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Article

Interactive Effects of Soil Water, Nutrients and Clonal Fragmentation on Root Growth of Xerophilic Plant Stipa breviflora

by
Ruyue Fan
1,2,†,
Shijie Lv
3,†,
Yong Ding
2 and
Qingfeng Li
1,*
1
College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010018, China
2
Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot 010010, China
3
College of Science, Inner Mongolia Agricultural University, Hohhot 010018, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2022, 12(12), 2112; https://doi.org/10.3390/agriculture12122112
Submission received: 21 October 2022 / Revised: 28 November 2022 / Accepted: 5 December 2022 / Published: 9 December 2022
(This article belongs to the Special Issue Restoration of Degraded Grasslands and Sustainable Grazing)
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Abstract

:
Root traits are often used to predict the ecological adaptations of plants. Water and nutrient availability together with fragment size are likely to affect the adaptative capacity of Stipa breviflora and help plants spread and explore new sites, while the effects of water, nutrients and fragment size on S. breviflora’s root traits have rarely been studied in combination. Here, a standard Taguchi L8(27) array design was conducted with four single factors, water (W), nitrogen (N), phosphorus (P) and fragment size (C), and three interactions (N × P, N × W and P × W). Each of the four factors had two levels (1 = low level and 2 = high level). This study found that water was the most important contributor influencing S. breviflora root growth, followed by N and P, respectively. W2 and P2 additions both promoted root growth, whereas N2 addition significantly inhibited root growth. Though C2 had higher values of total root length, surface area, volume, number of tips and biomass than C1, its root growth rate was lower than C1, and its small size fragment had a higher capacity of root growth under low N addition. These findings suggest that clonal fragmentation may enhance the adaptation of S. breviflora in low nitrogen habitats, and that nitrogen is one of the limiting factors influencing their growth and distribution.

1. Introduction

With a wide range of ecological adaptations, the Stipa steppe is one of the most common steppe types continuously distributed in the Eurasian grassland [1,2]. Although most Stipa species are xerophytes and grazing-tolerant [3,4,5], S. breviflora is distributed more widely than other Stipa species in the arid and semiarid areas [1,6]. This grass has strong ecological adaptability to diverse environments. It is not only one of the dominant species in the desert steppe [1], but also is a codominant species in the typical steppe [1,6].
Plant performance often varies with heterogeneous soil conditions, and during these procedures their root systems play important functional roles in acquiring and storing resources with various root architectures [7,8]. For example, root growth angle, root length, root volume and root branching influence exploration of the soil by the root system and hence plant uptake of soil resources [8,9]. Normally, roots with narrow, deep systems can improve water and nitrate capture, or with wide, shallow root systems can better uptake less mobile topsoil nutrients such as phosphorus [8,10]. In the arid and semiarid steppe ecosystems, water deficit is a severe environmental constraint to plant growth and distribution [11,12]. Increasing water uptake by improving roots’ extension and proliferation is one of main mechanisms for plants to adapt to drought environments [13]. Previous studies found that plants may also choose to reduce C demand by reducing the root elongating rate or the number of lateral roots [14], and displayed a resource conservation strategy with low specific root length (SRL) or high root tissue density (RTD) under drought stress [14,15]. However, in the arid and semiarid steppe ecosystems, plant growth is limited not only by the isolated effects of water, but also by the nitrogen (N) and phosphorus (P) and the interactions between them [16,17,18]. Generally, a soil water shortage limits the microbial mineralization for organic matter, and then negatively affects N and P availability, uptake and transport, which impact the nutrient absorption by plant roots [7,19,20,21]. In this case, under drought condition, the more severe the drought the lower the water and nutrient flow and the more limited the availability of nutrients for absorption and transportation by the root system [13,20]. However, most studies simply focus on assessing the effect of a single stressful condition on plant root growth, and they always ignore the reality that plant root growth is frequently exposed to soil constraints with shortages of water and nutrients together.
As a clonal tussock grass, S. breviflora usually adapts to heterogeneous environments through clonal plasticity and clonal aggregation within genets [22,23]. Recently, some studies pointed out that it also can improve aggregation by producing clonal fragments, and a high proportion of their genets can split into a group of individuals with different sizes by several clonal fragments [23]. Therefore, the ecological adaptative strategy of S. breviflora is not only driven by water and nutrients in environments, but also is affected by its self-growth rhythm. To some extent, the performance of clonal fragments also depends on water status and nutrient availability in environments [24]. Generally, connected ramets within clonal fragments can often exchange signals and resources with parental clones [25,26], and clonal fragmentation can increase the survival rates of vegetative offspring, especially when individual ramets experience low resource availability [24,27,28], though this has not been found in all cases [29]. Moreover, clonal fragmentation would help perennial plants occupy more space and enhance their dominance under stressful environments. For example, S. breviflora would produce more fragments with increasing grazing intensity and offspring clusters spread out from the center of the parent [23]. Generally, ramets connected by fragments can store more resource which would induce them with higher survival [24,30,31]. Clonal fragmentation is the process of one large cluster splitting into some small individuals with different fragment sizes, but the question is if the growth strategies would be different between big-size fragments and small ones when adapting to heterogenous environments. Above all, the root phenotyping of Stipa species has been investigated in many studies [32,33], but little is known about how root growth of S. breviflora responds to fragment size. For better understanding of the factors limiting S. breviflora’s distribution, we considered the effects of water, nutrients and their interactions together with fragment size on S. breviflora root growth. Here, we conducted a greenhouse Taguchi experiment to test the single and interactive effects of three factors on root traits and to confirm (1) which of soil water, N, P and their interactions are the main factors affecting the root growth of xerophyte S. breviflora; (2) how fragment size affects S. breviflora’s root growth and (3) if fragmentation could improve the capability of adaptation in stressed environments.

2. Materials and Methods

2.1. Experimental Design

Thirty plants of S. breviflora were randomly dug from a temperate grassland area located in Horinger County, Inner Mongolia, China (111°50′ E, 40°29′ N). Then, they were hand separated into two types of experimental units containing ramets with similar morphological size: individual with single ramet (C1) and individual with three ramets connected by rhizomes (C2). Twenty individuals of each experimental unit (C1 or C2) were transplanted to one square pot (60 cm length × 35 cm width × 18 cm height) filled with soil mix containing 20% field soil (from Horinger) and 80% vermiculite ((Mg, Fe, Al)3[(Si, Al)4 O10 (OH)2]. 4H2O) at the greenhouse of the College of Grassland, Resources, and Environment of the Inner Mongolia Agricultural University. The field soil was collected 0–40 cm from the same sites. Then, the soil was sieved and homogenized to remove roots and stones before mixing with vermiculite. There was a total of 12 square pots for C1 and 12 square pots for C2. The chemical properties of experimental soils are shown in Table 1. In the greenhouse, there was a 14 h light/10 h dark photoperiod. The air temperature was 26 ± 2 °C and 20 ± 2 °C for day/night, respectively.
The experimental design was a standard Taguchi L8(27) arrays including four factors, nitrogen (N), phosphorus (P) and water (W) and fragment size (C), and three interactions (N × P, N × W and P × W). Each of the four factors had two levels, and there was a total of 8 treatments (Table 2). This experiment used NO3NH4 and NaH2PO4·2H2O as N and P fertilizer with the additional concentrations of 15 mg N/kg and 120 mg N/kg and 2 mg P2O5/kg and 24 mg P2O5 (low level/high level), respectively. Water additions included 25%~30% field moisture capacity of mixture (FMC) and 75%~80% FMC, and fragment size consisted of individual with single ramet and individual with three ramets (Table 2). MINITAB 18.0 (Minitab, Inc., State College, PA, USA) software was employed in this data analysis step. The experiment was repeated 3 times with 5-day intervals. Before treatments, individuals were allowed to grow for 21 days to establish roots. Each experimental period lasted 17 weeks. The nitrogen and phosphorus additions were applied every 20 days, while water additions were applied every three days.

2.2. Measurements

Five plants were randomly selected from each treatment. To scan root traits of individual plants, the roots were severed from the shoot at the root collar and then were gently washed with running tap water over a sieve with a mesh size of 0.2 mm. Each root sample was scanned in water with a flatbed scanner (Epson Perfection V700 Photo, Seiko Epson Corporation, Nagano, Japan). Subsequently, images were analyzed using the software winRHIZO® (Regent Instruments Canada Inc., Quebec, QC, Canada). Root traits included total root length (calculated using a one-pixel thinned image and multiplying the number of pixels by pixel size), root surface area (calculated by determining the root diameter and length), root volume (calculated using the root surface area and length) and root tips [34]. After scanning, root samples were oven-dried at 65 °C to constant weights and then weighed to determine root dry biomass. Root tissue density (RTD) was determined by the ratio of root dry biomass to root volume. Specific root length (SRL) was estimated by the ratio of total root length to root dry biomass.

2.3. Statistical Analyses

The analysis of variance (ANOVA) was used to determine the effects of three factors (N, P and W), their interactions (N × P, N × W and P × W) and fragment size on seven root traits. Means were separated using Tukey’s test at p ≤ 0.05. In addition, the variance contribution rate (VCR) was calculated to determine the magnitude of the influence of the particular factor in terms of percentage on six root traits. The larger the VCR value, the greater the influence of the particular factor to root traits [35]. In our study, the VCR is the ratio of the sum of the squares (SSM) of the factor to the total sum of the square (SST) of all the factors. Meanwhile, factor analysis was used to determine the dependent relationship between seven root traits of root morphological traits and root biomass. Factor analysis is a type of multivariate analysis that can be used to reduce a large number of correlated variables to a smaller number of main factors [36]. Principal factor analysis was used for factor extraction and varimax rotation was used to define factors [36]. Furthermore, one-way ANOVA was used to identify the effects of N, P or W on six root traits (total root length, root surface areas, root volume, root tips, root dry biomass and specific root length) under different fragment sizes. Means were separated using Tukey’s test at p ≤ 0.05.

3. Results

3.1. Effects of Experimental Factors on Root Traits

No interactive effects of N × P, N × W and P × W were observed for total root length (TRL), root surface area (RSA), root volume (RV), root tips (RT) and root biomass (RB). The interactive effects of N × W and P × W for specific root length (SRL) were significant (p ≤ 0.05, Table 3).
Meanwhile, N addition significantly affected TRL (VCR = 22.23, p < 0.01) and RT (VCR = 19.88, p < 0.001, Table 4), P addition greatly influenced RT (VCR = 22.51, p < 0.001) and water addition had significant effects on RV (VCR = 45.83, p < 0.001), RSA (VCR = 34.78, p < 0.05) and RB (VCR = 21.19, p < 0.01). In addition, fragment size was significant for TRL (VCR = 21.97, p < 0.01), RSA (VCR = 20.79, p < 0.01), RV (VCR = 17.97, p < 0.01), RT (VCR = 26.54, p < 0.001), RB (VCR = 22.81, p < 0.01) and SRL (VCR = 16.51, p < 0.01). Moreover, when considering the total VCR from each experimental factor to six root traits, water addition (total VCR = 135.24) was the greatest contributing factor and fragment size (total VCR = 126.59) was the second factor, followed by N addition (total VCR = 69.54) and P addition (total VCR = 52.22) (Table 4).

3.2. Relationships among Root Traits

Based on Kaiser’s criterion [36], data could be condensed in two factors, and the results indicated that in the two—the first eigenvalue represented 88% of all the variability (Figure 1). After varimax rotation, high root growth correlation for the first factor was observed among TRL, RSA, RV and RT, and they all had positive correlations with the first factor or with each other, respectively. For the second factor, high root growth correlation was observed among root biomass, SRL and RTD, whereas SRL had a negative correlation with the second factor (Figure 1). In brief, there were two response types for assessing root growth of S. breviflora: one was related to root biomass and another was related to root morphological traits.

3.3. Root Morphological Traits and Root Biomass Respond to Water Addition

The root traits TRL, RSA, RV and RB were decreased by 16.5%, 31.6%, 44.3% and 41.4%, respectively, under 25% FMC water addition (W1) than those under 75% FMC water addition (W2) (p ≤ 0.05, Figure 2A–D).

3.4. Effects of Fragment Size on Root Growth

The C2 (individual with three ramets) showed 1.26-fold, 1.34-fold, 1.44-fold, 1.42-fold and 1.84-fold higher TRL, RSA, RV and RT than that of C1 (individual with single ramet) (p ≤ 0.05, Figure 3A–E). During the further analysis, within the treatment of C1 we found that the TRL, RSA and RB were significantly lower under N1 addition (15 mg N/kg) than that under N2 addition (120 mg N/kg), whereas there were no changes within the treatment of C2 (p ≤ 0.05, Table 5). In addition, the RSA and RV of C1 and C2 both were higher under W2 than under W1.

3.5. Root Morphological Traits and Root Biomass Respond to Nutrient Addition

N2 addition (120 mg N/kg) had negative effects on root growth by decreasing TRL, RSA, RV and RT (p ≤ 0.05, Figure 4A–C) as compared to N1 addition (15 mg N/kg). P2 addition (24 mg P2O5/kg) significantly promoted root growth via increasing RSA, RV and RT as compared to P1 addition (2 mg P2O5/kg) (p ≤ 0.05, Figure 5A–C).

3.6. Root Morphological Traits and Root Biomass Respond to the Interaction between Water and Nutrients

The N × W had significant effects on SRL (Table 3). Under the drought condition of 25% FMC water addition, the SRL was significantly lower in the 15 mg N/kg addition than that in the 120 mg N/kg addition, while there were no variations in the SRL between the two levels of nitrogen addition under the well-watered condition (75% FMC water addition) (p < 0.001, Figure 6A). In addition, the P × W interaction also had significant effects on SRL (Table 3), which showed that water addition had no effect on SRL under the condition of 2 mg P2O5/kg addition (P1), but under higher phosphorus condition with 24 mg P2O5/kg (P2), the SRL was significantly higher under drought condition (W1) than that under well-watered condition (W2) (p ≤ 0.05, Figure 6B).

4. Discussion

4.1. Effects of Drought on Root Growth

The wide distribution of S. breviflora in the desert steppe is closely related to its high drought tolerance [2,37]. Root systems are the main organs that uptake water from the soil and directly affect the water availability in plants, which show sensitivity to drought stress by modifying their morphological traits or biomass [38,39,40,41]. In this study, root biomass and morphological traits such as total root length, root surface area and root volume of S. breviflora at the 25% FMC were significantly lower than at the 75% FMC. These results are consistent with previous findings that drought caused a significant reduction in root biomass for grass species [15,38,39]. In addition, Huang [40] found that drought caused a significant decrease in the total root length of three tall fescue cultivars. A meta-analysis also showed that drought significantly decreased not only root biomass, but also total root length, root volume and root surface area [41].

4.2. Effects of Nutrient Additions on Root Growth

N and P are the two essential nutrient elements for plant growth, whereas they also are the two main limited elements in grassland ecosystems [16,18]. Generally, N or P deficiency can limit root branching or elongating [9,42,43,44]. Variations in the number of root branching not only influenced total root biomass, total root length and total root surface area, but also the availability of soil nutrients for plants [45]. In general, N and P contents are closely associated with root architecture formation. In our research, we found that S. breviflora’s roots proliferated with larger root surface area, bigger root volume and more root tips at high-level P addition than that at low-level P addition. This is in agreement with previous reports that low P supply decreased root length and root branching [44]. By contrast, in our study, high-level N addition restrained root growth, with significantly lower values of the total root length, root surface area and root tips than those in the condition of low-level N addition for S. breviflora, which was inconsistent with most of former studies [42,46]. Hodge (2004) pointed out that whether plant roots can proliferate in some nutrient-rich environments not only depends on the content of nutrients in the environments but also depends on the demand for the nutrients themselves, and there may be a specific threshold of nutrients to induce root morphological trait or biomass changing [47]. For example, though high-level N addition could induce root elongation and branching, sometimes the high internal nitrate/N may inhibit lateral root growth and influence the architecture or biomass of the root system [42]. Therefore, in our research, 120 mg N/kg may have exceeded the threshold value of N addition for promoting the root growth of S. breviflora, which caused its root growth to be restricted.

4.3. Effects of Interactions of Water and Nutrients on Root Growth

Mostly, soil moisture influences nutrients’ availability and their transportation or uptake in root systems [20], i.e., in some cases, having sufficient nutrients in the soil does not guarantee the improvement of plant growth during drought conditions [20]. Therefore, to some extent, root growth can be influenced by the interactions between soil moisture and nutrients. As results showed in this study, SRL was influenced by the interactions of N × W and P × W. During the procedures of plants adapting to environments, it is noteworthy that there would be a trade-off between resource acquisition and resource conservation use strategies for plants to adapt to soil heterogeneity [48]. RTD, SRL and biomass are always seen as indicators assessing this trade-off. Under poor nutrient environments, plants will develop an acquisition resource use strategy by producing thin roots (with high SRL, low RTD and low biomass), which can elongate root systems for acquiring more nutrients and water [15]. Furthermore, in this study, RTD and biomass both had negative correlations with SRL for S. breviflora, while under drought condition, there was higher SRL after 120 mg N/kg addition than that at 15 mg N/kg addition. This indicated that plants invest more thin roots, not for acquiring more nutrients or water, but it seems to escape high level N and drought condition, which both inhibited the S. breviflora’s root growth. By contrast, in general, under nutrient-rich environments, plants would develop a conservation resource use strategy with producing coarse roots (with low SRL, high RTD and high biomass), which have higher ability in transporting nutrients and water [49] and can store more resources with longer root spans than thin roots [15,48,50]. In this study, under low-level N addition, the root system of S. breviflora invested in more coarser roots to store more organic matter for maximum longevity under a drought environment, which may be related to the 15 mg/N addition contributing to the root growth of S. breviflora. This indicated that high-level N addition caused S. breviflora to develop an acquisitive resource-use strategy under drought condition, while developing a conservative resource-use strategy under low-level N addition; one was for escaping and the other for longevity. In addition, compared with N2 addition, the capacity of microbials to immobilize N should be low, and there was more organic matter for microbial decomposing under N1 addition; to some extent, microbial C/N will increase, which has been confirmed in some research that root growth with a conservative resource strategy can increase soil inorganic N availability, together with increasing microbial C/N [15,51]. To some extent, higher SRL and lower biomass were found under 25% FMC water addition (acquisition resource use strategy) than under 75% FMC water addition (conservation resource-use strategy) under sufficient P condition, which indicated the former for acquiring more resources and the latter for storing more resources. This study was consistent with previous studies [15,48,50].

4.4. Effects of Fragment Size on Root Growth

At the beginning of this study, C2 had more than 2-fold root biomass than C1, but at the end of study, C2 showed 1.26-fold, 1.34-fold, 1.44-fold, 1.42-fold and 1.79-fold higher total root length, root surface area, root volume, root tips and root biomass than C1. This result might indicate that the root growth rate of S. breviflora was higher for the small fragment than the large one. Moreover, the effects of nitrogen, phosphorus and water addition on root morphological traits and root biomass under the treatment of C1 and C2 were different. During the further analysis, within the treatment of C1 we found that the total root length, root surface area and root biomass were significantly lower under high-level N addition than that under low-level N addition, whereas there were no changes within the treatment of C2. These results also can be explained by the ideas of Hodge [47], in that the proliferation of root systems was determined by the content of extra and intra nutrients of plants together. For example, compared with the control, Poa pratensis had a shorter root length, lower root length density and smaller root biomass in a N-rich patch, where the plants can capture 13% of their total N content [52], but in another study where the N patch represented a larger proportion of the total N (18%), the plants had a higher root length density and higher root biomass [46]. In our study, compared with C2, C1 did not need more nitrogen to support individual plant growth, which may be caused by high N addition exceeding the specific thresholds of nitrogen to induce root growth for C1. Therefore, N was a major limiting factor to the root growth of small fragments.

5. Conclusions

The root growth strategies of S. breviflora can be assessed by two kinds of traits: one was related to root biomass (SRL and RTD) and another was related to root morphological architecture (TRL, RV, RSA and RT). In addition, water was the biggest contributor to the growth of the root system, followed by N and P, respectively. The root growth of S. breviflora was inhibited under high N addition, and clonal fragmentation is likely beneficial to improving its adaptability under low N conditions. These findings suggest that clonal fragmentation may enhance the adaptation of S. breviflora in low nitrogen habitats, and nitrogen is one of the limiting factors influencing their growth and distributions.

Author Contributions

Conceptualization, Q.L. and R.F.; methodology, S.L., R.F. and Q.L.; software, R.F.; formal analysis, S.L. and R.F.; data curation, R.F.; writing—original draft preparation, R.F.; writing—review and editing, R.F., Q.L., S.L. and Y.D.; visualization, R.F.; supervision, Q.L. and S.L.; project administration, Q.L. and Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Nature Conservancy (CN/IM/IMAU050517PGA) and the Major Projects of Inner Mongolia Natural Science Foundation (2020ZD06).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to an ongoing follow-up study.

Acknowledgments

We would like to thank the support of the Key Laboratory of Forage Cultivation, Processing and Efficient Utilization, Ministry of Agriculture and Key Laboratory of Grassland Resource, Ministry of Education.

Conflicts of Interest

The authors declare no conflict of interest.

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Agriculture 12 02112 g001 550
Figure 1. Factor analysis of seven root traits. Note: TRL, RSA, RV, RT, RB, SRL and RTD separately represented total root length, root surface area, root volume, root tips, root biomass, specific root length and root tissue density.
Figure 1. Factor analysis of seven root traits. Note: TRL, RSA, RV, RT, RB, SRL and RTD separately represented total root length, root surface area, root volume, root tips, root biomass, specific root length and root tissue density.
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Agriculture 12 02112 g002 550
Figure 2. Effects of water addition on total root length (A), root surface area (B), root volume (C) and root biomass (D). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. W1 = 25% FMC, W2 = 75% FMC.
Figure 2. Effects of water addition on total root length (A), root surface area (B), root volume (C) and root biomass (D). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. W1 = 25% FMC, W2 = 75% FMC.
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Agriculture 12 02112 g003 550
Figure 3. Effects of fragment size on total root length (A), root surface area (B), root volume (C), root tips (D) and root biomass (E). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. C1 = individual with single ramet, C2 = individual with three ramets.
Figure 3. Effects of fragment size on total root length (A), root surface area (B), root volume (C), root tips (D) and root biomass (E). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. C1 = individual with single ramet, C2 = individual with three ramets.
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Agriculture 12 02112 g004 550
Figure 4. Effects of N addition on total root length (A), root surface area (B) and root tips (C). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. N1 = 15 mg N/kg, N2 = 120 mg N/kg.
Figure 4. Effects of N addition on total root length (A), root surface area (B) and root tips (C). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. N1 = 15 mg N/kg, N2 = 120 mg N/kg.
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Figure 5. Effects of P addition on root surface area (A), root volume (B) and root tips (C). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. P1 = 2 mg P2O5/kg, P2 = 24 mg P2O5/kg.
Figure 5. Effects of P addition on root surface area (A), root volume (B) and root tips (C). Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. P1 = 2 mg P2O5/kg, P2 = 24 mg P2O5/kg.
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Agriculture 12 02112 g006 550
Figure 6. Effects of water addition × nitrogen addition (A) and water addition × phosphorus addition (B) on specific root length. Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. W1 = 25% FMC, W2 = 75% FMC. P1 = 2 mg P2O5/kg, P2 = 24 mg P2O5/kg.
Figure 6. Effects of water addition × nitrogen addition (A) and water addition × phosphorus addition (B) on specific root length. Bars with the same letters were not significantly different (p > 0.05) using Tukey’s test. Error bars indicate standard error of means. W1 = 25% FMC, W2 = 75% FMC. P1 = 2 mg P2O5/kg, P2 = 24 mg P2O5/kg.
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Table
Table 1. Chemical properties of soil used in the experiment.
Table 1. Chemical properties of soil used in the experiment.
Properties
pH8.29
Organic carbon3.30 g/kg
Total nitrogen0.34 g/kg
Total phosphorus0.32 g/kg
Total potassium20.21 g/kg
Available N29.25 mg/kg
Available P1.85 mg/kg
Available K73.70 mg/kg
Table
Table 2. Standard Taguchi L8(27) array experimental design.
Table 2. Standard Taguchi L8(27) array experimental design.
TreatmentsNitrogen Addition (N)Phosphorus Addition (P)N × PWater Addition (W)N × WP × WFragment Size (C)
1N1P1N1P1W1N1W1P1W1C1
2N1P1N1P1W2N1W2P1W2C2
3N1P2N1P2W1N1W1P2W1C2
4N1P2N1P2W2N1W2P2W2C1
5N2P1N2P1W1N2W1P1W1C2
6N2P1N2P1W2N2W2P1W2C1
7N2P2N2P2W1N2W1P2W1C1
8N2P2N2P2W2N2W2P2W2C2
Notes: N1 = 15 mg N/kg, N2 = 120 mg N/kg; P1 = 2 mg P2O5/kg, P2 = 24 mg P2O5/kg; W1 = 25% FMC (field moisture capacity), W2 = 75% FMC; C1 = individual with single ramet; C2 = individual with three ramets.
Table
Table 3. The analysis of variance of the effects of nitrogen addition (N), phosphorus addition (P) and water addition (W) and their interactions (N × P, N × W and P × W), in addition to fragment size (C), on seven root traits for Stipa breviflora.
Table 3. The analysis of variance of the effects of nitrogen addition (N), phosphorus addition (P) and water addition (W) and their interactions (N × P, N × W and P × W), in addition to fragment size (C), on seven root traits for Stipa breviflora.
TraitsNP N × PWN × WP × WC
Total root length (TRL)**NSNS*NSNS**
Root surface area (RSA)**NS***NSNS**
Root volume (RV)NS*NS***NSNS**
Root tips (RT)****NSNSNSNS***
Root biomass (RB)NSNSNS**NSNS**
SRL**NSNS*******
RTDNSNSNSNSNSNSNS
Note: SRL: specific root length; RTD: root tissue density; significant difference *, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001; NS, not significant.
Table
Table 4. Variance contribution rate (VCR) of the effects of nitrogen addition (N), phosphorus addition (P) and water addition (W) and their interactions (N × P, N × W and P × W), in addition to fragment size (C), on six root traits for Stipa breviflora.
Table 4. Variance contribution rate (VCR) of the effects of nitrogen addition (N), phosphorus addition (P) and water addition (W) and their interactions (N × P, N × W and P × W), in addition to fragment size (C), on six root traits for Stipa breviflora.
TraitsVCR (%)
NP N × PWN × WP × WC
Total root length (TRL)22.236.460.1213.681.750.8321.97
Root surface area (RSA)9.746.670.4234.780.963.3120.79
Root volume (RV)3.806.381.7445.830.575.0817.97
Root tips (RT)19.8822.513.624.832.990.1526.54
Root biomass (RB)0.456.046.3321.194.985.9422.81
SRL13.444.165.4214.939.2014.0416.51
Total69.5452.2217.65135.2420.4529.35126.59
Note: SRL: specific root length.
Table
Table 5. The one-way analysis of variance (ANOVA) of the effects of nitrogen addition, phosphorus addition and water addition on root biomass, total root length, root surface area, root volume, root tips and specific root length under each level of fragment size for Stipa breviflora.
Table 5. The one-way analysis of variance (ANOVA) of the effects of nitrogen addition, phosphorus addition and water addition on root biomass, total root length, root surface area, root volume, root tips and specific root length under each level of fragment size for Stipa breviflora.
Treatments
(120 Samples)		LevelTRL
(cm)		RSA
(cm2)		RV
(cm3)		RT
(Number/Plant)		RB
(g)		SRL
C1Nitrogen additionN11223.88 a148.50 a1.45 a3521.03 a0.33 a4262.66 b
N2896.76 b102.36 b0.94 a2524.07 a0.20 b6515.86 a
Phosphorus additionP11024.85 a117.95 a1.09 a2653.97 a0.26 a5238.14 a
P21095.79 a132.91 a1.31 a3391.13 a0.27 a5540.39 a
Water additionW1942.83 a100.91 b0.87 b2521.23 a0.27 a5622.80 a
W21177.81 a149.95 a1.54 a3523.87 a0.41 a5155.72 a
C2Nitrogen additionN11443.59 a174.11 a1.70 a4874.17 a0.43 a4166.34 a
N21222.25 a161.94 a1.74 a3690.57 a0.50 a4141.87 a
Phosphorus additionP11220.54 a151.39 a1.52 a3490.77 b0.36 a4925.05 a
P21445.30 a184.66 a1.92 a5073.97 a0.57 a3383.17 a
Water additionW11235.29 a137.45 b1.23 b4246.4 a0.44 b5095.07 a
W21430.55 a198.60 a2.22 a4318.33 a0.75 a3213.14 b
Note: Means within a column at each treatment level with a common lower-case letter are not significantly different (p > 0.05). TRL, RSA, RV, RT, RB and SRL separately represented total root length, root surface area, root volume, root tips, root biomass and specific root length: 120 samples in total, 60 samples for C1 and 60 samples for C2.
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Fan, R.; Lv, S.; Ding, Y.; Li, Q. Interactive Effects of Soil Water, Nutrients and Clonal Fragmentation on Root Growth of Xerophilic Plant Stipa breviflora. Agriculture 2022, 12, 2112. https://doi.org/10.3390/agriculture12122112

AMA Style

Fan R, Lv S, Ding Y, Li Q. Interactive Effects of Soil Water, Nutrients and Clonal Fragmentation on Root Growth of Xerophilic Plant Stipa breviflora. Agriculture. 2022; 12(12):2112. https://doi.org/10.3390/agriculture12122112

Chicago/Turabian Style

Fan, Ruyue, Shijie Lv, Yong Ding, and Qingfeng Li. 2022. "Interactive Effects of Soil Water, Nutrients and Clonal Fragmentation on Root Growth of Xerophilic Plant Stipa breviflora" Agriculture 12, no. 12: 2112. https://doi.org/10.3390/agriculture12122112

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