46.26\u0026plusmn;1.86 AB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eW \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003eF \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e12.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e8.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e6.384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e2.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e2.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eW\u0026times;D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e3.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: Values are shown as mean\u0026plusmn;SD (n = 5). Data with different capital letters refer to significant differences in different treatments at the 0.05 level. Treatment: control (CT), warming (W), water stress (D), and warming and water stress (WD). Bold numbers indicate significant differences.\u003c/p\u003e\n\u003cp\u003eEffects of warming and water stress on nutrient stoichiometry of leaves\u003c/p\u003e\n\u003cp\u003eThere was no significant difference in the C concentration among the four treatments (Fig. 2a). The N concentration was highly significantly increased by 24.1% under D treatment compared to CT (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, Fig. 2b), resulting in a significant decrease in the C:N ratio by 19.8% under the D treatment (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 2d). The P concentration was significantly different under the interaction of warming and water stress, and the P concentrations were reduced by 13.3% and 19.3%, respectively, under W and D treatments compared with CT (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 2c). As a result, the ratios of C:P and N:P were found to be significantly different under the interaction of warming and water stress, where C:P increased by 14% and 20.2% under W and D treatments, respectively, while the N:P ratio increased significantly by 51.7% under the D treatment (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 2e, f).\u003c/p\u003e\n\u003cp\u003eEffects of warming and water stress on photosynthetic nutrient-use efficiency of leaves\u003c/p\u003e\n\u003cp\u003eThe PNUE was significantly increased by 35.6% (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) under the W treatment (Fig. 3a) and was highly significantly decreased by 35.7% (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) under the D treatment. The PPUE was not changed significantly under either the W or D treatment, but the PPUE of W was greater than for the other three treatments (Fig. 3b). Through regression analysis, the photosynthetic nutrient-use efficiency and leaf LMA were significantly negatively correlated (Fig. 4, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), more so than the correlation between PPUN and LMA.\u003c/p\u003e\n\u003cp\u003eEffects of warming and water stress on P fractions of leaves\u003c/p\u003e\n\u003cp\u003eIn the CT and D treatments, the ratio of the four P fractions was metabolic P \u0026gt; structural P \u0026gt; nucleic acid P \u0026gt; residual P (Fig. 5). However, in the W and WD treatments, the ratio of the P fractions was structural P \u0026gt; metabolic P \u0026gt; nucleic acid P \u0026gt; residual P (Fig. 5), indicating that the changes in structural P and metabolic P were related to the change in temperature. Through our analysis, we found that only the metabolic P significantly differed under the interaction of warming and water stress (Fig. 5, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Through further analyses, we found that under the W treatment, metabolic P was significantly reduced by 32.5% compared with CT (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Under D treatment, meanwhile, it was significantly reduced by 32.1%, compared with CT (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). As such, we assert that the metabolic P is greatly affected by temperature and moisture.\u003c/p\u003e\n\u003cp\u003eBy analyzing the proportions of four P fractions, we found that metabolic P accounted for the largest proportion in all the four treatments, followed by structural P (Fig. 5). In addition, W, D, and WD treatments can increase the proportion of structural P and decrease the proportion of metabolic P (Fig. 5). Through the analysis of the relationship between the four P fractions, it was found that the proportion of metabolic P was inversely proportional to the proportion of structural P and nucleic acid P, respectively, indicating that the proportion of structural P and nucleic acid P decreased with the increase of the proportion of metabolic P in the P fractions distribution of leaves (Fig. 6).\u003c/p\u003e\n\u003cp\u003eThe correlation between the surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions of different treatment leaves\u003c/p\u003e\n\u003cp\u003eThe analysis results show that N and C:N ratios and P and C:P ratios were significantly negatively correlated in the four treatments (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). Under CT treatment, length was positively correlated with dry mass, area was positively correlated with dry mass and length, LMA was positively correlated with length and area, and PNUE was positively correlated with length, area, and LMA. Structural P was significantly positively correlated with C and P and negatively correlated with N/P and C/P, metabolic P was significantly positively correlated with P and width, and nucleic acid P was significantly negatively correlated with C/N and PPUE. Residual P was negatively correlated with N/P (Fig. 7a, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eUnder W treatment, length is negatively correlated with C:P ratios. Width is negatively correlated with P and positively correlated with C/P. Area and width are positively correlated. There is a significant positive correlation between LMA and dry mass. PNUE was positively correlated with length and area. PPUE was positively correlated with PNUE. Structural P was negatively correlated with N/P. Metabolic P was positively correlated with P, length, area, and PNUE, and negatively correlated with C:P ratios. Residual P was significantly negatively correlated with N:P ratios (Fig. 7b,\u003cem\u003e\u0026nbsp;p\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eUnder D treatment, area was positively correlated with length and width (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). LMA is negatively correlated with length. P was positively correlated with the four P fractions. And three P fractions negatively correlated with C:P ratios, except metabolic P. The nucleic acid P was positively correlated with structural P and residual P (Fig. 7c,\u003cem\u003e\u0026nbsp;p\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eUnder WD treatment, width is negatively correlated with length. LMA was negatively correlated with N and positively correlated with N:P ratios. Structural P was negatively correlated with C:P ratios. The nucleic acid P was negatively correlated with PPUE. Residual P was significantly negatively correlated with C:P ratios, and residual P was significantly positively correlated with structural P and nucleic acid P (Fig. 7d,\u003cem\u003e\u0026nbsp;p\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffect of warming and drought on leaf functional traits\u003c/h2\u003e \u003cp\u003eTemperature is an important factor affecting plant growth. Warming will directly affect the physiological characteristics and morphology of plants (Peppe et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Seth and Sebastian, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, we noted leaf trait responses, such as an increasing leaf area, leaf length, and lower LMA under experimental warming. Different from the results of this study, some studies have found that the leaf size decreases with increasing temperature (Kang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, Ren et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) measured the leaf size of a total of 1192 grassland species in the Tibetan Plateau, Loess Plateau, and Mongolian Platea; they found that the leaf size increases with temperature (Ren et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The plants can adjust their leaf length to add to the intercepting surface area for light (Yang et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which also allows leaves to fix more CO\u003csub\u003e2\u003c/sub\u003e. And some researchers also found that warming reduced the LMA of leaves (Yu et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); a decrease in LMA indicates that the ability of plants to capture light energy is enhanced (Scoffoni et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Houminer et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Both of them are beneficial to leaf photosynthesis.\u003c/p\u003e \u003cp\u003eWater stress, one of the major abiotic stresses, changes plant growth by affecting various physiological and biochemical processes (Chiappero et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Zhang et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this study, a leaf accumulated more N when exposed to water stress, resulting in low C:N and high N:P ratios. It has also been reported that drought-increased N is likely used for photosynthesis, given 50% of ribulose-1, 5-bisphosphate carboxylase/oxygenase, the major enzyme for C fixation in photosynthesis, consists of soluble proteins in \u003cem\u003eC. lanceolata\u003c/em\u003e (Feller, Anders and Mae \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, Shaw and Cheung \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, Orians et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found foliar N was reduced under drought in a Boston area climate experiment (Orians et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such a finding is notably different from our results, which may be explained by the fact that the object of this study was woody plants in subtropical regions, while the object of study for Orians et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) was herbaceous plants in temperate regions. Regardless, it can be seen that the response of the plant N concentration to water is closely related to the experimental area and experimental material. Changes in leaf C:N ratios can help us predict how plant productivity will respond to future climate change scenarios (Yue et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this area, plants will increase their N utilization efficiency while reducing their N consumption in the leaves to maintain basic metabolic activities, resulting in a decrease in C:N to adapt to a relatively drought-ridden environment under water stress.\u003c/p\u003e \u003cp\u003eHigher temperatures reduce relative humidity and soil moisture (Ren et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which can have a negative effect on photosynthesis and plant stoichiometry (Olivera Viciedo et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Huang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this study, the P concentration and C:P and N:P ratios were significantly affected by the combined effects of warming and water stress. Both warming and drought conditions decreased P concentration. A plant\u0026rsquo;s nutrient status response to warming was strongly dependent on its impact on soil moisture, given warming can simultaneously exacerbate water and nutrient limitation in dry lands via its negative effects on soil moisture (Ji et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Pe\u0026ntilde;uelas et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Sardans and Pe\u0026ntilde;uelas \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This is due to water stress, which can reduce the absorption, transportation, and redistribution of P by plants (Rouphael et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The C:P ratio can reflect the speed of plant growth (Sterner and Elser \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Since carbon is relatively constant, the C:P ratio was determined by the P concentration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe N and P allocation strategies in leaves under warming and drought conditions\u003c/h2\u003e \u003cp\u003eEnvironmental changes will induce adaptive modifications in the allocation of N and P, thereby adjusting the survival strategies of organisms (Tang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our analysis suggested that \u003cem\u003eC. lanceolata\u003c/em\u003e may have good potential for fast growth and high resource-use efficiency in a warmer climate in the future. This was evidenced by the increase in the PNUE and PPUE in the W treatment. The PNUE was increased with warming in our study, in line with the results of Yang et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), who found that \u003cem\u003eK. pygmaea\u003c/em\u003e leaves exhibited a higher PNUE under experimental warming, indicating advanced physiological activity (Yang et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The proportion of N in plant leaves involved in photosynthesis has also been noted to affect the PNUE (Hikosaka \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The higher the PNUE, the higher the N utilization rate of leaves, indicating that the plant can make better use of the N element under an increased temperature. In this way, plants adapt to the warming environment by decreasing their investment in cell wall N to reduce LMA, while increasing their N investment in Rubisco to increase the PNUE. On the contrary, under water stress treatment, PNUE significantly decreased while LMA increased. This indicates that \u003cem\u003eC. lanceolata\u003c/em\u003e allocates more N to the cell wall in order to enhance leaf toughness and cope with water shortage conditions. Simultaneously, water stress restricts N utilization, leading to reduced plant growth in N-restricted areas.\u003c/p\u003e \u003cp\u003eBesides, in the present study, we found the PNUE and PPUE were negatively correlated with LMA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.). The relationship between PNUE and LMA was found to be consistent with the results of previous studies (Hidaka and Kitayama \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Hidaka and Kitayama \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The PNUE likely decreased due to these physiological and anatomical changes. Increased LMA causes a decline in photosynthetic rates via higher resistance to CO\u003csub\u003e2\u003c/sub\u003e diffusion (Earles et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and via smaller N allocation to the metabolic fraction (e.g., ribulose-1,5-bisphosphate carboxylase/oxygenase) as a result of greater N allocation to the structural fraction (i.e., cell walls) (Onoda, Hikosaka, and Hirose \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Takashima, Hikosaka, and Hirose \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOrganisms need to constantly recalibrate development and physiology in response to changes in warming and drought (Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Seth and Sebastian, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this article, the combined effects of warming and water stress caused significant changes to the metabolic P and foliar P. Under warming and water stress treatments, the metabolic P was smaller than CT. P-containing metabolites play key roles in the Calvin\u0026ndash;Benson cycle, and insufficient metabolic P could limit the maximum photosynthetic rates (\u0026Aring;gren, Wetterstedt, and Billberger \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). On the other hand, through analysis, we found that compared with CT, W, and WD treatment, structure P all increased, but because D significantly reduced foliage P, structure P also decreased under D treatment, indicating that water has a great influence on P. Meanwhile, metabolic P and nucleic acid P decreased under W, D, and WD treatment. Han et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that faster-growing trees allocated more foliage P to nucleic acid P than slower-growing trees (Han et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The assignment of leaf phosphorus fractions may be related to subsistence requirements, as these fractions are functionally related to growth and reproduction (Han et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gao et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Presumably, \u003cem\u003eC. lanceolata\u003c/em\u003e in this study may have increased investment in leaf epidermal cells and decreased investment in mesophyll cells and ribosomal RNA, increasing the toughness and area of the leaves, slowing growth rates, and reducing photosynthetic efficiency to resist warming and water stress (Lambers et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, the research results of this study regarding PPUN and LMA are different from those of Hidaka and Kitayama (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). They suggested that there is not a negative correlation between PPUE and LMA. This study concluded that any negative correlation between PPUE and LMA may be caused by a significant decrease in leaf P due to a temperature increase and water stress, along with the N limitation of this sample site. To survive under conditions of low nutrient supply, drought, and high temperatures, leaves are expected to exhibit high LMA values relative to those of the species in more favorable environments. Thus, plants under warming and water stress need to invest more P in structural P to maintain a higher LMA, and plants with higher LMA usually exhibit slower growth and a longer leaf lifespan (Villar et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Houminer et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Yuki Tsujii et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) suggest that lower PPUE correlates with higher LMA, indicating a shift in ecological strategy toward greater investment in the structure of leaf P as LMA increases (Tsujii et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The results of this study show that structural P-ratios and nucleic acid P-ratios are inversely proportional to metabolic P-ratios (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003e.), indicating that with the increase in LMA, the concentration of metabolic P decreases, leading to a decrease in the photosynthetic rate due to higher resistance to CO\u003csub\u003e2\u003c/sub\u003e diffusion (Earles et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which causes a decrease in PPUE. In addition, the leaf area and leaf length increase for the W, D, and WD treatments, confirming our conjecture that \u003cem\u003eC. lanceolata\u003c/em\u003e faces climate change by slowing down its growth rate in the environment of warming and water stress.\u003c/p\u003e \u003cp\u003eThe correlation between the surface morphology, nutrient stoichiometry, photosynthetic nutrient-use efficiency, and P fractions of different treatment leaves\u003c/p\u003e \u003cp\u003eIf the climate changes, plants shift the distribution of phosphorus between the phosphorus fractions of the leaf surface, which may increase their fitness under prevailing conditions. Through analysis, we discovered a significant positive correlation between total P and all four fractions in water stress treatment. This is due to the fact that low total P levels are associated with lower concentrations of structural P and metabolic P because under low phosphorus conditions, phosphorus storage in the vacuole is reduced and rRNA levels are reduced (Tsujii et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, it was found that structure P, nucleic acid P, and residual P were significantly positively correlated. Residual P plays a role in protein phosphorylation (Lambers \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While nucleic acid P plays a role in protein synthesis and turnover, structure P is closely related to the endoplasmic reticulum, and they coordinate to influence the form of proteins.\u003c/p\u003e \u003cp\u003eIn addition, this study found that in warming and water stress NP was negatively correlated with all except nucleic acid P, which was the same as that of Yuki Tsujii (2024) (Tsujii et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). They suggested that nitrogen is positively correlated with the concentration of other P fractions, resulting in a negative correlation between structure P and nitrogen or the ratio of N:P. Residual P is negatively correlated with the ratio of N:P, reflecting a relatively small allocation of protein phosphorylation. In this study, a significant negative correlation between nucleic acid P and PPUE was found, indicating that when PPUE increased, the portion of P assigned to nucleic acid P decreased, and lower input of nucleic acid P was associated with a slower relative growth rate (Han et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is also related to the fact that \u003cem\u003eC. lanceolata\u003c/em\u003e is an evergreen coniferous plant, and fewer leaves will wither and fall. Overall, \u003cem\u003eC. lanceolata\u003c/em\u003e leaves adapt to the adverse environment by slowing down growth in the environment of temperature increase and water stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eStudies on \u003cem\u003eC. lanceolata\u003c/em\u003e under warming and water stress found that \u003cem\u003eC. lanceolata\u003c/em\u003e had a larger leaf area and smaller LMA under warming treatment, indicating the plant's potential for rapid growth and high resource-use efficiency under future warming. When studied under a warming treatment, a high PNUE is explained by a relatively greater investment of N in N-containing Rubisco and a relatively lesser investment in the cell wall. On the contrary, PNUE significantly decreased and LMA increased under water stress treatments, suggesting that more N is invested into the cell wall to increase leaf toughness and adapt to water deficit. Warming and drought treatments alone did not significantly affect P partitioning in \u003cem\u003eC. lanceolata\u003c/em\u003e leaves.\u003c/p\u003e \u003cp\u003eIn the final analysis, the combined effects of warming and water stress were assessed. Through our analysis of P fractions and PPUE, we found that water stress has a greater impact on the P concentration in the area, significantly reducing the foliar P concentration and restricting the PPUE, resulting in a greater LMA and lower PPUE. The analysis suggests that \u003cem\u003eC. lanceolata\u003c/em\u003e may increase investment in leaf epidermal cells, decrease investment in mesophyll cells and ribosomal RNA, increase leaf toughness and area, slow growth rate, and decrease photosynthetic efficiency to resist warming and water stress. Unexpectedly, our research results found that in this area, the N limitation on plant growth was alleviated by water stress, but leaves\u0026rsquo; P utilization was limited. In future research, we will set up restrictions on N and P for different degrees of water stress to determine the acceptable condition for each. Our study examined the allocation strategies of \u003cem\u003eC. lanceolata\u003c/em\u003e leaves in response to warming and drought conditions. The findings provide a valuable reference for understanding the growth adaptability strategies of leaves in the context of global climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest Statement\u003c/h2\u003e \u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflcit of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFundings\u003c/h2\u003e \u003cp\u003eThis research was funded by the National Natural Science Foundation of China (31930071) and the Natural Science Foundation of Fujian Province (2021J01146).\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe thank the School of Geographical Sciences, Fujian Normal University, and Fujian Sanming Forest Ecosystem National Observation and Research Station for providing us with experimental plots and experimental tools in the field. And thank you to all the teachers and staff at the field station. Finally, we thank anonymous reviewers and the editors for their work on this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e\u0026Aring;gren GI, Wetterstedt J\u0026Aring;M, Billberger MFK (2012) Nutrient limitation on terrestrial plant growth - modeling the interaction between nitrogen and phosphorus. 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Photosynthetica 51:245\u0026ndash;251. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11099-013-0016-3\u003c/span\u003e\u003cspan address=\"10.1007/s11099-013-0016-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"simulated soil warming, water stress, nutrients allocation, photosynthesis, foliar morphology, Cunninghamia lanceolata","lastPublishedDoi":"10.21203/rs.3.rs-9358268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9358268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eGlobal climate change may influence nutrient allocation strategies in subtropical trees. We aimed to understand the changes in nutrient allocation and the growth adaptability situation of plant leaves under conditions of continuous warming and water stress. \u003cem\u003eMethods\u003c/em\u003e In 2014, the experiments were established in 30 mini-plots (2 \u0026times;2 m) with the following treatments:control, soil warming (W, +\u0026thinsp;5\u0026deg;C), rainfall exclusion (D, 50% reduction in precipitation) and warming+rainfall exclusion. We sampled the leaf of \u003cem\u003eCunninghamia lanceolata\u003c/em\u003e to assess their morphological change, lemental and stoichiometric variables and photosynthetic nutrient-use efficiency under all four conditions. \u003cem\u003eResults\u003c/em\u003e Warming increased leaf area and length, decreased leaf mass per area (LMA), and enhanced photosynthetic nitrogen and phosphorus use efficiencies (PNUE, PPUE). Water stress increased leaf N, reduced C:N, raised N:P, and decreased PNUE.Under the combined effects of warming and water stress, more P was allocated to structural components, with less to metabolic and nucleic acid P, alongside increased leaf area. \u003cem\u003eConclusions\u003c/em\u003e Findings indicate that warming promoted N allocation to Rubisco rather than cell walls, supporting growth and resource efficiency. In contrast, drought shifted N toward cell walls, enhancing leaf toughness but limiting N use and slowing growth. Combined warming and drought conditions induced a preferential allocation of phosphorus to membrane phospholipids, thereby enhancing plant stress tolerance. In tandem, investment in key metabolic processes such as photosynthesis was reduced, and leaf toughness was further augmented. This integrated physiological and structural adjustment collectively reflects an adaptive trade-off between growth and survival under climate change.\u003c/p\u003e","manuscriptTitle":"Modeling the simulated soil warming and water stress on foliar Nutrients allocation of Cunninghamia lanceolata","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-24 13:04:10","doi":"10.21203/rs.3.rs-9358268/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5b78d64-fce8-4af9-8e59-cf9068ec67e8","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject with encouragement to resubmit","date":"2026-05-18T02:08:29+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T22:11:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 13:04:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9358268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9358268","identity":"rs-9358268","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}