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Article

Disentangling the Interspecific and Intraspecific Variation in Functional Traits of Desert Plant Communities under Different Moisture Gradients

by
Li Sun
1,
Hengfang Wang
1,*,
Yan Cai
2,
Qi Yang
1,
Caijin Chen
1 and
Guanghui Lv
1,*
1
Key Laboratory of Oasis Ecology of Education Ministry, College of the Ecology and Environment, Xinjiang University, Urumqi 830046, China
2
Student Work Department, Tarim University, Aral 843300, China
*
Authors to whom correspondence should be addressed.
Forests 2022, 13(7), 1088; https://doi.org/10.3390/f13071088
Submission received: 23 May 2022 / Revised: 4 July 2022 / Accepted: 8 July 2022 / Published: 11 July 2022
(This article belongs to the Section Forest Ecophysiology and Biology)
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Abstract

:
Studying the inter- and intraspecific variation in plant functional traits elucidates their environmental adaptation strategies and the mechanisms of community construction. This study selected the desert plant community in the Lake Ebinur watershed as the research object and considered five different traits: plant height (H), diameter at breast height/base diameter (DBH/BD), leaf length (LL), leaf width (LW), and leaf thickness (LT). This study used redundancy and correlation analyses to investigate the inter- and intraspecies variation in community-level traits, its relationship with soil physicochemical factors under different soil moisture conditions, and their change laws. We also used variance decomposition to analyze the contribution of inter- and intraspecific variation to community weighting. The results showed the following: (1) the values of the plant community functional traits varied according to the water gradient, and the LL (p = 0.01) and DBH/BD (p = 0.038) varied significantly; (2) for intraspecific variation, the DBH/BD variation was high at a low moisture gradient, LL (p = 0.018) and LT (p = 0.030) variation were high at a high moisture gradient, and the differences were significant; (3) under a high moisture gradient, inter- and intraspecific variation contributed 85.8% and 35.7% to community weighting, respectively, whereas under low moisture gradients, inter- and intraspecific variation contributed 53.3% and 25.1%, respectively.

1. Introduction

The variation in plant functional traits refers to the changes experienced by plants due to the interaction between their genes and the external environment at different community organization levels and spatial scales. These variations are widespread in individual plants, within species, and between species and communities [1]. Domestic and foreign studies have shown that intraspecific variation accounts for 25%–54.4% of plant characteristic variation, and it even accounts for up to 90% in some special environments [2,3]. Intraspecific variation represents the maximum adaptability of plants along biological and abiotic gradients, which fundamentally determines the niche breadth of plants [4,5]. A limitation of the aforementioned research is that the response of species to environmental changes and resource competition at an intraspecific level during community construction can only be accurately reflected by combining intraspecific and interspecific trait variations [6,7,8]. The inclusion of intraspecific variation in a community study improves the sensitivity of nonrandom ecological process detection [9,10,11], more accurately reflects functional diversity [12,13], and makes it possible to more precisely decompose or integrate various community construction processes [14,15,16]. In addition to explaining the variation in community traits, intraspecific trait variation also considerably impacts community construction and ecosystem function [17,18].
For a long time, the research on plant functional traits focused on interspecific rather than intraspecific variation [19]. Jackson et al. argued that interspecific variation contributes more to community construction and that intraspecific variation can neither predict the changes in plant functional traits nor improve the accuracy of prediction [20]. However, growing evidence suggests that quantitative intraspecific variation is important for understanding functional traits at the community level and in ecological processes [21]. Albert et al. selected 13 common and perennial plants (shrubs, Gramineae plants, legumes, and hybrids) in their studies and found that 30% of functional trait variation originated from individual intraspecific differences [6] and that inter- and intraspecific functional trait variation was also substantial in different environments and communities. Laforest-Lapointe et al. found that intraspecific trait variation is an important factor determining whether plants can cope with climate change and other environmental factors, and the vegetation types included Aleppo pinewoods, alpine pastures, deciduous woodlands, 158 Mediterranean maquis, non-Mediterranean coniferous woodlands, and sclerophyllous woodlands 159 [22]. In China, He Yan, Yao Yuping, et al. studied the plant functional traits of a Cyclobalanopsis glauca community in the karst mountains of Guilin; the interspecific variation (59.48%) was higher than the intraspecific variation (34.61%) [23]. Although interspecific variation is the main source of plant functional trait variation, both types of variation should be considered when studying the response of plant functional traits to the environment. The combination of intra- and interspecific variation more accurately reflects the response of species to habitat changes and resource competition during community construction and how species diversity and ecosystem characteristics are maintained [11,24,25].
Soil is the foundation of vegetation growth and development. Without fertile soil, vegetation has difficulty surviving. The distribution of a soil environment acts as both abiotic and biological screening by changing competitive relationships, so the soil conditions may influence plant trait differentiation more than its resource supply level. Theoretically, the higher the soil heterogeneity, the higher the heterogeneity of plant traits, that is, the higher the functional diversity [26]. Soil moisture is a key factor in plant water uptake and utilization strategies [27], and it improves habitat suitability by affecting the internal environment of communities, forcing plants to perform phenotypic regulation [28]. Under variable soil moisture conditions, plants must quickly adjust the allocation of biomass among the specific leaf area, leaf thickness, and other traits, improving their adaptability to environmental spatial heterogeneity [29,30]. Alterations in the morphology of leaves can promote soil moisture uptake by plants [31]. Yang et al. studied the leaf traits of typical shrub plants in an arid area of northwest China. The results showed that in the gradient zone from southeast to northwest, the drought plants increased their water storage capacity by increasing leaf thickness, reducing water dissipation by reducing leaf area, and reducing the specific leaf area to improve resource utilization, which reflects the strategy of plants to adapt to environmental changes [32]. Therefore, research must consider water and soil physicochemical factors when studying inter- and intraspecific variation in plant leaf functional traits.
Research on interspecific and intraspecific trait variation has mainly focused on tropical or temperate forests, alpine meadows, and grasslands [33]. Few researchers have investigated inter- and intraspecific variation in plant functional traits and their responses to soil environmental changes in arid desert ecosystems [34]. Soil erosion is the most prominent problem and the focus of ecological restoration in arid areas. Appropriate scientific vegetation construction is the key to ecological restoration and healthy and sustainable development in this area [35]. In view of this, research must consider inter- and intraspecific variation when studying the functional trait variation of desert plants in arid areas to understand the significance of community construction and ecological processes. As such, this study chose the typical desert plant communities of the Ebinur Lake Basin as the research object and investigated (1) the inter- and intraspecific variation of plant community functional traits, their differences according to the water gradient, and their relationships with soil physicochemical factors and (2) the contribution of inter- and intraspecific variation to community weighting. We attempted to clarify the differences and correlations between the main functional traits of plant communities in the study area and explore the environmental adaptation strategies of desert plants so as to provide a scientific basis for the management and protection of desert plant diversity.

2. Materials and Methods

2.1. Overview of Experimental Area

The study area was Ebinur Lake Wetland National Nature Reserve (44°30′−45°09′ N, 82°36′−83°50′ E). The Aqikesu River is located on the east side of the lake area and supplies water to Ebinur Lake. The soil water, salt, and nutrient contents decrease from the Aqikesu River bank to the Kumtag Desert. [36]. The basin belongs to the continental climate of the north temperate zone. The climate substantially varies between the four seasons. Rainfall is scarce in the summer, and the winter is cold and dry. The average annual temperature is 7.8 °C, and the maximum temperature and minimum temperature can reach 41.3 °C and −36.4 °C. The average annual precipitation is 90.9 mm. Therefore, the surrounding area is vulnerable to wind and sand, and the ecological environment is very fragile [37,38]. The typical zonal soils in the region are ash desert soil, ash palm desert soil, and aeolian sand soil, while the hidden zone soils are salt (salinization) soil, meadow soil, and marsh soil [37]. The wide variety of habitat types in the study area has given rise to a wealth of desert plant community types. There are rich salt-tolerant and drought-tolerant plants, as well as sandy, mesophyte, hygrophyte, and aquatic plants. There are more woody plants and herbaceous plants. The main plant species are Populus euphratica, Haloxylon ammodendron, Tamarix chinensis, Halostachys caspica, Kalidium foliatum, Reaumuria songonica, and Alhagi sparsifolia [38].

2.2. Research Methods

2.2.1. Sample Setting

A large sample area with a width of 30 m and a length of 3600 m in a vertical direction from the Aqikesu River to the Kumtag Desert was established in July 2018. A 30 m × 30 m plot (60 squares in total) was placed at the center of the sample area for the plant community characteristics survey and sample collection (Figure 1).

2.2.2. Collection of Soil Samples

During the peak period of plant growth in July 2018, within the determined standard quadrat, we selected soil sampling points in the standard quadrat using the diagonal sampling method (two diagonal intersection points and two diagonal vertexes as sampling points of the soil) and extracted 3 portions of 0–10 cm soil (3 replicates) from each quadrat. First, we collected the soil sample in an aluminum box (weighed in advance), numbered the sample, and determined the fresh soil weight. The soil sample was taken back to the laboratory, the soil was dried in the aluminum box in an oven until it reached a constant weight, and the dried soil and the aluminum box were weighed to calculate the soil moisture content. We collected another soil sample weighing about 500 g at the same point in the same square and put it into a sealed bag. After natural air drying, we determined other indicators, such as soil water content (SWC), soil salt content (SSC), soil pH, soil organic carbon (SOC), total phosphorus (TP), and total nitrogen (TN) (Table 1) [39,40].

2.2.3. Collection of Plant Samples

This study investigated and recorded the characteristics of the trees in each 30 × 30 m quadrat. This study selected two 5 × 5 m quadrats along the diagonal to investigate shrub characteristics and three 1 × 1 m quadrats on both diagonals of the tree quadrats to investigate herb characteristics. We recorded the species name, abundance, maximum plant height, and crown width of tree species; the species name, number, plant height, and crown width of shrub and herb plants; and the longitude and latitude of each quadrat. We selected five healthy leaves of the species in each quadrat and measured the leaf length, leaf width, leaf thickness, and diameter at breast height/base diameter with a vernier caliper.

2.3. Data Processing and Analysis

2.3.1. Division of Different Soil Moisture Gradients

In this study, the sample area was perpendicular to the Aqikesu River, and a natural water gradient was formed. Vertical to the river from near to far, the soil moisture decreased gradually. Due to the loss of sampling data, 52 samples were divided into two moisture gradients by cluster analysis on the basis of excluding 8 samples, namely high moisture gradient and low moisture gradient (Table 2).

2.3.2. Calculation of CWM

In this study, community functional traits (H, DBH/BD, LL, LW, and LT) and their interspecific and intraspecific variation at the community level were assessed using the community-weighted mean (CWM), which is determined by the relative abundance of species and their traits, represented by the formula [41]:
CWM = ∑ i = 1 s P i t i
where Pi is the relative abundance of species i, ti is the character of species i, and S is the number of species in the sample.
Following Lepš’s method, this study determined the CWM of the above traits by the intra-and interspecific variation. We calculated the interspecific variation, CWMF, by the average trait value and relative abundance of species in all quadrats between the two water gradients. The CWMF is a community-weighted trait only affected by interspecific variation. This study determined intraspecific variation, CWMI, by calculating the difference between the CWM and CWMF [42].

2.3.3. Data Analysis

We used an independent-samples t-test to analyze the inter- and intraspecific variation among different soil moisture gradients and single-factor analysis of variance (one-way ANOVA) to evaluate the plant trait and soil physicochemical factor variation according to the water gradient. For multiple comparisons, we used the least significant difference (LSD). We conducted the above analyses using SPSS 26.0 (IBM, New York, NY, USA) and produced graphics in Origin 2022. To study the relationship between the inter- and intraspecific variation in plant traits and soil factors, we implemented Pearson correlation analysis and redundancy degree analysis (RDA). We completed the correlation matrix diagram using the ‘corrplot()’ function in the corrplot package of R4.1.3 [43] and the redundant analysis diagram using Canoco5.0 (Copyright Petr Šmilauer 2012–2021). This study used the variance decomposition of the ‘varpart()’ function in the vegan package of R4.3.1 to calculate the weighted contribution rate of interspecific and intraspecific variation to the community [44] and visualized the contribution rate via a Wayne diagram.

3. Results and Analysis

3.1. Difference Analysis of Soil Factors and Plant Functional Traits under Different Water Gradients

Figure 2 shows that the H, DBH/BD, LL, LW, and LT of plant communities under a high moisture gradient were higher than those under a low moisture gradient, especially the LL (p = 0.01) and DBH/BD (p = 0.038). Although the soil pH (p = 0.863) did not significantly change according to the water gradient, the difference between the high and low moisture gradients was significant for other soil physicochemical factors, including SOC (p < 0.01), SSC (p < 0.01), TP (p = 0.036), and TN (p < 0.01).

3.2. Inter- and Intraspecific Variation in Plant Traits and Their Differences According to Water Gradient

The variation in traits between species and within species differed according to the water gradient (Table 3). The variation in LL, DBH/BD, H, LW, and LT was more substantial under a high moisture gradient, especially for LL (p = 0.014) and LT (p = 0.046). For intraspecific variation, DBH/BD variation was high at a low moisture gradient, LL (p = 0.018) and LT (p = 0.030) variation was high at a high moisture gradient, and the differences were significant. This study ranked the functional traits according to the extent of interspecific and intraspecific variation under different water gradients as follows: LL > DBH/BD > LW > H > LT.

3.3. Relationship between Inter- and Intraspecific Variation in Plant Functional Traits and Soil Physicochemical Factors

The RDA results are shown in Table 4 and Figure 3. Under a high moisture content, the first axis explained 66.08% of the relationship between soil physicochemical factors and plant functional traits, and the second axis explained 96.19%. The highest correlation in the first axis was between TN and SWC, and the highest correlation in the second axis was between salinity, pH, and SOC. Under a low moisture content, the first axis explained 97.43% of the relationship between soil physicochemical factors and plant functional traits, and the second axis explained 99.19%. The highest correlation on the first axis was between TN and pH, and the highest correlation on the second axis was between SSC and TP. The first axis mainly reflected the effect of TN, SWC, and pH on the interspecific and intraspecific variation of plant functional traits under different water conditions, while the second axis mainly reflected the effect of TP and SSC. Thus, soil pH, TP, SSC, and TN affected the inter- and intraspecific variation of plants under different water gradients.
Table 4 and Figure 3 and Figure 4 illustrate that under different water gradients, the trait variation responses to soil physicochemical factors substantially differed, indicating that the environmental effects on each functional trait varied. Under high water content, the interspecific variation in plant traits, such as H, LL, and LW, were generally positively correlated with soil environmental factors, and the correlations between SSC and H (r = 0.42), DBH/BD (r = 0.42), LW (r = 0.33), and LT (r = 0.30) were the strongest. For intraspecific variation, most soil physicochemical factors except TP had a strong negative correlation with LT. SOC and TN were positively correlated with LW, and H (r = 0.42), LL (r = 0.37), and LW (r = 0.55) were positively correlated with TN.
Under a low water content, the correlation between inter- and intraspecific variation in plant functional traits and soil physicochemical factors was generally stronger than that under a high water content. For interspecific trait variation, soil physicochemical factors were positively correlated with H, DBH/BD, and LT. We found a strong positive correlation between TN and H (r = 0.42), DBH/BD (r = 0.31), LW (r = 0.32), and LT (r = 0.41). For intraspecific variation, this study found a negative correlation between soil physicochemical factors and plant functional traits, particularly LT, H, and DBH/BD. The inter- and intraspecific variation in other functional traits had a weak correlation with soil physicochemical factors.

3.4. Contribution of Inter- and Intraspecific Variation to Community Weighting

Figure 5 shows that interspecific variation contributed 85.8% to community weighting under a high water content, while intraspecific variation contributed 35.7%. Under a low water content, interspecific and intraspecific variation contributed 53.3% and 25.1%, respectively. Thus, the weighting of community traits had a substantial impact on interspecific variation in both high- and low-water environments. In addition, the inter- and intraspecific variation according to soil water content considerably contributed to the community weighting, and the residual was less than 50%. However, we observed a negative covariance between inter- and intraspecific variation when they jointly contributed to the community weighting, which indicated that the total community-weighted variation was less than the sum of the inter-and intraspecific variation. Hence, intra- and interspecific variation had opposite effects, meaning that some dominant species in this study had functional traits that did not vary along the soil environmental gradient. Although the contribution of intraspecific variation to community variation was lower than that of interspecific variation, intraspecific variation cannot be ignored.

4. Discussion

4.1. Analysis of Inter- and Intraspecific Variation in Plant Functional Traits and Response to Community Construction

Intra- and interspecific plant functional trait variation has substantial ecological importance for community construction [18]. The habitat of the study area is harsh, and the community composition is simple. Most plants have strong salt resistance and drought resistance. The variability of herbaceous plants is greater than that of woody plants at the community level. This shows that herbaceous plants are more affected by spatial variability and more sensitive to environmental factors [36]. In this study, the effects of soil physical and chemical factors on the variation of plant functional traits under different water gradients were compared. The results showed that leaf length, leaf width, and leaf thickness had different degrees of variation to adapt to soil physical and chemical factors. The reason for this situation is likely the same as that proposed by Lichstein and other scholars: the changes in leaf-related traits (leaf length, leaf width, leaf area, etc.) reflected the nutrient utilization strategies formed by plants to adapt to the changes in soil factors. The growth strategies of plants and the ability of plants to utilize resources can be studied by plant leaf traits [45,46,47]. Reich et al. proved that plants with low specific leaf area can better adapt to a poor and arid environment [48]. Similarly, in this study, the leaf length, leaf width, and leaf thickness of interspecific and intraspecific variation decreased with the decrease in water content, which greatly reduced the specific leaf area and led to better adaptation to the drought environment. Some experts argued that in order to achieve maximum survival, the plasticity of leaf area and specific leaf area should be increased to cope with the limitation of light resources and soil nutrients in the community [49]. In this study, the variation in leaf length, leaf width, and leaf thickness with the direction of the water gradient also confirmed this result. There is a common phenomenon in this study area: Haloxylon ammodendron grows well in areas with a high soil water content, and its value in the community is high, as it is a constructive species of the desert community; by contrast, Haloxylon ammodendron is not a constructive species of desert communities because of its poor growth and low importance in communities in areas with low soil moisture [50]. This study also confirmed that the adaptation strategies of dominant species in this study area had intraspecific variation at different water gradients.

4.2. Effects of Soil Environment on Inter- and Intraspecific Variation in Community Functional Traits

Soil physicochemical factors directly affect the variation in plant functional traits. Analyzing the relationship between plant functional trait variation and soil physicochemical factors under different water gradients provides a theoretical basis and reference for predicting plant adaptation strategies under environmental changes. The change om soil water has different degrees of influence on the functional traits of the desert plant community in Ebinur Lake. Plant height is one of the most intuitive phenotypic characteristics of plants. Studies have shown that the phenotypic changes in response to non-climate factors (such as soil properties) at small spatial scales are more obvious [51]. This study demonstrated that the variation in plant functional traits under different water gradients considerably differed according to soil physicochemical factors. For example, under a high water content, both interspecific variation and intraspecific variation were generally positively correlated with soil physicochemical factors, but under a low water content, only interspecific variation was positively correlated with soil physicochemical factors, and intraspecific variation was mostly negatively correlated. This substantiates Jackson’s view that the intraspecific variation in plant function is an important response of plant communities to environmental factors, such as soil fertility [20]. The differences in plant functional traits organically link species’ adaptation strategies with the functions and processes of the community ecosystem; their variation varies from species to species and is closely related to environmental gradients [52,53]. In this study, different water gradients had different effects on the variation in plant functional traits, among which the contents of water, salt, and total phosphorus had the greatest effects on interspecific and intraspecific variation. It is well-known that the availability of nitrogen and phosphorus in soil is the main factor affecting plant growth and development [54]. In the same study, nitrogen and phosphorus in soil were the main factors affecting the variation of traits. This may be related to the growth and development of dominant species along the environmental gradient by adjusting the plasticity of functional traits in order to adapt to more complex environmental conditions. He D. showed that the variation degree of species traits was not related to soil moisture, organic carbon, or available phosphorus content [55]. However, in our study, soil pH, total phosphorus, salt content, total nitrogen, and organic carbon all affected the variation in plant traits to differing degrees. The reason for this may be that He D.’s study area had a southern subtropical humid monsoon climate, and the soil type was mainly mountain red soil, which is acidic and rich in iron. Our study area had a northern temperate continental climate, and the soil types were mainly gray desert soil, aeolian sandy soil, and hidden saline soil. The differences between the findings of these two studies may be due to the long-term environmental adaptation of plants in different habitats and their inherent genetic characteristics [26]. They may also be related to the different species and seasons selected for study, as species can improve their fitness by increasing the intraspecific variation in functional traits [56]. However, in most cases, intra- and interspecific traits vary according to the environment. Hulshof and Wright et al. [16,57] argued that the intra- and interspecific variation levels of plant functional traits are closely related to their inherent characteristics and the external environmental conditions.

4.3. Contribution and Importance of Inter- and Intraspecific Variation to Community Weighting

In general, interspecific variation contributed more to community weighting than intraspecific variation under different soil water gradients. Our results also support the view that although intraspecific variation is generally less extensive than interspecific variation [58], it is an important source of trait variation [9,59]. The researchers used Donglingshan Forest Farm as the study area and found that elevation and slope were the primary factors involved in the formation of community differences in plant functional traits; in addition, soil nutrients changed with succession due to different forest communities at different succession stages, which led to the differences in nitrogen and phosphorus characteristics in the soil of different communities. In general, intraspecific variation is a critical mechanism of plants’ response to environmental changes, and it is useful for predicting plants’ dynamic changes [60]. Intraspecific trait variation accurately reflects the adaptability of plants to specific external environments. [61]. Studies have shown that intraspecific variation plays an important role in driving short-term responses of community functional composition to increased nitrogen and water supply in temperate grasslands. The higher the contribution of intraspecific variation to community traits, the stronger the adaptability of a plant species [62]. Violle C. and others have shown that the relative contribution of intraspecific variation was greater than that of species replacement. Intraspecific variation was found everywhere in grassland communities along the flooding gradient, which was the basis of Darwin’s natural selection theory and further proved the importance of intraspecific variation [18]. Sun Xiaoying studied the effect of intraspecific variation on the individual growth of woody plants and the response of interspecific relationships [63]. The effect of interspecific functional variation was stronger than that of intraspecific functional variation in shaping the individual growth of plants. However, intraspecific variation plays a regulatory role in interspecific relationships that may even promote species coexistence. Therefore, intraspecific variation cannot be ignored in many ecological processes of natural communities. The combination of intra- and interspecific trait variation more precisely reflects the responses of species to habitat changes and resource competition during community construction and more effectively illustrates the maintenance mechanisms of species diversity and ecosystem characteristics [11,24,25].

5. Conclusions

In this study, we investigated plant functional trait variation (plant height, diameter at breast height/base diameter, leaf length, leaf width, and leaf thickness) under different water gradients and its relationship with soil physicochemical factors. The interspecific and intraspecific variation of plant community leaf traits differed according to the water gradient. Under different water gradients, the variation responses of each functional trait to certain soil physicochemical factors differed considerably. The inter- and intraspecific variation of plant functional traits under a low water content maintained a relatively high correlation with soil physicochemical factors under a high water content. Interspecific variation under different soil water gradients contributed more to community weighting than intraspecific variation, but both contributed more under a high water content than under a low water content. Therefore, future ecological studies on functional traits should consider the combination of intra- and interspecific variation and soil environmental factors in individual horizontal sampling to explore the source and potential driving mechanism of plant functional trait variation. This would elucidate the environmental adaptation strategies of plants and the mechanisms of plant community construction and biodiversity maintenance.

Author Contributions

Conceptualization, L.S., H.W. and G.L.; methodology, L.S.; software, L.S., Y.C. and Q.Y.; writing—original draft preparation, L.S. and C.C.; writing—review and editing, L.S. and C.C.; supervision, H.W.; funding acquisition, H.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of Xinjiang Province (2022D01C42) and the National Natural Science Foundation of China (42171026).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not available.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Forests 13 01088 g001 550
Figure 1. Research area and survey plot overview. Note: Photo shows changes in vegetation vertical to the Aqikesu River from near to far.
Figure 1. Research area and survey plot overview. Note: Photo shows changes in vegetation vertical to the Aqikesu River from near to far.
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Figure 2. Soil physicochemical factors and community-weighted traits in different water gradients. (a) Community-weighted mean traits under different water gradients. (b) Soil factors under different water gradients. * Significant differences between high and low moisture gradient (p < 0.05); ** extremely significant differences between high and low moisture gradient (p < 0.01). Note: LL—leaf length, DBH/BD—diameter at breast height/base diameter, H—plant height, LW—leaf width, LT—leaf thickness.
Figure 2. Soil physicochemical factors and community-weighted traits in different water gradients. (a) Community-weighted mean traits under different water gradients. (b) Soil factors under different water gradients. * Significant differences between high and low moisture gradient (p < 0.05); ** extremely significant differences between high and low moisture gradient (p < 0.01). Note: LL—leaf length, DBH/BD—diameter at breast height/base diameter, H—plant height, LW—leaf width, LT—leaf thickness.
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Figure 3. RDA of inter- and intraspecific variation in plant community and soil physicochemical factors under different soil water gradients. (a) High moisture gradient; (b) low moisture gradient. When the angle is between 0° and 90°, a positive correlation exists between plant functional trait variation and soil environment; between 90° and 180°, the correlation is negative; at 90°, no obvious correlation exists. Red arrows represent soil physicochemical factors, and blue arrows represent inter- and intraspecific trait variation.
Figure 3. RDA of inter- and intraspecific variation in plant community and soil physicochemical factors under different soil water gradients. (a) High moisture gradient; (b) low moisture gradient. When the angle is between 0° and 90°, a positive correlation exists between plant functional trait variation and soil environment; between 90° and 180°, the correlation is negative; at 90°, no obvious correlation exists. Red arrows represent soil physicochemical factors, and blue arrows represent inter- and intraspecific trait variation.
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Figure 4. Correlation between interspecific and intraspecific variation and soil factors under different water gradients. (a) High moisture gradient; (b) low moisture gradient. SWC—soil water content, SSC—soil salt content, pH—pH value, SOC—soil organic carbon, TN—total nitrogen, TP—total phosphorus, H—plant height, D—diameter at breast height/base diameter, LL—leaf length, LW—leaf width, LT—leaf thickness. F denotes interspecific variation, and I denotes intraspecific variation.
Figure 4. Correlation between interspecific and intraspecific variation and soil factors under different water gradients. (a) High moisture gradient; (b) low moisture gradient. SWC—soil water content, SSC—soil salt content, pH—pH value, SOC—soil organic carbon, TN—total nitrogen, TP—total phosphorus, H—plant height, D—diameter at breast height/base diameter, LL—leaf length, LW—leaf width, LT—leaf thickness. F denotes interspecific variation, and I denotes intraspecific variation.
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Figure 5. Contribution of intraspecific variation to community weighting under different soil moisture gradients. (a) High moisture gradient; (b) low moisture gradient.
Figure 5. Contribution of intraspecific variation to community weighting under different soil moisture gradients. (a) High moisture gradient; (b) low moisture gradient.
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Table
Table 1. Soil index and determination method.
Table 1. Soil index and determination method.
Soil FactorsMethod
SWCDrying and weighing method
SSCResidue method
pHAcidimeter
SOCPotassium dichromate dilution heating method
TNKjeldahl method
TPMolybdenum antimony colorimetric method
Table
Table 2. Basic statistical value of soil water content in different moisture gradients.
Table 2. Basic statistical value of soil water content in different moisture gradients.
MoistureNumber of PlotMean/%Stand DeviationMin/%Max/%
High moisture gradient267.10 a4.723.5821.21
Low moisture gradient261.85 b1.090.293.51
Note: a and b indicate significant difference between the data (p < 0.05); the statistical data in the table are soil moisture content values.
Table
Table 3. Variation in plant functional traits among and within species under different water gradients (mean ± SD).
Table 3. Variation in plant functional traits among and within species under different water gradients (mean ± SD).
Functional TraitInterspecific VariationIntraspecific Variation
Low MoistureHigh MoistureLow MoistureHigh Moisture
LL9.047 ± 21.016 a12.215 ± 25.628 b−7.767 ± 21.151 a−9.033 ± 25.639 b
DBH/BD2.107 ± 2.677 a2.449 ± 2.633 a−1.704 ± 2.684 a−1.644 ± 2.726 a
H1.388 ±1.278 a1.590 ± 1.253 a−1.074 ± 1.294 a−1.192 ± 1.276 a
LW1.448 ± 1.916 a1.661 ± 2.13 a−1.238 ± 1.927 a−1.245 ± 2.156 a
LT0.315 ± 0.591 a0.387 ± 0.642 b−0.235 ± 0.591 a−0.273 ± 0.644 b
Note: a,b—different letters indicate significant differences in interspecific and intraspecific variation between the two water gradients (p < 0.05).
Table
Table 4. Soil factor RDA: explanation rates of plant functional trait variation and environmental variables under different soil water gradients.
Table 4. Soil factor RDA: explanation rates of plant functional trait variation and environmental variables under different soil water gradients.
Soil FactorHigh Moisture GradientLow Moisture Gradient
Explanation %Contribution %pExplanation %Contribution %p
TN6.432.40.1889.132.80.134
TP8.3420.1221.34.60.588
pH1.99.50.510.41.60.858
SOC1.15.70.6229.333.50.088
SWC0.94.60.6863.111.30.352
SSC1.15.80.6444.516.30.244
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Sun, L.; Wang, H.; Cai, Y.; Yang, Q.; Chen, C.; Lv, G. Disentangling the Interspecific and Intraspecific Variation in Functional Traits of Desert Plant Communities under Different Moisture Gradients. Forests 2022, 13, 1088. https://doi.org/10.3390/f13071088

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Sun L, Wang H, Cai Y, Yang Q, Chen C, Lv G. Disentangling the Interspecific and Intraspecific Variation in Functional Traits of Desert Plant Communities under Different Moisture Gradients. Forests. 2022; 13(7):1088. https://doi.org/10.3390/f13071088

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Sun, Li, Hengfang Wang, Yan Cai, Qi Yang, Caijin Chen, and Guanghui Lv. 2022. "Disentangling the Interspecific and Intraspecific Variation in Functional Traits of Desert Plant Communities under Different Moisture Gradients" Forests 13, no. 7: 1088. https://doi.org/10.3390/f13071088

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