Conceptio › Archive › NCBI PubMed Central
NCBI PubMed Central open access

Early physiological response of Pinus yunnanensis Franch. seedlings to simulated karst rocky desertification stress.

Lu Z et al. · ncbi_pmc
NCBI PubMed Central · Papers
Open Source ↗Direct PDF ↓
information-security-management
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

Early physiological response of Pinus yunnanensis Franch. seedlings to simulated karst rocky desertification stress - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Plant Biol . 2026 May 22;26:968. doi: 10.1186/s12870-026-09002-x Early physiological response of Pinus yunnanensis Franch. seedlings to simulated karst rocky desertification stress Zhuangyue Lu 1 , Puyan Fu 1 , Yufan Hou 1 , Honglin Wang 1 , Yuji Zhou 1 , Chengxiang Gao 1 , Zilin Cao 1 , Xiaoli Wang 1, ✉ Author information Article notes Copyright and License information 1 Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China Southwest Forestry University, Ministry of Education, Kunming, 650224 China ✉ Corresponding author. Received 2026 Mar 27; Accepted 2026 May 14; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13234980  PMID: 42174410 Abstract Rocky desertification in the karst regions of southwestern China is characterized by shallow soils, nutrient depletion, and ionic imbalance, which severely restrict vegetation recovery and ecological restoration. Pinus yunnanensis Franch., a native conifer adapted to nutrient-poor karst habitats, has been widely used for ecological restoration. However, its early physiological responses to rocky desertification stress remain poorly understood, particularly the coordination among growth, carbon metabolism, nutrient dynamics, and ion homeostasis. In this study, one-year-old P. yunnanensis seedlings were grown for 60 days in soils collected from Yunnan Province, China, representing a non-karst rocky desertification control (CK) and three rocky desertification levels: light (LRD), moderate (MRD), and severe (SRD). Growth, non-structural carbohydrates (NSC), nutrient stoichiometry, and ion profiles were evaluated. The results indicated that P. yunnanensis responds to rocky desertification stress via coordinated physiological adjustments. Seedling growth was maintained under CK and LRD but was progressively suppressed under MRD and SRD. NSC analysis showed that LRD promoted soluble sugar accumulation and increased the sugar-to-starch ratio, which may enhance metabolic flexibility and stress tolerance. Organ-specific N: P ratios were 2.42 in roots, 0.73 in stems, and 1.04 in needles, with an overall mean of 1.40, indicating nitrogen limitation and pronounced organ-specific nutrient allocation. Under SRD, K⁺ content declined significantly, whereas Mg²⁺ and Ca²⁺ accumulated in stems and needles, suggesting dynamic ion regulation under severe stress. Na⁺ content was markedly reduced, indicating restricted ion uptake and transport under degraded substrate conditions. Overall, P. yunnanensis exhibited ecological adaptability under LRD, while MRD and SRD increasingly restricted growth and metabolic coordination. These findings highlight the integrative role of the carbon–nutrient–ion network in early stress adaptation and provide a physiological basis for karst ecosystem restoration. Supplementary Information The online version contains supplementary material available at 10.1186/s12870-026-09002-x. Keywords: Pinus yunnanensis Franch., Non-structural carbohydrates, Mineral ions, Rocky desertification, Stoichiometric characteristics Introduction Rocky desertification is a widespread form of land degradation in arid and semi-arid karst regions worldwide. It is characterized by intensified soil erosion, increased bedrock exposure, and a significant reduction in vegetation cover [ 1 – 3 ]. This process is typically driven by both natural factors and human disturbances, resulting in the transformation of previously soil- and vegetation-covered karst landscapes into barren rocky terrain [ 3 , 4 ]. In China, rocky desertification primarily occurs on the Yunnan–Guizhou Plateau and adjacent areas, impacting several provinces, including Yunnan, Guizhou, and Chongqing. The total affected area exceeds 120,000 km², and these regions are ecologically highly vulnerable [ 3 , 5 ]. Yunnan is characterized by highly developed karst topography and contains one of the largest karst areas in China [ 2 ]. Rocky desertification compromises not only the structural and functional integrity of regional ecosystems but also the long-term stability of ecological restoration efforts [ 6 – 8 ]. In karst rocky desertification (KRD) regions, vegetation is exposed to severe edaphic and hydrological constraints. Shallow soils, poor water retention, low organic matter, and ionic imbalances create persistent barriers to plant establishment and growth [ 9 , 10 ]. These environmental pressures require native species to develop complex physiological adaptations to survive under multiple concurrent stressors [ 10 , 11 ]. One important adaptive strategy involves the regulation of non-structural carbohydrates (NSC). Functioning as readily mobilizable carbon and energy pools, NSC help maintain metabolic activity during drought or photosynthetic limitation, while also contributing to osmotic regulation, tissue recovery, and the stabilization of cellular energy supply [ 12 , 13 ]. In rocky desertification environments, NSC mobilization supports short-term physiological resilience and may also contribute to long-term survival. Ecological stoichiometry, particularly the balance of carbon (C), nitrogen (N), and phosphorus (P), provides important insights into plant adaptation at the biochemical level [ 14 – 16 ]. The C: N:P ratio reflects internal nutrient allocation and links plant metabolism with environmental nutrient availability. Ecological stoichiometry has generated important theoretical advances, including the “limiting element stability hypothesis” and the use of plant N: P ratios to identify nutrient limitation [ 15 , 17 ]. Previous studies have extensively examined nutrient contents and ecological stoichiometry in soils and plants across different ecosystems. In non-karst areas, such as the Loess Plateau [ 18 , 19 ] and degraded alpine grasslands [ 20 , 21 ], research has mainly focused on soil and plant C, N, and P stoichiometry, as well as the associated nutrient limitations. In karst regions of Southwest China, where nutrient limitation is severe, understanding stoichiometric regulation is essential for evaluating plant resource-use efficiency and stress tolerance [ 22 , 23 ]. Mineral ions such as potassium (K⁺), calcium (Ca²⁺), sodium (Na⁺), and magnesium (Mg²⁺) are also critical for osmotic regulation and enzymatic activity. Karst soils typically exhibit low bioavailability of essential ions and high Na⁺ levels, which disrupt ionic homeostasis and impair physiological function [ 24 , 25 ]. In karst regions undergoing rocky desertification, plants often rely on selective ion uptake, transporter regulation, and inter-organ redistribution to maintain mineral ion homeostasis, thereby enhancing nutrient-use efficiency under nutrient-poor conditions [ 26 ]. However, under severe rocky desertification stress, these regulatory mechanisms may be substantially impaired, particularly the uptake efficiency of K⁺ and Ca²⁺, which become critical limiting factors for plant growth and stress resistance [ 22 ]. Despite advances in understanding these mechanisms individually [ 12 , 24 , 27 ], an integrative view of how carbon allocation, nutrient stoichiometry, and ion regulation interact under combined environmental stress remains lacking. Therefore, this study employed a three-dimensional analytical framework to investigate the physiological adaptation mechanisms of seedlings under simulated KRD conditions. This approach was intended to reveal synergistic strategies by which seedlings optimize internal resource use and maintain physiological function under extreme ecological stress. Pinus yunnanensis Franch., an evergreen conifer in the family Pinaceae, is native to the Yunnan–Guizhou Plateau and is mainly distributed in Yunnan Province, western Guizhou, and southwestern Sichuan, where the climate is strongly influenced by the southwestern monsoon [ 28 – 30 ]. This species shows strong ecological adaptability and tolerance to drought and nutrient-poor soils. For decades, it has been widely used as both a pioneer species and a major timber tree for afforestation on barren land in the karst regions of southwestern China [ 31 ]. In the karst landscapes of Yunnan Province, P. yunnanensis functions as a dominant conifer species with strong natural regenerative capacity and substantial importance for forest restoration and vegetation reestablishment [ 32 , 33 ]. Despite its broad cultivation and considerable restoration potential in rocky desertification areas, systematic studies on the early physiological responses of P. yunnanensis seedlings to different degrees of rocky desertification stress remain limited. Previous studies have mainly focused on provenance comparisons [ 34 , 35 ] and silvicultural management [ 28 , 36 ], whereas the coordinated regulation of growth, carbon metabolism, nutrient balance, and ion homeostasis during early seedling development under rocky desertification stress remains poorly understood. In particular, under the dual constraints of habitat degradation and resource limitation, the mechanisms by which P. yunnanensis seedlings maintain stress adaptation through carbon–nutrient–ion coordination remain unclear. Therefore, this study investigated how increasing KRD intensity affects the early growth and physiological regulation of P. yunnanensis seedlings. Specifically, we examined seedling growth, C:N: P stoichiometry, NSC accumulation, and mineral ion profiles during early development. We hypothesized that: (1) increasing rocky desertification intensity would progressively suppress seedling growth and disturb physiological homeostasis; (2) P. yunnanensis seedlings would respond to stress through coordinated adjustments in carbon reserves, nutrient stoichiometry, and ion balance; and (3) seedlings exposed to LRD would maintain relative physiological stability, whereas those under MRD and SRD would exhibit stronger metabolic disturbance and growth inhibition. This study aimed to clarify the early physiological responses of P. yunnanensis seedlings to simulated KRD stress and to provide a theoretical basis for native species selection, ecological restoration, and the development of stress-resilient germplasm in karst ecosystems. Materials and methods Study area The experiment was conducted in a greenhouse at Southwest Forestry University, located in Kunming, Yunnan Province, China (102°45′41″ E, 25°04′00″ N), at an elevation of approximately 1,945 m above sea level. The site is characterized by a subtropical plateau monsoon climate. The mean annual temperature is 14.7 °C, with an absolute maximum of 32.5 °C and an absolute minimum of -9.0 °C. The average annual relative humidity is 68.2%, and annual precipitation ranges from 700 to 1,100 mm, with the most rainfall occurring from May to October. The maximum monthly rainfall is 208.3 mm, and the maximum daily rainfall is 153.3 mm. The region receives an average of 2,445.6 h of sunshine annually, with a sunshine percentage of 56%. The annual total solar radiation is approximately 543.4 MJ·m⁻², and the mean annual evaporation is 1,856.4 mm [ 31 ]. Soil sample collection Soil samples were collected from Lingjiao Township, Zhanyi District, Qujing City, Yunnan Province, China (103°29′08″ E, 25°31′16″ N), at an elevation of approximately 2,000 m above sea level. The region has a mean annual temperature of 14.5 °C and annual precipitation ranging from 800 to 1,300 mm. The soil type was classified as red soil [ 37 ]. Rocky desertification in karst areas is characterized by progressive loss of soil and vegetation cover and increasing bedrock exposure, which collectively reduce habitat quality [ 38 – 40 ]. In the present study, rocky desertification severity was classified using three key indicators: slope, bare rock fraction, and fractional vegetation cover [ 41 , 42 ]. The criteria used to classify the non-karst rocky desertification control (CK), light rocky desertification (LRD), moderate rocky desertification (MRD), and severe rocky desertification (SRD) treatments are listed in Table 1 . Table 1. Rocky desertification factor index system used to classify the experimental stress gradient Stress intensity Slope Bare rock fraction (%) Fractional vegetation cover (%) Values CK 0–5° ≤ 10% > 80% 1 LRD 5–15° 10–30% 60–80% 2 MRD 15–25° 30–50% 40–60% 3 SRD 25–35° 50–70% 20–40% 4 Open in a new tab In May 2023, three fixed plots (10 m × 10 m) were established at representative bare-land sites for each of the four rocky desertification levels, namely CK, LRD, MRD, and SRD [ 3 , 43 ]. In each plot, approximately 3 cm of surface soil was removed before soil samples were collected in layers from the 0–30 cm profile. The collected soils were subsequently used as growth substrates in the pot experiment to preserve the edaphic characteristics associated with different rocky desertification intensities while reducing interference from uncontrolled field factors. This approach allowed the early physiological responses of P. yunnanensis seedlings to be evaluated under relatively uniform conditions. For each rocky desertification level, samples from the three plots were combined, thoroughly homogenized, and transported to the laboratory for the potted seedling experiments using P. yunnanensis . Undisturbed soil samples were collected using a ring cutter (internal diameter: 5.04 cm; height: 5.00 cm) and analyzed for physicochemical properties of the soils (Table 2 ). Table 2. Physicochemical properties of soils with varying degrees of rocky desertification Stress intensity SM (%) pH OM (mg.g − 1 ) TN (mg.g − 1 ) TP (mg.g − 1 ) TK (mg.g − 1 ) Ca²⁺ (mg.g − 1 ) Mg²⁺ (mg.g − 1 ) CK 24.00 ± 1.50a 5.45 ± 0.12c 56.15 ± 3.50a 4.39 ± 0.28a 1.83 ± 0.10a 11.15 ± 1.20a 4.20 ± 0.95a 0.28 ± 0.20a LRD 17.00 ± 1.20b 6.47 ± 0.25b 49.36 ± 3.00b 1.97 ± 0.15b 1.35 ± 0.08b 4.80 ± 0.90b 2.05 ± 0.15b 0.38 ± 0.17a MRD 10.00 ± 0.80c 6.65 ± 0.18b 42.04 ± 2.49c 1.18 ± 0.11c 1.21 ± 0.07c 1.80 ± 0.06c 1.48 ± 0.07c 0.44 ± 0.18a SRD 6.00 ± 0.50d 7.46 ± 0.22a 34.25 ± 2.01d 0.87 ± 0.08d 0.93 ± 0.07d 1.70 ± 0.07c 1.33 ± 0.16c 0.56 ± 0.20a Open in a new tab SM Soil moisture (%), OM Organic matter (mg.g − 1 ), TN Total nitrogen (mg.g − 1 ), TP Total phosphorus (mg.g − 1 ), TK Total potassium (mg.g − 1 ), Ca 2+ content (mg.g − 1 ); Mg 2+ content (mg.g − 1 ). Different lowercase letters indicate significant differences in different levels of rocky desertification ( p < 0.05) Plant material source The experimental materials consisted of one-year-old P. yunnanensis seedlings with uniform growth that had been previously cultivated by the research team. The seeds were sourced from Leye County, Guangxi Province, China (accession number: LY2-1). All samples were collected with the approval of the local government. Species identification was performed by Prof. Mou Fengjuan, a plant taxonomist at Southwest Forestry University, based on the morphological classification of P. yunnanensis . All specimens were deposited in the Herbarium of Southwest Forestry University (acronym: SWFU), pending formal accession numbering. In May 2023, equal volumes of soil representing four rocky desertification levels (CK, LRD, MRD, and SRD) were placed into plastic containers (top diameter: 20.60 cm; bottom diameter: 15.00 cm; height: 17.50 cm). 60 containers were prepared for each treatment. A total of 240 healthy P. yunnanensis seedlings of uniform height were individually transplanted into the containers, each fitted with a tray. During the initial transplanting phase, soil moisture was manually adjusted to maintain field capacity and ensure successful seedling establishment. After seedling establishment, soil moisture was regulated within different field capacity (FC) ranges to simulate rocky desertification stress: 15–20% for CK, 10–15% for LRD, 5–10% for MRD, and 0–5% for SRD. These treatments were consistent with established drought-simulation protocols and reflected the typical water-limited conditions of karst regions [ 44 , 45 ]. Soil moisture was monitored regularly using a soil moisture meter in combination with the gravimetric method. To minimize the potential influence of sampling disturbance on seedling growth, seedlings used for physiological, nutrient, and mineral-ion analyses at each sampling time were independent destructive samples and were not used for subsequent growth monitoring. Seedlings selected for dynamic growth measurements were monitored non-destructively for height and basal diameter throughout the experiment. This sampling design allowed temporal physiological and stoichiometric responses to be evaluated while avoiding cumulative damage to the same individuals. The experiment was conducted for 60 days, from July to September 2023. Greenhouse temperature (18.5–45.0 °C) and relative humidity (22.3–48.0%) were allowed to fluctuate naturally with day–night variation. This design enabled an assessment of seedling responses to different rocky desertification stress intensities under controlled pot conditions. Morphological trait assessment In July 2023, baseline morphological measurements were taken for all P. yunnanensis seedlings included in the experiment. Seedling height was measured using a ruler (precision: 1.0 mm), and basal diameter was measured using a digital caliper (precision: 0.02 mm). These values were recorded as baseline data for the experiment. After the simulated rocky desertification experiment began, seedling height and basal diameter were measured on days 15, 30, 45, and 60. Once soil moisture in each treatment reached the target range corresponding to its rocky desertification level, seedling height and basal diameter were measured every 15 days to ensure data continuity and accuracy. Determination of non-structural carbohydrates, nutrient elements, and mineral ions At each sampling time point (15, 30, 45, and 60 days after treatment), four seedlings per treatment were destructively harvested and separated into roots, stems, and needles for physiological and chemical analyses. Organ samples were heat-inactivated, oven-dried, ground into powder, passed through a 40-mesh sieve, sealed, and stored until analysis. Four biological replicates were included for each treatment at each sampling stage, resulting in a total of 64 destructively sampled seedlings across the four sampling stages. For each organ and treatment, 0.100 g of dry powder was used to determine NSC content using the phenol–sulfuric acid colorimetric method [ 46 ]. NSC content was defined as the sum of soluble sugar and starch contents. For nutrient-element analysis, 0.020 g of dry powder was used to determine C, N, and P concent using heated potassium dichromate redox titration [ 47 ], Nessler’s reagent colorimetry [ 48 ], and the vanadomolybdate yellow colorimetric method [ 49 ], respectively. For mineral-ion analysis, 0.020 g of dry tissue powder was used to determine K⁺, Ca²⁺, Na⁺, and Mg²⁺ concent by inductively coupled plasma optical emission spectrometry (ICP-OES) according to the Chinese National Standard GB/T 26416.3–2022. Statistical analysis All statistical analyses were performed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). One-way analysis of variance (ANOVA) was performed to assess differences in the growth parameters of P. yunnanensis seedlings, followed by Duncan’s multiple range test to determine significant differences among treatments ( p < 0.05). Duncan’s multiple range test was also used to evaluate significant differences in NSC, nutrient element, and mineral ion concentrations of P. yunnanensis seedlings across rocky desertification levels. Principal component analysis (PCA) and Pearson correlation analysis were used to evaluate coordinated relationships among growth, physiological, stoichiometric, and mineral ion traits. In this study, structural equation modeling (SEM) was performed using the partial least squares (PLS) method. Figures were generated using Microsoft Excel 2021 and Origin 2021. All data were presented as mean ± standard error (SE). Results Effects of rocky desertification intensity on the growth characteristics of P. yunnanensis seedlings Rocky desertification intensity significantly affected the growth of P. yunnanensis seedlings (Fig. 1 , p < 0.05). Seedling height increased over time under all treatments, with the greatest increase observed under CK and LRD (Fig. 1 A). At 60 days, seedling height increased by 6.72 cm under CK and 7.59 cm under LRD, both of which were significantly greater than the increases observed under MRD (3.47 cm) and SRD (0.99 cm). The persistently low height increment under SRD indicates that severe rocky desertification significantly inhibits vertical growth. Basal diameter showed a similar response pattern (Fig. 1 B). At 60 days, basal diameter increments reached 3.14 mm under CK and 4.31 mm under LRD. These values were significantly higher than those recorded under MRD (1.30 mm) and SRD (0.26 mm). Although early differences in basal diameter between LRD and MRD were limited, LRD showed a clear growth advantage at later stages. Fig. 1. Open in a new tab Variations in the growth of P. yunnanensis seedlings under soil habitats with different rocky desertification levels. A Seedlings height growth (cm). B Basal diameter growth (mm). Different lowercase letters indicate significant differences among rocky desertification levels at the same stress duration ( p < 0.05) Effects of rocky desertification intensity on non-structural carbohydrate content in P. yunnanensis seedlings Rocky desertification intensity, stress duration, and their interaction significantly affected most NSC-related traits in the roots, stems, and needles of P. yunnanensis seedlings (Table S1, p < 0.05). Soluble sugar content showed the strongest response to stress duration in roots (F = 57.00), followed by needles. Starch content was also significantly affected, with marked variation in roots and stems, whereas needles showed greater sensitivity to stress intensity. Total NSC content showed a strong response to stress duration in roots (F = 52.12), while needles showed a significant response to the interaction between stress duration and stress intensity. The sugar-to-starch ratio also showed significant variation in needles (F = 45.07). Different KRD intensities significantly affected soluble sugar, starch, total NSC content, and sugar-to-starch ratio (Fig. 2 , p < 0.05). Soluble sugar content showed an initial increase followed by a decline across all treatments, with greater accumulation in roots, stems, and needles under LRD. At 45 days, soluble sugar content under LRD reached peak values in stems (118.34 mg·g⁻¹) and needles (123.50 mg·g⁻¹), both of which were significantly higher than those in roots, indicating preferential accumulation of soluble sugars in aboveground organs (Fig. 2 A). Under SRD and MRD, starch content initially increased and then declined, with significant decrease during the later stage of stress (45–60 days). In contrast, starch levels under CK and LRD fluctuated only slightly, and needle starch content remained within 56.37–82.02 mg·g⁻¹, indicating that mild stress caused only limited disturbance to carbon reserves (Fig. 2 B). Under LRD and MRD, NSC contents in stems and needles remained relatively high, with needle NSC reaching a peak at 60 days (197.85 mg·g⁻¹). In contrast, NSC content under SRD was generally lower than that under the other treatments, reflecting a reduced capacity to maintain carbon reserves under severe rocky desertification. Root NSC content showed a transient increase at 30 days and was significantly higher than at the other time points, suggesting that NSC regulation may exhibit organ-specific patterns (Fig. 2 C). The sugar-to-starch ratio was generally higher under stress treatments than under CK, and the highest values under CK and LRD were observed at 45 days. At most time points, the sugar-to-starch ratio under LRD was higher than that under the other treatments, indicating that carbon allocation under mild rocky desertification stress was biased toward the soluble sugar form. In contrast, the sugar-to-starch ratio under SRD showed an initial decline followed by an increase and reached its maximum at 60 days, indicating that the interconversion between soluble sugars and starch was dynamically adjusted under severe stress (Fig. 2 D). P. yunnanensis seedlings exhibited organ-specific patterns of carbohydrate response under different stress conditions. Fig. 2. Open in a new tab Dynamic changes in non-structural carbohydrate traits in roots, stems, and needles of P. yunnanensis seedlings under different rocky desertification levels. A Soluble sugar content (mg.g⁻ 1 ). B Starch content (mg.g⁻ 1 ). C NSC content (mg.g⁻ 1 ). D Soluble sugar : Starch ratio. Values are means ± standard deviation. Different lowercase letters indicate significant differences among stress intensities at the same stress duration, whereas different uppercase letters indicate significant differences among stress durations within the same stress intensity ( p < 0.05) Effects of rocky desertification intensity on C:N:P stoichiometric characteristics of P. yunnanensis seedlings C:N:P stoichiometric responses were evaluated by comparing nutrient-element concent and stoichiometric ratios in the roots, stems, and needles of P. yunnanensis seedlings under different KRD intensities (Fig. 3 ). Rocky desertification intensity significantly influenced the C: N:P stoichiometric traits of P. yunnanensis seedlings ( p < 0.05). Throughout the treatment period, carbon content remained relatively high in all organs, with roots showing greater sensitivity to stress intensity. From 30 to 60 days, root carbon concent were significantly higher under LRD and MRD than under CK and SRD. At 60 days, carbon contents in roots and stems under LRD exceeded 360 mg·g⁻¹, whereas those under SRD declined significantly to below 300 mg·g⁻¹ (Fig. 3 A). Differences in nitrogen content among organs were relatively small, but nitrogen concentration was significantly affected by rocky desertification stress. Nitrogen concent were generally higher under CK and LRD, whereas SRD significantly reduced nitrogen concent in all organs by 60 days (Fig. 3 B). Phosphorus content showed clear organ-specific differences and were generally higher in needles and stems than in roots. Needle phosphorus concent remained relatively high under CK and LRD. In contrast, SRD markedly reduced needle phosphorus concent (Fig. 3 C). In terms of stoichiometric ratios, stem C: N was significantly higher than that in roots and needles. The C: N ratio under SRD and MRD increased significantly and showed greater variation during the later treatment stage, whereas that under CK and LRD remained relatively stable and generally lower (Fig. 3 D). Root C: P was significantly higher than that in stems and needles, and under most treatments, stem and needle C: P ratios reached peak values at 15 days (approximately 37.2–63.5) (Fig. 3 E). Root N: P was consistently higher than stem and needle N: P across treatments. Under stress treatments, root N: P generally peaked at 30 days. Needle N: P peaked during the early treatment stage and was higher under MRD and SRD than under CK and LRD. Stem N: P remained consistently low throughout the experiment (Fig. 3 F). Across the entire experiment, the mean N: P ratios were 2.42 in roots, 0.73 in stems, and 1.04 in needles, with an overall mean of 1.40, indicating pronounced organ-specific differences in nutrient allocation and suggesting a tendency toward nitrogen limitation in P. yunnanensis seedlings. Fig. 3. Open in a new tab Effects of different rocky desertification levels on nutrient contents and stoichiometric ratios in various organs of P. yunnanensis seedlings. A C content (mg.g⁻ 1 ); ( B ) N content (mg.g⁻ 1 ); ( C ) P content (mg.g⁻ 1 ); ( D ) C: N ratio; ( E ) C: P ratio; ( F ) N: P ratio. Different lowercase letters indicate significant differences among different stress intensity at the same stress duration, while different uppercase letters indicate significant differences among different stress duration within the same stress intensity ( p < 0.05) Effects of rocky desertification intensity on mineral ion content in P. yunnanensis seedlings Mineral ion responses were evaluated by comparing K⁺, Ca²⁺, Na⁺, and Mg²⁺ concent in roots, stems, and needles under different KRD intensities (Fig. 4 ). Different degrees of rocky desertification had significant effects on mineral ion contents in P. yunnanensis seedlings ( p < 0.05). For K⁺, roots under CK and LRD maintained relatively high and stable contents, remaining above approximately 4.1 mg·g⁻¹ at 60 days, which were significantly higher than those under MRD and SRD. Root K⁺ content under MRD and SRD decreased markedly over time, with a sharper decline after 30 days, and had fallen to approximately 50% of the CK level by 60 days. Stem K⁺ content generally declined over time, and the differences among treatments became more pronounced as the experiment progressed. Needle K⁺ content was generally high at 15 days but declined markedly under LRD and SRD from 30 to 45 days. By 60 days, needle K⁺ content under CK and MRD had recovered to 8.00 and 7.84 mg·g⁻¹, respectively, whereas that under LRD and SRD remained markedly lower (Fig. 4 A). Ca²⁺ concent showed clear organ-specific and temporal variation. In roots, Ca²⁺ content was generally higher under CK and LRD than under MRD and SRD. Under LRD, it peaked at 30 days (2.87 mg·g⁻¹) and remained relatively high during the later stage of treatment. Root Ca²⁺ concent was lower and more variable under MRD and SRD. Needle Ca²⁺ concent changed more markedly with increasing stress duration. Under SRD, needle Ca²⁺ concent increased markedly by 60 days (Fig. 4 B). Root Na⁺ concent remained higher under CK but decreased under rocky desertification stress, particularly under SRD by 60 days. Stem Na⁺ content varied only slightly, with no significant differences among treatments. Under CK, needle Na⁺ content gradually increased over time. In contrast, needle Na⁺ concent remained lower under SRD than under CK during the middle treatment stage. These results indicate that Na⁺ accumulation in roots and needles was inhibited under rocky desertification stress, which may be associated with the regulation of ion uptake and transport (Fig. 4 C). Mg²⁺ concent showed clear temporal and treatment-dependent variation across organs. Root Mg²⁺ concent tended to increase under MRD by the end of the experiment. Stem Mg²⁺ concent increased under MRD and remained relatively high under SRD during the middle-to-late treatment stages. Needle Mg²⁺ concent increased under SRD during the early stage and peaked under LRD and MRD during the middle-to-late stages. By 60 days, Mg²⁺ content had become relatively stable. Overall, Mg²⁺ showed clear temporal responses and treatment differences, suggesting that it may be redistributed among organs under stress to maintain metabolism-related ionic supply (Fig. 4 D). Fig. 4. Open in a new tab Dynamics of mineral element contents in different organs of P. yunnanensis seedlings under varying rocky desertification levels. A Potassium (K⁺); ( B ) Calcium (Ca²⁺); ( C ) Sodium (Na⁺); ( D ) Magnesium (Mg²⁺). Different lowercase letters indicate significant differences among different stress intensity at the same stress duration, while different uppercase letters indicate significant differences among different stress duration within the same stress intensity ( p < 0.05) Relationships among growth, nutrient status, non-structural carbohydrates, and mineral ion traits in P. yunnanensis seedlings Principal component analysis showed treatment-related separation for NSC components, C, N, and P contents and stoichiometric ratios, and mineral ion traits in the two-dimensional principal component space (Fig. 5 A–C). In the PCA of NSC components, the first two principal components explained 74.0% of the total variance (PC1 = 46.8% and PC2 = 27.2%). The separation among treatments was mainly associated with organ-specific variation in soluble sugars, starch, total NSC, and the sugar-to-starch ratio. These variables showed high loadings on the principal component axes, indicating that carbon storage and soluble sugar–starch conversion contributed strongly to treatment separation (Fig. 5 A). In the PCA of stoichiometric traits, the first two principal components explained 44.1% of the total variance (PC1 = 28.1% and PC2 = 16.0%). Treatment separation was mainly driven by organ C, N, and P concent and their stoichiometric ratios. In particular, C:N, C:P, and N: P ratios contributed to the differentiation of nutrient-balance patterns among treatments (Fig. 5 B). In the PCA of mineral ions, the first two principal components explained 44.9% of the total variance (PC1 = 28.7% and PC2 = 16.2%). CK and LRD were clearly separated from SRD, indicating distinct mineral ion regulation patterns between mild and severe rocky desertification stress. K⁺- and Na⁺-related variables contributed more strongly to PC1, whereas Ca²⁺- and Mg²⁺-related variables contributed more prominently to PC2, suggesting that K⁺/Na⁺ balance and divalent-cation regulation were the main drivers of separation in the mineral ion PCA (Fig. 5 C). Fig. 5. Open in a new tab Principal component analysis of NSC, stoichiometric characteristics, and mineral ions in P. yunnanensis seedlings under varying rocky desertification levels. A PCA of NSC-related traits, including soluble sugars (SS), starch (S), and NSC contents in root (RSS, RS, RNSC), stem (SSS, SS, SNSC), and needle (NSS, NS, NNSC). B PCA of stoichiometric ratios, including carbon-to-nitrogen (C: N), carbon-to-phosphorus (C: P), and nitrogen-to-phosphorus (N: P) ratios in root (RC: N, RC: P, RN: P), stem (SC: N, SC: P, SN: P), and needle (NC: N, NC: P, NN: P). C PCA of mineral ions elements (K⁺, Ca²⁺, Na⁺, and Mg²⁺) in root (RK⁺, RCa²⁺, RNa⁺, RMg²⁺), stem (SK⁺, SCa²⁺, SNa⁺, SMg²⁺), and needle (NK⁺, NCa²⁺, NNa⁺, NMg²⁺) Pearson correlation heatmaps and network analysis further showed coordinated relationships among the measured variables (Fig. 6 ). Within the NSC module, soluble sugars, starch, and NSC contents in different organs were generally positively correlated at highly significant levels. In the stoichiometric module, significant correlations were observed among N and P contents and stoichiometric ratios. In the mineral ion module, K⁺ in roots, stems, and needles was predominantly negatively correlated with soluble sugar and starch contents and their related ratios. Mg²⁺ concent also showed negative correlations with NSC-related traits. Ca²⁺ concent were negatively correlated with N- and P-related variables. Na⁺ concent were positively correlated with N and P concent. The network structure further showed that, with increasing rocky desertification intensity from CK to SRD, positive correlations within the system became stronger, and a dense positive correlation network formed, particularly under SRD. This suggests that under stress conditions, different functional traits within seedlings may help maintain system stability through coordinated regulatory mechanisms. Fig. 6. Open in a new tab Correlation matrix of NSC, stoichiometric traits, and mineral ions in P. yunnanensis seedlings under different rocky desertification levels. Correlation heatmap and network analysis based on Pearson’s correlation coefficients between all variables. Colored squares represent correlation strength (R), with warm colors indicating positive correlations and cool colors indicating negative correlations. Red and blue lines indicate significant positive and negative correlations ( p < 0.05), respectively Structural equation modeling (SEM) was used to clarify the pathways through which treatment-driven changes in soil properties were associated with seedling physiological regulation and growth (Fig. 7 ). The model showed an acceptable fit, with a goodness of fit (GOF) value of 0.49. The explained variance of the composite variable modules showed that mineral ions (R² = 0.80) and plant growth (R² = 0.72) had relatively high explanatory power, followed by stoichiometric properties (R² = 0.62), whereas soil properties (R² = 0.10) and non-structural carbohydrates (R² = 0.10) had lower explanatory power. In terms of path coefficients, soil properties showed a strong positive association with mineral ion traits (β = 0.90, p < 0.001) and a significant negative association with stoichiometric properties (β = −0.55, p < 0.01). Stoichiometric properties were negatively associated with NSCs (β = −0.50, p < 0.05), whereas NSCs showed the strongest positive direct association with plant growth (β = 0.65, p < 0.001). These results indicate that treatment-driven changes in soil conditions were associated with seedling growth through integrated mineral ion, stoichiometric, and carbon-regulatory pathways (Fig. 7 A). Effect decomposition further showed that both soil properties and non-structural carbohydrates had positive direct effects on plant growth, with soil properties showing the stronger promotive effect. By contrast, stoichiometric properties and mineral ions showed negative direct effects on plant growth, with the inhibitory effect of stoichiometric properties being more pronounced. Meanwhile, soil properties and mineral ions had positive indirect effects on plant growth, indicating that both could further promote plant growth by regulating other mediating variables. In contrast, stoichiometric properties showed a negative indirect effect, whereas the indirect effect of non-structural carbohydrates was relatively weak, suggesting that the latter influenced plant growth mainly through direct effects (Fig. 7 B). P. yunnanensis seedlings exhibited a highly coordinated physiological response to simulated KRD stress. Fig. 7. Open in a new tab Structural equation modeling of the relationships among soil properties, non-structural carbohydrates, stoichiometric properties, mineral ions, and plant growth in P. yunnanensis seedlings under different KRD treatments. A Structural equation model showing standardized path coefficients among composite variable modules. Rectangular nodes represent composite variable modules derived from multiple measured indicators rather than single observed variables. Red solid arrows indicate positive pathways, and blue dashed arrows indicate negative pathways. Numbers beside arrows indicate standardized path coefficients (β). Asterisks indicate significant pathways: * p < 0.05, ** p < 0.01, and *** p < 0.001. R² values indicate the proportion of variance explained for each endogenous variable module. GOF indicates the goodness of fit index, not a significance p value. B Direct effects, indirect effects, and total effects of soil properties, mineral ions, stoichiometric properties, and non-structural carbohydrates on plant growth Discussion Morphological adaptation strategies of P. yunnanensis to rocky desertification stress Rocky desertification represents an extreme form of ecological degradation in karst regions because it simultaneously alters soil structure, reduces water-holding capacity, depletes organic matter, and constrains nutrient availability, thereby weakening the environmental basis required for plant establishment and forest recovery [ 50 ]. Under such conditions, seedling height and basal diameter provide integrative indicators of early structural development and stress response. In the present study, P. yunnanensis maintained relatively stable increases in seedling height and basal diameter under CK and LRD, whereas growth was progressively restricted under MRD and SRD. This pattern suggests that mild rocky desertification remained within the physiological buffering range of the species, whereas moderate and severe rocky desertification exceeded this range and constrained structural development. The relatively favorable growth under LRD indicates that P. yunnanensis seedlings have a degree of early-stage plasticity in response to habitat deterioration. Such a response may reflect a mild-stress compensation effect, in which plants maintain or even transiently enhance growth by optimizing internal resource allocation and preserving metabolic activity under sublethal stress [ 51 , 52 ]. Basal diameter differed little among treatments during the early stage, but treatment differences became more pronounced as stress duration increased. After 45 days, seedlings under LRD exhibited significantly greater basal diameter than those under MRD and SRD. This delayed divergence may be related to carbon reallocation, hormonal regulation, and reinforcement of mechanical tissues under mild to moderate stress, which can support structural integrity and water transport during later development [ 47 , 53 – 55 ]. In contrast, SRD markedly suppressed both height and basal diameter increments. Under severe rocky desertification, limited soil moisture and nutrient availability, together with ionic imbalance associated with Na⁺ accumulation, may hinder cell division and expansion in seedlings [ 56 , 57 ]. Previous studies have demonstrated that plants often experience a trade-off between growth and survival under stress conditions [ 10 ]. Under CK and LRD, sustained seedling height and basal diameter growth may have been supported by relatively stable carbon reserves and physiological regulation, enabling seedlings to respond to environmental variation [ 58 ]. In contrast, growth inhibition under MRD and SRD suggests that seedling performance may decline once KRD stress exceeds a physiological tolerance threshold [ 57 ]. P. yunnanensis appears to exhibit substantial phenotypic plasticity under light to moderate rocky desertification conditions, making it a promising candidate species for afforestation in these environments. However, its morphological development is significantly constrained under severely degraded conditions [ 58 ]. Therefore, future afforestation efforts should consider the effects of stress intensity on seedling morphogenesis in order to optimize site selection and implement appropriate silvicultural strategies. Effects of different rocky desertification levels on non-structural carbohydrate contents in P. yunnanensis seedlings Non-structural carbohydrates, mainly soluble sugars and starch, are important carbon reserves and metabolic buffers under abiotic stress [ 13 , 59 , 60 ]. By supporting respiration, osmotic adjustment, and rapid metabolic regulation, NSC are pivotal for preserving physiological stability when external resource supply becomes limited [ 10 , 13 ]. In KRD ecosystems, where soils are nutrient-poor and water availability is limited, plants must adopt flexible carbon allocation strategies to maintain metabolic homeostasis and improve environmental adaptability [ 61 ]. Therefore, investigating the dynamic accumulation and allocation of NSC can provide important insights into the physiological mechanisms underlying plant adaptation to rocky desertification stress [ 61 ]. In the present study, P. yunnanensis seedlings exhibited pronounced organ-specific NSC responses under different levels of rocky desertification, indicating that carbon allocation was actively adjusted according to stress intensity. Under LRD, soluble sugars increased and peaked in stems and needles at 45 days, suggesting a shift toward soluble carbon forms that may support osmotic adjustment and stress signaling. This pattern is consistent with previous findings showing that moderate stress promotes the allocation of NSC to rapidly mobilizable forms, such as soluble sugars, thereby facilitating short-term physiological adaptation [ 60 , 62 ]. Starch content remained relatively stable under CK and LRD but declined significantly during the late-stage of MRD and SRD, suggesting that high-intensity stress may inhibit starch biosynthesis or accelerate starch hydrolysis, thereby intensifying carbon depletion. Under SRD, NSC levels declined markedly across multiple organs, indicating that prolonged and severe rocky desertification stress substantially impaired carbon assimilation, ultimately limiting energy reserves and constraining seedling growth potential [ 10 ]. Variations in the sugar-to-starch ratio further highlight the dynamic regulation of carbon allocation strategies [ 63 ]. Under LRD, the sugar-to-starch ratio peaked during the mid-stress phase, indicating that light stress promoted a shift in carbon allocation toward soluble sugars. This shift may enhance metabolic flexibility and improve stress resilience in seedlings. In contrast, under SRD, the sugar-to-starch ratio initially declined and then increased, indicating restricted soluble sugar accumulation during the early stage of stress. The subsequent rebound may reflect a compensatory mechanism that restores carbon reserves and sustains minimal metabolic activity under prolonged stress. As the primary photosynthetic organ, needles showed high sensitivity to NSC dynamics under stress. The early increase in the sugar-to-starch ratio, together with reduced starch content, suggests that needles may participate in early carbon adjustment under stress [ 10 ]. Root NSC also fluctuated markedly, indicating that roots were important sites of carbon regulation related to water and nutrient acquisition. Given their direct exposure to substrate deterioration, NSC accumulation and redistribution in roots are likely essential for maintaining physiological activity in P. yunnanensis under adverse conditions [ 64 ]. Similar root-centered NSC responses under stress have been reported in woody plants, in which carbohydrate depletion or redistribution in roots is closely associated with drought resistance and survival processes [ 64 ]. In addition, previous studies in woody plants have shown that NSC regulation under environmental stress involves source–sink reconfiguration across organs, resource reallocation, and the activation of sugar metabolic pathways, with these responses being strongly dependent on stress intensity [ 65 ]. In summary, P. yunnanensis seedlings exhibited a multilayered regulatory strategy of NSC in response to different intensities of rocky desertification. Light stress enhanced tolerance by promoting the accumulation of soluble sugars and elevating the sugar-to-starch ratio, whereas severe stress markedly impaired carbon assimilation and energy distribution, thereby restricting seedling growth and survival. The dynamic shifts in NSC levels and the functional divergence among organs underscore the strategic physiological adaptation of this species to complex environmental stress [ 64 , 65 ]. These findings help explain how carbon-reserve regulation contributes to early seedling adaptation in degraded karst habitats. Nutrient accumulation and C: N:P stoichiometric responses of P. yunnanensis seedlings under different levels of rocky desertification C: N:P stoichiometric characteristics are important indicators of plant physiological status, nutrient acquisition strategies, and ecological adaptability [ 66 ]. In KRD habitats, limited water and nutrient availability impose strong constraints on seedling growth and nutrient regulation [ 67 ]. Therefore, elucidating the C: N:P stoichiometric characteristics across different desertification intensities is essential for understanding plant nutrient regulation mechanisms and guiding regional ecological restoration strategies. In the present study, C, N, and P concent and their stoichiometric ratios varied markedly among roots, stems, and needles across KRD intensities, indicating stress-dependent nutrient regulation. Carbon content remained relatively high in all organs, but greater accumulation in roots and stems under LRD and MRD than under CK and SRD suggests that moderate stress may promote carbon retention to maintain metabolic activity and structural stability [ 68 ]. C content was significantly reduced under SRD, likely because of impaired photosynthetic carbon assimilation, which limited both the accumulation and translocation of carbon resources [ 69 ]. Similarly, N content varied significantly among treatments. Seedlings under LRD maintained relatively high N levels across organs, suggesting that light stress did not substantially impair nitrogen uptake at the root-soil interface. In contrast, N content in roots, stems, and needles declined markedly under SRD, indicating that increasing stress intensity inhibited nitrogen absorption and translocation. Similar stoichiometric responses have been reported in plantation species growing in karst ecosystems, where nutrient limitation becomes increasingly pronounced with habitat degradation [ 70 ]. Phosphorus showed more pronounced inter-organ variation. Its concentration was generally higher in needles and stems than in roots, reflecting functional differentiation among organs. Under SRD, P content declined significantly, suggesting that severe rocky desertification may reduce soil P availability or impair root uptake efficiency [ 71 ]. The C: N and C: P ratios serve as key ecological indicators of carbon–nutrient balance, and their dynamic variation reflects the metabolic adaptation strategies of seedlings under nutrient stress [ 72 ]. In the later stages under SRD and MRD, the C: N ratio increased significantly, indicating relative carbon accumulation and nitrogen deficiency, which together formed a “high-carbon, low-nitrogen” resource profile. This metabolic imbalance may hinder the synthesis of enzymatic proteins and structural compounds, ultimately restricting plant growth [ 73 ]. The C: P ratio peaked during the early stage of treatment and subsequently stabilized, suggesting that plants are highly sensitive to phosphorus during initial stress and respond rapidly. Dynamic changes in the N: P ratio further reflect the coordination between nitrogen and phosphorus uptake. The highest root N: P ratio was observed under LRD, indicating enhanced nitrogen uptake under light stress, which contributes to nutrient balance. In contrast, the N: P ratio decreased significantly under SRD, implying restricted phosphorus uptake, which may impair energy metabolism and nucleic acid synthesis [ 16 ]. This study found that the needle N: P ratio fluctuated markedly across treatments, with a peak observed under SRD as early as day 15. This suggests that needles exhibit greater sensitivity to stress during the early stage, with nitrogen being preferentially allocated to support photosynthetic processes. This is consistent with the shoot-priority response hypothesis, which proposes that plants under early stress preferentially maintain photosynthetic structures and metabolic activity [ 74 ]. It is generally accepted that when N: P < 14, N is the primary limiting element for plant growth; when N: P > 16, P is the primary limiting element; and when 14 ≤ N: P ≤ 16, both N and P are limiting factors for plant growth [ 75 ]. In this study, the overall mean N: P ratio was 1.40, indicating that the growth of P. yunnanensis was primarily limited by nitrogen, with a more pronounced limitation than that reported in previous studies [ 31 , 76 ]. The observed variations in elemental concentrations across rocky desertification levels indicate significant differences in nutrient distribution among plant organs, potentially reflecting organ-specific nutrient allocation strategies [ 31 ]. Comprehensive analysis revealed that P. yunnanensis exhibits distinct organ-specific nutrient responses under different levels of rocky desertification stress. Under LRD, seedlings maintained relatively stable C: N:P balance, supporting metabolic stability under mild stress. In contrast, MRD and SRD disrupted carbon–nutrient coordination, resulting in stoichiometric imbalance and growth limitation. Mineral ion accumulation and ionic homeostasis in P. yunnanensis under rocky desertification stress In KRD habitats, nutrient-poor soils, uneven precipitation, and limited ion exchange capacity severely constrain the uptake and regulation of mineral elements in plants, thereby disrupting growth and metabolic homeostasis [ 57 , 77 ]. Plants may maintain physiological function under stress by adjusting ion accumulation across organs and preserving ionic homeostasis [ 78 , 79 ]. In the present study, mineral ion responses of P. yunnanensis seedlings differed among organs and KRD intensities. K⁺, a key ion for osmotic regulation and stomatal control, remained stable under LRD but declined significantly under SRD, particularly in roots and stems. These results suggest that severe stress may inhibit K⁺ uptake at the root–soil interface or disrupt its transmembrane transport, thereby impairing osmotic adjustment and associated carbon metabolism [ 79 , 80 ]. In contrast, under MRD, K⁺ levels remained relatively high at certain stages, potentially due to the activation of compensatory uptake mechanisms or specific ion transporters [ 57 ]. Ca²⁺ is essential for cellular signal transduction, membrane stabilization, and the regulation of stress responses [ 81 , 82 ]. Under SRD, Ca²⁺ concent increased significantly in the roots and needles, with needle Ca²⁺ levels peaking during the later stages of stress. This pattern may indicate the involvement of Ca²⁺-mediated signaling in the response to severe rocky desertification stress [ 81 , 82 ]. Under MRD, Ca²⁺ homeostasis was effectively maintained, suggesting that moderate stress may promote Ca²⁺ uptake and redistribution, thereby enhancing stress tolerance. Although Na⁺ is a non-essential element, it must be tightly regulated in plants to prevent potential cytotoxicity. Under SRD, Na⁺ accumulation was significantly inhibited in all organs, with the greatest reduction observed in roots. This indicates that severe stress may impair Na⁺ transmembrane transport or selective uptake at the cellular level, helping to mitigate ion toxicity [ 57 ]. In addition, Na⁺ content in needles gradually increased over time under CK, while remaining consistently low under SRD. This indicates that P. yunnanensis may actively restrict Na⁺ translocation to leaves in order to protect photosynthetic tissues. Mg²⁺, as a core component of chlorophyll, is essential for photosynthesis and energy transfer [ 83 ]. In this study, Mg²⁺ concent in stems and needles increased under MRD and SRD, with relatively high levels maintained under SRD during the later treatment stages. These findings indicate that enhanced Mg²⁺ accumulation may sustain photosynthetic activity and cellular metabolism under prolonged stress [ 84 , 85 ]. Moreover, root Mg²⁺ concent gradually increased under MRD, indicating a stress-induced compensatory regulatory mechanism. This adjustment may stabilize root metabolism and improve resource uptake efficiency [ 85 ]. Overall, P. yunnanensis exhibited distinct organ-specific strategies for regulating mineral ions under different levels of rocky desertification stress. Under moderate stress, seedlings maintained relatively stable K⁺, Mg²⁺, and Ca²⁺ regulation. In contrast, severe rocky desertification disrupted K⁺, Na⁺, and Ca²⁺ balance, which may have weakened ionic homeostasis and growth maintenance. Effects of rocky desertification intensity on the interrelationships among physiological traits in P. yunnanensis seedlings Early seedling adaptation to KRD stress depends on coordinated regulation of carbon metabolism, nutrient balance, and ion homeostasis rather than on a single physiological trait [ 86 ]. Previous studies have shown that the coupling between NSC and nutrient elements is an important component of plant stress responses by influencing osmotic regulation, energy balance, and resource allocation strategies [ 61 , 87 ]. In the present study, multivariate analyses further supported this integrative view. PCA revealed clear treatment-related shifts in the distribution of NSC-, stoichiometric-, and ion-related traits, indicating that rocky desertification intensity altered the overall physiological organization of P. yunnanensis seedlings rather than affecting isolated variables alone. In the NSC module, the association of SRD samples with needle NSC and soluble sugars suggests that severe stress altered carbon allocation toward metabolically active organs [ 88 ]. By contrast, CK samples were closely associated with needle starch and a higher sugar-to-starch ratio, indicating that carbon storage is favored under non-stress conditions. Under LRD, the marked accumulation of root NSC and stem starch suggests that mild stress may promote carbon redistribution to belowground organs, thereby enhancing resource acquisition and transport capacity [ 61 ]. Similar inter-organ adjustments in carbon allocation have been reported in other woody species under environmental stress, in which source–sink reconfiguration improves resource-use efficiency and buffering capacity [ 88 , 89 ]. These results suggest that carbon redistribution among organs is an important component of the seedling response to different KRD intensities. From a nutrient perspective, rocky desertification stress significantly altered C, N, and P contents and their stoichiometric relationships in P. yunnanensis seedlings. Under MRD, the C: N and C: P ratios in seedling organs increased significantly, suggesting that seedlings may enhance stress tolerance by increasing carbon reserves to compensate for limitations in N and P [ 90 ]. By contrast, the relative stability of N and P contents and their associated ratios under CK and LRD indicates stronger internal coordination of nutrient acquisition and utilization under non-stress and light stress conditions [ 91 ]. The organ-specific pattern of C: N:P ratios further suggests that P. yunnanensis maintains internal homeostasis through differential nutrient allocation among roots, stems, and needles. SEM further showed that soil properties were negatively associated with C: N:P stoichiometric traits, which were then negatively associated with NSCs. This pathway suggests that substrate deterioration may disrupt nutrient balance and subsequently constrain carbon-reserve regulation. Thus, stoichiometric imbalance may represent an important link between soil degradation and carbon-reserve limitation during early seedling establishment. Mineral ions responses further highlighted the role of ionic regulation in the integrated stress response. PCA showed that K⁺- and Na⁺-related traits contributed strongly to treatment separation, indicating that ion homeostasis was highly sensitive to substrate degradation. Under severe stress, the separation of SRD samples from K⁺- and Na⁺-associated variables suggests that both nutrient-ion retention and ionic balance were altered as stress intensified. In addition, Ca²⁺ and Mg²⁺ appeared to contribute more strongly under MRD and SRD, implying that these ions may play compensatory roles in stress buffering, possibly through membrane stabilization, osmotic adjustment, and signal transduction [ 91 , 92 ]. SEM showed a strong pathway from soil properties to mineral ions, supporting the role of mineral ions regulation as an intermediate process linking soil conditions with seedling growth. Effect decomposition indicated that mineral ions contributed to growth through both direct and indirect pathways, suggesting that ion regulation involved both homeostatic adjustment and stress-related costs. Appropriate ion uptake and distribution may sustain metabolism, whereas ionic imbalance may increase physiological burden. Pearson correlation analysis and the network structure provided additional evidence for strong cross-module coordination among carbon, nutrient, and ion traits. Significant positive correlations among NSC components, and between NSC indices and stoichiometric ratios such as C: N and C: P, indicate that P. yunnanensis seedlings maintain metabolic stability through coordinated regulation of carbon storage and nutrient balance [ 93 ]. At the same time, the negative correlations of K⁺ and Mg²⁺ with soluble sugars, starch, and related indices, together with the negative association of Ca²⁺ with N- and P-related traits and the positive association of Na⁺ with N and P contents, suggest that ionic variation is tightly coupled with both carbon metabolism and elemental allocation under stress [ 92 , 94 ]. Notably, as rocky desertification intensified, the network became progressively denser and more positively connected, especially under SRD. This pattern suggests that severe stress increased the degree of coupling among functional modules within seedlings, likely because the system stability could only be maintained through tighter coordination among multiple physiological pathways. Overall, P. yunnanensis seedlings exposed to different rocky desertification intensities exhibited a coordinated carbon–nutrient–ion regulatory network in which NSC allocation formed the metabolic core, while nutrient balance and ion homeostasis acted as critical supporting mechanisms. Combined with the SEM pathway of “soil–ions–stoichiometry–NSC–growth,” these findings indicate that early adaptation to rocky desertification stress depends on whole-system physiological integration rather than the adjustment of individual traits in isolation. This integrated strategy may help seedlings maintain short-term stability under degraded karst conditions, but it likely becomes increasingly costly under severe stress, where stronger coupling reflects tighter physiological constraint rather than greater functional efficiency. Although this study evaluated dynamic changes in seedling height, basal diameter, physiological traits, C:N: P stoichiometry, and mineral ion regulation, biomass allocation traits were not measured. Therefore, the present study could not directly quantify aboveground–belowground biomass partitioning, root-to-shoot ratio, or carbon investment among organs. Future studies should incorporate final biomass harvests and root–shoot allocation analyses to further clarify how KRD stress affects biomass partitioning and growth-allocation strategies in P. yunnanensis seedlings. Conclusion In summary, the early responses of P. yunnanensis seedlings to simulated KRD stress depended on the coordinated regulation of carbon allocation, nutrient balance, and ion homeostasis. Seedlings under LRD retained relatively stable growth and metabolic flexibility, indicating that light stress was maintained within their physiological buffering capacity. By contrast, MRD and SRD progressively disrupted carbon reserves, stoichiometric balance, and ionic regulation, ultimately constraining growth and weakening overall metabolic coordination. These patterns suggest that P. yunnanensis seedlings adopt different adaptive strategies depending on stress intensity: under LRD, they maintain growth through physiological adjustment, whereas under SRD, they shift toward a more conservative survival-oriented strategy that prioritizes maintenance over biomass accumulation. Although this strategy may improve short-term persistence in degraded karst habitats, it likely does so at the cost of growth potential and developmental performance. Overall, this study clarifies the physiological basis of early seedling adaptation to rocky desertification stress and provides a useful basis for native species selection and vegetation restoration in fragile karst ecosystems. Supplementary Information Supplementary Material 1. (16.4KB, docx) Acknowledgements We are very grateful to every scientific researcher who supports and helps us in our work. Clinical trial number Not applicable. Abbreviations KRD Karst rocky desertification CK Non-karst rocky desertification LRD Light rocky desertification MRD Moderate rocky desertification SRD Severe rocky desertification NSC Non-structural carbohydrates (mg·g − 1 ) SS Soluble sugars (mg·g − 1 ) S Starch (mg·g − 1 ) C Carbon (mg·g − 1 ) N Nitrogen (mg·g − 1 ) P Phosphorus (mg·g − 1 ) C:N Carbon-to-nitrogen C:P Carbon-to-phosphorus N:P Nitrogen-to-phosphorus K⁺ Potassium (mg·g − 1 ) Ca²⁺ Calcium (mg·g − 1 ) Na⁺ Sodium (mg·g − 1 ) Mg²⁺ Magnesium (mg·g − 1 ) PCA Principal component analysis SM Soil moisture (%) OM Organic matter (mg.g − 1 ) TN Total nitrogen (mg.g − 1 ) TP Total phosphorus (mg.g − 1 ) TK Total potassium (mg.g − 1 ) FC Field capacity ANOVA One-way analysis of variance SEM Structural equation modeling GOF Goodness of fit Authors’ contributions Z.L.: Writing-review & editing, Methodology, Investigation, Validation, Writing-original draft. P.F.: Methodology, Investigation, Validation. Y.H. & H.W.: Investigation, Validation. Y.Z. & C.G.: Formal analysis, Investigation. Z.C.: Investigation. X.W.: Writing-review & editing, Supervision, Funding acquisition, Conceptualization. All authors read and approved the final manuscript. Funding This research was supported by Yunnan Fundamental Research Project, grant NO. 202301BD070001-042, Scientific Research Fund of Yunnan Provincial Department of Education (2026Y0896), and Scientific Research Fund of Yunnan Provincial Department of Education (2024Y575). Data availability All data generated or analyzed during this study are included in this manuscript, and materials used in the experiments are available upon request. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Wang X, Liu Y, Xiong K, Huang X, Zhang Z. Supportive functions of soil organic carbon for ecosystem services in karst desertification areas. Ecol Ind. 2025;170:113050. [ Google Scholar ] 2. Wang S, Liu Q, Zhang D. Karst rocky desertification in southwestern China: geomorphology, landuse, impact and rehabilitation. Land Degrad Dev. 2004;15(2):115–21. [ Google Scholar ] 3. Jiang Z, Lian Y, Qin X. Rocky desertification in Southwest China: Impacts, causes, and restoration. Earth Sci Rev. 2014;132:1–12. [ Google Scholar ] 4. Yuan D. Rock desertification in the subtropical karst of south China. Z fur Geomorphologie. 1997;108:81–90. [ Google Scholar ] 5. Feng Q, Zhou Z, Zhu C, Luo W, Zhang L. Quantifying the ecological effectiveness of poverty alleviation relocation in karst areas. Remote Sens. 2022;14(23):5920. [ Google Scholar ] 6. Zhang X, Yue Y, Tong X, Wang K, Qi X, Deng C, Brandt M. Eco-engineering controls vegetation trends in southwest China karst. Sci Total Environ. 2021;770:145160. [ DOI ] [ PubMed ] [ Google Scholar ] 7. Chen J, Yu J, Bai X, Zeng Y, Wang J. Fragility of karst ecosystem and environment: Long–term evidence from lake sediments. Agric Ecosyst Environ. 2020;294:106862. [ Google Scholar ] 8. Wu Z, Zhu D, Xiong K, Wang X. Dynamics of landscape ecological quality based on benefit evaluation coupled with the rocky desertification control in South China Karst. Ecol Ind. 2022;138:108870. [ Google Scholar ] 9. Hou F, Cheng J, Zhang H, Wang X, Shi D, Guan N. Response of preferential flow to soil–root–rock fragment system in karst rocky desertification areas. Ecol Ind. 2024;165:112234. [ Google Scholar ] 10. McDowell N, Pockman W, Allen C, Breshears DD, Cobb N, Kolb T, Plaut J, Sperry J, West A, Williams DG. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytol. 2008;178(4):719–39. [ DOI ] [ PubMed ] [ Google Scholar ] 11. Jaume F, Josefina B, Josep C, José ME, Jeroni G, Javier G, El-kadri L, Sara FMC, María TM, MiquelI RC. Understanding down–regulation of photosynthesis under water stress: future prospects and searching for physiological tools for irrigation management. Ann Appl Biol. 2004;144(3):273–83. [ Google Scholar ] 12. Hartmann H, Trumbore S. Understanding the roles of nonstructural carbohydrates in forest trees–from what we can measure to what we want to know. New Phytol. 2016;211(2):386–403. [ DOI ] [ PubMed ] [ Google Scholar ] 13. Sala A, Woodruff DR, Meinzer FC. Carbon dynamics in trees: feast or famine? Tree Physiol. 2012;32(6):764–75. [ DOI ] [ PubMed ] [ Google Scholar ] 14. Han W, Fang J, Guo D, Zhang Y. Leaf nitrogen and phosphorus stoichiometry across 753 terrestrial plant species in China. New Phytol. 2005;168(2):377–85. [ DOI ] [ PubMed ] [ Google Scholar ] 15. Elser J, Hamilton A. Stoichiometry and the new biology: the future is now. PLoS Biol. 2007;5(7):e181. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Hu T, Xiong K, Yu Y, Wang J, Wu Y. Ecological stoichiometry and homeostasis characteristics of plant-litter-soil system with vegetation restoration of the karst desertification control. Front Plant Sci. 2023;14:1224691. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Tessier J, Raynal D. Use of nitrogen to phosphorus ratios in plant tissue as an indicator of nutrient limitation and nitrogen saturation. J Appl Ecol. 2003;40(3):523–34. [ Google Scholar ] 18. Bai X, Wang B, An S, Zeng Q, Zhang H. Response of forest species to C: N: P in the plant–litter–soil system and stoichiometric homeostasis of plant tissues during afforestation on the Loess Plateau, China. CATENA. 2019;183:104186. [ Google Scholar ] 19. Zhang J, Yang X, Song Y, Liu H, Wang G, Xue S, Liu G, Ritsema CJ, Geissen V. Revealing the nutrient limitation and cycling for microbes under forest management practices in the Loess Plateau–ecological stoichiometry. Geoderma. 2020;361:114108. [ Google Scholar ] 20. Zeng Q, Li X, Dong Y, An S, Darboux F. Soil and plant components ecological stoichiometry in four steppe communities in the Loess Plateau of China. CATENA. 2016;147:481–8. [ Google Scholar ] 21. Sun J, Liu B, You Y, Li W, Liu M, Shang H, He J-S. Solar radiation regulates the leaf nitrogen and phosphorus stoichiometry across alpine meadows of the Tibetan Plateau. Agric For Meteorol. 2019;271:92–101. [ Google Scholar ] 22. Du C, Gao Y. Grazing exclusion alters ecological stoichiometry of plant and soil in degraded alpine grassland. Agric Ecosyst Environ. 2021;308:107256. [ Google Scholar ] 23. Su L, Du H, Zeng F, Peng W, Rizwan M, Núñez-Delgado A, Zhou Y, Song T, Wang H. Soil and fine roots ecological stoichiometry in different vegetation restoration stages in a karst area, southwest China. J Environ Manage. 2019;252:109694. [ DOI ] [ PubMed ] [ Google Scholar ] 24. Munns R, Tester M. Mechanisms of salinity tolerance. Annu Rev Plant Biol. 2008;59(1):651–81. [ DOI ] [ PubMed ] [ Google Scholar ] 25. Chen H, Li D, Mao Q, Xiao K, Wang K. Resource limitation of soil microbes in karst ecosystems. Sci Total Environ. 2019;650:241–8. [ DOI ] [ PubMed ] [ Google Scholar ] 26. Tang J, Tang X, Qin Y, He Q, Yi Y, Ji Z. Karst rocky desertification progress: Soil calcium as a possible driving force. Sci Total Environ. 2019;649:1250–9. [ DOI ] [ PubMed ] [ Google Scholar ] 27. Sardans J, Rivas Ubach A, Peñuelas J. The C: N: P stoichiometry of organisms and ecosystems in a changing world: a review and perspectives. Perspectives in Plant Ecology. Evol Syst. 2012;14(1):33–47. [ Google Scholar ] 28. Deng X, Huang B, Wen Q, Hua C, Tao J, Zheng J. Dynamic of Pinus yunnanensis forest resources in Yunnan. J Nat Resour. 2014;29(08):1411–9. [ Google Scholar ] 29. Zheng Y, Huang X, Wang D, Li G. Research advance and prospects of Pinus yunnanensis Franch. Mod Agricultural Technol. 2013(13):169–71. 30. Wang D, Li Y, Sun J, Li J, Chen S, Xu Y, Cai N. The allometry growth of Pinus yunnanensis seedlings from different families. Bull Bot Res. 2021;41(06):965–73. [ Google Scholar ] 31. Lu Z, Pan Z, Chen L, Chen S, Tang J, Cai N, Wang X, Xu Y. Integrating analysis of nutrient elements, endogenous phytohormones, and transcriptomics reveals factors influencing variation of growth in height in Pinus yunnanensis Franch. Plant Physiol Biochem. 2025;223:109866. [ DOI ] [ PubMed ] [ Google Scholar ] 32. Tang C, He L, Su W, Zhang G, Wang H, Peng M, Wu Z, Wang C. Regeneration, recovery and succession of a Pinus yunnanensis community five years after a mega-fire in central Yunnan, China. For Ecol Manag. 2013;294:188–96. [ Google Scholar ] 33. Feng J, Wang B, Xian M, Zhou S, Huang C, Cui X. Prediction of future potential distributions of Pinus yunnanensis varieties under climate change. Front Forests Global Change. 2023;6:1308416. [ Google Scholar ] 34. Liu Z, Gao C, Li J, Miao Y, Cui K. Phenotypic diversity analysis and superior family selection of industrial raw material forest species–Pinus yunnanensis Franch. Forests. 2022;13(4):618. [ Google Scholar ] 35. Li X, Li K, Duan A, Cui K, Gao C. Biomass allocation and allometry of Pinus yunnanensis seedlings from different provenances. J Beijing Forestry Univ. 2019;41(04):41–50. [ Google Scholar ] 36. Li Z, Chai Y, Gao C, Li J, Cui K. The heterogeneity of Pinus yunnanensis plantation growth was driven by soil microbial characteristics in different slope aspects. BMC Plant Biol. 2025;25(1):114. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 37. Wang M, Peng J, He X, Fan C, Chen X, Miao X. Tree canopy coverage and plant diversity in Zhanyi District. J Northeast Forestry Univ. 2023;51(02):24–32. [ Google Scholar ] 38. Gou M, Li L, Ouyang S, Shu C, Xiao W, Wang N, Hu J, Liu C. Integrating ecosystem service trade-offs and rocky desertification into ecological security pattern construction in the Daning river basin of southwest China. Ecol Ind. 2022;138:108845. [ Google Scholar ] 39. Pan L, Li R, Shu D, Zhao L, Chen M, Jing J. Effects of rainfall and rocky desertification on soil erosion in karst area of Southwest China. J Mt Sci. 2022;19:3118–30. [ Google Scholar ] 40. Shuai N, Hu Y, Gao M, Guo Z, Bai Y. Construction and optimization of ecological networks in karst regions based on multi-scale nesting: A case study in Guangxi Hechi, China. Ecol Inf. 2023;74:101963. [ Google Scholar ] 41. Gai H, Wu B, Wu Y, Ren Z. Construction and optimization of ecological network in karst regions under rocky desertification disturbance: A case study of Qujing City, China. Ecol Model. 2026;512:111389. [ Google Scholar ] 42. Chen Y, Ma Y, Pan J, Zhang S, Zhang X, Wu R, Li X. Integrating ecosystem health diagnosis into the construction of ecological security network—A case study in Qujing City, China. Ecol Ind. 2023;146:109780. [ Google Scholar ] 43. Ma T, Deng X, Chen L, Xiang W. The soil properties and their effects on plant diversity in different degrees of rocky desertification. Sci Total Environ. 2020;736:139667. [ DOI ] [ PubMed ] [ Google Scholar ] 44. Xu T, Wu X, Tian Y, Li Y, Zhang W, Zhang C. Soil property plays a vital role in vegetation drought recovery in karst region of Southwest China. J Geophys Research: Biogeosciences. 2021;126(12):e2021JG006544. [ Google Scholar ] 45. Hosseini R, Heidari M. Impact of drought stress on biochemical and molecular responses in lavender (Lavandula angustifolia Mill.): effects on essential oil composition and antibacterial activity. Front Plant Sci. 2025;16:1506660. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 46. DuBois M, Gilles K, Hamilton J, Rebers P, Smith F. Colorimetric method for determination of sugars and related substances. Anal Chem. 1956;28(3):350–6. [ Google Scholar ] 47. Winkler A, Oberhuber W. Cambial response of Norway spruce to modified carbon availability by phloem girdling. Tree Physiol. 2017;37(11):1527–35. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 48. Liu Q, Huang Z, Wang Z, Chen Y, Wen Z, Liu B, Tigabu M. Responses of leaf morphology, NSCs contents and C: N: P stoichiometry of Cunninghamia lanceolata and Schima superba to shading. BMC Plant Biol. 2020;20:1–10. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. Gilmar DS, Hurtado AC, De Souza Junior JP, De Mello Prado R, De Cássia Piccolo M, Dos Santos DMM. Beneficial role of silicon on regulating C, N, and P stoichiometric homeostasis and the growth of sugarcane seedlings under aluminum toxicity. J Soil Sci Plant Nutr. 2022;22(4):4138–52. [ Google Scholar ] 50. Jiao M, Yan J, Zhao Y, Xia T, Shen K, He Y. Dominance of rock exposure and soil depth in leaf trait networks outweighs soil quality in karst limestone and dolomite habitats. For Ecosyst. 2024;11:100220. [ Google Scholar ] 51. Zhou Z, Zhang L, Wu T, Luo D, Wu L, Chen Q, Feng Q. Changes in ecosystem service values of forests in southwest China’s karst regions from 2001–2020. Forests. 2023;14(8):1534. [ Google Scholar ] 52. Yang Y, Nie X, Cong Z, Pan X, Gong X, Zhang Z. Assessing the carbon-water compound use efficiency in fragile karst region: The Yunnan-Guizhou Plateau, China. Ecol Ind. 2024;166:112320. [ Google Scholar ] 53. Sorce C, Giovannelli A, Sebastiani L, Anfodillo T. Hormonal signals involved in the regulation of cambial activity, xylogenesis and vessel patterning in trees. Plant Cell Rep. 2013;32:885–98. [ DOI ] [ PubMed ] [ Google Scholar ] 54. López R, Brossa R, Gil L, Pita P. Stem girdling evidences a trade–off between cambial activity and sprouting and dramatically reduces plant transpiration due to feedback inhibition of photosynthesis and hormone signaling. Front Plant Sci. 2015;6:285. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 55. Brunner I, Herzog C, Dawes M, Arend M, Sperisen C. How tree roots respond to drought. Front Plant Sci. 2015;6:547. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 56. Shi J, Tan J, Li S, Tao L, Jiang X, Zhang Q, Zhang F, Liao Y, Zhang Y, Chen Q. Leaf adaptation strategy of non–tree plants altered by community structure implies vegetation degradation risk in alpine rocky desertification areas. Sci Rep. 2025;15(1):8561. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 57. Zheng S, Wang L, Dong Q, Zeng H, Li X, Li L, Hua Q, Wu Y, Yang J, Chen F. Effects of different karst fissures and rainfall distribution on the biomass, mineral nutrient elements, antioxidant substances, and photosynthesis of two coniferous seedlings. BMC Plant Biol. 2024;24(1):1017. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 58. Liu Y, Jing H, Wu J. Non–structural carbohydrate (NSC) content and C: N: P stoichiometry of Pinus yunnanensis seedling needles in response to shade treatment. Ind Crops Prod. 2024;210:118138. [ Google Scholar ] 59. Tian J, Zhang H, Wang A, Wu J, Rosner S, Zhu K, Cai R, Yuan F. Unravelling the combined effects of drought and nitrogen addition on carbon assimilation and reserves in Korean pine saplings. Front Plant Sci. 2025;16:1574468. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 60. Zhang X, Qin H, Kan Z, Liu D, Wang B, Fan S, Jiang P. Growth and non–structural carbohydrates response patterns of Eucommia ulmoides under salt and drought stress. Front Plant Sci. 2024;15:1436152. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Liu C, Wu J, Gu J, Duan H. Responses of non–structural carbohydrate and carbon, nitrogen, and phosphorus chemometrics in needles of early shaded Pinus yunnanensis seedlings to drought. BMC Plant Biol. 2025;25(1):270. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 62. Lemoine R, Camera S, Atanassova R, Dédaldéchamp F, Allario T, Pourtau N, Bonnemain J-L, Laloi M, Coutos-Thévenot P, Maurousset L. Source–to–sink transport of sugar and regulation by environmental factors. Front Plant Sci. 2013;4:272. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 63. Zhai Z, Fang Y, Cheng J, Tian Y, Liu L, Cao X. Intrinsic morphology and spatial distribution of non–structural carbohydrates contribute to drought resistance of two mulberry cultivars. Plant Biol. 2023;25(5):771–84. [ DOI ] [ PubMed ] [ Google Scholar ] 64. Hartmann H, Ziegler W, Trumbore S. Lethal drought leads to reduction in nonstructural carbohydrates in N orway spruce tree roots but not in the canopy. Funct Ecol. 2013;27(2):413–27. [ Google Scholar ] 65. Peng L, Hao G, Liu H, Shen H, Zhou X, Zang Y, Zhang J, Zhang Y. Impacts of groundwater depth and tree age on the non–structural carbohydrates of Haloxylon ammodendron. Plant Stress. 2024;14:100659. [ Google Scholar ] 66. Güsewell S. N: P ratios in terrestrial plants: variation and functional significance. New Phytol. 2004;164(2):243–66. [ DOI ] [ PubMed ] [ Google Scholar ] 67. Song M, Peng W, Du H, Xu Q. Responses of soil and microbial C: N: P stoichiometry to vegetation succession in a karst region of Southwest China. Forests. 2019;10(9):755. [ Google Scholar ] 68. Li M, Du M, Chen H, Shi Y, Yao D, Shi Q. Stoichiometric coupling of C, N, P, and K in the litter and soil of Rosa roxburghii tratt woodlands across rocky desertification grades and seasons. Forests. 2024;15(8):1415. [ Google Scholar ] 69. Meng W, Dai Q, Ren Q, Tu N, Leng T. Ecological stoichiometric characteristics of soil–moss C, N, and P in restoration stages of karst rocky desertification. PLoS ONE. 2021;16(6):e0252838. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 70. Pang D, Wang G, Li G, Sun Y, Liu Y, Zhou J. Ecological stoichiometric characteristics of two typical plantations in the karst ecosystem of southwestern China. Forests. 2018;9(2):56. [ Google Scholar ] 71. Bai X, Feng T, Zou S, He B, Chen Y, Li W. The stoichiometric characteristics of liana leaves in different rocky desertification habitats. Diversity. 2025;17(3):193. [ Google Scholar ] 72. Wang L, Arif M, Zheng J, Li C. Patterns and drivers of plant carbon, nitrogen, and phosphorus stoichiometry in a novel riparian ecosystem. Front Plant Sci. 2024;15:1354222. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 73. Zhao W, Yang Y, Wu P, Hou Y, Jiang X, Zhou HC. N, P, and K ecological stoichiometry characteristics of different organs of tree species in dolomite and limestone karst areas of Southwestern China. Forests. 2025;16(3):480. [ Google Scholar ] 74. Li Y, He W, Wu J, Zhao P, Chen T, Zhu L, Ouyang L, Ni G, Hölscher D. Leaf stoichiometry is synergistically–driven by climate, site, soil characteristics and phylogeny in karst areas, Southwest China. Biogeochemistry. 2021;155(2):283–301. [ Google Scholar ] 75. Jiang P, Cao Y, Chen Y, Wang F. Seasonal dynamics and allometric growth relationships of C, N, and P stoichiometry in the organs of Cunninghamia lanceolata from Huitong. Acta Ecol Sin. 2016;36(19):6188–97. [ Google Scholar ] 76. Liang S, Tan T, Wu D, Li C, Jing H, Wu J. Seasonal variations in carbon, nitrogen, and phosphorus of Pinus yunnanenis at different stand ages. Front Plant Sci. 2023;14:1107961. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 77. Yang T, Zhang H, Zheng C, Wu X, Zhao Y, Li X, Liu H, Dong L, Lu Z, Zhou J. Bacteria life-history strategies and the linkage of soil CNP stoichiometry to microbial resource limitation differed in karst and non–karst plantation forests in southwest China. CATENA. 2023;231:107341. [ Google Scholar ] 78. Gill R, Ahmar S, Ali B, Saleem MH, Khan MU, Zhou W, Liu S. The role of membrane transporters in plant growth and development, and abiotic stress tolerance. Int J Mol Sci. 2021;22(23):12792. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 79. Hasanuzzaman M, Bhuyan M, Nahar K, Hossain MS, Mahmud JA, Hossen MS, Masud AAC. Moumita, Fujita M. Potassium: a vital regulator of plant responses and tolerance to abiotic stresses. Agronomy. 2018;8(3):31. [ Google Scholar ] 80. Shabala S, Pottosin I. Regulation of potassium transport in plants under hostile conditions: implications for abiotic and biotic stress tolerance. Physiol Plant. 2014;151(3):257–79. [ DOI ] [ PubMed ] [ Google Scholar ] 81. Reddy AS, Ali GS, Celesnik H, Day IS. Coping with stresses: roles of calcium– and calcium/calmodulin–regulated gene expression. Plant Cell. 2011;23(6):2010–32. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 82. Dodd A, Kudla J, Sanders D. The language of calcium signaling. Annu Rev Plant Biol. 2010;61(1):593–620. [ DOI ] [ PubMed ] [ Google Scholar ] 83. Fiedor L, Kania A, Myśliwa-Kurdziel B, Orzeł Ł, Stochel G. Understanding chlorophylls: central magnesium ion and phytyl as structural determinants. Biochim et Biophys Acta (BBA)-Bioenergetics. 2008;1777(12):1491–500. [ DOI ] [ PubMed ] [ Google Scholar ] 84. Verbruggen N, Hermans C. Physiological and molecular responses to magnesium nutritional imbalance in plants. Plant Soil. 2013;368:87–99. [ Google Scholar ] 85. Tränkner M, Tavakol E, Jákli B. Functioning of potassium and magnesium in photosynthesis, photosynthate translocation and photoprotection. Physiol Plant. 2018;163(3):414–31. [ DOI ] [ PubMed ] [ Google Scholar ] 86. He S, Xiong K, Song S, Chi Y, Fang J, He C. Research progress of grassland ecosystem structure and stability and inspiration for improving its service capacity in the karst desertification control. Plants. 2023;12(4):770. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 87. Cataldo E, Fucile M, Mattii G. Leaf eco–physiological profile and berries technological traits on potted Vitis vinifera L. cv pinot noir subordinated to zeolite treatments under drought stress. Plants. 2022;11(13):1735. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 88. Kong J, Liu W, Huang F, Hua L, Yu F, He Q, Su Y, Li J, Qiu Q. Spatial patterns of non-structural carbohydrates in Eucalyptus urophylla× E. grandis under dry–season irrigation with fertilization. Forests. 2021;12(8):1049. [ Google Scholar ] 89. Hu H, Liu Y, He B, Chen X, Ma L, Luo Y, Fei X, Wei A. Integrative physiological, transcriptome, and metabolome analysis uncovers the drought responses of two Zanthoxylum bungeanum cultivars. Ind Crops Prod. 2022;189:115812. [ Google Scholar ] 90. Ullah A, Tariq A, Sardans J, Peñuelas J, Zeng F, Graciano C, Asghar MA, Raza A, Xiong Y-C, Chai X. Alhagi sparsifolia acclimatizes to saline stress by regulating its osmotic, antioxidant, and nitrogen assimilation potential. BMC Plant Biol. 2022;22(1):453. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 91. Pan L, Li Y, Zhao W, Sui Y, Yang N, Liu L, Liu Y, Tang Z, Mu L. Metabolomics analysis of different diameter classes of Taxus chinensis reveals that the resource allocation is related to carbon and nitrogen metabolism. BMC Plant Biol. 2024;24(1):383. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 92. Guo H, Huang Z, Li M, Hou Z. Growth, ionic homeostasis, and physiological responses of cotton under different salt and alkali stresses. Sci Rep. 2020;10(1):21844. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 93. Li W, Zhang H, Wang W, Zhang P, Ward ND, Norwood M, Myers-Pigg A, Zhao C, Leff R, Yabusaki S. Changes in carbon and nitrogen metabolism during seawater-induced mortality of Picea sitchensis trees. Tree Physiol. 2021;41(12):2326–40. [ DOI ] [ PubMed ] [ Google Scholar ] 94. Nazir F, Jahan B, Iqbal N, Rajurkar AB, Siddiqui MH, Khan MIR. Methyl jasmonate influences ethylene formation, defense systems, nutrient homeostasis and carbohydrate metabolism to alleviate arsenic–induced stress in rice (Oryza sativa). Plant Physiol Biochem. 2023;202:107990. [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1. (16.4KB, docx) Data Availability Statement All data generated or analyzed during this study are included in this manuscript, and materials used in the experiments are available upon request. Articles from BMC Plant Biology are provided here courtesy of BMC ACTIONS View on publisher site PDF (11.1 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

Record · ID 263227 · SHA-256 7d27d974e0dd4578
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive