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Ecological Processes
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Strong conservatism in leaf anatomical traits and their multidimensional relationships with leaf economic traits in grasslands under different stressful environments

Ecological Processes volume 13, Article number: 71 (2024) Cite this article

Abstract

Background

Plant traits and plant adaptive strategies have been affected by the increasing intensity and severity of environmental changes. Given the uncertainty surrounding future environmental conditions, investigating plant trait variations under various stresses is crucial for unraveling plant survival strategies. Leaf anatomical traits are closely responsible for plants’ photosynthesis, respiration and transpiration. However, knowledge of how the multi-species leaf anatomical traits varied in extremely and moderately stressful environments is limited. Our objective was to compare the variation of leaf anatomic traits and adaptation strategies in two different stressful regions of the Qinghai-Tibet Plateau (TP) and Mongolian Plateau (MP) of China.

Methods

We sampled ten sites in each of the two regions (MP and TP) along an environmental gradient. Seven leaf anatomical traits and two leaf economic traits were measured for all leaf samples. Leaf anatomical traits include the traits related to leaf physiological processes (mesophyll thickness (MT), palisade tissue thickness (PT), spongy tissue thickness (ST), palisade-spongy tissue thickness ratio (PST) and epidermal thickness (ET)) and the traits related to trait construction investment (epiderm-leaf thickness ratio (ET/LT) and mesophyll-leaf thickness ratio (MT/LT)). Leaf economic traits include specific leaf area (SLA) and leaf nitrogen content (LN).

Results

The results revealed that leaf anatomical traits in the TP exhibited greater phylogenetic conservation with thicker structures, being less susceptible to environmental impacts than those in the MP. Additionally, the leaf anatomical and economic traits decoupled both in the MP and TP.

Conclusion

These findings highlight that plants adopt diverse strategies to cope with extremely and moderately environmental stresses, but multidimensional trait patterns are generally favored in stressful environments.

Introduction

Intense environmental change has stimulated our interest in understanding plant adaptive strategies. Plant traits have received positive attention as measurable indicators that can reflect plant strategies (de la Riva et al. 2017; He et al. 2018). Over the past decade, scientists have studied plant height, leaf morphology, element content, and other traits in relation to environmental changes (Carvajal et al. 2019; Baird et al. 2021). However, leaf anatomical traits were largely to be overlooked, despite being more directly and closely related to leaf function (Baird et al. 2021; Liu et al. 2021; Pardo and VanBuren 2021; Zhang et al. 2022). For instance, the mesophyll tissues with numerous chloroplasts act as the primary site for photosynthesis (Kofidis et al. 2003). The epidermis tissue covers the whole leaf surface and is primarily used for defensive and protective purposes (Bernado et al. 2021; Harrison et al. 2021). Therefore, understanding the adaptation of plants to the environment from the perspective of leaf anatomic traits is urgently required.

Ecologists have found that under favorable environments, plants generally adopt the resource-acquiring strategies with larger leaf area and smaller leaf thickness, which correlate with heightened photosynthetic capacity but weaker defensive capabilities (Baird et al. 2021). By contrast, conservative survival strategies are favored in stressful environments (Guo et al. 2017; Carvajal et al. 2019). For example, in high altitude environments, evergreen coniferous trees with thick leaf anatomical traits grow in low-temperature conditions (Liu et al. 2021). Moreover, the cost of trait plasticity may exhibit a tendency to escalate with the intensification of stresses, albeit the amplitude of variation diverges across different plant traits (Stotz et al. 2021). Previous studies suggested that structural traits (e.g., leaf thickness) owned high cost of trait plasticity and undergo minimal changes, while low-cost and reversible traits, such as photosynthetic rate and stomatal conductance, were easier to modify (Grime and Mackey 2002; Stotz et al. 2021). However, the changes in leaf anatomical traits under unfavorable habitats are poorly understood.

Previous studies have found that the phylogenetic background of species could influence trait variation (de la Riva et al. 2017; Wang et al. 2018). Most leaf traits have been reported to be significantly influenced by phylogenetic evolutionary history during the plant formation and development (Wang et al. 2018; Amaral et al. 2021; Filartiga et al. 2022). Generally, the leaves of angiosperms are larger and more planate in contrast to gymnosperms (Falcon-Lang 2000). Moreover, herbaceous plants rapidly evolved and widely distributed on the earth by their low demand for environmental resources, among which C4 plants with Kranz structure developed rapidly with the period of increased temperature and decreased CO2 (Pardo and VanBuren 2021). In herbaceous plants, the monocotyledonous herbs might produce thinner leaf structures to adapt to changed environments (Guo et al. 2017). To date, however, the evolution and variation patterns of leaf anatomical structure across multiple species and at larger spatial scales are still unclear.

Trait-trait relationships reflect the synergistic plant adaptations to environmental changes, and have gained increasing attention from ecologists (Wright et al. 2004; Diaz et al. 2016). A crucial breakthrough was the description of leaf economics spectrum (LES) (Wright et al. 2004), which showed the continuum of variations in leaf economic traits that represent a trade-off between strategies of resource acquisition (associated with the traits, such as high leaf nitrogen content (LN) and specific leaf area (SLA)) and conservation (such as low LN and SLA). However, the role of leaf anatomical traits on the LES is still an open question. The negative relationships between leaf palisade cell density and LN are reported in woody species (Harrison et al. 2021), but weak correlation in other forest ecosystems (Liu et al. 2019). Furthermore, previous research found that size and economic traits exhibited distinct patterns in an unfavorable environment (Joswig et al. 2022). The multidimensional patterns of plant traits were favored in stressful environments, due to the low plant resources availability and high survival cost (Weigelt et al. 2021; Wang et al. 2022). Thus, the relationships between leaf anatomic and economic traits might be also correlated with environmental conditions. We aim to explore the trade-offs of plant traits in different habitats by studying the various relationships between leaf anatomical and economic traits under different environmental conditions.

Here, we aimed to assess the variation in leaf anatomical traits and explore their relationships with leaf economic traits in grasslands subjected to varying stressful environments. We designed two grassland transects with "natural control experiments" in the Mongolian Plateau (MP) and Qinghai-Tibet Plateau (TP), which have different environmental constraints. TP is characterized by extremely low temperature and high ultraviolet (UV) radiation (Ma et al. 2012). MP belongs to the zone of moderately environmental stresses, and precipitation is the dominant factor that controls vegetation growth (Qin et al. 2018). We measured seven leaf anatomical traits, including mesophyll thickness (MT, μm), palisade tissue thickness (PT, μm), spongy tissue thickness (ST, μm), epidermal thickness (ET, μm), palisade-spongy tissue ratio (PST), epiderm-leaf thickness ratio (ET/LT), mesophyll-leaf thickness ratio (MT/LT), and two economic traits, including SLA (cm2 g−1), and LN (%). We hypothesized that (1) in contrast with MP, plants in TP would adopt the more conservative traits with higher leaf anatomical thickness; (2) given the high cost of trait plasticity in extreme habitats, leaf anatomical traits in the TP would show more strongly phylogenetic conservatism and less influenced by environmental factors than those of MP; (3) and the anatomical traits would co-vary with leaf economic traits in the MP, but decouple in the TP.

Materials and methods

Study area and site design

The field plots were designated in the Mongolian Plateau (MP; 43.55‒45.11°N, 112.15–123.51°E) and Qinghai-Tibet Plateau (TP; 31.38–32.48°N, 80.15–95.45°E) of China (Fig. 1, Table S1). The TP is the largest plateau in China over an area of 2.5 × 106 km2. Averaging in excess of 4500 m above sea level, the plateau is the highest alpine grassland in the world (Spicer et al. 2021). The survey sites vary in mean annual temperature (MAT) from −6.8 to 0.4 °C, mean annual precipitation (MAP) from 191 to 620 mm, and UV radiation exceeds 4.1 MJ m−2 day−1 (Table S1). The MP is the main temperate grasslands area in China. The climate of the MP is a typical temperate continental monsoon that winters are long and cold, summers are warm and dry (Bai et al. 2008). The MAP of these sampling sites in the MP was less than 450 mm. Each plateau shows the precipitation decreasing from northeast to southwest, and then we selected the sampling grassland transects along the environmental gradient (Fig. 1, Table S1).

Fig. 1
figure 1

Locations of study sites within the Mongolian Plateau (MP) and Qinghai-Tibet Plateau (TP) (a). The leaf trait measuring information (b). The hypotheses in this study (c)

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Field sampling

During the growth peak of grassland species, the field survey and leaf sampling were conducted in July and August 2018. We set 10 sites across meadow (MD), typical grassland (TG), and desert grassland (DG) from east to west at each plateau (Fig. 1, Table S1). Subsequently, at each site, all herbs appeared within a 1 km radius circle were collected to measure leaf anatomical traits. A total of 30 healthy, fully expanded sun-exposed leaves were collected and bulked together from five individuals of each species. Plant species identification was performed in the field by experienced plant taxonomists and checked by Flora Reipublicae Popularis Sinicae (http://www.iplant.cn/frps). In total, 398 plant samples were collected in the MP, belonging to 172 species, 111 genera and 42 families. In the TP, 174 plant samples were collected, belonging to 108 species, 74 genera and 35 families (Table S2). Leaf samples were immediately stored in a cool box with ice and transported to the lab for the measurement of leaf economic traits. To measure leaf anatomical traits, rectangular sections measuring 1.0 cm × 0.5 cm were cut from the leaves (including the midrib and a portion of the lamina), and fixed in formaldehyde-acetic acid–ethanol fixative (FAA, 5 ml of 38% formalin, 5 ml of glacial acetic acid, and 90 ml of 50% ethanol with 5 ml glycerin) (Sobrado 2007; Tian et al. 2016) for further measurement. Meanwhile, soil samples (0–10 cm) were collected within each plot using a 6-cm-diameter auger at the center and two corners of the plot, and then mixed thoroughly.

Measurement of leaf traits

Leaf samples for measuring anatomical traits were progressively dehydrated in an ethanol series (50–100%), and infiltrated with warm paraffin (56–58 °C). Then leaf transverse sections thickness of 5–10 μm were cut by the rotary microtome (Leica RM2235, Germany). After staining with saffron and solid green, leaf sections were mounted in slides and sealed with neutral glue. For each species, we made two slices and took six images using a light microscope. Finally, a total of 18 data points of each leaf anatomical traits for each species were gathered with software (Motic Images Plus 3.0) to measure adaxial epidermis thickness (AD, μm), abaxial epidermis thickness (AB, μm), leaf thickness (LT, μm), MT (μm), PT (μm), and ST (μm). In addition, PST is the ratio of PT and ST. ET (μm) is the sum of AD and AB. ET/LT and MT/LT were calculated. Leaf area was measured for 20 randomly chosen full leaves for each species. To obtain the leaf area (cm2) data, we scanned these leaves with a scanner (CanoScan LiDE 110; Canon, Japan) and analyzed the pictures with ImageJ software. The leaves were then dried in an oven until a constant weight gaining leaf dry weight (g). SLA for each individual was calculated by dividing the leaf area by leaf dry weight. The oven-dried leaf samples were ground into a fine powder using a ball mill (MM400 Ball Mill, Retsch, Germany) and an agate mortar grinder (RM200, Retsch, Haan, Germany) to extract LN.

Measurement of soil nutrient

Soil samples were air-dried and sieved with the roots removed, then ground to pass through a 2-mm sieve, next using a ball mill grind to a fine powder (through 0.180 mm mesh). The soil nitrogen content (SN, mg g−1) was determined with an elemental analyzer (Vario MAX CN Elemental Analyzer, Elementar, Hanau, Germany).

Climate data

Mean annual temperature (MAT, °C) and mean annual precipitation MAP (mm) were obtained from the National Meteorological Information Center of China. Aridity index (AI) was obtained at the following website: https://cgiarcsi.community/2019/01/24/global-aridity-indexand-potential-evapotranspiration-climate-database-v2/. UV radiation (MJ m−2 day−1) data were derived during the growing season in this study area from UV radiation datasets in Chinese terrestrial ecosystems (Liu et al. 2017).

Phylogeny

The names of all 266 species were checked and verified according to The Plant List (http://www.theplantlist.org/). The classification of angiosperm orders and families was determined based on the Angiosperm Phylogeny Group IV (Byng et al. 2016). A phylogenetic tree was constructed by the comprehensive phylogeny from Zanne et al. (2014) (https://github.com/camwebb/phylomatic-awk).

Data analysis

We used independent-sample test to analyze the difference in leaf traits between the MP and TP plateaus because the data variance was not uniform and did not conform to normal distribution. Blomberg’s K statistics were used to measure the intensity of the phylogenetic signal for leaf anatomical traits (Blomberg et al. 2003). To determine the effect of phylogenetic and environmental variables on the leaf anatomical traits of all species, the variance component of each trait was partitioned into taxonomic (clade, family, genus, species), environmental (region), and residual factors by using residual maximum likelihood procedures (Watanabe et al. 2007; Wang et al. 2020). Due to clade's larger explanation in trait variation, one-way ANOVA with Games-Howell post-hoc comparisons were used to compare leaf anatomical traits across various clades.

In addition, generalized linear models (GLMs) were used to analyze the variation in leaf anatomical traits with environmental factors. The environmental factors include mean annual temperature, mean annual precipitation, aridity index, ultraviolet radiation, and soil total nitrogen content, which are the environmental limiting factors in the study area, and these factors were found to have a significant impact on the leaf traits in previous studies (Ren et al. 2021; Liu et al. 2023a). Then the effects of each environmental factor on leaf traits were calculated. Relationships among leaf traits in each plateau were analyzed using principal component analysis (PCA), and we extracted the λ value (Eigenvalue) and the explanation rate of the top three axes (λ > 1.00, total explanation rate > 79.0%). Moreover, we tested the Pearson’s correlation coefficient between the axis of PCA and the environmental factors. The statistical analyses were conducted using R 4.3.1. (R Development Core Team, 2016).

Results

Variations of leaf anatomical traits in the MP and TP

The ET, PT, and PST of TP were larger than that of MP (P < 0.05), while the ET/LT and MT/LT were conversely (Fig. 2). In addition, MT and ST did not significantly differ between MP and TP (P > 0.05, Fig. 2b, d). When considering abundant plant species, there were large coefficients of variation (CV) of leaf anatomical traits in the two plateaus (from 9.5 to 94.0%) (Figs. S1 and S2). The skewness and kurtosis values of most leaf anatomical traits were > 0 in the TP and MP.

Fig. 2
figure 2

Variations in leaf anatomical traits between the Mongolian Plateau (MP) and Qinghai-Tibet Plateau (TP). Panels are respectively leaf anatomical traits a ET: epidermal thickness (μm); b MT: mesophyll thickness (μm); c PT: palisade tissue thickness (μm); d ST: spongy tissue thickness (μm); e ET/LT: the ratio of epidermal thickness to leaf thickness; f MT/LT: the ratio of mesophyll thickness to leaf thickness; g PST: the ratio of palisade tissue thickness to spongy tissue thickness. Different letters indicate significant differences between the two plateaus (P < 0.05)

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In addition to the differences in leaf anatomical traits between MP and TP found in the overall comparison (Fig. 2), there were also great differences in leaf anatomical traits between the two plateaus within the same grassland type (Fig. S3). Specifically, plants of TP had larger PT than that of MP in the meadow and typical grassland, yet ET/LT was conversely (P < 0.05, Fig. S3). In the desert grassland, plant MT, MT/LT, and ST were smaller in the TP than in the MP (P < 0.05, Fig. S3). In addition, at the clade level, the asterids, rosids, and superasterids clades of TP had larger ET, MT, PT, and ST (P < 0.05, Fig. S4). However, the monocots clade of TP were all isophylloid plants with smaller ET and MT/LT than those of MP plants (P < 0.05, Fig. S5).

Phylogenic effects on the variation in leaf anatomical traits

Results of Blomberg's K statistic indicated that the phylogenetic information strongly influences leaf anatomical traits (K = 0.05–0.53, P < 0.05, Fig. 3). Phylogenetic signals were found to be significant for ET, MT, MT/LT, and PST in the TP, and for ET, MT, and ST in the MP (P < 0.05, Fig. 3). However, for ET/LT and PT, the phylogenetic signals were not significant both in the MP and TP. Moreover, leaf anatomical traits of TP had greater K values than those of MP (Fig. 3, K = 0.18–0.53 vs. 0.02–0.23). However, for leaf economic traits, only LN of the TP had significant phylogenetic signals (K = 0.29, P < 0.01) (Table S3).

Fig. 3
figure 3

Phylogenetic tree and phylogenetic signal K-value of the plants in the Mongolian Plateau (MP) and Qinghai-Tibet Plateau (TP). Branch colors in phylogeny represent different clades. K-value (Blomberg’s K value) indicates the phylogenetic signal for the leaf anatomical traits. ET: epidermal thickness (μm); MT: mesophyll thickness (μm); PT: palisade tissue thickness (μm); ST: spongy tissue thickness (μm); ET/LT: the ratio of epidermal thickness to leaf thickness; MT/LT: the ratio of mesophyll thickness to leaf thickness; PST: the ratio of palisade tissue thickness to spongy tissue thickness

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The results of nested ANOVA revealed that leaf anatomical traits were strongly influenced by phylogenetic taxonomy (including clade, family, and genus), while were weakly influenced by regional differences (Fig. 4). For the leaf anatomical traits, MT and ET, related to photosynthesis and defensive functions, clade information supported higher variance explanation in the TP compared with in the MP (average 59.9% vs. 39.3%, Fig. 4). In addition, the oldest genus was found in the TP, while the most recently evolved plants were found in the MP (Table S2).

Fig. 4
figure 4

Variance component analysis of leaf anatomical traits into phylogenetic and environmental factors in the a Mongolian Plateau (MP) and b Qinghai-Tibet Plateau (TP). ET: epidermal thickness (μm); MT: mesophyll thickness (μm); PT: palisade tissue thickness (μm); ST: spongy tissue thickness (μm); ET/LT: the ratio of epidermal thickness to leaf thickness; MT/LT: the ratio of mesophyll thickness to leaf thickness; PST: the ratio of palisade tissue thickness to spongy tissue thickness

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Effect of environmental factors on the variation in leaf anatomical traits

Similar to the results of nested ANOVA, GLMs analyses revealed that leaf anatomical traits were less influenced by the environmental factors (Fig. S6). Especially, in the TP, only ET was significantly positively related to AI but negatively to UV radiation (R2 = 0.03, P < 0.05). In the MP, AI was the main environmental factor driving the variation in leaf anatomical traits. MT, PT, and ST significantly increased with the increasing AI, but ET/LT significantly decreased (R2 = 0.02–0.03, P < 0.01). Moreover, PT increased significantly along with UV radiation. Compared to leaf anatomical traits, leaf economic traits showed more significant relationships with environmental factors (R2 = 0.16–0.39, P < 0.05, Table S3). According to the variation partition analysis results, AI and MAT were found to be the major factors driving the plant traits variation in the MP and TP, respectively (Fig. S7). When examining the trait variations within the same species across different environments, it was observed that smaller coefficient of variation values of PT and ST were showed in the TP than MP, i.e., for a single species, the environment of TP had little effect on photosynthetic anatomical traits (Fig. S8).

Relationship between leaf anatomical and economic traits

The first three principal components of the PCA on the trait data represent over 77% variation (Table S4). Both in the MP and TP, PCA1 was loaded with defensive functions (i.e., ET). Species vary along this axis from having low to high defensive capacity (thinner and thicker, respectively). PCA2 was dominated by anatomical traits associated with photosynthesis (i.e., MT). This axis captured differences in photosynthetic efficiency or structural characteristics among species. As for the economic traits related to the PCA3, there was not a complete consistency in the two plateaus. In the MP, PCA3 was primarily loaded with SLA, a key economic trait reflecting leaf growth rate and resource use efficiency. However, in the TP, PCA3 was loaded with LN, indicating differences in leaf allocation strategies (Fig. 5, Table S4). The defense-related, photosynthesis-related, and economic traits were selected from the three main axes of PCA. In addition, in the MP and TP, PCA1, PCA2, and PCA3 had negative relationships with environmental factors (Fig. S9).

Fig. 5
figure 5

Results of principal components analysis (PCA) for leaf traits in the a Mongolian Plateau (MP) and b Qinghai-Tibet Plateau (TP). ET: epidermal thickness (μm); MT: mesophyll thickness (μm); PT: palisade tissue thickness (μm); ST: spongy tissue thickness (μm); ET/LT: the ratio of epidermal thickness to leaf thickness; MT/LT: the ratio of mesophyll thickness to leaf thickness; PST: the ratio of palisade tissue thickness to spongy tissue thickness; SLA: Specific leaf area (cm2 g−1), LN: leaf nitrogen content (%)

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Discussion

More conservative leaf anatomical traits in the TP than MP

We systematically analyzed the variation in leaf anatomical and economic traits and the multidimensional relationships among these traits under different stressful environments. Our results strongly support hypothesis 1, showing that the leaf anatomy of TP is more conservative than that of MP, and that ET, PT, and PST were higher, while ET/LT and MT/LT were lower in the TP (Fig. 2). Regional environments strongly influenced the characteristics of plant traits (de la Riva et al. 2017; Bernado et al. 2021). Previous studies found that herbs (i.e., Byrsonima verbascifolia (L.)) had small leaf anatomical trait values under warm and humid environment (Kuster et al. 2016). In our study, herbs growing in the water-limited MP areas displayed greater ET and MT values compared to those in regions with MAP exceeding 1000 mm (Tian et al. 2016). Notably, larger leaf anatomical trait values, such as ST, indicated higher water retention ability by increasing moisture diffusion resistance and distance (Chen et al. 2015; Amaral et al. 2021). Additionally, a thicker PT suggested a higher photosynthetic capacity and increased the accumulation of photosynthetic products (Chen et al. 2015; He et al. 2018).

In the extreme conditions of the TP, where low temperatures significantly limit plant growth (Ma et al. 2012), the thick anatomical traits enable plants to adopt resource-conservative strategies to cope with these environmental stresses. This is consistent with observations in other extreme environments, where plants exhibit strong vitality and special adaptability. For example, Rhodiola rosea was extremely thick in leaf structure with scaly leaves and large cell volume (Golovko et al. 2008). The thick structure increasing the well-developed ventilation tissue can make up for the deficit of CO2 in the atmosphere, and a thicker blade and epidermis can lessen the temperature range between the leaf internal and external spaces for keeping leaf temperature stable (Ma et al. 2012). These conservative characteristics were similar to the results in previous studies, more resource-conservative strategies were selected rather than resource-acquisitive strategies under stress conditions (Carvajal et al. 2017; Wang et al. 2018).

Additionally, when comparing the trait variation between the MP and TP in a grassland type, we observed that meadow and typical grassland species in the TP exhibited more conservative leaf anatomical traits than those in the MP (Fig. S3). However, there was an opposite result in the desert grassland (Fig. S3b, d). Similarly, in the monocots clade, plants with thin structures in the TP showed a strategy for quick returns on investments (Figs. S4, S5). These results might be related to the species differences, primarily due to variations in genetic features. For example, the main species in the desert grassland and Monocots clade of TP are isophyllous plants with thin leaf structure, but their slender leaf characteristics epidermis can adapt to stressful environment in morphology (Baird et al. 2021). In addition, researchers found that Stipa purpurea, native to the northern TP, optimized its gene expression for epidermis wax biosynthetic pathway, subsequently enhancing the wax layer on the leaf epidermis to mitigate water loss (Yang et al. 2020). Taken together, the plants in the TP chose more conservative leaf anatomical traits than in the MP, which was the main result of an extremely low-temperature environment, but the differences in adaptation strategies among different species cannot be ignored.

More stronger phylogenetic conservatism and less environmental effects on leaf anatomical traits in the TP than MP

Consistent with the hypothesis 2, our findings indicated that most leaf anatomical traits showed stronger phylogenetic conservatism and a weaker relationship with environmental factors in the TP than MP. Although leaf anatomical traits had significant phylogenetic signals both in the MP and TP, the K values of anatomical traits in the TP were larger than those in the MP. Moreover, the plant traits of TP had more conserved phylogenetic signals than those found in tropical regions (Amaral et al. 2021). The K values in the TP closer to 1 and the greater variance explanation of phylogenetic information both indicated the more conservative trait characteristics in the TP (Figs. 3 and 4; Münkemüller et al. 2012; Wang et al. 2020). When tracing the evolutionary history of the TP region, the surface of TP uplift began in the Miocene (Spicer et al. 2021). The geographic isolation caused by heterogeneous orogenic activities and climatic oscillation might greatly impeded gene flow in species formation, thus the older plant clades of TP may be conservative in leaf traits (Table S2; Mosbrugger et al. 2018; Wu et al. 2022). Similarly, researchers demonstrated the basal species tended to be more conserved with conservative characteristics (Ding et al. 2020; Shi et al. 2022). However, the uplift of the MP occurred later than the main body of the TP (Ao et al. 2021). There were many recently differentiated plants and many C4 plants with evolutionary leaf structure in the MP (Table S2). Therefore, the occurrence and development of these recently diverged plants may explain the lower trait conservatism observed in the MP.

Environmental effects on leaf anatomical traits were weaker than phylogenetic effects (Figs. 4 and S5). Particularly, in the TP, our study only found a significant relationship between ET and environmental factors. However, in the MP, more leaf anatomical traits showed a significant relationship with environmental factors (Fig. S5). The degree of variation in these traits may be linked to the intensity of environmental stresses (Amaral et al. 2021; Stotz et al. 2021). Previous studies suggested trait plasticity would decrease in the extremely stressful conditions due to the high energy costs involved (Carvajal et al. 2019). In particular, altering leaf anatomical traits, such as adjusting the size and number of leaf cells, was more difficult compared to modifying physiological traits (Guo et al. 2017; Velikova et al. 2020; Stotz et al. 2021). However, a recent study found that plants would increase epidermal hardness or wilt bulliform cells to form curling leaves as an adaptation to high radiation and low precipitation (Iqbal et al. 2022). Thus, modifying epidermal traits (e.g., ET), rather than the inner leaf anatomical structures, appeared to be a more efficient and rapid response to extreme environments.

For moderately stressed environmental regions, the trait plasticity is higher than that of extreme stress, and the trait variability is also greater (Carvajal et al. 2019). In the MP, plant growth was mainly limited by water (Qin et al. 2018). MT, PT, and ST showed a decreasing trend with the increasing AI, while ET/LT was opposite. Therefore, high defensive trait (i.e., ET) and low photosynthetic traits (i.e., MT, PT and ST) were the plant survival strategies in the moderately stressed conditions. The thicker leaf structure suggested that plants preferred to adopt a conservative survival strategy in water-shortage conditions (Gonzalez-Paleo and Ravetta 2018; Liu et al. 2023a). In addition, the larger intraspecific variation of MP also reflected its more sensitive environmental response. In a word, we found different environmental regions showed various strategies in leaf anatomical traits, demonstrating more severe trait variation and more conservative strategies in the extreme environment. From MP to TP, as the available resources decreased, the variation in leaf anatomical traits decreased, and the conservation of traits increased.

Decoupled relationships between leaf anatomical and economic traits

Both in the MP and TP, leaf anatomical traits and leaf economic traits were uncoupled and divided into photosynthesis-related trait axis, defense-related trait axis, and economic trait axis, which partly supported our hypothesis 3. The decoupled relationships among these leaf functional traits can be explained from multiple perspectives, such as leaf structures, species evolution, and environment selections. First, the independent trait-trait pattern was related to a physical segregation within leaf structures. LN is a fundamental component of plant enzymes and chlorophyll and is thus regarded as a representative of plant photosynthesis capacity in most studies (Zhang et al. 2020). In addition, a proportion of LN was allocated to the cell wall and free compounds for defensive functions (Xu et al. 2022). It is often stated that there was a trade-off relationship between LN allocated to photosynthesis and that allocated to defensive functions (Xu et al. 2022). However, high defensive cost with low allocation of nitrogen content to the chloroplasts in leaves may occur under stressful environment (Onoda et al. 2017; Cui et al. 2020). Therefore, the different nitrogen allocation pattern in unfavorable habitats may obscure the linkage between total leaf nitrogen content and each component of leaf anatomical structure. In addition, the other leaf economic trait, SLA, referred to the ratio of leaf area to dry mass (Wright et al. 2004). The leaf dry matter content is mainly derived from cell walls and nonstructural carbohydrates, which are not uniformly distributed in the leaf anatomy. Therefore, a direct relationship between SLA and the individual components of leaf internal structure might be weak (Li et al. 2015; Liu et al. 2019).

Moreover, the lack of interdependence between these two groups of leaf traits could be attributed to their divergent evolutionary paths. For instance, the development of the Kranz structure in C4 plants to adapt to drought and low atmospheric CO2 conditions was an important revolution in the evolutionary history of leaf structure (Beerling 2005; Osborne et al. 2014). These plants had high growth capacity, high carbon dioxide utilization, and low water requirements, leading to their further expansion during the late Miocene and early Pleistocene (Osborne et al. 2014; Pardo and VanBuren 2021). Evolutionary history had a significant influence on leaf structure (Liu et al. 2023a), and the abundance of C4 plants (23.3% of the total number of plants) in our study reflected more changes in structural traits (Table S2). However, compared with anatomical traits, economic traits were weakly influenced by phylogenetic information (Table S3; Ren et al. 2021; Liu et al. 2023b), indicating that different major factors drive the changes in these two types of traits. Furthermore, the timing of divergence for the significant variations observed in leaf anatomical and economic traits was inconsistent (Beerling 2005; Osborne et al. 2014). When concerning the evolution of morphological traits, ecologists found that leaf size (or area) was related to the massive disappearance of gymnosperms and the rapid development of angiosperms during the Cretaceous period (Beerling 2005). Thus, the independence between anatomical and economic traits may be an imprint of their divergent evolutionary patterns.

Finally, the environmental background may also affect trait coordination. Under the favorable environment, such as the tropical regions with high temperatures and precipitation, the ratio of palisade tissue thickness and leaf thickness was positively correlated with LN (Harrison et al. 2021). Plants preferred to invest more in photosynthetic traits under adequate resource conditions, and the investment trend of plants was consistent with economic and structural traits (Coley 1983; Tian et al. 2016). Different from the previous studies, our study showed that leaf anatomical and economic traits decoupled in grasslands with different stressful environments. However, to our surprise, each dimension of leaf traits was not significantly influenced by the environments (Fig. S9). The absence of this trait relationship might be partly due to the multidimensional adaptation strategies under unfavorable habitats (Zhou et al. 2018; Liu et al. 2019). Multiple directions of trait variation optimized plant availability to limited resources (both in moderately and extremely stressful environments). The PCA1 was the anatomical traits related to photosynthesis. The PCA2 corresponded to a defensive trait (i.e., ET). Based on the results of leaf trait variation, ET would be more likely to change than other anatomical traits under stressful conditions, at the same time stressful environments lead to increased plant defensive function. The PCA3 corresponded to the leaf economic traits emerging from the necessity for plants to balance leaf persistence against plant growth potential (Wright et al. 2004). The orthogonality of these three axes indicated the asynchrony of their variation in response to environmental stress. The independent development of the three axes conferred more plant adaptive pathways to adjust their functioning to the local environment (Diaz et al. 2016), especially in resource-limited environments (Laughlin 2014). Therefore, multidimensional relationships serve as a more effective strategy for plant survival and development, particularly in these harsh habitats.

Conclusions

By comparing leaf anatomical traits from two different plateaus, we identified distinct strategies employed by plants under moderately and extremely stressful environments (i.e., MP and TP, respectively). We found that, in contrast with plants in the MP, more conservative strategies and higher phylogenetic conservatism in leaf anatomical traits were favored for plants in the TP. Furthermore, leaf anatomical and economic traits decoupled and were represented by three independent dimensions, including photosynthesis-, defense-related, and economic trait axes. These multidimensional adaptation strategies provided more possibilities for survival and development in resource-constrained environments. Overall, these results suggest that environmental stresses could exert the strong selective pressure in leaf anatomical traits, but do not necessarily affect the independent adaptation of leaf anatomical structure and economic traits. This is insightful for a holistic understanding of the adaptation and responses of leaf traits in stressful habitats to climatic change.

Availability of data and materials

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

MT:

Mesophyll thickness

PT:

Palisade tissue thickness

ST:

Spongy tissue thickness

PST:

Palisade-spongy tissue thickness ratio

ET:

Epidermal thickness

ET/LT:

Epiderm-leaf thickness ratio

MT/LT:

Mesophyll-leaf thickness ratio

SLA:

Specific leaf area

LN:

Leaf nitrogen content

MP:

Mongolian Plateau

TP:

Qinghai-Tibet Plateau

MD:

Meadow

TG:

Typical grassland

DG:

Desert grassland

MAT:

Mean annual temperature

AI:

Aridity index

UV:

Ultraviolet radiation

SN:

Soil total nitrogen content

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Acknowledgements

We thank the associate editor and the anonymous reviewers for their helpful remarks

Funding

This work was supported by the National Natural Science Foundation of China (No. 32271611), and the Qinling National Forest Ecosystem Research Station in 2020 financed by Ministry of Education of China.

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Authors and Affiliations

  1. College of Forestry, Northwest A&F University, 3 Taicheng Road, Yangling, 712100, Shaanxi, China

    Xinrui Liu, Xue Wang, Jiang Zhu, Xiaochun Wang, Kaixi Chen, Yanqi Yuan, Xue Yang, Weiyi Mo, Ruili Wang & Shuoxin Zhang

  2. Qinling National Forest Ecosystem Research Station, Yangling, 711600, Shaanxi, China

    Ruili Wang

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Contributions

Xinrui Liu, Xue Wang, Jiang Zhu, Xiaochun Wang and Weiyi Mo performed the fieldwork. Xinrui Liu, Xiaochun Wang, Kaixi Chen, Yanqi Yuan and Xue Yang performed the lab experiments. Xinrui Liu analyzed the data and wrote the manuscript. Ruili Wang and Shuoxin Zhang designed the research and revised the manuscript.

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Liu, X., Wang, X., Zhu, J. et al. Strong conservatism in leaf anatomical traits and their multidimensional relationships with leaf economic traits in grasslands under different stressful environments. Ecol Process 13, 71 (2024). https://doi.org/10.1186/s13717-024-00548-y

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