Lake Erhai (25°36′~25°58′ N, 100°06′~100°18′ E), located in Yunnan Province, China, is a faulted freshwater lake formed by crustal movement ( Figure 1 ). The lake covers an area of 252 km², with average annual temperatures of 15.1°C. It has distinct wet and dry seasons, but precipitation is unevenly distributed, with more than 85% occurring during the rainy season from May to October (approximately 870 mm). A total of 117 tributaries flow into Lake Erhai, with legally authorized maximum and minimum operating water levels of 1966.0 m and 1964.3 m, respectively (Gong et al., 2023). Under the combined influence of reduced precipitation and artificial regulation since 2004, the time lag between water level and precipitation in Lake Erhai has become longer, with longer time intervals between the highest and lowest water levels, consequently altering the inundation time in the lakeshore zone (Wen et al., 2021). Lake Erhai is an important ecological area in China, characterized by high plant diversity and coverage, and rich biodiversity. The Cangshan and Erhai Nature Reserves were upgraded to national nature reserve in 1993 (Wang et al., 2023).

This study conducted plant surveys and soil sampling along the lakeshore zone of Lake Erhai in the summer (mid-July) and winter (mid-December) of 2023. We selected 29 fixed sample sites based on their accessibility and the distinct, high coverage of dominant plant communities. Each site was vertically divided into three zones based on the number of days of submergence: supralittoral (1965.77m-1967.37m), eulittoral (1965.06m-1965.74m), and infralittoral (1964.30m-1965.06m). In 2023, the average number of flooding days was 0 in the supralittoral, 98 in the eulittoral, and 283 in the infralittoral ( Figure 1C ). Three parallel quadrats (1m×1m) were randomly set up in each zone, and plant name, height, coverage, biomass (fresh weight), and numbers were recorded within each quadrat. The geographical coordinates of each quadrat were recorded using a portable GPS locator and combined with spray paint and red string markers for reference.

After harvesting the aboveground biomass in the quadrats using a sickle, three soil cores (0-20 cm) were collected diagonally using a soil auger. The soil samples from each zone were thoroughly mixed to form a composite sample and transported back to the laboratory for physicochemical properties analysis. The relative elevation above the water surface in each zone was measured using a level instrument and combined with the water level recorded on the survey day to calculate the elevation of each zone (Shen et al., 2019).

The soil samples were divided into three sub-samples for different analyses. One sub-sample was used to determine soil water content (SW) using fresh soil; one sub-sample was refrigerated at 4°C to determine ammonium nitrogen (NH₄ ⁺-N) and nitrate nitrogen (NO₃ ⁻-N); and the other sub-sample was freeze-dried, grind, and preserved by passing it through a 0.149-mm nylon sieve to determine total phosphorus (TP), C/N ratio, total nitrogen (TN), soil organic matter (SOM), and pH.

SW was determined using the thermostat drying method: dried at 105°C for 24 hours. pH was measured using a pH meter in a mixture with a soil-water ratio of 1:2.5. NH₄ ⁺-N, NO₃ ⁻-N and TP were determined by UV/visible spectrophotometer (UV-1900i). TN (%) and C/N ratio were determined with an elemental analyzer (Vario Macro Cube, Germany). SOM was analyzed by the potassium dichromate volumetric method under externally heated conditions (Ji, 2005).

At the species level, the seasonal variation of the top 30 dominant species were calculated based on the ordering of importance values (IV). At the diversity level, assessed by Patrick index (R), Shannon-Wiener index (H), Simpson Index (D), Pielou Evenness index (E), and dominance index (λ). The equations for all indices were calculated as follows Equations 1–6:

where S is the total number of species (species richness) recorded in each zone and Pi represents the relative abundance of ith species in each zone.

Plant species niche breadth and littoral widths were calculated using the Levins method from package spaa. Meanwhile, Generalized Additive Models (GAMs) were constructed to understand the distribution ranges of plants, and to assess plant responses to elevation changes. GAMs are more flexible than generalized linear models, to explore nonlinear relationships between independent and dependent variables, and perform well in spatial prediction (Elith et al., 2006). GAMs were performed using the mgcv package, employing a Gaussian distribution and nonlinear fitting of species abundance and elevation through a smoothing function. The smoothing parameter was automatically selected by generalized cross validation (GCV), which obtained a low GCV value, indicating a good fit of the model (Guisan et al., 2002). The spaa and mgcv packages were both used for analysis in R (version 4.3.2).

Principal component analysis (PCA) was performed to assess correlations between components and identify the main components associated with littoral widths. PCA is an unsupervised method that identifies principal components capturing the maximum variance in the dataset without predefined explanatory variable relationships (Lever et al., 2017). Structural equation modeling (SEM) was employed to explore the relationships among flooding days, soil nutrients, SW, soil pH, plant diversity, plant parameters (R, biomass, coverage), and littoral widths. SEM is a multivariate statistical analysis method that allows for the simultaneous examination of both direct and indirect relationships among multiple observed variables, thereby revealing hidden structural patterns within complex systems. For SEM construction, we ensured the key assumptions of the linearity of relationships among variables and sufficient sample size were met. Model fitting was completed by removing the observed variables based on the modification indices and confirming that the key fit metrics met the thresholds.

All data tested for significance were assessed for variance homogeneity and normal distribution, and data satisfied with normal distribution were tested using the independent sample t-test; otherwise, the Mann-Whitney U-test was used. All significance tests for the data were conducted using IBM SPSS 27.0 software. PCA and mapping were performed using Origin2023b and ArcMap 10.8. SEM was constructed and analyzed using IBM SPSS Amos 28 software.

A total of 110 species belonging to 40 families and 82 genera were recorded in the summer, with the highest species richness in the order of Poaceae (N=23, 20.9%), Asteraceae (N=16, 14.5%), Polygonaceae (N=7, 6.4%), and Cyperaceae (N=6, 5.5%). A total of 71 species belonging to 30 families and 58 genera were recorded in the winter, with the highest species richness in the order of Poaceae (N=18, 25.4%), Asteraceae (N=10, 14.1%), Polygonaceae (N=5, 7.0%), and Fabaceae (N=4, 5.6%). All species surveyed in this study were listed in Appendix 1 .

Compared to summer, the importance values (IV) of dominant species showed seasonal differences across the three zones during winter ( Figure 2 ). In the supralittoral, 7 dominant species showed an increase in IV, with Trifolium repens exhibiting the highest increase of 416.9%, while 10 species showed a decrease, with Cynodon dactylon exhibiting the highest decrease of 31.8%. In the eulittoral, 11 dominant species showed an increase in IV, with Alternanthera philoxeroides exhibiting the highest increase of 66.5%, while 13 species showed a decrease, with Ageratina adenophora exhibiting the highest decrease of 62.3%. In the infralittoral, both increased and decreased in IV were 11 dominant species, with Phragmites karka exhibiting the highest increase of 100% and Phragmites australis exhibiting the highest decrease of 40.2%.

Compared to summer, the diversity indices showed seasonal differences across the three zones during winter ( Figure 3 ). Specifically, in the supralittoral, the Evenness index increased significantly by 31.0%. In the eulittoral, the Dominance index and Evenness index increased significantly by 46.3% and 64.5%, respectively, while the Simpson index, Shannon-Wiener index, and species richness decreased significantly by 48.3%, 56.8%, and 67.3%. In the infralittoral, the Shannon-Wiener index and species richness decreased significantly by 40.4% and 50.8%, respectively, while the Evenness index increased significantly by 43.0%. In summary, seasonal differences in diversity indices were most significant in the eulittoral, followed by the infralittoral and supralittoral.

The biomass did not differ seasonally in the supralittoral and infralittoral, but increased significantly by 85.9% in the eulittoral. The coverage did not differ seasonally in the supralittoral and eulittoral, but decreased significantly by 40.1% in the infralittoral.

Seasonal comparisons of niche breadths showed significant differences among species ( Figure 4A ). The niche breadth of Alternanthera philoxeroides was largest in summer (21.39), but only 9.39 (decreased by 56.1%) in winter. This significant decrease indicates that rising water levels may be limiting the habitat of this species, affecting its dispersal and competitive ability. Similarly, other perennial herbaceous plants with high niche breadths in summer and significant decreases in winter include Cynodon dactylon, Phragmites australis, Urtica fissa, and Epilobium hirsutum. However, there was no significant seasonal difference in the niche breadth of the helophytes Zizania latifolia. This indicates that the habitat of this species is not limited by changes in water level and that it has strong adaptability. In summary, the mean niche breadth for perennial plants was 5.45 in the summer and 3.03 in the winter, showing a significant decrease of 44.4%. Most annual plants, such as Solanum nigrum, Polypogon fugax, and Rorippa palustris, showed a 100% decrease in niche breadth during winter.

There were no significant seasonal differences in littoral widths between the supralittoral and infralittoral ( Figure 4B ), suggesting that species composition and habitat conditions are relatively stable in both zones. However, the eulittoral exhibited a significant decrease in littoral width of 48.6% during winter ( Figure 4B ), probably caused by rising water levels that narrowed the habitat range in this zone.

The GAMs fitting was successful for the six dominant species (all P < 0.01, Table 1 ; Figure 5 ), exhibiting different elevation response curves. The response curves of Alternanthera philoxeroides and Leersia hexandra decreased with increasing elevation. Conversely, the response curve of Cynodon dactylon increased with increasing elevation. One species (Zizania latifolia) exhibited a monotonically decreasing response curve. Two species (Phragmites australis and Ageratina adenophora) exhibited symmetrical unimodal response curves.

There were significant seasonal changes in soil physico-chemical properties, but the differences varied across zones during winter ( Figure 6 ). Specifically, in the supralittoral, SW, NO₃ ⁻-N, and the C/N ratio increased significantly, while pH and TN decreased significantly, and there were no significant differences in NH₄ ⁺-N, SOM, and TP. In the eulittoral, SW, NO₃ ⁻-N, and the C/N ratio increased significantly, while pH, TP, and TN decreased significantly, and there were no significant differences in NH₄ ⁺-N and SOM. In the infralittoral, SW and NH₄ ⁺-N increased significantly, while pH decreased significantly, and there were no significant differences in NO₃ ⁻-N, SOM, TP, TN, and the C/N ratio. In summary, the seasonal differences in soil physico-chemical properties were most significant in the eulittoral, followed by the supralittoral and infralittoral. SW and pH exhibited significant seasonal differences in all three zones.

Principal component analysis determined the relationship among littoral widths, soil physico-chemical properties, flooding days, plant diversity index, coverage, and biomass ( Figure 7 ). The analysis results showed that the eigenvalues of the first principal component (PC1) and the second principal component (PC2) were 4.60 and 3.21, respectively, explaining 27.0% and 18.9% of the total variability. The eigenvectors of the PC1 in descending order were Shannon-Wiener index (0.43), Simpson index (0.41), species richness (0.40), TP (0.14), TN (0.10), and SOM (0.08), all of which were positively correlated with littoral widths. The eigenvectors of the PC2 in descending order were SW (0.46), FD (0.32), biomass (0.25), E (0.23), and NH₄ ⁺-N (0.15), all of which were negatively correlated with littoral widths.

Structural equation modeling path analyses revealed significant correlations among hydrology, soil, and plant variables, and that each variable was closely related to changes in littoral widths ( Figure 8 ). The flooding days (FD) had a significant positive correlation with soil water content (SW) and pH, indicating that higher FD increased SW and regulated soil pH. FD had a significant negative correlation with plant parameters, indicating that changes in FD may have an important impact on plant productivity, coverage, and species richness. Moreover, plant parameters showed a significant positive correlation with plant diversity. Both soil nutrients and plant diversity exhibited a significant positive correlation with littoral widths, while FD, SW, pH, and plant parameters had no significant impact on littoral widths. In summary, FD directly affects soil (SW and pH) and plant parameters, while littoral widths were directly affected by soil nutrients and plant diversity.

Hydrological gradient changes directly determine the composition and range of plant communities across different elevations in the lakeshore zone (Holmquist et al., 2021; Zheng et al., 2019). We found that the importance values of hydrophytes and helophytes increased in the eulittoral and infralittoral under high water levels, while mesophytes decreased ( Figure 2 ). This may be attributed to the frequent alternation of water levels in both zones, causing edge effects and changes in plant community structure and composition. Heterogeneity in lakeshore soil physicochemical properties under low-water conditions promoted microhabitat diversity, and hydrophytes and mesophytes coexisted by reducing direct competition (Zhang et al., 2022). A bigger challenge for these plants is to tolerate anoxic conditions in the substrate and supply oxygen to the roots during the high water. Hydrophytes and helophytes have well-developed root systems that efficiently absorb soil nutrients, allowing them to survive in flooded environments (Yang et al., 2024). Growth and biomass accumulation of the flood- and drought-tolerant invasive Alternanthera philoxeroides were promoted by adequate sunlight and water availability (Peng et al., 2021). This explains its increased importance value and biomass in the eulittoral ( Figures 2 , 3B ), with a mean biomass of 0.33 kg/m² in summer and 0.79 kg/m² in winter.

Significant seasonal differences were observed in diversity indices, biomass, and coverage in both the eulittoral and infralittoral, which are susceptible to water level fluctuations ( Figure 3 ). Longer flooding durations, as an abiotic stressor, inhibit the survival of flood-intolerant species, thereby reducing species richness and diversity (Casanova and Brock, 2000; Huang et al., 2021). Previous studies suggest that rising water levels regulate competition in eulittoral plant communities, favoring flood-tolerant plants and driving species homogenization (Garssen et al., 2017), which is consistent with our findings. Flood-adapted species occupy broader niches, and their increased relative abundance may enhance evenness (Altenfelder et al., 2016). Supralittoral plant communities maintain stable species composition and diversity, possibly because they are unaffected by flooding ( Figure 3A ).

Plants adjust their niche to optimize resource use (Carscadden et al., 2020), with niche breadth being positively correlated with their adaptability and tolerance to the environment (Costa et al., 2018). Wetland plants exhibit distinct adaptive strategies across hydrological gradients, with niche breadth variations reflecting species-specific hydrologic responses (Lou et al., 2018). In this study, the niche breadth of dominant species decreased in winter ( Figure 4A ), suggesting that rising water levels reduced their resource utilization capacity. The invasive Alternanthera philoxeroides exhibits the highest niche breadth, suggesting it is a generalist species. However, high water levels can inhibit its regeneration and dispersal (Zhang et al., 2024). Helophytes such as Zizania latifolia are distributed at lower elevations, and their niche breadths are almost unaffected by water level changes ( Figures 4A , 5 ). High seed production and dispersal capacity enable Cynodon dactylon to quickly colonize and expand in receding environments (Li et al., 2023). Therefore, rising water levels may narrow its niche breadth.

Littoral width determines plant survival space and resource utilization, and is significantly influenced by water level changes. Rising water levels inundate low-elevation zones, driving vegetation migration upland and reducing primary distribution ranges (Leyer, 2005). Declining water levels expand plant-growing space in the lakeshore zone, increasing habitat diversity and availability (Dai et al., 2019). Our results indicated that rising water levels significantly decreased the eulittoral width but had no effect on the infralittoral and supralittoral ( Figure 4B ).

Littoral width differences are explained by seasonal variations in flooding days ( Figure 1C ): (1) Eulittoral plants are highly sensitive to periodic flooding and exposure, and prolonged inundation leads to the disappearance of flood-intolerant species (Garssen et al., 2015; Ye et al., 2020), while combined low-temperature and flooding stress restricts growth and niche breadth. (2) The supralittoral at higher elevations is less sensitive to water level fluctuations, providing stable conditions for plant survival and growth. (3) The aerenchyma and specialized leaves of helophytes and floating plants facilitate survival in hypoxic and fluctuating aquatic environments (Björn et al., 2022; Chen et al., 2002; Venter et al., 2017). Stable niche breadths were maintained by infralittoral plants despite increased flooding days, with growth likely constrained by water nutrients, water exchange, and sunlight conditions (Jin et al., 2024; Wu et al., 2023).

Seasonal variations in flooding duration caused significant changes in plants, soils, and littoral widths in the lakeshore zone. We observed that plant diversity indices were positively correlated with littoral widths ( Figures 7 , 8 ), suggesting that higher plant diversity contributes to expanding niche breadth. Plant communities with high diversity reduce interspecific competition through niche differentiation, promoting efficient resource partitioning and enhancing community stability (McKane et al., 2002). Littoral width is a metric for predicting range size and is positively correlated with environmental tolerance breadth (Slatyer et al., 2013). A broader width indicates that plant communities can adapt to a wider range of environmental conditions, with high ecological resilience and competitiveness.

Subtle water level fluctuations alter wetland plant distribution and ecological processes (Liu et al., 2020; Qin et al., 2017), and similarly impact habitat conditions such as soil redox potential, microbial activity, and oxygen availability, which in turn influence plant growth and community composition (Hájek et al., 2013; Huang et al., 2023). Nutrient availability gradients alter plant diversity and productivity, influencing habitat ranges for different vegetation types (Zhang et al., 2022). For example, organic-rich soils foster aquatic plant growth (Silveira and Thomaz, 2015), while xerophytes dominate in low-nutrient soils (Fan et al., 2019). Therefore, flood duration influences littoral width by altering soil properties, plant diversity and niche breadth, and promoting plant community environmental adaptations.

Our results suggest that high water levels reduced the niche breadth of most dominant perennial plants and narrowed the eulittoral width, while littoral widths were positively correlated with plant diversity and soil nutrients. Based on our findings and management needs, we recommend: 1) Regulate water levels to stabilize eulittoral habitat and promote plant diversity; 2) Optimize plant community vertical structure across elevation gradients to maintain plant diversity under water level fluctuations; 3) Develop appropriate water level thresholds to avoid extreme drought-flood events that threaten lakeshore plants.