The stoichiometric traits and biogeochemical niches of four alpine herbs along elevation gradient in southeastern Tibet

doi:10.21203/rs.3.rs-8303088/v1

Download PDF

Research Article

The stoichiometric traits and biogeochemical niches of four alpine herbs along elevation gradient in southeastern Tibet

https://doi.org/10.21203/rs.3.rs-8303088/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Ecological stoichiometry is a fundamental concept for understanding nutrient allocation strategies and ecosystem functioning. However, the spatial and elevational variability of stoichiometric traits across different plant species and their organs remains poorly understood, particularly in high-altitude ecosystems. This study systematically investigated the C:N:P ecological stoichiometry of four alpine herbaceous species-Potentilla saundersiana, Carex moorcroftii, Kobresia humilis, and Leontopodium leontopodioides—across an elevation gradient ranging from 2,647 to 4,898 meters in the alpine grasslands of southeastern Tibet. A total of 433 samples were collected from 34 distinct sites to assess the influence of elevation gradient on plant stoichiometry. Our results revealed significant intra- and interspecific variations in stoichiometric traits among organs and species. Carex moorcroftii exhibited the largest biogeochemical niche size, while L. leontopodioides showed the smallest. Leaves generally exhibiting higher biogeochemical niche size than stems and roots. Elevation significantly influenced plant nitrogen and phosphorus concentrations, with species-specific responses. Climatic factors explained most of the variance in carbon-related stoichiometric traits, while soil nutrients primarily affected phosphorus-related traits. These results highlight the complex interactions among climatic, soil, and biological factors in shaping plant stoichiometry along elevation gradients. This study confirms the intraspecific and interspecific variations in plant stoichiometry and altitudinal heterogeneity in alpine grassland ecosystem, offering valuable insights for future ecological modeling and conservation efforts.

Ecological stoichiometry

biogeochemical niche

elemental phenotype

adaptive strategy

intraspecific and interspecific variation

Ecological stoichiometry considers the balance of multiple chemical elements—such as carbon (C), nitrogen (N), and phosphorus (P)—in organisms and ecosystems. This balance is crucial for understanding plant nutrient dynamics, ecosystem functioning, and biogeochemical cycles (Elser et al. 2000). Plant stoichiometric traits, which include the concentrations and ratios of C, N, and P, serve as indicators of nutrient use efficiency, growth strategies, and responses to environmental changes (Feng et al. 2024; Liu and Wang 2021; Reich and Oleksyn 2004). Specifically, leaf N and P concentrations can reveal information about the leaf economic spectrum and resource acquisition strategies (Leal et al. 2017; Wright et al. 2005). These traits are essential for predicting how plants adapt to varying environmental conditions and how ecosystems respond to global changes, including climate change and nutrient deposition (He et al. 2006; Moody et al. 2025; Zhang et al. 2023). Consequently, investigating the plasticity and drivers of inter- and intraspecific variation in stoichiometric traits will enhance our understanding of plant resource utilization strategies and the mechanisms underlying plant adaptation to environmental conditions (Elser et al. 2010; Leal et al. 2017; Liu and Wang 2021; López-Sepulcre et al. 2024; Qin et al. 2022a).

Plant stoichiometric traits are regulated by a suite of abiotic and biotic factors, including soil nutrient availability, climatic conditions, plant functional types, tissue-specific allocation patterns, and biotic stress (Reich and Oleksyn 2004; Yu et al. 2011). Notably, elevation gradients in alpine ecosystems have received considerable scientific interest because they drive pronounced variations in temperature, precipitation, and soil nutrient distribution across limited spatial scales (Körner 2007; Yang et al. 2015). Elevation gradients represent valuable natural laboratories for studying ecological responses to global change, effectively addressing the spatial and temporal limitations of traditional manipulative experiments (Binter et al. 2025; Sundqvist et al. 2013).

Empirical studies consistently demonstrate significant variation in plant C:N:P stoichiometric ratios along elevation gradients, with foliar N and P concentrations showing particularly strong elevational dependence (Körner 1989; Gong et al. 2020; Qin et al. 2022b). However, these stoichiometric responses display significant species-specific variation (Minden and Kleyer 2014; Reich and Oleksyn 2004). The literature reveals divergent patterns: while some studies report positive correlations between elevation and both leaf N and P concentrations (Cao et al. 2020; Gong et al. 2020; Han et al. 2005), others observe inverse relationships, with leaf N content and N:P ratios decreasing with elevation (Macek et al. 2012; Tong et al. 2021; Zhang et al. 2019).

While early research predominantly focused on whole-plant and foliar stoichiometric characteristics (Han et al. 2005; Reich and Oleksyn 2004), recent advances have revealed critical functional divergence among plant organs (Yang et al. 2015). This organ-specific stoichiometry reflects differential resource allocation strategies, with leaves typically exhibiting 20–30% higher nitrogen concentrations than stems and roots due to their photosynthetic specialization (Körner 1989; Qin et al. 2022b; Schreeg et al. 2014). Such patterns are particularly pronounced along elevation gradients, where foliar N and P concentrations demonstrate non-linear responses to environmental covariates (Gong et al. 2020; Tong et al. 2021; Zhang et al. 2019).

The Biogeochemical Niche (BN) hypothesis provides a unifying framework for these observations, proposing that each species occupies a unique position in elemental composition space as an adaptive strategy (Peñuelas et al. 2019). The plasticity of a species' biogeochemical niche manifests as positional shifts within a multidimensional elemental space (Fernández-Martínez et al., 2022), which can be quantified through multivariate analyses (Yang et al. 2015). The BN framework thus provides a powerful approach for examining both intraspecific and interspecific variability in elemental composition, while elucidating the dynamic interplay between stoichiometric homeostasis and plasticity (Sardans et al. 2015; Wang et al. 2023).

The Qinghai-Tibet Plateau, recognized as the world's "Third Pole", hosts the highest-altitude grassland ecosystem globally, with mean elevations exceeding 4,500 m (Dong et al. 2023). This unique ecoregion, where alpine grasslands cover > 60% of the land area (Wei et al. 2023), exhibits characteristic nutrient limitations - particularly low soil nitrogen availability resulting from cold-temperature constraints on decomposition (Müller et al. 2017). While previous studies have documented elevational patterns in foliar stoichiometry (Gong et al. 2020; Qin et al. 2022b), critical knowledge gaps remain regarding: (1) whole-plant stoichiometric strategies across organs (Wang et al. 2022), (2) interspecific comparisons along elevation gradients (Tong et al. 2021), and (3) the integration of stoichiometry theory with high-altitude plant adaptations (Sundqvist et al. 2014). To address these gaps, we conducted a comprehensive field study across a 2,251 m elevation gradient (2,647-4,898 m) on the southeastern Tibetan Plateau, analyzing C:N:P stoichiometry in four organs (leaves, stems, roots, flowers) of four alpine herbs. Specifically, we hypothesized that: (1) Spatial heterogeneity in stoichiometric traits along elevation will reveal species-specific BN optimization (Peñuelas et al. 2019). (2) Climatic factors will dominate over edaphic factors in governing elevational stoichiometric pattern.

Description of study area

Field investigations were conducted along a 1,300-km transect in the southeastern Tibetan Plateau during July and August 2020. The study area spanned latitudes of 29°20'N to 29°53'N and longitudes of 91°00'E to 95°46'E, with elevations ranging from 2,647 to 4,898 meters above sea level. Climatic data were obtained from the Xizang Meteorological Stations via the China Meteorological Network, covering the period from 1990 to 2020. Based on these data, we calculated the mean annual temperature (MAT), mean annual precipitation (MAP), and mean annual sunshine hours for each sampling site. Across all sites, the average MAT was 5.03°C, the average MAP was 647.78 mm, and the mean annual sunshine duration totaled 2,556.52 hours.

The Qinghai-Tibet Plateau is dominated by alpine meadows and alpine steppes, with temperate grasslands occurring at lower elevations. Due to the harsh climatic conditions, the plant growing season is notably short. Dominant species in the study area include Kobresia spp., Potentilla spp., and Poa spp.

Field transect survey and sampling methodology

We established 34 sampling sites along the transect, with geographic coordinates (latitude, longitude) and elevation recorded at each site using a GPS device (eTrex Venture, Garmin, USA). To ensure spatial independence, sites were spaced more than 50 km apart. Within each site, we systematically placed five quadrats (1m×1m) with a 100m interval between different quadrats. We conducted comprehensive vegetation surveys in each quadrat, measuring community and species-level parameters. We recorded the plant density, mean height, coverage, and aboveground biomass of each plant species. Based on their widespread distribution across sampling sites, we selected four plant species for stoichiometric analysis: Potentilla saundersiana (PS), Carex moorcroftii (CM), Kobresia humilis (KH), and Leontopodium leontopodioides (LL).

When the four target species did not co-occur at a site, we collected only the available species, and stoichiometric traits were analyzed for each species across sites. Overall, we gathered data from 14 sites for PS, 17 sites for CM, 13 sites for KH, and four sites for LL (Fig. 1). At each study site, we collected 30 intact specimens per target species for stoichiometric characterization. This sampling design provided three biological replicates per species per site, with each replicate consisting of ten individual plants. Following plant collection, we extracted soil samples (0–15 cm depth) from the rhizosphere of each species. Soil from 10 individuals was composited per replicate. In total, we analyzed three elements across 138 individuals, yielding 433 samples (site locations and climatic data are detailed in Table S1).

Laboratory analysis

All plant samples were oven-dried at 65°C for 48 hr until reaching constant weight, then finely ground using a ball mill (Retsch MM 400, Germany). Soil samples were air-dried, homogenized, and sieved (2.0 mm mesh) to remove coarse debris. The N concentrations in leaves, stems, roots, and soil were quantified via the Kjeldahl digestion-distillation method. For total P concentrations, plant and soil samples underwent persulfate-mediated oxidative digestion, followed by ammonium molybdate spectrophotometric detection. The organic carbon contents were determined using the Springer-Klee wet oxidation method, involving dichromate (K₂Cr₂O₇)-sulfuric acid (H₂SO₄) digestion under controlled heating.

Data calculation and statistical analysis

Data normality was assessed using the Kolmogorov-Smirnov test before conducting statistical analyses. When required, log-transformation was applied to normalize the data distribution. We initially conducted Pearson's correlation analysis to examine the influence of elevation gradients on the stoichiometric traits of four plant species. Subsequently, a two-way ANOVA was performed to assess the effects of species and organs on these stoichiometric traits. Additionally, multiple comparisons of means were performed using Tukey’s HSD test for roots and soil stoichiometric traits, while paired t-tests were applied to assess stoichiometric traits of shoots for KH and LL, and stem and leaves for CM and PS. Significance levels were set at P<0.05, P<0.01, and P<0.001. We performed the principal component analysis (PCA) to quantify the biogeochemical niche of four plant species based on three elemental traits. The first three principal components (PC1, PC2, and PC3) were extracted using the stats package in R. Biogeochemical niche differentiation was further assessed by calculating hypervolumes from the PCA scores using the hypervolume package. To examine how climatic factors (MAT and MAP), soil properties (C, N, and P concentrations), and biological factors (species and organ type) influenced stoichiometric variation along the elevation gradient, we employed both Generalized Linear Mixed Models (GLMMs) and Linear Mixed Effects Models (LMEMs), with elevation included as a random effect. Because of missing soil phosphorus data for LL, the GLMM and LMEM analyses were restricted to PS, CM, and KH. All statistical analyses were performed in R version 4.1.1 (R Core Team, 2015), using the lmer package for LMEMs and glmm.hp for GLMMs. All the graphs were generated using OriginPro 2024 (Education Edition) or ArcGIS (version 10.8, ESRI, Redlands, CA).

Overall evaluation of stoichiometric traits of four alpine herbs

For PS, the C:N:P ratios were as follows: root (263:9:1), stem (318:9:1), leaf (250:14:1), flower (481:23:1), soil (176:12:1). For CM, the C:N:P ratios were: root (357:11:1), stem (288:9:1), leaf (214:10:1), soil (137:10:1). In the case of KH, the measured ratios were: root (866:13:1), shoot (783:20:1), soil (171:12:1). Finally, for LL, the observed C:N:P ratios were: root (1296:22:1) and shoot (1312:25:1). A comprehensive evaluation of these stoichiometric traits across the organs of the four species was presented in Table S2.

The impact of elevation gradient on stoichiometric traits of four plant species

Along the elevation gradient, C concentrations decreased significantly for both CM (P = 0.016) and KH (P = 0.014) (Fig. 2a), whereas N concentrations increased significantly for PS (P = 0.014) (Fig. 2b). P concentrations increased significantly in PS and KH (P < 0.001 for both) but decreased significantly in CM (P < 0.001) (Fig. 2c). Regarding stoichiometric ratios, the C:N ratio of PS decreased significantly with elevation (P < 0.001; Fig. 2d), while the C:P ratio increased significantly in CM (P < 0.001) but decreased in PS and KH (P < 0.001; Fig. 2e). Finally, the N:P ratio increased significantly in CM (P < 0.001) and decreased in KH (P < 0.001; Fig. 2f).

The intraspecific and interspecific difference in stoichiometric traits

Soil substrates displayed uniformly significantly lower C, N, and P concentrations along with reduced C:N and C:P ratios compared to plant tissues across all four species(P < 0.01). For PS, the highest C and N concentrations, along with C:P and N:P ratios, were all found in flowers (P < 0.01). For CM, leaves showed significantly higher N and P concentrations, along with lower C:N, C:P, and N:P ratios compared to roots and stems (P < 0.05). As for KH, shoots showed significantly higher N concentrations and N:P ratios, coupled with lower C:N ratios than roots (P < 0.05). While LL did not show significant differences in stoichiometric traits between shoots and roots.

When comparing stoichiometric traits across different species, both PS and CM had considerably higher root N and P concentrations, and had significantly lower root C:N and C:P ratios compared to KH and LL (P < 0.01). PS exhibited significantly higher leaf C concentrations, stem C:N ratios, and leaf N:P ratios, alongside lower stem N:P ratios than CM (P < 0.05). KH had significantly lower shoot C:N and C:P ratios in comparison to LL (P < 0.05). The soil stoichiometric traits did not reveal significant differences among four plant species.

The first three components explained 93.7% of the total variations of the elemental contents for all the four species in our study region (PC1, PC2 and PC3 explained 52.7%, 28.4% and 12.6% of the variation, respectively). PC1 was most positively influenced by soil N concentration, while negatively influenced by soil C concentration; PC2 was most positively driven by soil P concentration. While CM displayed the largest niche sizes and LL displayed the least niche sizes. Leaf occupied the largest niche size compared with other organs for PS and CM.

Driving factors of plant stoichiometric traits along elevation gradients

The results from LMEMs indicate that MAT and MAP had no significant effect on plant stoichiometric traits (Fig. 5). However, species (PS, CM, KH, and LL) showed a significant negative effect on N concentrations (Effect Value [EV]: -2.94, P < 0.001) and P concentrations (EV: -0.34, P < 0.001), while showed a significantly positive impact on plant C:N ratios (EV: 7.79, P < 0.001) and C:P ratios (EV: 177.12, P < 0.001). Organs (root, stem, leaf, and flower) exhibited a significant positive effect on plant N concentrations (EV: 4.01, P < 0.001), P concentrations (EV: 0.23, P < 0.001) and C:P ratios (EV: -65.23, P < 0.001). Soil P concentrations had a significant positive impact on both plant N concentrations (EV: 7.39, P = 0.03) and P concentrations (EV: 1.72, P = 0.002). Soil C concentrations positively influenced plant C:N ratios (EV: 0.41, P = 0.02) and C:P ratios (EV: 10.97, P < 0.001), while soil N concentrations had a negative impact on plant C:N ratios (EV: -6.46, P = 0.02) and C:P ratios(EV: -137.52, P = 0.002).

As for the driving factors of plant stoichiometric traits along elevation gradients, climatic factors (MAT and MAP) could explain 87.90% and 62.67% of variances for plant C concentrations and C:N ratios. Biotic factors (species and organ), climatic factors, and soil nutrition explained 46.68%, 30.66%, and 22.66% of variances for plant N concentrations, respectively. Soil nutrition explained 60.31%, 47.86% and 59.17% of variances for P concentrations, C:P and N:P ratios, respectively.

Intraspecific and interspecific variation in stoichiometric traits along elevation gradients

This study found that, except for C and N:P ratio, the stoichiometric traits varied significantly among species and organs, indicating a high level of specificity in these traits in the QTP. The differential stoichiometric regulation among plant organs represents a fundamental strategy for optimizing resource acquisition, metabolic efficiency, and environmental adaptation(Wang et al. 2023; Zhang et al. 2020a). Flowers consistently demonstrating the highest C and N concentrations for PS, and this result is consist with another alpine herb (Gentiana rigescens) conducted in Southwest China (Zhang et al. 2020b). The results indicate that flowers serve as the primary nutrient sink, necessitating greater allocations of carbon and nitrogen (Wang et al. 2023). Nutrient deficiencies trigger organ-dependent C reallocation strategies (Liu et al. 2024). Such trade-offs highlight why whole-plant biogeochemical models must resolve organ-specific stoichiometric responses rather than averaging across tissues (Leroux et al. 2017). Organ-specific stoichiometry is not merely a passive outcome of nutrient availability but an active modulator of plant adaptation (Leal et al. 2017; Lemmen et al. 2019). Therefore, embedding these organ-resolved dynamics into ecological models will be pivotal for predicting biogeochemical cycles (EI-Sabaawi et al. 2023).

The observed stoichiometric plasticity across four alpine herbs demonstrated the dynamic adjustments in C:N:P ratios among organs and species, which is align with the concept of the elemental phenotype (EI-Sabaawi et al. 2023; Leal et al. 2017; Lemmen et al. 2019). In alpine ecosystems, where nutrient availability is limited by low temperatures, short growing seasons, and heterogeneous soils, such plasticity enables plants to reallocate elements to prioritize growth or stress defense (Zhang et al. 2020a). PS shifting N to leaves for photosynthesis and plant growth along elevation gradient (Fig. 2 and Fig. 3). While LL adapted to stressful environment by maintain stoichiometric homeostasis in our study site (Table S2). The variation in leaf N:P ratios among four alpine herbs highlights the species-specific nutrient utilization strategies in spite of relatively constant soil N:P ratios (Fig. 3).

Our results confirm the biogeochemical niche (BN) hypothesis, with four alpine herbs exhibit distinct elemental phenotypes reflecting evolutionary strategies for resource acquisition and utilization along elevation gradient, which support our first hypothesis (He et al. 2025; Peñuelas et al. 2019). The coexistence of four tested species exemplifies biogeochemical niche partitioning, such BN differentiation in alpine communities result in reduce competition in community and buffer metabolic disruptions caused by stoichiometric mismatches (Zhang et al. 2024). The divergent elemental acquisition and utilization strategies mark the potential strategies for species in faced with biotic and abiotic stresses (Fahimipour and Gross 2020;Sardans et al. 2015). LL’s high N:P (> 16) and low P content reflect preferential N allocation in alpine area (Wang et al. 2022). In contrast, high N and P contents in PS and CM support ATP-intensive growth and competitive biomass accumulation (Hüseyinoğlu and Yalcin 2017).

Following the C-S-R (Competitor-Stressor-Ruderal) strategies theory, species with low N and P contents, high N:P ratios and low stoichiometry flexibility are classified as stress-tolerator, while species with high N and P contents are classified as competitor, and species with high stoichiometry flexibility are classified as ruderal (Grime, 2001; Güsewell, 2004; Peñuelas et al. 2019). Based on this theory, LL exhibit S (stressor) strategy, whereas PS and CM are categorized under CR (Competitor-Ruderal) strategies due to their high concentrations of both N and P (Table S2). The elevated N:P ratios observed in LL(Fig. 2) may partially explain its adaptability to stressful environments and the bimodal distribution of LL in degraded grasslands of the QTP (Wang et al. 2022). KH can be classified as a CS strategy for its competitive nutrient acquisition strategy (microbial symbiosis) and tolerance to P limitation (high N:P ratios). Previous studies have indicated that KH can recruit rhizosphere growth-promoting bacteria, thereby enhancing soil nutrient utilization despite low mineralization rates in alpine soils (Li et al. 2024). Given the harshness of their habitat, none of the four herbs demonstrated ruderal (R-selected) traits typically associated with rapid nutrient acquisition (Gibson 2008). Such CSR framework reveals divergent vulnerabilities among keystone alpine species under anthropogenic change. For LL would face high extinction risks from nitrogen deposition due to narrow biogeochemical niches and limited plasticity (Fig. 4). Meanwhile, CR-strategists such as PS and CM would eroding niche complementarity through competitive exclusion (Fig. 4).

Driving factors of stoichiometric traits along elevation gradients

Given the pronounced geographic gradients in climate, altitude, and soil conditions across the eastern Tibetan Plateau, we expected to detected the biogeographic pattern of stoichiometry of four alpine herbs along elevation gradients. Our findings of elevated N and P concentrations at higher elevations is consistent with observations in northern China's Artemisia species (Yang et al. 2015), which demonstrate the operation of the Growth Rate Hypothesis in alpine ecosystems (Elser et al. 2000). While C concentrations remained stable due to their fundamental structural role and metabolic processes (Gong et al. 2020; Qin et al. 2022b).

Notably, MAT emerged as the dominant climatic driver of stoichiometric variation, exerting positive effects on plant C content and C:N, C:P, and N:P ratios (Fig. 5). This aligns with global meta-analyses demonstrating that temperature gradients strongly regulate plant nutrient allocation strategies by modulating microbial activity, soil mineralization rates, and growth-resource trade-offs (Körner 2007; Reich and Oleksyn 2004). The pronounced MAT variability across our study sites (range: −2.97 to 10.32°C; CV = 90.71%) likely amplified these thermal effects, low-temperature in alpine ecosystem would constraint the N and P cycling along elevation gradients (Sundqvist et al. 2013; Wang et al. 2022). In contrast, the limited impact of MAP (range: 537.09–769.09 mm; CV = 10.48%) on stoichiometric traits may be due to insufficient variation in precipitation. Together, these results advance our mechanistic understanding of how alpine plants reconcile the fundamental trade-off between growth and stress resistance through stoichiometric adjustments.

Our results demonstrated that phosphorus-related stoichiometric traits, including plant P content, N:P, and C:P ratios, were predominantly regulated by soil nutrient availability, particularly soil phosphorus concentrations. In contrast, carbon-related metrics, including C content and C:N ratios, were strongly driven by climatic factors, especially MAT, partially supporting our second hypothesis. These findings align with global-scale studies on plant stoichiometry (Du et al. 2020), suggesting that carbon-related traits are more indicative of the climatic regulation of plant growth and metabolism (Elser et al. 2000; Reich and Oleksyn 2004). On the other hand, nitrogen-related stoichiometric traits were influenced by a combination of climatic factors, soil nutrients, and species interactions, highlighting the greater complexity of nitrogen allocation strategies (Yu et al. 2011; Wang et al. 2019). The decoupled drivers of C-, N-, and P-related stoichiometry suggest that climate change will have asymmetric effects on plant elemental composition in QTP, where rising temperature may enhance C assimilation, reducing foliar C:N ratios due to increased N demand for growth (Reich and Oleksyn 2004).

Our study revealed pronounced intraspecific and interspecific variability in stoichiometric traits, with organs exhibiting greater heterogeneity in stoichiometric ratios. The four studied species demonstrate biogeochemical niche partitioning, particularly through LL's elevated N:P ratios - an adaptive strategy that maximizes phosphorus use efficiency in the P-limited alpine ecosystem, thereby reducing interspecific competition for this critical resource. Using the C-S-R framework, we identified CM as high-homeostasis species with competitive (CR) strategies, while LL’s high N:P ratios suggest stress-tolerator (SR) strategies. Climatic factors account for most of the variance in carbon-related stoichiometric traits along elevation gradient, and soil-available nutrients predominantly influenced phosphorus-related stoichiometric traits. These findings highlight the necessity of considering organ-specific and species-specific responses when investigating plant stoichiometry in alpine ecosystems. Ultimately, this research could enhance our understanding of nutrient cycling and plant adaptation strategies in high-altitude environments.

A key strength of this study lies in its systematic evaluation of multi-organ stoichiometric traits across four dominant QTP species, advancing beyond the common leaf-centric approach in alpine plant stoichiometry. Particularly, this research highlights the stoichiometric traits of flowers for PS, an aspect often overlooked in other studies. However, it is important to note that only PS sampled flowers in this research, and the stoichiometric traits of LL (4 sites) were relatively limited. Thus, we recommend a more comprehensive comparison of stoichiometric traits among different plant organs, not only focus on the commonly used three elements (C, N and P), but also concern with other elements such as K, Mg, Fe, Cu etc. This may enhance our understanding of stoichiometric theory related to plant adaptation in stressful environments within the QTP. Future studies should expand sampling of reproductive organs (flowers, seeds) to test their role in stoichiometric fitness trade-offs. Meanwhile, linking stoichiometric traits with functional traits (e.g., specific leaf area, root morphology) to decode the biogeochemical niche partitioning would enhance our understanding of elemental strategies in stressful condition.

Authors’ Contributions

Tudi Yimiti (Data curation, Formal analysis, Software, Visualization, Writing - Original Draft), Ziwei Zhang (Conceptualization, Data curation, Investigation, Methodology, Resources), Yiqian Du (Resources, Validation. Derong Su: Data curation, Resources), Xiaoyan Ping (Conceptualization, Funding acquisition, Supervision, Writing - Original Draft, Writing - Review & Editing).

Conflict of interest statement.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Funding

This work was supported by the Second Tibetan Plateau Scientific Expedition and Research (Grant 2019QZKK0302-02) and Open bidding for selecting the best candidates for National Forestry and Grassland Administration (202401-06-04).

Binter J, Macek M, Dolezal J. (2025). Integrating morphological, anatomical, and physiological traits to explain elevational distributions in Himalayan steppe and alpine plants. J Integr Plant Biol 00: 1–15. https://doi.org/10.1111/jipb.13971
Cao J, Wang X, Adamowski, JF, et al. (2020) Response of leaf stoichiometry of Oxytropis ochrocephala to elevation and slope aspect. Catena 194: 104772. https://doi.org/10.1016/j.catena.2020.104772
Dong S, Zhang Y, Shen H, et al. (2023) Grasslands on the Third Pole of the World: Structure, Function, Process, and Resilience of Social-Ecological Systems. Springer Cham. https://doi.org/10.1007/978-3-031-39485-0.
Du E, Terrer C, Pellegrini AFA, et al. (2020) Global patterns of terrestrial nitrogen and phosphorus limitation. Nat Geosci 13: 221–226. https://doi.org/10.1038/s41561-019-0530-4
El-Sabaawi RW, Lemmen KD, Jeyasingh PD, et al. (2023) SEED: a framework for integrating ecological stoichiometry and eco-evolutionary dynamics. Ecol Lett 26: S109–S126. https://doi.org/10.1111/ele.14285
Elser JJ, Sterner RW, Gorokhova E, et al. (2000) Biological stoichiometry from genes to ecosystems. Ecol Lett 3: 540-550. https://doi.org/10.1111/j.1461-0248.2000.00185.x.
Elser JJ, Fagan WF, Kerkhoff AJ, et al. (2010) Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change. New Phytol 186: 593-608. https://doi.org/10.1111/j.1469-8137.2010.03214.x.
Fahimipour AK, Gross T (2020) Mapping the bacterial metabolic niche space. Nat Commun 11: 4887. https://doi.org/10.1038/s41467-020-18695-z
Feng WL, Yang JL, Xu LG, et al. (2024) The spatial variations and driving factors of C, N, P stoichiometric characteristics of plant and soil in the terrestrial ecosystem. Sci Total Environ 951: 175543. https://doi.org/10.1016/j.scitotenv.2024.175543
Fernández-Martínez M, Preece C, Corbera J, et al. (2021) Bryophyte C:N:P stoichiometry, biogeochemical niches and elementome plasticity driven by environment and coexistence. Ecol Lett 24: 1375–1386. https://doi.org/10.1111/ele.13752
Gibson DJ (2008) Grasses and Grassland Ecology. Oxford Univ Press. https://doi.org/10.1093/oso/9780198529187.001.0001
Gong H, Li Y, Yu T, et al. (2020) Soil and climate effects on leaf nitrogen and phosphorus stoichiometry along elevational gradients. Glob Ecol Conserv 23: e01138. https://doi.org/10.1016/j.gecco.2020.e01138
Grime J (2001) Plant Strategies, Vegetation Processes, and Ecosystem Properties. 2nd ed. Wiley.
Güsewell S (2004) N:P ratios in terrestrial plants: variation and functional significance. New Phytol 164: 243–266. https://doi.org/10.1111/j.1469-8137.2004.01192.x
Han W, Fang J, Guo D, et al. (2005) Leaf nitrogen and phosphorus stoichiometry across 753 terrestrial plant species in China. New Phytol 168: 377–385. https://doi.org/10.1111/j.1469-8137.2005.01530.x
He J, Fang J, Wang Z, et al. (2006) Stoichiometry and large-scale patterns of leaf carbon and nitrogen in the grassland biomes of China. Oecologia 149: 115–122. https://doi.org/10.1007/s00442-006-0425-0
He P, Ni Y, Sardans J, et al. (2025) Evolutionary history shapes plant elementome and biogeochemical niches in a forest-steppe ecotone. Plant Soil https://doi.org/10.1007/s11104-025-07353-2
Hüseyinoğlu R, Yalcin E (2017) Competitive, stress-tolerant and ruderal based classification of some plant species in an alpine community of the Giresun Mountains in Turkey. J Environ Biol 38: 761–769. https://doi.org/10.22438/jeb/38/5/MRN-302
Körner C (1989) The nutritional status of plants from high altitudes: a worldwide comparison. Oecologia 81: 379–391. https://doi.org/10.1007/BF00377088
Körner C (2007) The use of ‘altitude’ in ecological research. Trends Ecol Evol 22: 569–574. https://doi.org/10.1016/j.tree.2007.09.006
Leal MC, Seehausen O, Matthews B (2017) The ecology and evolution of stoichiometric phenotypes. Trends Ecol Evol 32: 108–117. https://doi.org/10.1016/j.tree.2016.11.006
Lemmen KD, Butler OM, Koffel T, et al. (2019) Stoichiometric traits vary widely within species: a meta-analysis of common garden experiments. Front Ecol Evol 7: 339. https://doi.org/10.3389/fevo.2019.00339
Leroux SJ, Van Wal E, Wiersma YF, et al. (2017) Stoichiometric distribution models: ecological stoichiometry at the landscape extent. Ecol Lett 20: 1495–1506. https://doi.org/10.1111/ele.12859
Li J, Wu L, Zhou Y, et al. (2024) Kobresia humilis via root-released flavonoids recruit Bacillus for promoted growth. Microbiol Res 287: 127866. https://doi.org/10.1016/j.micres.2024.127866
Liu JY, Zhang XL, Jin XY, et al. (2024) Nutrient allocation patterns in different aboveground organs at different reproductive stages of four introduced Calligonum species in a common garden in Northwestern China. Front Plant Sci 15: 1504216. https://doi.org/10.3389/fpls.2024.1504216
Liu R, Wang D (2021) C:N:P stoichiometric characteristics and seasonal dynamics of leaf–root–litter–soil in plantations on the Loess Plateau. Ecol Indic 127: 107772. https://doi.org/10.1016/j.ecolind.2021.107772
López-Sepulcre A, Amaral JR, Gautam N, et al. (2024) The eco-evolutionary dynamics of stoichiometric homeostasis. Trends Ecol Evol 39: 1111–1118. https://doi.org/10.1016/j.tree.2024.08.002
Macek P, Klimeš L, Adamec L, et al. (2012) Plant nutrient content does not simply increase with elevation under the extreme environmental conditions of Ladakh, NW Himalaya. Arct Antarct Alp Res 44: 62–66. https://doi.org/10.1657/1938-4246-44.1.62
Minden V, Kleyer M (2014) Internal and external regulation of plant organ stoichiometry. Plant Biol 16: 897–907. https://doi.org/10.1111/plb.12155
Moody EK, Anania K, Boersma KS, et al. (2025) Linking functional responses and effects with stoichiometric traits. Ecology 106: e70080. https://doi.org/10.1002/ecy.70080
Müller M, Oelmann Y, Schickhoff U, et al. (2017) Himalayan treeline soil and foliar C:N:P stoichiometry indicate nutrient shortage with elevation. Geoderma 291: 21–32. https://doi.org/10.1016/j.geoderma.2016.12.015
Peñuelas J, Fernández-Martínez M, Ciais P, et al. (2019) The bioelements, the elementome, and the biogeochemical niche. Ecology 100: e02652. https://doi.org/10.1002/ecy.2652
Qin H, Jiao L, Zhou Y, et al. (2022a) Elevation affects the ecological stoichiometry of Qinghai spruce in the Qilian Mountains of northwest China. Front Plant Sci 13: 917755. https://doi.org/10.3389/fpls.2022.917755
Qin Y, Liu W, Zhang X, et al. (2022b) Leaf stoichiometry of Potentilla fruticosa across elevations in China’s Qilian Mountains. Front Plant Sci 13: 814059. https://doi.org/10.3389/fpls.2022.814059
Reich PB, Oleksyn J et al. (2004) Global patterns of plant leaf N and P in relation to temperature and latitude. Proc Natl Acad Sci USA 101: 11001–11006. https://doi.org/10.1073/pnas.0403588101
Sardans J, Janssens IA, Alonso R, et al. (2015) Foliar elemental composition of European forest tree species associated with evolutionary traits and present environmental and competitive conditions. Glob Ecol Biogeogr 24: 240–255. https://doi.org/10.1111/geb.12253
Schreeg LA, Santiago LS, Wright SJ, et al. (2014) Stem, root, and older leaf N:P ratios are more responsive indicators of soil nutrient availability than new foliage. Ecology 95: 2062–2068. https://doi.org/10.1890/13-1671.1
Sundqvist M, Sanders N, Wardle D (2013) Community and ecosystem responses to elevational gradients: processes, mechanisms, and insights for global change. Annu Rev Ecol Evol Syst 44: 261–280. https://doi.org/10.1146/annurev-ecolsys-110512-135750
Sundqvist MK, Liu Z, Giesler R, et al. (2014) Plant and microbial responses to nitrogen and phosphorus addition across an elevational gradient in subarctic tundra. Ecology 95: 1819–1835. https://doi.org/10.1890/13-0869.1
Tong R, Zhou B, Jiang L, et al. (2021) Spatial patterns of leaf carbon, nitrogen, and phosphorus stoichiometry and nutrient resorption in Chinese fir across subtropical China. Catena 201: 105221. https://doi.org/10.1016/j.catena.2021.105221
Wang H, Su H, Biswas A, et al. (2022) Leaf stoichiometry of Leontopodium lentopodioides at high altitudes on the northeastern Qinghai-Tibetan Plateau, China. J Arid Land 14: 1124–1137. https://doi.org/10.1007/s40333-022-0033-9
Wang J, Wang J, Wang L, et al. (2019) Does stoichiometric homeostasis differ among tree organs and with tree age? For Ecol Manag 453: 117637. https://doi.org/10.1016/j.foreco.2019.117637
Wang Y, Han Q, Kitajima K, et al. (2023) Resource allocation strategies in the reproductive organs of Fagaceae species. Ecol Res 38: 306–316. https://doi.org/10.1111/1440-1703.12350
Wei G, Weisai L, Zhou Z, et al. (2023) Impact of a retrogressive thaw slump on surrounding vegetation communities in the Fenghuoshan mountains, Qinghai-Tibet Plateau. Res Cold Arid Reg 15: 11–17. https://doi.org/10.1016/j.rcar.2023.04.004
Wright IJ, Reich PB, Cornelissen JHC, et al. (2005) Assessing the generality of global leaf trait relationships. New Phytol 166: 485–496. https://doi.org/10.1111/j.1469-8137.2005.01349.x
Yang X, Huang Z, Zhang K, et al. (2015) C:N:P stoichiometry of Artemisia species and close relatives across Northern China: unravelling effects of climate, soil and taxonomy. J Ecol 103: 1020–1031. https://doi.org/10.1111/1365-2745.12409
Yu Q, Elser JJ, He N, et al. (2011) Stoichiometric homeostasis of vascular plants in the Inner Mongolia grassland. Oecologia 166: 1–10. https://doi.org/10.1007/s00442-010-1902-z
Zhang J, He N, Liu C, et al. (2020a) Variation and evolution of C:N ratio among different organs enable plants to adapt to N-limited environments. Glob Change Biol 26: 2534–2543. https://doi.org/10.1111/gcb.14973
Zhang J, Wang Y, Cai C (2020b) Multielemental stoichiometry in plant organs: a case study with the alpine herb Gentiana rigescens across Southwest China. Front Plant Sci 11: 441. https://doi.org/10.3389/fpls.2020.00441
Zhang K, Chang L, Li G, et al. (2023) Advances and future research in ecological stoichiometry under saline-alkali stress. Environ Sci Pollut Res 30: 5475–5486. https://doi.org/10.1007/s11356-022-24293-x
Zhang P, Zhou Z, Liu W, et al. (2024) Detritivores maintain stoichiometric homeostasis, but alter body size and population density in response to altitude induced stoichiometric mismatches. Geoderma 446: 116897. https://doi.org/10.1016/j.geoderma.2024.116897
Zhang Y, Li C, Wang M (2019) Linkages of C:N:P stoichiometry between soil and leaf and their response to climatic factors along altitudinal gradients. J Soils Sediments 19: 1820–1829. https://doi.org/10.1007/s11368-018-2173-2
Zhu J, Jiang L, Zhang Y (2016) Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands. Sci Rep 6: 34105. https://doi.org/10.1038/srep34105

No competing interests reported.

Download PDF

Reviewers agreed at journal
08 Jan, 2026
Reviewers agreed at journal
07 Jan, 2026
Reviewers agreed at journal
07 Jan, 2026
Reviewers invited by journal
09 Dec, 2025
Editor assigned by journal
09 Dec, 2025
Submission checks completed at journal
09 Dec, 2025
First submitted to journal
07 Dec, 2025

You are reading this latest preprint version

The stoichiometric traits and biogeochemical niches of four alpine herbs along elevation gradient in southeastern Tibet

Status:

Version 1

Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

RESULTS

Overall evaluation of stoichiometric traits of four alpine herbs

The impact of elevation gradient on stoichiometric traits of four plant species

The intraspecific and interspecific difference in stoichiometric traits

Driving factors of plant stoichiometric traits along elevation gradients

DISCUSSION

Intraspecific and interspecific variation in stoichiometric traits along elevation gradients

Driving factors of stoichiometric traits along elevation gradients

CONCLUSIONS

Declarations

References

Additional Declarations

Status:

Version 1