Effects of Soil Heterogeneity and Species on Plant Interactions

Abstract

Plant interactions are central in driving the composition and structure of plant populations and communities. Soil heterogeneity and species identity can modulate such interactions, yet require more studies. Thus, a manipulative experiment was done where three soil heterogeneity levels were developed by mixing local soil and sand in three different ratios (i.e., soil:sand ratio = 2:8, 5:5, and 8:2), and three typical species (i.e., Festuca elata, Bromus inermis, and Elymus breviaristatus) were used in different combinations. Soil heterogeneity was assumed to affect plant interactions, which were in turn modified by species. Plant height was applied as an indicator for plant interactions. Relative competition intensity (RCI) was used to quantify plant interactions, where RCI was applied as a ratio of monoculture and mixture performance. Results showed that soil heterogeneity and soil heterogeneity × species significantly affected the RCI in mixtures compared with plant individuals growing alone (i.e., RCI₁). However, species as a single factor did not affect RCI₁. Moreover, species and soil heterogeneity × species significantly affected the RCI in mixtures compared with two individuals growing together (i.e., RCI₂), and the difference between RCI₁ and RCI₂ (i.e., RCI_diff). Soil heterogeneity significantly affected RCI₂ of F. elata. This study suggests that soil heterogeneity could buffer the stability of plant populations by modifying plant interactions, which would subsequently drive plant establishment. To explore the underlying mechanisms of such patterns, further studies considering more species and plant traits are needed.

Introduction

Plant interactions play an important role in shaping the composition and structure of plant populations and communities (Baer et al., 2003; Rajaniemi et al., 2009; Wassmuth et al., 2009; Cahill and McNickle, 2011; Houseman, 2014; Zhang et al., 2020). Numerous studies have explored plant interactions (Robinson et al., 1999; O’Brien et al., 2007; Allesina and Levine, 2011; Roiloa et al., 2014; Ravenek et al., 2016; Fichtner et al., 2018; Garlick et al., 2021), yet, several factors impede researchers to exactly quantify such interactions. For example, it is difficult to connect the cause and effect of plant interactions in natural communities with multiple species growing together, where many other factors such as climate change, disturbance, and natural heterogeneity may affect the results (Ravenek et al., 2016; Liu et al., 2019). Previous controlled studies often explored plant interactions in pairs for simplification (Johansson and Keddy, 1991; Chesson, 2000; Day et al., 2003; Rajaniemi, 2011; Li et al., 2018). However, plant individuals interact not only in pairs but are also affected by higher-order patterns (i.e., the interactions between two species are likely to be modified by other species, Pierik et al., 2013; Grilli et al., 2017; Levine et al., 2017; Fichtner et al., 2018; Li et al., 2020, 2021; Chu et al., 2021). Thus, to quantify plant interactions more accurately, it is necessary to quantify the differences between higher-order interactions and pairwise interactions.

Natural soils are heterogeneous, and this soil heterogeneity has two components, namely, qualitative heterogeneity and configurational heterogeneity (Kelly and Canham, 1992; Maestre and Cortina, 2002; Wijesinghe et al., 2005; Maestre and Reynolds, 2007). The former refers to the variations of texture, nutrients, pH, etc., between patches in the soils, while the latter reflects the size of these patches (Dufour et al., 2006). Soil heterogeneity in this study refers to the qualitative heterogeneity. Qualitative heterogeneity affects plant interactions by altering the availability of soil resources such as water and nutrients (Fransen et al., 2001; Schenk, 2006; Zhang et al., 2020).

Plants growing in a population or a community interact with each other (Chesson, 2000; Levine et al., 2017; Garlick et al., 2021). However, how to quantify such interactions is a hot topic in ecology. Many parameters can be applied to quantify plants interactions (Weigelt and Jolliffe, 2003), where relative competition intensity (RCI) is a widely used one. Previous studies found that plant interactions vary with species identity (Catorci et al., 2011; Raath-Krüger et al., 2019) and their growing stages (Yang and Rudolf, 2010; Li et al., 2019). Plant interaction at the early growing stage is crucial for plant establishment in plant populations and communities (Lortie and Turkington, 2008; Hart et al., 2018), and warrants more research. Plant height is a good indicator of plant interactions since it plays a vital role in determining light interception (Xiao et al., 2007), and thus, it is widely applied to quantify plant interactions non-destructively (Cui et al., 2004; Chen and Nelson, 2006; Xiao et al., 2007).

To explore the effects of soil heterogeneity and species identity on plant interactions, a controlled experiment was conducted, where three levels of soil heterogeneity were developed by mixing local soil and sand in three different ratios (i.e., soil:sand ratio = 2:8, 5:5, and 8:2), and three typical forage grasses were used (Festuca elata, Bromus inermis, and Elymus breviaristatus). RCI was applied to quantify plant interactions, where RCI was calculated as a direct ratio of monoculture and mixture performance, and positive (or negative) values simply indicated that a plant individual experiences stronger (or weaker) competition in mixtures compared with growing alone (Weigelt and Jolliffe, 2003). Specifically, we put forward three hypotheses: (i) RCI is expected to increase with increasing soil heterogeneity, where higher soil heterogeneity could reduce plant interactions due to an increase in the available resources at higher soil heterogeneity levels (Levine et al., 2017; Liu et al., 2017b); (ii) Such patterns may be modified by plant species identity since responses to soil heterogeneity can be modified via strategies or traits such as plasticity (Hodge, 2004; Craine and Dybzinski, 2013); (iii) Soil heterogeneity and species are assumed to jointly affect RCI since plant responses to soil resources depend on their neighbor identity and the distribution pattern of soil resources (Mommer et al., 2012; Garlick et al., 2021).

Materials and Methods

Experimental Design

This experiment was conducted at Linze Grassland Agriculture Trial Station of Lanzhou University (m.a.s.l. 1,400 m, 100°3′25^″E, 39°14′30^″N), in Gansu Province, China. This station is located in the middle of the Hexi Corridor (Hou and Shen, 1999). It is characterized by a temperate continental arid monsoon climate. The mean annual temperature and mean annual precipitation are 9.3°C and 112.9 mm, respectively. Temperatures range between extremes of 3°C and −28°C, and more than 60% of the rainfall occurs in summer and autumn, while the mean annual evaporation is 2,338 mm. The natural soils are saline due to the large difference between rainfall and evaporation (Zhu et al., 1997).

To explore the effects of soil heterogeneity (i.e., soil–sand ratio in this case) and species identity on plant interactions (i.e., quantified by RCI), a controlled experiment was conducted (Figure 1). Three levels of soil–sand ratio (i.e., soil:sand = 2:8, 5:5, and 8:2) were applied (details of these soil–sand ratios can be found in Table 1), where the sand was bought from a local commercial company, while the soil was collected from the local crop field. Three typical forage grasses were used (i.e., F. elata, B. inermis, and E. breviaristatus). These species were selected as they are dominant in the grasslands of China, and they differ both in their adaptation to saline soils and in their phenology, which should yield some growth divergence in our experimental treatments. Seeds of these species were bought from a commercial company (BEST, Beijing, China). On May 31, 2021, they were separately sowed into three identical trays with the same soils collected from the nearby field. Pots of 17.5 cm height, with a 16 cm top diameter and 13 cm bottom diameter were filled with one of the three types of soil–sand ratios. Seedlings of similar size were transplanted into the pots 1 week after sowing using three patterns (i.e., one, two, or three individuals). There were five replications of each treatment. Six holes with a 10-mm diameter were drilled in the bottom of each pot to ensure adequate drainage of water. Pots were watered evenly using a hose (0.4 L per pot per day), avoiding water runoff at the soil surface.

FIGURE 1

The plant height of each individual in each pot was measured 1 month after transplanting (details of plant height growing in different patterns can be found in Appendix Figures 1–3). RCI was calculated to quantify the plant interactions in mixtures with two and three individuals growing together.

Data Analysis and Statistics

No competition exists in pots with one individual, while only direct interaction occurred in pots with two individuals. However, both direct and indirect interactions appeared in pots with three individuals. To separate and quantify the indirect interaction in pots with three individuals, two ways could be applied to calculate plant interactions in this mixture. One is by comparing three individuals growing together with one individual, and the other is by comparing three individuals growing together with two individuals growing together (Figure 2).

FIGURE 2

(1) By comparing with plant individuals growing alone, plant interactions in pots with three individuals can be calculated as RCI₁ = (plant height in pots with one individual – plant height in pots with three individuals)/plant height in pots with one individual. The same calculation is used to quantify plant interactions in pots with two individuals.

(2) By comparing with two individuals growing together, plant interactions in pots with three individuals can be calculated: RCI₂ = (the average plant height in pots with two individuals – plant height in pots with three individuals) the average plant height in pots with two individuals.

RCI₁ in pots with three individuals includes both direct and indirect interactions. However, RCI₂ in pots with three individuals can be viewed as only including direct interactions. This is similar to comparing two individuals growing together with one individual growing alone. The only difference is that the two individuals were grouped in formula (2). As a result, the indirect interaction in pots with three individuals (labeled as RCI_diff) can be calculated by the following formula:

To explore the effects of soil–sand ratio (i.e., low, medium, and high), species (i.e., F. elata, B. inermis, and E. breviaristatus), and the number of individuals (i.e., two or three individuals in a pot) and their interactions on the RCI₁, ANOVA were conducted. To investigate the effects of soil–sand ratio, species, number of individuals, and their interactions on RCI₂ and RCI_diff, ANOVAs were performed. Results show that species identity was a significant factor. Thus, RCI₂ and RCI_diff of each species were analyzed separately, with soil–sand ratio and their interaction as fixed factors. Note that plant individuals in a mixture with two or three individuals growing together were treated as an extra factor as these individuals may perform differently. Post hoc analyses (pairwise comparisons with Bonferroni corrections) were carried out in these analyses when differences among the variables were significant. Log transformations were performed when necessary. All statistics were carried out with SPSS 21.0.

Note that biomass was not measured at this stage since doing so would impact plant growth at the following stages. However, measuring plant height was non-destructive, making it a reasonable parameter for exploring plant interactions at the early growing stage of plants.

Results

Soil–sand ratio and species × soil–sand ratio significantly affected RCI₁ (Table 2 and Figure 3). For mixtures with two individuals, RCI₁ of F. elata and B. inermis was highest at the medium soil–sand ratio, while RCI₁ of E. breviaristatus was highest at high soil–sand ratio (Figure 3A). For mixtures with three individuals, similar patterns were found (Figure 3B). However, species as a single factor did not affect RCI₁ (Table 2).

FIGURE 3

Species, soil–sand ratio × species significantly affected RCI₂ (Table 3 and Figure 4A). Specifically, RCI₂ of F. elata was higher in medium soil–sand ratio, while RCI₂ of B. inermis and E. breviaristatus increased with increasing soil–sand ratios (Figure 4A). However, soil–sand ratio as a single factor did not affect RCI₂ (Table 3). The separated analyses demonstrated that soil–sand ratios significantly affected RCI₂ of F. elata (Table 4). Specifically, RCI₂ of F. elata was higher at the medium soil–sand ratio, while RCI₂ of B. inermis and E. breviaristatus increased with increasing soil–sand ratios (Figure 4B).

FIGURE 4

Furthermore, species, soil–sand ratio × species significantly affected RCI_diff (Table 3 and Figure 4B). However, soil–sand ratio as a single factor did not affect the RCI_diff (Table 3).

Discussion

We found that plant interactions were affected by soil–sand ratio, which differed among plant species. Specifically, RCI (RCI₁, RCI₂, or RCI_diff) of F. elata and B. inermis was the highest in the medium soil–sand ratio, while RCI₁ of E. breviaristatus was the highest in the high soil–sand ratio.

Our first hypothesis, stating that RCI would increase with increasing soil heterogeneity (i.e., soil–sand ratio), was supported. We found that soil–sand ratio significantly affected RCI₁ (Figure 3 and Table 2), which is likely caused by the impacts of soil heterogeneity on the root foraging and distribution of plants (Levine et al., 2017; Liu et al., 2017b). However, root performance was not measured at this stage as harvesting roots affects plant growth at the following stages. This finding (i.e., RCI increased with increasing soil heterogeneity) is consistent with previous studies, such as that of Yu et al. (2019) who found that soil heterogeneity increased plant competition intensity within a population at a relatively low plant density. Such positive effects of soil–sand ratio on RCI could be caused by the indirect effect of soil–sand ratio on mycorrhizal fungi, where the effects of mycorrhizal fungi on plant performance increased with increasing soil–sand content (Zaller et al., 2011). Yet, other studies reported that plant competition was affected by resource heterogeneity only when plant individuals were not genetically identical (Day et al., 2003; Zhou et al., 2012). Furthermore, the positive effect may disappear at the later growing stage of plants when the soil–sand ratio was modified by these plants during the growing stages (Roiloa and Retuerto, 2006; Dong et al., 2015). Moreover, such an effect may disappear in a population or community since some individuals in this population or community could detect the neighbors and avoid direct competition (Novoplansky, 2009; Lepik et al., 2021), and some other individuals may perform in the opposite direction. The result depends on the combination of these two effects. Thus, we assumed that both positive and negative effects on plant competition are present simultaneously along the gradient of soil–sand ratio. Generally, plants adopt a diversity of responses to environmental variation (Lawson et al., 2015). However, the potential mechanisms of soil heterogeneity on plant interactions merit further investigation.

Our second hypothesis assumed that the effects of soil–sand ratio on RCI could be modified by plant species identity. In line with our expectation, species significantly affected RCI₂ and RCI_diff (Table 3). This is consistent with previous studies that grasses-mixture had higher shoot biomass than root biomass (Bessler et al., 2009). Specifically, we found that in mixtures with two individuals, the medium soil–sand ratio supported higher RCI₂ of F. elata than the other two ratios. This may be related to differences in the electrical conductivity (EC), where the medium soil–sand ratio had a higher EC value than the other two ratios (Table 1). However, the high soil–sand ratio supported a higher RCI₂ of B. inermis and E. breviaristatus than the other two ratios (Figure 3A). This may be related to pH, where the high ratio had the highest pH value (Table 1). Yet, the underlying mechanisms of these two different patterns merit further study.

Plant responses depend on neighbor identity and resource distribution (Mommer et al., 2012; Garlick et al., 2021). Yet, it refers to the same species but different individuals in this case. Thus, we expected that soil heterogeneity and species would jointly affect plant interactions. This was supported since significant interactions between soil–sand ratio and species were found (Table 2), in line with previous studies. For instance, Nakamura et al. (2008) found that soil heterogeneity affected larger individuals but not smaller individuals, where smaller individuals were strongly impacted by their neighbors (Chen et al., 2020). Moreover, the effects of soil heterogeneity on plant height could also be caused by the different growth rates of these individual plants (Hutchings, 1997), where plants growing in patches with more resources tend to grow faster. Such results could be derived from the different germinations at the beginning of the experiment, where Liu and Hou (2021) found that the heterogeneous distribution of soil resources affected seed germinations, which might further affect their heights. Plant heights of the target species in this study may differ after germinations even plants with the similar size were transplanted in this study since the earlier germination seeds may have a high chance to access light, which would be much higher in the later growing stage. However, the lack of germination information of these species in this study impedes us to further test such a hypothesis.

Results of this study should be interpreted and extrapolated with caution due to the following reasons. (1) This was a short-term experiment with only three soil–sand ratios, which impedes us to make comprehensive conclusions. Thus, further research should include a series of soil–sand ratios in longer term experiments. (2) Previous studies found that natural conditions include diverse plant functional groups. However, only three grass varieties were applied in this study. Therefore, future studies should consider competitive exclusion or a wider range of species, including clonal and N-fixing species (Mayfield and Levine, 2010), where the former can improve their nutrient-use efficiency via clone integration (Ying et al., 2018), and the latter can modify soil conditions through increasing soil nitrogen by fixing nitrogen from the air (Carlsson and Huss-Danell, 2003; Bhandari et al., 2020). (3) Plant interactions are affected by many factors, which is why drivers (e.g., climate) should be considered (McKane et al., 2002; Harpole and Tilman, 2007). (4) Similarly, other physiological and morphological traits such as specific leaf area should be considered in calculating plant interactions (Janecek et al., 2004). (5) Plant interactions vary in time, so results in this study at the early growing stage may not be applicable for the following growth stages (Li et al., 2019).

This is, to our best knowledge, likely to be the first time to quantify the indirect interaction of plants in a controlled experiment, and such interaction is modified by the joint effect of soil heterogeneity and species identity. Natural soils include both qualitative heterogeneity and configurational heterogeneity. However, this study only considered qualitative heterogeneity. Future studies should take the configurational heterogeneity, especially in three dimensions, into account (Liu et al., 2017a,b, 2021). Moreover, only aboveground competition intensity was explored here, future studies should consider plant interactions belowground as plants having a size-based competitive advantage aboveground may not have the same competitive advantage belowground and vice versa (Casper and Jackson, 1997; Poorter and Nagel, 2000; Brown et al., 2019; Liu et al., 2021).

Publisher’s Note

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