Next Article in Journal
Insights into the Root Sprouts of Toona fargesii in a Natural Forest: From the Morphology, Physiology, and Transcriptome Levels
Previous Article in Journal
Analysis of Factors Driving Subtropical Forest Phenology Differentiation, Considering Temperature and Precipitation Time-Lag Effects: A Case Study of Fujian Province
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 15
Issue 2
10.3390/f15020336
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Differences in Fine Root Foraging Traits of Two Dominant Tree Species (Cunninghamia lanceolata and Quercus acutissima) in Subtropical Forests

by
Xinying Xu
1,2,
Rui Tan
1,2,
Huimei Shao
1,2,
Jiacun Gu
3,
Weifeng Wang
1,2,
Guobing Wang
1,2 and
Shuiqiang Yu
1,2,*
1
Department of Ecology, College of Ecology and Environment, Nanjing Forestry University, Nanjing 210037, China
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
3
Key Laboratory of Sustainable Forest Ecosystem Management—Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, China
*
Author to whom correspondence should be addressed.
Forests 2024, 15(2), 336; https://doi.org/10.3390/f15020336
Submission received: 1 January 2024 / Revised: 30 January 2024 / Accepted: 31 January 2024 / Published: 8 February 2024
(This article belongs to the Section Forest Ecophysiology and Biology)
Browse Figures
Review Reports Versions Notes

Abstract

:
Root biomass and length growth, functional traits, and their responses to soil nutrient availability are crucial for resource acquisition under environmental change. Previous studies have focused on the response of root morphological, architectural, and chemical traits to fertilization, while less attention has been given to root biomass and length growth, as well as mycorrhizal symbiosis, impeding a full understanding of root resource acquisition strategies. Here, using a nutrient addition experiment (control, inorganic, and organic nutrients), we explored the responses of function-based root (absorptive fine roots [AFRs] versus transport fine roots [TFRs]) growth, functional traits (morphological, architectural, and chemical traits), and mycorrhizal colonization of C. lanceolat and Q. acutissim, which are the dominant tree species in subtropical China. The results showed that the fine root biomass and total root length of AFRs for both tree species basically decreased significantly after nutrient addition, but TFRs responded less sensitively than AFRs. Nutrient addition significantly increased the mycorrhizal colonization rate in C. lanceolata but decreased it in Q. acutissima. The diameter of AFRs for C. lanceolata increased significantly, while the branch ratio and branch intensity decreased significantly in both inorganic nutrients (NPK) and organic nutrients (F); however, the opposite response pattern occurred for Q. acutissima. Fine root biomass, total root length, and root nutrient concentration exhibited the most plastic responses to changes in nutrient availability. The magnitude of the plastic response of fine root traits was slightly higher in the NPK treatment than in the F treatment. Our findings suggest that the responses of fine root traits and mycorrhizal fungi to nutrient addition were species-specific: C. lanceolata depended on mycorrhizal fungi for resource acquisition, while Q. acutissima could acquire soil nutrient resources by increasing root branching. The contrasting nutrient acquisition strategies between tree species may facilitate plant species coexistence and distribution under soil nutrient change. Fine root biomass and total root length emerged as more pivotal indicators for nutrient acquisition strategies compared to morphological traits.

1. Introduction

Plant nutrient acquisition can be represented by adjustments in fine root proliferation and a series of interrelated root functional traits including morphology, architecture, nutrient concentration, and mycorrhizal colonization [1,2,3,4]. The diverse trade-offs among fine root traits may lead to a range of distinct resource-foraging strategies [5], which may vary depending on the tree species, nutrient type (organic vs. inorganic nutrients), and fine root traits (thicker vs. thinner roots) [5,6,7,8]. Currently, it remains unclear whether and how changes in soil nutrient availability will lead to integrated responses in root traits within and across species.
Recent studies suggest that resource acquisition may be categorized into acquisition and conservation strategies based on root functional trait combinations [9,10,11]. Thinner roots with higher branching [12] and a higher specific root length (SRL) [2,13] represent one acquisition strategy. In contrast, roots with conservative strategies typically have thicker roots [14], a lower SRL [14], less branching, and greater dependence on mycorrhizal fungi [5,13]. However, the response of root functional traits to soil fertility is inconsistent within and between species. According to recent research, when nitrogen was added, fine root diameter decreased and SRL increased in terms of morphological traits [15,16]. However, no significant effects were observed in other related studies [17,18]. Meanwhile, tremendous variation has often been observed even for the same tree species. For instance, Pinus sylvestris showed contrasting variation patterns in the morphological traits of absorptive roots in two studies along similar latitudinal and nutrient availability gradients [19,20]. Overall, discovering how root functional traits mediate below-ground foraging strategies will require further investigation.
Fine root proliferation (via biomass allocation) should be another important dimension of the foraging strategies of fine roots, which is distinct from root functional traits (such as root morphology and architecture) [4]. Some studies have shown that fine root proliferation is more plastic under nutrient limitation than that caused by morphological traits [21,22]. In response to variations in nutrient supply, phenotypic modifications in root biomass allocation were 2.5 times more significant than in SRL in modulating the relative length of roots in plants exploring soil [21]. Currently, most previous studies on nutrient acquisition strategies have focused on the plasticity of root morphological and architectural traits [3,10,23], while less attention has been focused on biomass plasticity and its contribution to nutrient acquisition. The responses of fine root proliferation to changes in soil nutrients remain inconsistent. For example, in nutrient-rich patches, plants may increase [24,25,26] or decrease [27,28] absorptive root biomass or show no effects [29,30,31]. Therefore, elucidating how fine root biomass (FRB) responds to changes in soil nutrients and the trade-off between root biomass allocation and functional trait plasticity is central to clarifying the nutrient acquisition strategies of plants and predicting tree species’ adaptability to global changes.
Furthermore, responses of fine root proliferation and functional traits to soil nutrients may vary with nutrient patch type and mycorrhizal colonization [6,32,33]. A study by Liu et al. [6] showed that root growth increased but mycorrhizal colonization decreased significantly under multi-nutrient addition; nevertheless, the addition of N or P did not result in any appreciable changes. Li et al. [34] reported a significant decrease in absorptive root biomass and tissue density (RTD) and a significant increase in SRL in C. lanceolata under the addition of P. In contrast, none of these traits changed significantly under the addition of N. Recent studies revealed that fine root growth and mycorrhizal associations are complementary in resource acquisition [2]. Thinner-root species rely more on root growth and the associated traits, whereas thicker-root species depend more on mycorrhizae to obtain soil nutrients [5,6]. Therefore, different nutrient types may influence the responses of roots and mycorrhizal fungi in a different manner. A comprehensive understanding of how different nutrient types influence the responses of fine root growth remains limited. It is necessary to pay more attention to the effects of nutrient types on root nutrient acquisition.
Fine roots with an average diameter (AD) of less than 2 mm comprise a complex system with significant functional differences among other root orders [35]. Fine roots can be functionally divided into two modules according to the branching level: orders 1 and 2 for absorptive fine roots (AFRs) and orders 3 to 5 for transport fine roots (TFRs). Significant differences exist in the morphological, architectural, and chemical traits between the two modules [26,36,37], which better reflect differentiated functions. Therefore, the use of function-based root classification methods may help us gain insight into the strategies employed by roots to acquire nutrients. The present study investigated the responses of proliferation and morphological traits of AFRs and TFRs to inorganic and organic nutrient addition.
C. lanceolata, as a vital source of timber and bioenergy, is widely distributed and cultivated in subtropical regions in China. Despite its widespread cultivation, the monolithic cultivation practices have led to a series of problems such as simple stand structure, poor resilience, and soil nutrient loss, which in turn has led to a reduction in productivity. To address these challenges, recent studies have shown that the establishment of coniferous–broadleaf mixed forests can improve forest productivity, carbon sequestration capacity, and soil nutrient status [38]. Q. acutissima is a deciduous broad-leaved tree species, which is the main component of forest vegetation in the warm temperate and subtropical regions of China. Due to its strong adaptability and easy afforestation and cultivation, Q. acutissima is an excellent tree species for soil and water conservation. In recent years, mixing C. lanceolata and Q. acutissima to form a mixed forest is a common practice in forest management in China. Therefore, understanding the fine root acquisition strategies of both tree species for different nutrients is important for plantation management. We hypothesized the following: (1) nutrient addition results in decreased carbon (C) allocation to fine roots (decreased biomass, total root length (TRL), and mycorrhizal colonization rate), and root biomass and length growth exhibits stronger plasticity than morphological traits; (2) AFRs (resource acquisition module) are more responsive in biomass growth and morphological plasticity than TFRs; and (3) fine root biomass (FRB) and the mycorrhizal colonization rate for C. lanceolata are higher in inorganic nutrient patches and, correspondingly, higher in organic nutrient patches for Q. acutissima.

2. Materials and Methods

2.1. Study Site and Species Selection

This study was conducted at Wuxiang Temple National Forest Park in Nanjing City, Jiangsu Province, China (31°36′ N, 119°01′ E). The site is located in a subtropical monsoon climate zone with distinct seasons, often experiencing simultaneous rainfall and heat. The hilly terrain of the site has an average elevation of around 100 m. The sandy, slightly acidic soil is covered by forest vegetation that mainly consists of secondary forests formed through planting C. lanceolata and Q. acutissima. Understory vegetation includes Ilex chinensis, Ilex cornuta, Smilax china, Lygodium japonicum, and Ophiopogon japonicus. C. lanceolata is a thicker-root species (AM tree, AFRs diameter < 0.60 mm) and Q. acutissima is a thinner-root species (ECM tree, AFRs diameter < 0.30 mm). The average diameter (AD) at breast height of Q. acutissima was 18.75 cm, with an average tree height of 20.93 m, while the corresponding values for C. lanceolata were 15.8 cm and 17.3 m. Three 30 × 30 m2 plots were established in both C. lanceolata and Q. acutissima forests for a total of six plots. In late April 2022, 12 trees of each of the two species were selected, which had a healthy appearance and similar diameters at breast height. Early in April 2022, soil samples were collected and measured for their chemical properties from 0 to 10 cm depth. Soil total C and total N were 47.14 ± 6.51 and 2.71 ± 0.36 g kg−1 (mean ± SE), respectively. Soil available N (KCl-extractable ammonium and nitrate) was 20.46 ± 1.18 mg kg−1. Soil total and available phosphorus were 0.40 ± 0.02 g kg−1 and 14.12 ± 2.38 mg kg−1, respectively. Soil pH was 4.4 ± 0.1 (soil-to-water mass ratio of 1:2.5).

2.2. Nutrient Treatment and Root Chamber Installation

Considering that chemical fertilizers such as urea and calcium superphosphate are commonly applied as base fertilizers during the planting phase or the early growth stage (typically 1–5 years) for both tree species, and the subsequent self-fertilization effect of litter during the later growth stages in the plantation management [39], three treatments were applied around each species: control (unfertilized, CK), inorganic nutrient (NPK, Osmocote, slow-release fertilizer containing 15%N-9%P-10%K, duration for 8–9 months), and organic nutrient (F, crushed leaf litter). According to the results of Adams et al. [40], for an effective root response, 9 g of chemical fertilizer per root chamber was applied, resulting in a significant eight-fold increase in ammonium and nitrate release relative to background available soil N concentration, and they observed significant increases in root length growth at higher levels of N fertilization (10–30 times available soil N concentration) and 20 g leaf litter per root chamber for organic nutrient treatment [5,40]. In the fall of 2021, we collected leaves from both stands and mixed equal amounts of each species to make a single homogeneous deciduous layer to be used as the organic nutrient treatment (F). To reduce the effects of soil heterogeneity and ensure comparability between species, soil from the mixed forest of C. lanceolata and Q. acutissima was chosen. Soil at a 0–10 cm depth from the mixed forest was sieved (5 mm) to remove roots and gravel. Before installing the root chamber, the sieved soil was mixed with inorganic nutrients (NPK) and organic nutrients (F) in the amounts described above, respectively. And then the soil mixed with fertilizers were divided into root chambers for subsequent installation. No further fertilizer was applied during the growing season.
After completing the fertilization treatment, the root chamber was installed (Figure 1). Root chambers with a height, width, and length of 8, 10, and 15 cm, respectively, were made of 0.1 cm thick PVC plastic and surrounded by 1 mm diameter holes to enhance water and gas exchange with the surrounding soil [41]. Removable upper covers facilitated root arrangement and removal. One hole with a diameter of 1 cm was set on one side of each chamber for the insertion of fine roots. Root tips with a consistent branching status were selected to reduce differences between treatments. A root tip was carefully cleaned and inserted into each root chamber through the side hole, with the inserted root tip length standardized at 5 cm. Each root chamber was then filled with treated soil based on treatment type, sealed with a top cover, buried at a depth of 0–10 cm, and covered with litter. Locations of all root chambers were marked and mapped.

2.3. Root Chamber Harvesting and Processing

Root chambers were harvested in September 2022. Roots entering chambers were cut with scissors from the primary root system without ripping or tearing. Chambers were placed in zip-lock-type plastic bags, transported to the lab, and stored at 4 °C until further analysis. In the lab, all roots were carefully removed from each chamber and divided into absorptive roots (ephemeral first- and second-order roots) and transport roots (third- to fifth-order roots) [42] using the functional classification [36]. Roots were scanned with an Expression 10000XL scanner at 400 dpi (Epson Seiko Corp., Nagano, Japan), and morphological traits were determined (average diameter, total root length, total surface area, total volume); in addition, the number of root tips was quantified using WinRHIZO Pro 2005b software (Regent Instruments Inc., Quebec City, QC, Canada). After scanning, root samples were oven-dried (65 °C, 72 h) and weighed. Soil in chambers was collected and stored (4 °C) for soil physico-chemical analyses. Detailed descriptions for root traits are shown in Table 1.
Dried root samples (AFRs and TFRs) were mixed, ball-milled, and analyzed for root nitrogen concentration (RN) by a PerkinElmer 2400II CN-element analyzer (PerkinElmer, Waltham, MA, USA) [43]. The root samples were digested by H2SO4-H2O2 solution, and then root phosphorus concentration (RP) was quantified by Mo–Sb spectrometry after conversion to phosphomolybdenum blue [44].
Acid fuchsin staining was used to measure the AM colonization of C. lanceolata roots [45]. After removing the sample from the FAA solution, it was washed carefully with deionized water. The roots were then cleaned in a heated 10% (w/v) KOH solution for 50 min at 90 °C, acidified for 5 min at ambient temperature using 2% HCl, and dyed for 20 min at 90 °C using 0.05% (w/v) acid fuchsin [6]. Subsequently, at ×200 magnification (Leica DM 2500; Leica Mikrosysteme Vertrieb GmbH, Bensheim, Germany), the AM colonization of fifty 1-cm-long root segments of each tree’s first-order roots was measured. Arbuscules, vesicles, non-septate, and pink-colored hyphae within the roots were all considered evidence of AM colonization [46]. For each Q. acutissima root sample, 100 root tips were inspected under a 20× magnification microscope. The root tip with a cover of yellow-brown to golden-brown swollen mantle was determined to have ECM colonization [47]. The formula below was used to calculate mycorrhizal colonization [6]: colonization (%) = number of root tips colonized/total number of root tips × 100%.
To compare the magnitude of plasticity for root traits, the Coefficient of Variation (CV) was calculated as an index of trait plasticity [22,48]. For each trait and species, CV scores were calculated as 100 × SDX/ X ¯ where SDX is the standard deviation of treatment means, and X ¯ is the grand mean of treatment means. The CV scores of AFRs and TFRs for both species were calculated among the CK, NPK, and F treatments or between the CK and NPK or F treatment; then, these were averaged for each trait and ranked to compare the relative plasticity.

2.4. Data Analysis

A multivariate analysis of variance (ANOVA) was performed to explore the effects of species, treatments, root orders, and their interactive effects on FRB, TRL, AD, SRL, SRA, and RTD. A two-way ANOVA was used to analyze the effects of species and treatments on BR, BI, RN, and RP. We also analyzed the effect of nutrient additions on each trait index by one-way ANOVA. When appropriate, post hoc means comparisons were made using least squares difference tests for further interpretations and to produce graphical illustrations. Prior to statistical analysis, Shapiro–Wilk and Levene’s tests were used to check the normality of the data and homogeneity of variance, and they were transformed if needed using either logarithmic or square-root transformation to meet the criteria for normal distribution and homogeneity of variance. Differences at p < 0.05 were considered significant. All analyses were performed in SPSS v25 software (IBM Corp., Armock, NY, USA).

3. Results

3.1. Response of Fine Root Growth to Nutrient Addition

Root category, nutrient treatments, species, and their interactions significantly affected TRL and FRB (Table 2, p < 0.01). Compared to CK, the FRB and TRL of AFRs for C. lanceolata significantly decreased in NPK and F treatments, while TFRs remained stable for FRB and decreased for TRL only in NPK treatment (Figure 2, p < 0.05). In contrast, FRB decreased for Q. acutissima after nutrient addition, but the difference was only significant between NPK and CK treatments. The TRL of AFRs for Q. acutissima significantly decreased by 81 and 52% in NPK and F treatments, but the TRL of TFRs showed no response effects in NPK treatment, while the F treatment increased by 21% (Figure 2).
In addition, the relative biomass of AFRs to TFRs also showed different patterns between both species (Figure 3). The AFR proportion of FRB decreased markedly for C. lanceolata in NPK and F treatments by 39 and 21%, respectively, whereas the AFR proportion for Q. acutissima slightly declined after nutrient additions for an 8%–9% change.

3.2. Response of Root Functional Traits and Mycorrhizal Colonization Rate to Nutrient Addition

The effects of nutrient addition on AD, SRL, SRA, and RTD depended on nutrient type, species, and root category (Table 2; Figure 4). Compared to CK treatment, the AD of AFRs for C. lanceolata significantly increased by 37 and 19% in NPK and F treatments (p < 0.05, Figure 4a), but no significant effects occurred in TFRs. In contrast, the AD of AFRs and TFRs for Q. acutissima decreased significantly only in NPK treatment (p < 0.05). SRL decreased significantly in AFRs for both species and TFRs for C. lanceolata in the NPK treatment but increased in TFRs for Q. acutissima (p < 0.05, Figure 4b). However, only the SRA of TFRs for Q. acutissima and RTD of AFRs for C. lanceolata showed significant differences in NPK treatment. There were no significant differences in SRL, SRA, and RTD between F and CK treatments (Figure 4b–d).
Nutrient addition had significant effects on BR and BI of both tree species (p < 0.01, Table 2; Figure 4e,f). In the NPK treatment, the BR and BI for C. lanceolata decreased significantly by 57.11 and 66.23%, respectively, when compared with the CK treatment (p < 0.05). However, the opposite results were observed for Q. acutissima. In the F treatment, the BR and BI increased significantly for Q. acutissima by 170 and 302%, respectively (p < 0.05). In contrast, the BR and BI showed a decreasing pattern for C. lanceolata, which was only significantly different in the BR.
Nutrient addition, tree species, and their interaction significantly affected the RN and RP (p < 0.01, Table 2). Inorganic nutrient addition significantly increased the RP of both species and the RN of Q. acutissima, but decreased the RN of C. lanceolata by 20%. However, the RN of both species and the RP of C. lanceolata were significantly lower after organic nutrient addition compared to CK treatment, but Q. acutissima had a 66% increase in RP (Figure 5a).
Nutrient addition had opposite effects on mycorrhizal colonization rates for both tree species. The AM colonization rate for C. lanceolata increased significantly by 43.6 and 21.5% in NPK and F treatments, respectively (p < 0.05, Figure 5b). In contrast, the ECM colonization rate of Q. acutissima decreased significantly in the F treatment and declined slightly in the NPK treatment (p < 0.05, Figure 5b).

3.3. Plasticity of Fine Root Proliferation and Functional Traits to Nutrient Addition

Traits varied markedly in response to soil nutrient availability (Table 3). The traits TRL, TP, FRB, and BI exhibited the highest plasticity in response to fertilization. The four least plastic root traits in response to fertilization were AD, SRA, RTD, and SRL. At the same time, most root traits showed a higher CV between the CK and NPK treatments, indicating a stronger plasticity response of root traits in the NPK treatment. The AFRs showed a stronger plasticity response of root biomass and length than the TFRs across species.

4. Discussion

4.1. Responses of Fine Root Proliferation and Mycorrhizae to Nutrient Addition

In our study, nutrient addition resulted in decreased FRB and TRL (Figure 2 and Figure 3; Table 2), supporting our first hypothesis and coinciding with previous studies reporting a decrease in FRB or TRL in nutrient-rich patches [8,22]. According to the cost–benefit theory [49], trees can maximize benefits and minimize costs by allocating less carbon (C) to soil resource acquisition in nutrient-rich patches [18,50]. However, the results were inconsistent with other studies in which nutrient addition increased FRB or TRL [8,22]. The different conclusions might result from the difference in soil nutrient availability and other soil conditions since earlier studies were conducted in temperate or subtropical forests with lower soil nutrient concentrations. In our plots, the average total C, total N, and available N concentrations in surface soil were 47.14 ± 6.51, 2.71 ± 0.36 g kg−1, and 20.46 ± 1.18 mg kg−1, respectively, which were much higher than the finding in the investigation by Liu et al. [49], resulting in relatively high nutrient levels in nutrient-rich patches.
Nutrient addition resulted in a decreased rate of mycorrhizal colonization in Q. acutissima but increased C. lanceolata, which partially supported our first hypothesis. These results indicated that the nutrient acquisition strategies of these two species were inconsistent. C. lanceolata depended more on mycorrhizal fungi to acquire nutrients in nutrient-rich patches, while fine roots were more sensitive than mycorrhizal symbiosis in Q. acutissima. Previous studies showed that trade-offs and competition existed between fine roots and mycorrhizal fungi in below-ground carbon (C) allocation for growth and maintenance [5,17]. Compared to hyphae with a high turnover rate, thinner-root species (e.g., Q. acutissima) have lower root construction costs; therefore, it is not surprising that they exhibit thinner roots and have more branching to acquire nutrients from the soil (Figure 4a,e) [5,7,8]. In contrast, increasing root biomass and length may be inefficient for expanding the surface area of absorptive roots in thick-root species (e.g., C. lanceolata) due to higher construction costs. Instead, it may be more efficient to invest C into finer mycorrhizal fungal hyphae [23,49,51]. The inconsistent nutrient acquisition strategies between tree species may facilitate ecological niche partitioning and inter-specific coexistence in mixed forests.
For root biomass and growth in length, AFRs were more responsive to nutrient addition than TFRs (Figure 2, Table 3). Although a decreasing trend in root biomass and length under nutrient addition was observed for both AFRs and TFRs for Q. acutissima, the magnitude of the decrease was more pronounced for AFRs compared to TFRs (Table 3). This result supports our second hypothesis and agrees with previous findings that lower-order roots (i.e., AFRs) respond more strongly than higher-order roots (i.e., TFRs) to increased nutrient availability [16,47]. This occurs because AFRs play an important role in resource acquisition, making them more responsive to environmental changes [26,52].

4.2. Response of Fine Root Functional Traits to Nutrient Addition

Root foraging strategies can shift between a conservative and an acquisitive strategy by adjusting functional root traits [3,53]. In the present study, although root biomass and length growth responded similarly to nutrient addition in both tree species, functional root traits responded differently (Figure 4 and Figure 5). The diameter of AFRs for C. lanceolata increased, while RN, BR, and BI decreased after nutrient addition; the opposite occurred for Q. acutissima. This indicated the shifts of different root foraging strategies after nutrient addition with more acquisitive roots for Q. acutissima and more conservative roots for C. lanceolata, which was consistent with previous studies [3,13,14,54]. Typically, an increase in the branching ratio and root nitrogen (N) concentration indicates a shift toward an acquisitive strategy, as pointed out by Weemstra et al. [13] and Li et al. [13]. This strategy tends to enhance the efficiency of soil exploration per unit carbon (C) and simultaneously diminishes the reliance on mycorrhizal fungi [13]. The increase in mycorrhizal colonization represents a conservative strategy in which roots allocate more C to mycorrhizal fungi [13]. The proportion of AFR biomass in C. lanceolata significantly declined after nutrient addition, which also verified the conservative traits in root foraging strategies (Figure 3).

4.3. Comparison of the Magnitude of Plasticity between Root Growth and Morphological Traits

In the present study, FRB and length growth showed stronger plasticity to nutrient addition than morphological traits (Table 3). These results also supported the first hypothesis and were consistent with recent views that FRB was more plastic in response to environmental changes and adjustments in carbohydrate allocation to root biomass, rather than morphological adjustments to SRL; these were important patterns for plant adaptation to changes in soil fertility [21,22]. The results of this study suggested that plasticity in root functional traits, at least in terms of morphological traits (e.g., root diameter, SRL), may be less important for resource acquisition than plasticity in leaf traits (e.g., specific leaf area) [21,22] and that root biomass plasticity may be more important in below-ground nutrient acquisition strategies [22]. Furthermore, root traits affecting nutrient acquisition involve three aspects: the amount of fine roots (FRB), morphological traits (AD, SRL, BI, and BR), and root activity (root N concentration) [4,14]. We therefore speculated that the most important action for a plant was to adjust the amount of carbohydrates distributed to roots (FRB) in response to changes in soil nutrients and then optimize morphological traits and root activity to maximize nutrient absorption efficiency. This highlighted the need for researchers to better understand the role of root functional traits in plant economics, emphasizing that root biomass allocation should be central in plant responses to changing environmental conditions, especially in changes in soil fertility.

4.4. Responses of Roots and Mycorrhizal Fungi to Different Types of Nutrient-Rich Patches

The results of the present study did not support the third hypothesis that the FRB and the mycorrhizal colonization rate were higher in inorganic nutrient patches for C. lanceolata and higher in organic nutrient patches for Q. acutissima. We found similar plasticity responses of FRB and morphological traits in NPK and F patches (Figure 2 and Figure 3) but a greater magnitude of phenotypic plasticity in the NPK patches than in F patches (Figure 2, Figure 3 and Figure 4; Table 3). This may depend on soil nutrient content. In this study, although slow-release fertilizer was used, nutrient availability in NPK patches was higher than in F patches (Table S1). However, organic matter (leaf) mineralization in F patches provides long-lasting nutrient release [55] but with lower immediate nutrient availability. Our experiment only had an observation period of 4–5 months, which may be insufficient for producing enough nutrients from organic matter to elicit a strong response in fine root traits. Thus, we suggest that a longer observation period will be needed to investigate the plastic responses of fine root traits to organic nutrient patches.

5. Conclusions

In this study, the nutrient-foraging strategies of fine roots exhibited marked differences between the roots of Q. acutissima and C. lanceolata. Although root biomass and length growth decreased under nutrient addition for both species, fine root morphological and architectural traits showed significantly different plastic responses. C. lanceolata depends on mycorrhizal fungi for resource acquisition, while Q. acutissima may acquire soil nutrients by increasing root branching. The divergent nutrient acquisition strategies among tree species may facilitate plant species coexistence and distribution under nutrient availability change. By comparing the CV of fine root traits across treatments and species, total root length (TRL) and fine root biomass (FRB) were the most plastic traits in response to nutrient addition. The results suggested that FRB and length growth were more important indicators for nutrient acquisition strategies than morphological traits. Additionally, the root biomass growth and functional traits of AFRs were more responsive to nutrient addition than TFRs, and the magnitude of root trait plasticity in inorganic patches was greater than in organic patches. Future research is needed to reveal how root biomass, functional traits, and soil conditions together mediate below-ground resource-foraging strategies under root competition, especially for the contribution of root biomass allocation.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/f15020336/s1, Table S1: Soil nutrient concentration in root chamber after root harvesting.

Author Contributions

Conceptualization, X.X. and S.Y.; methodology, X.X., G.W. and S.Y.; software and formal analysis, X.X. and R.T.; validation, S.Y. and X.X.; investigation, X.X., R.T. and H.S.; data curation, X.X.; writing—original draft preparation, X.X.; writing—review and editing, X.X., S.Y., J.G. and W.W.; visualization, X.X.; project administration, S.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Key Research and Development Program of China (No. 2021YFD2200402), the Key Project of the Open Competition in Jiangsu Forestry (No. LYKJ [2022]01), and the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 20KJA220002).

Data Availability Statement

Data will be made available on request.

Acknowledgments

The authors thank Wenbin Zhai and Xiaoshun Fu for their help with field and laboratory work.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Bardgett, R.D.; Mommer, L.; De Vries, F.T. Going underground: Root traits as drivers of ecosystem processes. Trends Ecol. Evol. 2014, 29, 692–699. [Google Scholar] [CrossRef]
  2. Bergmann, J.; Weigelt, A.; van Der Plas, F.; Laughlin, D.C.; Kuyper, T.W.; Guerrero-Ramirez, N.; Valverde-Barrantes, O.J.; Bruelheide, H.; Freschet, G.T.; Iversen, C.M. The fungal collaboration gradient dominates the root economics space in plants. Sci. Adv. 2020, 6, eaba3756. [Google Scholar] [CrossRef] [PubMed]
  3. Liao, Y.; Fan, H.; Wei, X.; Wang, H.; Shen, F.; Hu, L.; Li, Y.; Fang, H.; Huang, R. Shifting of the first-order root foraging strategies of Chinese fir (Cunninghamia lanceolata) under varied environmental conditions. Trees 2023, 37, 921–932. [Google Scholar] [CrossRef]
  4. McCormack, M.L.; Guo, D.; Iversen, C.M.; Chen, W.; Eissenstat, D.M.; Fernandez, C.W.; Li, L.; Ma, C.; Ma, Z.; Poorter, H. Building a better foundation: Improving root-trait measurements to understand and model plant and ecosystem processes. New Phytol. 2017, 215, 27–37. [Google Scholar] [CrossRef] [PubMed]
  5. Chen, W.; Koide, R.T.; Adams, T.S.; Deforest, J.L.; Cheng, L.; Eissenstat, D.M. Root morphology and mycorrhizal symbioses together shape nutrient foraging strategies of temperate trees. Proc. Natl. Acad. Sci. USA 2016, 113, 8741. [Google Scholar] [CrossRef] [PubMed]
  6. Liu, B.; Li, H.; Zhu, B.; Koide, R.T.; Eissenstat, D.M.; Guo, D. Complementarity in nutrient foraging strategies of absorptive fine roots and arbuscular mycorrhizal fungi across 14 coexisting subtropical tree species. New Phytol. 2015, 208, 125–136. [Google Scholar] [CrossRef] [PubMed]
  7. Cheng, L.; Chen, W.; Adams, T.S.; Wei, X.; Li, L.; McCormack, M.L.; DeForest, J.L.; Koide, R.T.; Eissenstat, D.M. Mycorrhizal fungi and roots are complementary in foraging within nutrient patches. Ecology 2016, 97, 2815–2823. [Google Scholar] [CrossRef] [PubMed]
  8. Ma, X.; Ni, X.; Guo, Z.; Zou, X.; Chen, J.; Shen, W.; Kuzyakov, Y. Nitrogen addition influences fine root growth and mycorrhizal symbiosis formation in trees with contrasting root morphology. Appl. Soil Ecol. 2023, 189, 104987. [Google Scholar] [CrossRef]
  9. Ostonen, I.; Helmisaari, H.S.; Borken, W.; Tedersoo, L.; Kukumägi, M.; Bahram, M.; Lindroos, A.J.; Nöjd, P.; Uri, V.; Merilä, P. Fine root foraging strategies in Norway spruce forests across a European climate gradient. Glob. Change Biol. 2011, 17, 3620–3632. [Google Scholar] [CrossRef]
  10. Kong, D.; Wang, J.; Wu, H.; Valverde-Barrantes, O.J.; Wang, R.; Zeng, H.; Kardol, P.; Zhang, H.; Feng, Y. Nonlinearity of root trait relationships and the root economics spectrum. Nat. Commun. 2019, 10, 2203. [Google Scholar] [CrossRef]
  11. Weemstra, M.; Freschet, G.T.; Stokes, A.; Roumet, C. Patterns in intraspecific variation in root traits are species-specific along an elevation gradient. Funct. Ecol. 2021, 35, 342–356. [Google Scholar] [CrossRef]
  12. Kramer-Walter, K.R.; Bellingham, P.J.; Millar, T.R.; Smissen, R.D.; Richardson, S.J.; Laughlin, D.C. Root traits are multidimensional: Specific root length is independent from root tissue density and the plant economic spectrum. J. Ecol. 2016, 104, 1299–1310. [Google Scholar] [CrossRef]
  13. Ma, Z.; Guo, D.; Xu, X.; Lu, M.; Bardgett, R.D.; Eissenstat, D.M.; McCormack, M.L.; Hedin, L.O. Evolutionary history resolves global organization of root functional traits. Nature 2018, 555, 94–97. [Google Scholar] [CrossRef]
  14. Weemstra, M.; Mommer, L.; Visser, E.J.; van Ruijven, J.; Kuyper, T.W.; Mohren, G.M.; Sterck, F.J. Towards a multidimensional root trait framework: A tree root review. New Phytol. 2016, 211, 1159–1169. [Google Scholar] [CrossRef] [PubMed]
  15. Wang, W.; Mo, Q.; Han, X.; Hui, D.; Shen, W. Fine root dynamics responses to nitrogen addition depend on root order, soil layer, and experimental duration in a subtropical forest. Biol. Fertil. Soils 2019, 55, 723–736. [Google Scholar] [CrossRef]
  16. Wang, G.; Fahey, T.J.; Xue, S.; Liu, F. Root morphology and architecture respond to N addition in Pinus tabuliformis, west China. Oecologia 2013, 171, 583–590. [Google Scholar] [CrossRef]
  17. Ma, X.; Zhu, B.; Nie, Y.; Liu, Y.; Kuzyakov, Y. Root and mycorrhizal strategies for nutrient acquisition in forests under nitrogen deposition: A meta-analysis. Soil Biol. Biochem. 2021, 163, 108418. [Google Scholar] [CrossRef]
  18. Li, W.; Jin, C.; Guan, D.; Wang, Q.; Wang, A.; Yuan, F.; Wu, J. The effects of simulated nitrogen deposition on plant root traits: A meta-analysis. Soil Biol. Biochem. 2015, 82, 112–118. [Google Scholar] [CrossRef]
  19. Zadworny, M.; McCormack, M.L.; Żytkowiak, R.; Karolewski, P.; Mucha, J.; Oleksyn, J. Patterns of structural and defense investments in fine roots of Scots pine (Pinus sylvestris L.) across a strong temperature and latitudinal gradient in Europe. Glob. Change Biol. 2017, 23, 1218–1231. [Google Scholar] [CrossRef]
  20. Ostonen, I.; Truu, M.; Helmisaari, H.S.; Lukac, M.; Borken, W.; Vanguelova, E.; Godbold, D.L.; Lõhmus, K.; Zang, U.; Tedersoo, L. Adaptive root foraging strategies along a boreal–temperate forest gradient. New Phytol. 2017, 215, 977–991. [Google Scholar] [CrossRef]
  21. Freschet, G.T.; Swart, E.M.; Cornelissen, J.H. Integrated plant phenotypic responses to contrasting above-and below-ground resources: Key roles of specific leaf area and root mass fraction. New Phytol. 2015, 206, 1247–1260. [Google Scholar] [CrossRef]
  22. Kramer-Walter, K.R.; Laughlin, D.C. Root nutrient concentration and biomass allocation are more plastic than morphological traits in response to nutrient limitation. Plant Soil 2017, 416, 539–550. [Google Scholar] [CrossRef]
  23. Kong, D.; Ma, C.; Zhang, Q.; Li, L.; Chen, X.; Zeng, H.; Guo, D. Leading dimensions in absorptive root trait variation across 96 subtropical forest species. New Phytol. 2014, 203, 863–872. [Google Scholar] [CrossRef] [PubMed]
  24. Bolte, A.; Villanueva, I. Interspecific competition impacts on the morphology and distribution of fine roots in European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.). Eur. J. For. Res. 2006, 125, 15–26. [Google Scholar] [CrossRef]
  25. Cahill, J.F., Jr.; McNickle, G.G.; Haag, J.J.; Lamb, E.G.; Nyanumba, S.M.; St. Clair, C.C. Plants integrate information about nutrients and neighbors. Science 2010, 328, 1657. [Google Scholar] [CrossRef] [PubMed]
  26. Kou, L.; Jiang, L.; Fu, X.; Dai, X.; Wang, H.; Li, S. Nitrogen deposition increases root production and turnover but slows root decomposition in Pinus elliottii plantations. New Phytol. 2018, 218, 1450–1461. [Google Scholar] [CrossRef] [PubMed]
  27. Fitter, A.; Caldwell, M.; Pearcy, R. Architecture and biomass allocation as components of the plastic response of root systems to soil heterogeneity. In Exploitation of Environmental Heterogeneity by Plants: Ecophysiological Processes Above-and Belowground; Academic Press: New York, NY, USA, 1994; Volume 7, pp. 305–323. [Google Scholar]
  28. Grime, J.P.; Mackey, J. The role of plasticity in resource capture by plants. Evol. Ecol. 2002, 16, 299–307. [Google Scholar] [CrossRef]
  29. Farley, R.; Fitter, A. The responses of seven co-occurring woodland herbaceous perennials to localized nutrient-rich patches. J. Ecol. 1999, 87, 849–859. [Google Scholar] [CrossRef]
  30. Johnson, H.A.; Biondini, M.E. Root morphological plasticity and nitrogen uptake of 59 plant species from the Great Plains grasslands, USA. Basic Appl. Ecol. 2001, 2, 127–143. [Google Scholar] [CrossRef]
  31. Peng, Y.; Guo, D.; Yang, Y. Global patterns of root dynamics under nitrogen enrichment. Glob. Ecol. Biogeogr. 2017, 26, 102–114. [Google Scholar] [CrossRef]
  32. Hodge, A.; Fitter, A.H. Substantial nitrogen acquisition by arbuscular mycorrhizal fungi from organic material has implications for N cycling. Proc. Natl. Acad. Sci. USA 2010, 107, 13754–13759. [Google Scholar] [CrossRef]
  33. Chen, W.; Koide, R.T.; Eissenstat, D.M. Nutrient foraging by mycorrhizas: From species functional traits to ecosystem processes. Funct. Ecol. 2018, 32, 858–869. [Google Scholar] [CrossRef]
  34. Li, L.; Zhou, G.; Liu, J.; Li, H. The resource investigation and community structure characteristics of mycorrhizal fungi associated with Chinese fir. Afr. J. Biotechnol. 2011, 10, 5719–5724. [Google Scholar]
  35. McCormack, M.L.; Kaproth, M.A.; Carlson, E.; Hipp, A.L.; Han, Y.; Kennedy, P.G. Climate and phylogenetic history structure morphological and architectural trait variation among fine-root orders. New Phytol. 2020, 228, 1824–1834. [Google Scholar] [CrossRef]
  36. McCormack, M.L.; Dickie, I.A.; Eissenstat, D.M.; Fahey, T.J.; Fernandez, C.W.; Guo, D.; Helmisaari, H.S.; Hobbie, E.A.; Iversen, C.M.; Jackson, R.B. Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes. New Phytol. 2015, 207, 505–518. [Google Scholar] [CrossRef]
  37. Xia, M.; Guo, D.; Pregitzer, K.S. Ephemeral root modules in Fraxinus mandshurica. New Phytol. 2010, 188, 1065–1074. [Google Scholar] [CrossRef] [PubMed]
  38. Wan, X.; Huang, Z.; He, Z.; Hu, Z.; Yang, J.; Yu, Z.; Wang, M. Effects of broadleaf plantation and Chinese fir (Cunninghamia lanceolata) plantation on soil carbon and nitrogen pools. Chin. J. Appl. Ecol. 2013, 24, 345–350. [Google Scholar]
  39. Sharma, A.; Chetani, R. A review on the effect of organic and chemical fertilizers on plants. Int. J. Res. Appl. Sci. Eng. Technol. 2017, 5, 677–680. [Google Scholar] [CrossRef]
  40. Adams, T.S.; McCormack, M.L.; Eissenstat, D.M. Foraging strategies in trees of different root morphology: The role of root lifespan. Tree Physiol. 2013, 33, 940–948. [Google Scholar] [CrossRef] [PubMed]
  41. Hertel, D.; Leuschner, C. The in situ root chamber: A novel tool for the experimental analysis of root competition in forest soils. Pedobiologia 2006, 50, 217–224. [Google Scholar] [CrossRef]
  42. Pregitzer, K.S.; DeForest, J.L.; Burton, A.J.; Allen, M.F.; Ruess, R.W.; Hendrick, R.L. Fine root architecture of nine North American trees. Ecol. Monogr. 2002, 72, 293–309. [Google Scholar] [CrossRef]
  43. Yang, N.; Wang, B.; Liu, D.; Wang, X.; Li, X.; Zhang, Y.; Xu, Y.; Peng, S.; Ge, Z.; Mao, L. Long-term nitrogen deposition alters ectomycorrhizal community composition and function in a poplar plantation. J. Fungi 2021, 7, 791. [Google Scholar] [CrossRef] [PubMed]
  44. Bao, S. Agricultural Chemical Analysis of Soil, 3rd ed.; China Agriculture Press: Beijing, China, 2016. [Google Scholar]
  45. Giovannetti, M.; Mosse, B. An evaluation of techniques for measuring vesicular arbuscular mycorrhizal infection in roots. New Phytol. 1980, 489–500. [Google Scholar] [CrossRef]
  46. McGonigle, T.P.; Miller, M.H.; Evans, D.; Fairchild, G.; Swan, J.A. A new method which gives an objective measure of colonization of roots by vesicular—Arbuscular mycorrhizal fungi. New Phytol. 1990, 115, 495–501. [Google Scholar] [CrossRef]
  47. Kou, L.; Guo, D.; Yang, H.; Gao, W.; Li, S. Growth, morphological traits and mycorrhizal colonization of fine roots respond differently to nitrogen addition in a slash pine plantation in subtropical China. Plant Soil 2015, 391, 207–218. [Google Scholar] [CrossRef]
  48. Schlichting, C.D.; Levin, D.A. Phenotypic plasticity: An evolving plant character. Biol. J. Linn. Soc. 1986, 29, 37–47. [Google Scholar] [CrossRef]
  49. Eissenstat, D.; Yanai, R. The ecology of root lifespan. In Advances in Ecological Research; Elsevier: Amsterdam, The Netherlands, 1997; Volume 27, pp. 1–60. [Google Scholar]
  50. Li, L.; McCormack, M.L.; Chen, F.; Wang, H.; Ma, Z.; Guo, D. Different responses of absorptive roots and arbuscular mycorrhizal fungi to fertilization provide diverse nutrient acquisition strategies in Chinese fir. For. Ecol. Manag. 2019, 433, 64–72. [Google Scholar] [CrossRef]
  51. Lee, M.-H.; Comas, L.H.; Callahan, H.S. Experimentally reduced root–microbe interactions reveal limited plasticity in functional root traits in Acer and Quercus. Ann. Bot. 2014, 113, 513–521. [Google Scholar] [CrossRef]
  52. Noguchi, K.; Nagakura, J.; Konôpka, B.; Sakata, T.; Kaneko, S.; Takahashi, M. Fine-root dynamics in sugi (Cryptomeria japonica) under manipulated soil nitrogen conditions. Plant Soil 2013, 364, 159–169. [Google Scholar] [CrossRef]
  53. Ding, J.; Kong, D.; Zhang, Z.; Cai, Q.; Xiao, J.; Liu, Q.; Yin, H. Climate and soil nutrients differentially drive multidimensional fine root traits in ectomycorrhizal-dominated alpine coniferous forests. J. Ecol. 2020, 108, 2544–2556. [Google Scholar] [CrossRef]
  54. Li, H.; Liu, B.; McCormack, M.L.; Ma, Z.; Guo, D. Diverse belowground resource strategies underlie plant species coexistence and spatial distribution in three grasslands along a precipitation gradient. New Phytol. 2017, 216, 1140–1150. [Google Scholar] [CrossRef] [PubMed]
  55. Chapin, F.S.; Matson, P.A.; Vitousek, P.M. Principles of Terrestrial Ecosystem Ecology; Springer: New York, NY, USA, 2011. [Google Scholar]
Forests 15 00336 g001
Figure 1. Schematic diagram of the structure of the root chamber.
Figure 1. Schematic diagram of the structure of the root chamber.
Forests 15 00336 g001
Forests 15 00336 g002
Figure 2. Effects of nutrient addition on (a) fine root biomass (FRB) and (b) total root length (TRL) of different functional root modules in C. lanceolata and Q. acutissima stands (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control; AFR, absorptive fine root; TFR, transport fine root).
Figure 2. Effects of nutrient addition on (a) fine root biomass (FRB) and (b) total root length (TRL) of different functional root modules in C. lanceolata and Q. acutissima stands (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control; AFR, absorptive fine root; TFR, transport fine root).
Forests 15 00336 g002
Forests 15 00336 g003
Figure 3. Effects of nutrient addition on relative biomass allocation of absorptive and transport roots (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control).
Figure 3. Effects of nutrient addition on relative biomass allocation of absorptive and transport roots (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control).
Forests 15 00336 g003
Forests 15 00336 g004
Figure 4. Effects of nutrient addition on (a) root average diameter (AD), (b) specific root length (SRL), (c) specific root area (SRA), (d) root tissue density (RTD), (e) root branching ratio (BR), and (f) branching intensity (BI) for absorptive fine roots (AFRs) and transport fine roots (TFRs) in C. lanceolata and Q. acutissima (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control; AFR, absorptive fine root; TFR, transport fine root).
Figure 4. Effects of nutrient addition on (a) root average diameter (AD), (b) specific root length (SRL), (c) specific root area (SRA), (d) root tissue density (RTD), (e) root branching ratio (BR), and (f) branching intensity (BI) for absorptive fine roots (AFRs) and transport fine roots (TFRs) in C. lanceolata and Q. acutissima (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments (NPK, inorganic nutrient treatment; F, organic nutrient treatment; CK, control; AFR, absorptive fine root; TFR, transport fine root).
Forests 15 00336 g004
Forests 15 00336 g005
Figure 5. Effects of nutrient addition on (a) root N (RN) and root P (RP) and (b) root mycorrhizal colonization concentrations (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments.
Figure 5. Effects of nutrient addition on (a) root N (RN) and root P (RP) and (b) root mycorrhizal colonization concentrations (means ± SE, n = 12, p < 0.05). Different letters represent statistical significance among treatments.
Forests 15 00336 g005
Table 1. Abbreviations, definitions, and descriptions of the growth, morphological, architectural, and chemical traits.
Table 1. Abbreviations, definitions, and descriptions of the growth, morphological, architectural, and chemical traits.
Root TraitsAbbreviationUnitsDescription
Growth traits
Fine root biomassFRBmgDry mass of fine roots in root chamber
Total root lengthTRLmmTotal length of fine roots in root chamber
Morphological traits
Average diameterADmmAverage root diameter
Specific root lengthSRLm g−1Length per unit root dry mass
Specific root areaSRAcm2 g−1Area per unit root dry mass
Root tissue densityRTDg cm−3Mass per unit root volume
Architectural traits
Branching ratioBR The number of AFRs/the number of TFRs
Branching intensityBIind cm−1The number of AFRs/total root length of TFRs
Chemical traits
Root N concentrationRNg kg−1Total nitrogen content per unit root dry mass
Root P concentrationRPg kg−1Total phosphorus content per unit root dry mass
Note: AFRs, absorptive fine roots; TFRs, transport fine roots.
Table 2. Analysis of variance results for effects of species, root category, treatment, and interactions on fine root traits.
Table 2. Analysis of variance results for effects of species, root category, treatment, and interactions on fine root traits.
SRTS × RS × TR × TS × R × T
FpFpFpFpFpFpFp
TRL18.44<0.001 **86.61<0.001 **40.72<0.001 **10.890.001 **4.960.009 **41.17<0.001 **8.050.001 **
AD109.62<0.001 **140.40<0.001 **0.020.9770.200.6538.020.001 **1.970.1460.520.598
FRB9.510.003 **7.970.006 **10.82<0.001 **4.560.036 *5.400.006 **5.090.008 **1.480.233
SRL41.90<0.001 **200.72<0.001 **7.81<0.001 **15.39<0.001 **0.490.6147.620.001 **6.420.003 **
SRA5.820.018 *48.85<0.001 **0.900.4125.400.022 *2.530.0861.400.2530.670.514
RTD6.950.010 *1.660.2020.510.6040.170.6840.310.7380.040.9624.040.021 *
BR23.89<0.001 **——2.910.003 **——22.23<0.001 **————
BI1.320.273 **——7.140.009 **——10.500.002 **————
TN807.88<0.001 **——462.76<0.001 **——418.86<0.001 **————
TP13.500.003 **——131.59<0.001 **——4.980.027 *————
* p < 0.05; ** p < 0.01. Species (S); Root category (R); Treatment (T). Table 1 provides definitions of listed root trait acronyms.
Table 3. Coefficient of Variation (CV%) for each trait and species among three treatments, ranked from highest to lowest according to average CV among three treatments across species.
Table 3. Coefficient of Variation (CV%) for each trait and species among three treatments, ranked from highest to lowest according to average CV among three treatments across species.
TraitsC. lanceolataQ. acutissimaAverage CV
AFRsTFRsAFRsTFRsTotalTotalTotal
IN-OR-CKIN-OR-CKIN-CKOR-CK
TRL91.244.7106.145.871.979.152.3
TP71.462.566.971.948.1
FRB73.410.880.162.056.673.435.4
BI46.251.348.759.930.1
TN27.548.738.132.644.3
BR39.122.330.737.922.9
SRL15.533.525.631.426.536.112.0
RTD12.426.38.534.220.326.78.7
SRA8.010.57.335.015.218.66.9
AD15.67.86.414.711.115.67.9
IN-OR-CK: Coefficient of Variation was calculated among CK, NPK, and F treatments; IN-CK: Coefficient of Variation was calculated between CK and NPK treatments; OR-CK: Coefficient of Variation was calculated between CK and F treatments. AFRs: absorptive fine roots; TFRs: transport fine roots. Total: total fine roots. Table 2 provides definitions of listed root trait acronyms.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Xu, X.; Tan, R.; Shao, H.; Gu, J.; Wang, W.; Wang, G.; Yu, S. Differences in Fine Root Foraging Traits of Two Dominant Tree Species (Cunninghamia lanceolata and Quercus acutissima) in Subtropical Forests. Forests 2024, 15, 336. https://doi.org/10.3390/f15020336

AMA Style

Xu X, Tan R, Shao H, Gu J, Wang W, Wang G, Yu S. Differences in Fine Root Foraging Traits of Two Dominant Tree Species (Cunninghamia lanceolata and Quercus acutissima) in Subtropical Forests. Forests. 2024; 15(2):336. https://doi.org/10.3390/f15020336

Chicago/Turabian Style

Xu, Xinying, Rui Tan, Huimei Shao, Jiacun Gu, Weifeng Wang, Guobing Wang, and Shuiqiang Yu. 2024. "Differences in Fine Root Foraging Traits of Two Dominant Tree Species (Cunninghamia lanceolata and Quercus acutissima) in Subtropical Forests" Forests 15, no. 2: 336. https://doi.org/10.3390/f15020336

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop