Hydrological conditions lead to asynchronised responses of alpine plant communities to temperature changes at the watershed scale

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Data may be preliminary. 9 January 2025 V1 Latest version Share on Hydrological conditions lead to asynchronised responses of alpine plant communities to temperature changes at the watershed scale Authors : Liyuan Ma , Wencong Lv , Jianqing Du 0009-0009-9409-2498 [email protected] , Qiang Liu , Yanbin Hao , Zhe Pang , Kui Wang , Youqing Yang , Zongsong Wang , Haishan Niu 0000-0001-5701-4487 , Xiaoyong Cui , and Yanfen Wang 0000-0001-5666-9289 Authors Info & Affiliations https://doi.org/10.22541/au.173640765.51202973/v1 Published Plant and Soil Version of record Peer review timeline 277 views 195 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Temperature and water are critical drivers of alpine plant communities. However, uncertainties persist regarding their combined effects, particular in alpine watersheds experiencing rapid changes in temperature and hydrological process over the past decades. In this study, we investigated how hydrological conditions mediate alpine plant communities’ response to temperature changes at the watershed scale. Our study showed that in water-deficient grasslands, an unimodal response of species richness (p < 0.05) and a linear decrease in coverage (p 0.05) were revealed with increasing temperature. These asynchronized changes in coverage and productivity are ascribed to plant adaptation to water stress. Plant communities shifted from low and dense cushions to taller and sparser vegetations, while dominant species changed from small and shallow-rooted species (Kobresia pygmaea) to large and deep-rooted (Potentilla bifurca) ones. In contrast, riverine wetlands showed no significant changes (p > 0.05) in community structure or productivity, likely due to their high hydrological connectivity that promoted propagule dispersal and soil environment homogenisation. Moreover, temperature and its mediated soil properties strongly influenced plant community structure in grasslands and transitional zones (R2 = 0.69 and 0.73 in Structural Equation Modeling, respectively) but not in wetlands (R2 = 0.25 in Structural Equation Modeling). This also indicates the prevailing of homogenization of habitat and species pool via strong hydrological dispersal in wetland community assembly. Overall, this study highlights that complex temperature-water interactions shape alpine plant communities at the watershed scale, which is unlikely to be understood from site-scale warming experiments focusing on a single vegetation. Future studies in these mountainous areas should consider the spatial heterogeneity induced by their complex vegetation types and hydrological conditions, while understanding the effects of intensifying stochastic processes on alpine ecosystems experiencing drastic hydrological changes. Hydrological conditions lead to asynchronised responses of alpine plant communities to temperature changes at the watershed scale Abstract Temperature and water are critical drivers of alpine plant communities. However, uncertainties persist regarding their combined effects, particular in alpine watersheds experiencing rapid changes in temperature and hydrological process over the past decades. In this study, we investigated how hydrological conditions mediate alpine plant communities’ response to temperature changes at the watershed scale. Our study showed that in water-deficient grasslands, an unimodal response of species richness ( p < 0.05) and a linear decrease in coverage ( p 0.05) were revealed with increasing temperature. These asynchronized changes in coverage and productivity are ascribed to plant adaptation to water stress. Plant communities shifted from low and dense cushions to taller and sparser vegetations, while dominant species changed from small and shallow-rooted species ( Kobresia pygmaea) to large and deep-rooted ( Potentilla bifurca ) ones. In contrast, riverine wetlands showed no significant changes ( p > 0.05) in community structure or productivity, likely due to their high hydrological connectivity that promoted propagule dispersal and soil environment homogenisation. Moreover, temperature and its mediated soil properties strongly influenced plant community structure in grasslands and transitional zones (R 2 = 0.69 and 0.73 in Structural Equation Modeling, respectively) but not in wetlands (R 2 = 0.25 in Structural Equation Modeling). This also indicates the prevailing of homogenization of habitat and species pool via strong hydrological dispersal in wetland community assembly. Overall, this study highlights that complex temperature-water interactions shape alpine plant communities at the watershed scale, which is unlikely to be understood from site-scale warming experiments focusing on a single vegetation. Future studies in these mountainous areas should consider the spatial heterogeneity induced by their complex vegetation types and hydrological conditions, while understanding the effects of intensifying stochastic processes on alpine ecosystems experiencing drastic hydrological changes. Keywords alpine ecosystem; plant adaptation; community assembly; hydrological conditions; global warming 1. Introduction Climate warming has profoundly affected alpine ecosystems’ community structure and function at multiple levels Dorji, et al. 2012Ma, et al. 2022Yasin, et al. 2022(, ). Manipulated experiments have shown that plant community responses to climate warming are closely linked to water availability Li, et al. 2018Xue, et al. 2015(, ). Under dry conditions, warming will likely induce water stress, restricting plant photosynthetic processes and reducing plant biomass Li, Peng, Xue, You, Lai, Zhang and Cheng 2018Zong, et al. 2013(, ). Conversely, warming can enhance vegetation height and net ecosystem photosynthesis under wet conditions, leading to higher primary productivity Feng, et al. 2023Li, et al. 2017(, ). However, the effects of warming on plant diversity remain controversial, varying with vegetation type and treatment duration. For example, warming has been shown to reduce species richness in the alpine steppe Wang, et al. 2022(). In contrast, it generally has minimal effects on alpine meadows and wetlands Chen, et al. 2020(). These findings underscore the crucial role of water availability in modulating plant community responses to temperature changes. Alpine ecosystems are sensitive to global warming Kuang and Jiao 2016() and generally have complex climatic and hydrological conditions with diverse vegetation types Lamprecht, et al. 2018Tague 2009(, ). Meanwhile, they are widely distributed in high-elevation mountainous regions, featuring a considerable elevation drop and establishing a natural temperature gradient from the headstream to downstream Auda, et al. 2023Huang, et al. 2024Zhou, et al. 2019(, ). Additionally, they also exhibited distinct spatial heterogeneity of water availability and hydrological processes owing to complex topography Fan, et al. 2019Philben, et al. 2020(, ), thus forming a natural water availability gradient from the uplands to the riparian zone Cavalli, et al. 2013Marston 2010(, ). Therefore, it is essential to understand how water and temperature jointly drive alpine ecosystem changes. However, previous studies regarding the effects of warming and changing precipitation were mainly conducted in grassland ecosystems at the local site scale Kwaku, et al. 2021Wang, et al. 2019Zhang, et al. 2017(, ). At the same time, many uncertainties remain unexplored at the watershed scale and limit the comprehensive understanding of alpine ecosystems’ responses to climate change. Previous watershed-scale studies mainly focus on elevation gradients Fernandez‐Conradi, et al. 2021Luo, et al. 2023Masviken, et al. 2020(, ), while rarely investigating how water mediates the effects of temperature on plant communities. For instance, although many studies found an unimodal biodiversity change along elevation gradients Wang, et al. 2013(), others also reported a monotonically decreasing species richness with increasing altitude Dani, et al. 2023(). Such inconsistent results are probably due to the complex interactions of water and temperature Dani, Divakar and Baniya 2023(). Additionally, plants’ responses to experimental warming were generally based on short-term studies; it remains to be explored whether plants exhibit adaptation to warming during long-term succession and whether such an adaptation varies according to water conditions. Moreover, intensifying hydrological activities in alpine watersheds could also build up habitat connectivity and facilitate propagule dispersal, thus mediating plant community structure in small watersheds Bejarano, et al. 2017Lee, et al. 2018Sander, et al. 2018(, ). Therefore, it is essential to understand how various hydrological conditions mediate the responses of alpine plant communities to temperature changes at the watershed scale. The Tibetan Plateau comprises numerous small watersheds Zhang 2019(), covering over 70% of the total watershed area and over 95% of the total watershed amount (Supplementary material, Figure S1). Therefore, this study was conducted in a representative small alpine watershed on the Tibetan Plateau (Niyaqu, Nam Co). Three long-term observation transects from 4,700 m to 5,300 m above sea level (a.s.l.) were established in the wetlands, transition zones, and grasslands to represent the water availability differences (wetlands also have high hydrological connectivity; Supplementary material, Figure S2). Specifically, we aimed to test the following assumptions: (1) increasing temperate imposes water stress on plant communities with limited water availability and leads to unimodal species richness pattern and decreasing productivity along elevation gradients, and (2) increasing temperate in wetlands may increase the productivity, while may not affect the community structure due to the high hydrological connectivity. 2. Materials and methods 2.1 Study area and sampling design The Niyaqu watershed, situated in the eastern part of the Nam Co Lake, has an area of approximately 400 km 2 and is one of the largest water sources for the lake Anslan, et al. 2020Zhang, et al. 2011(, ). The watershed has an elevation range of 4732-5703 m a.s.l. The climate in this region is cold and dry, with a mean annual temperature of -0.6 °C and mean annual precipitation of 406 mm, with more than 90% precipitation occurring from June to September Anslan, Azizi Rad, Buckel, Echeverria Galindo, Kai, Kang, Keys, Maurischat, Nieberding, Reinosch, Tang, Tran, Wang and Schwalb 2020(). The vegetation within the Niyaqu Watershed is primarily characterised by dwarf or cushion herbaceous plants that have adapted to the cold and arid climate, for instance, Kobresia pygmaea and Kobresia tibetica Maurischat, et al. 2022(). In the summer of 2019, six long-term observation sites were established along the elevation gradient from upstream to downstream along the Niyaqu River (Figure 1). Within each site, a 20 × 20 m long-term monitoring site was designated by selecting habitat-homogeneous areas perpendicular to the riverbank at wetlands (water-rich), grasslands (water-limited), and the areas in between (namely, the transition zone). In each site, five 50 × 50 cm sample plots were randomly allocated, with a 10 m separation between each other. Consequently, three transects were established to represent different water availability conditions, while each transect contains six sampling sites with changing elevations to represent the temperature gradient. We also used the “distm” function from the R packet geosphere v.1.5-14 Hijmans 2022() to calculate the straight-line distance of each sample from the water source of Niyaqu River, as well as the geographic distance between sample plots based on their GPS coordinates. 2.2 Vegetation survey During the peak growing season (mid-August) in 2019, a vegetation survey was conducted to record the species presence, abundance, plant height (averaged over three random measurements), and coverage of each sample plot. The sample plots’ latitude, longitude, and elevation were recorded using a handheld GPS (eTrex 10, Gramin, Swiss). The AGB for each sample plot was obtained by cutting and measured after constant-temperature drying at 68°C for 24 hrs. For plant diversity, we first counted all the species occurring in each sample plot at the family, genus, and species levels; then, we calculated species richness, Simpson’s diversity index, community coverage, above-ground biomass (AGB), and species’ importance value (IV) at the plot level: \begin{equation} \begin{matrix}\text{IV}_{p}=\frac{\left(Rh+Rc+Rd\right)}{3}\#\left(1\right)\\ \end{matrix}\nonumber \\ \end{equation} Where Rh, Rc, and Rd are relative height, relative coverage, and relative density, respectively, calculated at plot level. 2.3 Soil sampling and analyses After the vegetation survey, soil samples were collected using diagonal sampling with a soil auger (7.5 cm in diameter). Three cores were extracted from 0 to 10 cm depth (the major root layer) and mixed to form one sample within each plot. The collected soil samples were passed through a 2 mm soil sieve to eliminate gravel, roots, and other impurities, temporarily stored in an insulated box with ice packs, and then brought back to the laboratory and stored in a refrigerator at -20°C immediately after the end of sampling day. Soil water content (SWC) was determined by the dry weighing method, soil pH by the glass electrode method, soil total organic carbon (TOC) and total carbon (TC) by the potassium dichromate heating method, total nitrogen (TN) by the Kjeldahl method, ammonium nitrogen (NH 4 + -N) and nitrate nitrogen (NO 3 - -N) by the colourimetric method, total phosphorus (TP) and quick-acting phosphorus (AP) by the molybdenum antimony blue colourimetric method. 2.4 Data analyses Quadratic and linear regression models were used to identify the changes in plant biodiversity, coverage, and productivity along the temperature gradient. A two-way analysis of variance (ANOVA) was used to further analyse the effects of water (relatively low, moderate, and high availability as represented by the grassland, transition zone, and wetland groups, respectively) and temperature (relatively low, moderate, and high temperature as represented by upstream [5048–5333 m], midstream [4858–4905 m], and downstream [4735–4768 m] groups, respectively) on plant biodiversity, coverage, and productivity. The Tukey HSD (Honestly Significant Difference) was used for multiple comparisons. As for the plant community composition analyses, non-metric multidimensional scaling analysis (NMDS) based on Bray-Curtis distances was performed using the metaMDS function based on the R package vegan v.2.6-4 Oksanen, et al. 2022(), and the adonis2 function for PERMANOVA test in post hoc. Given that the vegetation here is very dense, we calculated the distance with IV p rather than relative abundance to lower the unreliability caused by large numerical differences Curtis and McIntosh 1951(). Further, the differences among communities were analysed using the index of community dissimilarity based on the Bray-Curtis distance with the Kruskal-Wallis test used for multiple comparisons. The distance decay of community similarity based on geographic distance was also performed. The Mantel test with Pearson’s correlation was used to analyse how environmental factors affect the community composition. The structural equation model (SEM) was constructed to separate each factor’s direct and indirect influences. The LinkET package was used to visualise the results of the Mantel test. In SEM, we constructed a composite variable: “Soil. Chem” using the “psem” function from the R package piecewiseSEM v.2.3.0 Lefcheck 2016(), while the co-linearity explanatory variables were eliminated at VIF > 10. Geographic distances were transformed using log(x+1). All data used in SEM were standardised using the Stdize function from the R package MuMin v.1.47.5. Other unspecified analyses were performed using R version 4.3.1 and visualised with ggplot2. 3. Results 3.1 Dominant family and species change Ninety-three species belonging to 26 families and 64 genera were found in the Niyaqu watershed. One-way ANOVA results revealed significant differences in the dominant families across water availability levels (i.e., wetlands, transition zones, and grasslands). Specifically, Gentianaceae were significantly more predominant in wetlands than in transition zones and grasslands, Rosaceae were significantly more dominant in transition zones than in wetlands and grasslands, whereas Gramineae were more dominant in grasslands (Table 1; Supplementary material, Figure S3). Similar results were also reported at the species level. The dominant wetland species was Kobresia tibetica (IV = 20.95%). In comparison, it transformed to Kobresia pygmaea (IV = 16.50%) in water-deficient grasslands, together with more drought-tolerant species such as Potentilla bifurca and Carex moorcroftii (Supplementary material, Table S1). These findings suggest a declining dominance of hygrophilous species as water availability decreases, with an increase of mesophytic and xerophytic plants capable of thriving under arid conditions. Along the elevation gradient, the dominant species of wetlands were always sedge. In contrast, a slightly rising dominance of forbs and grass was found in water-deficient grasslands from upstream to downstream (Supplementary material, Table S2). 3.2 Plant diversity and productivity change Regression analyses along the elevation gradient showed that plant diversity and productivity changes differed in wetlands, transition zones, and grasslands. In water-deficient grasslands, species richness showed an unimodal pattern ( p < 0.01, Figure 2a), coverage showed a liner decrease ( p 0.05, Figure 2d). In contrast, neither the plant diversity nor the productivity significantly changed in water-sufficient wetlands (all p > 0.05, Figure 2a-d). In water-moderate transition zones, community diversity and productivity followed a significant unimodal model, peaking at moderate elevations ( p < 0.01, Figure 2a-d). Similar results were also suggested by the two-way ANOVA analyses (Figure 3). Furthermore, in grasslands, our results identified a vegetation shift from low height (1.47 ± 0.15 cm）and high-density (876.80 ± 83.54 individual m -2 ) cushion to taller (2.26 ± 0.20 cm) and sparser (674.00 ± 125.45 individual m -2 ) grassland with decreasing elevation (Supplementary material, Table S3). Meanwhile, the dominant species shifted from perennial shallow-rooted plants with small individual but high density ( Kobresia pygmaea , IV = 51.63%) to deep-rooted, large individual and low-density species ( Potentilla bifurca , IV = 34.49%) (Figure 4a). 3.3 Community composition change The NMDS analysis revealed significant differences in plant community composition among water availability groups (type in Figure 4a: R 2 = 0.22, p < 0.001) and temperature groups (position in Figure 4a: R 2 = 0.16, p < 0.001). PERMANOVA tests on β diversity indicated that community dissimilarity was significantly lower in wetlands than in grasslands and transition zones ( p < 0.001, Figure 4b). Moreover, community dissimilarity also increased from upstream to downstream ( p < 0.001, Figure 4c), suggesting that the community dissimilarity across water availability levels was magnified by increasing temperature. Moreover, distance decay analysis indicated that plant community similarity declined at a progressively greater rate as water availability decreased (slope from -0.52 [wetlands] to -0.92 [grasslands]; Figure 5). Such results highlighted that the wetland’s plant community was more stable when facing temperature changes. 3.4 Influencing factors of community composition Mantel test showed that the main factors affecting community composition varied across water availability levels, and the effects of elevation strengthened with increasing water stress (Mantel’s r = 0.25, 0.52, and 0.55, in wetlands, transition zones, and grasslands, respectively; Figure 6). In water-deficient grasslands (Figure 6c), community composition was primarily influenced by elevation, soil TN, SOM, and pH (Mantel’s r > 0.3, p < 0.001), species richness was influenced by pH (Mantel’s r = 0.23, p < 0.01), and AGB was influenced by AP (Mantel’s r = 0.32, p < 0. 01) and NO 3 - -N (Mantel’s r = 0.27, p 0.3, p < 0.01) played essential roles in shaping community composition. In contrast, the community composition in wetlands was predominantly influenced by TK (Mantel’s r = 0.39, p < 0.001) in addition to elevation and SWC, whereas soil attributes did not significantly affect plant AGB (Figure 6a). The SEM further revealed that elevation and its mediation of soil attributes strongly affected the community composition of the relatively water-deficient grasslands and transition zones (R 2 = 0.69 and 0.73, respectively; Figure 7 b and c). However, these factors rarely affected the community composition of wetlands (R 2 = 0.25; Figure 7a), implying the prevailing stochastic processes in plant community assembly. 4. Discussion This study highlights that even adjacent alpine ecosystems may respond differently to temperature changes due to their different soil water availability at the small-watershed scale. Significant responses of plant community structure and productivity to temperature changes were only found in water-deficient ecosystems rather than in water-sufficient wetlands. Moreover, a shifting plant morphology and community structure characterise plant productivity in water-deficient grasslands adapted to rising temperatures. The underlying mechanisms of these phenomena are essential for comprehending how alpine watersheds respond and adapt to global warming; therefore, they are discussed as follows. 4.1 Water availability regulates the response of productivity to temperature changes Our findings indicated that water-sufficient communities could maintain their productivity in facing rising temperatures. This observation aligns with warming experiments conducted in alpine swamps and meadows, where increasing temperature generally does not alter plant productivity Chen, et al. 2021Ganjurjav, et al. 2022(, ). The main reason for this outcome is the adequate soil moisture in wetlands, which helps prevent the soil from drying as temperatures rise Xue, Peng, You, Xu and Dong 2015(). These findings suggest that water is the major limiting factor for productivity in alpine ecosystems. In water-deficient grasslands, a significant decrease in plant coverage instead of plant productivity was revealed along the elevation gradient, which is inconsistent with results based on warming experiments. Under experimental warming, increasing temperature could reduce soil water content, species richness, and the photosynthetic rate, consequently decreasing the primary productivity of plant communities Hasbagan Ganjurjav, et al. 2016Li, Peng, Xue, You, Lai, Zhang and Cheng 2018Li, et al. 2021(, ). We ascribe these different findings to plant adaptation to water stress, as observed in this study, which reflects ecosystem succession and generally takes much longer than the warming experiments could observe. In water-deficient grasslands, the plant community transformed from low and densely cushioned to taller and sparser vegetation as temperature increased, decreasing vegetation coverage. However, the dominant species shifted from small individuals with shallow roots to large ones with deep roots, which helps maintain plant productivity. Long-term experiments on the Tibetan Plateau also reported similar results that warming could increase grass abundance at the expense of sedges and forbs, leading to shifted plant biomass allocation belowground without affecting total net primary productivity (NPP) Alatalo, et al. 2021Ganjurjav, et al. 2018Liu, et al. 2018(, ). Differently, our study highlights that plant morphology shift and community change could also maintain the stability of AGB in response to warming. These findings underscore that ecosystem adaptations should be well considered in predicting the alpine ecosystem’s responses to global warming, particularly in long-term scenarios. 4.2 Hydrological connectivity may help maintain ecosystem stability in facing temperature changes Our findings revealed that temperature changes had much weaker effects on the water-sufficient wetland community structure than relatively water-deficient grasslands and transition zones. Furthermore, the explained variance in plant community composition of wetlands was also quite low (R 2 = 0.25 vs. R 2 = 0.73 in the transition zone and R 2 = 0.69 in the grassland), suggesting that stochastic processes such as propagule dispersal and habitat homogenisation of soil nutrients Chen, et al. 2022He, et al. 2022(, ) may largely contribute to the plant community assembly in alpine ecosystems with high hydrological connectivity. Similar results were also reported, such as a gradual decrease in community similarity away from the riverbank Flanagan, et al. 2015Zhu, et al. 2023(, ). Additionally, TK was the only soil nutrient affecting the composition of wetland plant communities; this is likely because potassium has very low movability in dry soil. However, high lateral hydrological and soil pore connectivity in wetlands could lead to a large amount of potassium loss and thus become a major limiting factor for plant growth Defterdarović, et al. 2023Yin, et al. 2020(, ). In contrast, plant diversity follows an unimodal pattern along the elevation gradient in water-deficient grasslands, with the highest diversity observed at intermediate elevations. These findings are consistent with the stress-gradient hypothesis, which suggests that moderate stress supports greater species coexistence Callaway, et al. 2002He, et al. 2013(, ). Moreover, multiple environmental factors strongly affected the grasslands’ community composition (e.g., temperature, SOM, TN, TK, etc.); this is because the complex topography of alpine grasslands generally forms high heterogeneity in microclimate and soil nutrients, thus resulting in a stronger association between plant community and environmental factors in grasslands than in flat and homogeneous wetlands Marsman, et al. 2020Marston 2010F. Peng, et al. 2020(, ). 4.3 Implications for alpine ecosystem changes under global warming This study highlighted the differential responses of various ecosystems to temperature changes within the alpine watershed. Notably, wetlands − characterised by the highest productivity − exhibited limited sensitivity to temperature changes regarding plant community structure and productivity; this suggests that the overall functioning of the alpine watershed may undergo less change under global warming than previously anticipated based on site-scale studies (mainly grasslands). Given that plant diversity, productivity, and ecosystem carbon sequestration in wetlands could maintain or even increase under global warming H. Ganjurjav, et al. 2016A. H. Peng, et al. 2020Qin, et al. 2023(, ), wetlands may offset the negative effects of warming on upland water-deficient grasslands, thereby promoting ecosystem stability at the watershed scale. Furthermore, previous studies revealed that wetlands can retain water and nutrients from melting glaciers and permafrost for their benefit while slowly releasing them to support downstream ecosystems in dry periods de Sosa, et al. 2018Kadykalo and Findlay 2016Yager, et al. 2021(, ). They may also serve as crucial areas for biodiversity maintenance in the context of climate change Mętrak, et al. 2023Wei, et al. 2019(, ). Nevertheless, compared to the well-established knowledge in grasslands, we lack a quantitative understanding of alpine wetlands’ role in sustaining ecosystem function and stability. Still, we also face significant deficiencies in the classification and mapping of alpine wetlands at the regional scale. Therefore, more attention should be devoted to these vital and unique alpine ecosystems to predict the trajectory of alpine watersheds under global climate change. 5. Conclusion This study unveils the intricate interactions between hydrological conditions and temperature drive plant community changes in alpine watersheds. Specifically, the adaptive adjustment of plant morphology and community structure to water stress and the homogenisation of habitat and species pool via hydrological dispersal may uphold watershed-scale ecosystem stability amidst global warming. Such watershed-scale compensatory effects among ecosystems are likely to be magnified in the future due to increasing hydrological connectivity caused by glacial retreat and permafrost thawing in alpine regions (Maurischat et al., 2022; Yu et al., 2023). Consequently, a comprehensive understanding and assessment of alpine watersheds’ responses to climate change are urgently needed, necessitating increased watershed-scale monitoring and comparative experimental studies across diverse ecosystems in the same alpine watershed. References Alatalo, J. M., et al. 2021. 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One-way ANOVA analyses for the differences of the top ten families among wetlands, transition zones, and grasslands. Wetland Transition Grassland Chenopodiaceae 0.00 ± 0.00 1.35 ± 0.43 1.16 ± 0.71 Compositae 3.10 ± 0.65 3.24 ± 0.92 4.06 ± 1.07 Cyperaceae 3.11 ± 0.18 3.51 ± 0.92 2.61 ± 0.29 Gentianaceae 2.12 ± 0.48 *** 1.08 ± 0.51 0.29 ± 0.29 Gramineae 2.54 ± 0.22 2.97 ± 0.51 4.93 ± 1.09 ** Labiatae 0.14 ± 0.14 0.81 ± 0.54 1.16 ± 0.54 Leguminosae 2.12 ± 0.29 1.62 ± 0.51 2.03 ± 0.74 Primulaceae 1.13 ± 0.18 0.27 ± 0.27 0.29 ± 0.29 Ranunculaceae 1.12 ± 0.28 0.81 ± 0.33 0.58 ± 0.35 Rosaceae 1.27 ± 0.48 4.32 ± 0.79 * 2.90 ± 0.65 Notes: Data showed are mean ± 1SE. ***: p < 0.001, **: p < 0.01, *: p < 0.05. Figure 2. Changes of the species richness (a), Simpson diversity (b), coverage (c), and above-ground biomass (AGB; d) along the elevation gradient. The R 2 represents the adjusted R 2 . Figure 3. Effects of temperature (by watershed location) and water availability (by vegetation types) on species richness (a), Simpson diversity (b), coverage (c), and above-ground biomass (AGB; d). The different uppercase letters indicate significant differences among watershed locations; NS: non-significant difference. Asterisks mark significant differences among vegetation types within a given watershed location. ***: p < 0.001; **: p < 0.01**; *: p < 0.05*. Figure 4. Non-metric multidimensional scaling (NMDS) analysis of plant community composition across different groups (a), PERMANOVA tests for the differences in community dissimilarity across vegetation types (b), and watershed locations (c). Different subplot letters b and c mark significant differences at p < 0.05 (Kruskal-Wallis test). Figure 5. Distance decay of the community similarity in wetlands (a), transition zones (b), and grasslands (c) along the Niyaqu River. The R 2 represents the adjusted R 2 . Figure 6. Mantel’s heatmap between environmental factors and plant attributes in wetlands (a), transition zones (b), and grasslands (c). Edge width and colour represent the Mantel’s r values and statistical significances, respectively. Pairwise Pearson correlations between environmental factors are presented with a colour gradient. Ele: elevation; TN: total nitrogen; TP: total phosphorus; TK: total potassium; SOM: soil organic matter; AP: available phosphorus; NO 3 - -N: nitrate nitrogen; NH 4 + -N: ammonium nitrogen; pH: soil pH; SWC: soil water content. Figure 7. Structural equation model (SEM) for the community similarity in wetlands (a), transition zones (b), and grasslands (c). Green and orange arrows indicate positive and negative effects, respectively. Solid and dotted lines indicate significant and non-significant effects, respectively. The width of the lines indicates the strength of the causal effect. The R 2 values represent the proportion of variance explained for each variable. Information & Authors Information Version history V1 Version 1 09 January 2025 Peer review timeline Published Plant and Soil Version of Record 17 Jun 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords alpine ecosystem community assembly global warming hydrological conditions plant adaptation Authors Affiliations Liyuan Ma University of the Chinese Academy of Sciences College of Resources and Environment View all articles by this author Wencong Lv University of the Chinese Academy of Sciences Sino-Danish college View all articles by this author Jianqing Du 0009-0009-9409-2498 [email protected] University of Chinese Academy of Sciences View all articles by this author Qiang Liu University of the Chinese Academy of Sciences College of Resources and Environment View all articles by this author Yanbin Hao University of the Chinese Academy of Sciences College of Life Sciences View all articles by this author Zhe Pang Northwest Institute of Plateau Biology Chinese Academy of Sciences View all articles by this author Kui Wang University of the Chinese Academy of Sciences College of Resources and Environment View all articles by this author Youqing Yang University of the Chinese Academy of Sciences College of Life Sciences View all articles by this author Zongsong Wang University of the Chinese Academy of Sciences College of Life Sciences View all articles by this author Haishan Niu 0000-0001-5701-4487 University of the Chinese Academy of Sciences College of Resources and Environment View all articles by this author Xiaoyong Cui University of Chinese Academy of Sciences View all articles by this author Yanfen Wang 0000-0001-5666-9289 University of the Chinese Academy of Sciences College of Resources and Environment View all articles by this author Metrics & Citations Metrics Article Usage 277 views 195 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Liyuan Ma, Wencong Lv, Jianqing Du, et al. 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