Effects of Planting Density and Nitrogen Fertilization on Growth Traits and Leaf and Wood Characteristics of Three Poplar Clones

Abstract

A comprehension of the effects planting density and nitrogen (N) fertilization have on the physiological and morphological characteristics of trees is critical for optimizing the require size and characteristics of wood products. We evaluated the growth traits and the leaf and wood characteristics of three clone poplars including Populus simonii × P. nigra ‘Xiaohei’, ‘Xiaohei-14’ and ‘Bailin-3’ under five planting densities (1666, 1111, 833, 666, and 555 tree ha⁻¹) and four N fertilization rates (0, 100, 160, and 220 g tree⁻¹ year⁻¹). The results show that the clone type significantly affected all observed indicators, while planting density and N fertilization treatments had a significant effect on growth traits and leaf characteristics, but not on wood characteristics. Specifically, the clone ‘Bailin-3’ exhibited the largest annual increments in tree height and diameter at breast height (DBH), leaf width, N content, and soluble protein content. A decrease in initial planting density (from 1666 to 555 tree ha⁻¹) led to an increased annual incremental tree height and DBH, regardless of clone type and N fertilization treatment. N fertilization treatment significantly impacted the annual increment in DBH, but not that of tree height. Further, the annual increments in tree height and DBH were positively correlated with leaf width, N content, chlorophyll content, and soluble protein content, and negatively correlated with hemicellulose content. In addition, the chlorophyll and soluble protein contents were identified as the most reliable predictors of the annual increments in tree height and DBH. Our results demonstrate the clone ‘Bailin-3’ with 555 tree ha⁻¹ under 160 g N tree⁻¹ yr⁻¹ showed superior growth traits and leaf characteristics. Thus, it is recommended for future poplar silviculture of larger diameter timber production at similar sites. The results contribute to understanding of the effects of planting density and fertilization on the growth traits and the leaf and wood characteristics of three poplar clones, offering valuable guidance for the sustainable development and long-term productivity of poplar plantations.

1. Introduction

Planting density and fertilization are two crucial cultivation factors that affect tree growth, wood quality, stand production, and soil sustainability in intensively managed plantations [1,2]. Plant density and nitrogen (N) fertilization can affect leaf area, the nutritional state of plants, light interception, and canopy structure [3]. Reasonable planting density can effectively control canopy structure, maintain sufficient resources for tree growth and development, and maximize the utilization of water and nutrients [4,5]. In general, a trade-off exists between higher planting density and biomass production per area, and planting density strongly affects tree growth during stand development [6,7,8]. The individual tree diameter at breast height (DBH) and volume enhanced with increasing planting spacing [9,10,11]. Planting density also influences wood fiber traits, wood density, and chemical composition [12,13,14]. Fertilization significantly improved tree growth and stand production through promoting the absorption of nutrients by trees, the regulation of leaf area, and the improvement of photosynthetic rate [15,16]. Therefore, selecting suitable planting density and fertilizer planning is crucial to improving the biomass production without a change in wood quality. Collectively, understanding the influence of various controllable factors (e.g., planting density and fertilization) on the growth and development of trees is critically significant, and facilitates the strategy for improving tree growth, stand productivity, and soil sustainability, particularly for directional cultivation of plantations [17,18,19].

Poplars (Populus spp.) are a dominant species for afforestation and reforestation in temperate regions in the world, and are recommended for wood and pulp production because of the fast growth, good coppicing ability, desirable adaptability, and high productivity of the trees [20,21,22]. Poplar plantations provide a high proportion of the timber supply, cover seven million hectares, and are subject to various silvicultural treatments including fertilization, irrigation, and stand density management for increasing the growth efficiency and productivity [15,23,24]. In practice, density and fertilization are very important and are the most easily controlled factors in the directional cultivation of poplar plantations [25,26,27]. Several studies demonstrate that planting density and fertilization have a major effect on tree growth [28,29]. A reasonable planting density can effectively control canopy structure, and it should also keep adequate resources for the growth and development of the individual trees [30,31]. Fertilization stimulates the translocation of soil nutrients to shoots and promotes tree growth [32]. The responses of tree physiological traits to planting spacing and fertilization were less readily available, and this identified the importance of studies detailing tree physiological response to fertilization and planting density to indicate the essential requirement for physiological evaluations in order to develop specific management treatments for individual species [8,33]. However, little is known about the combination of planting density and N fertilization on the growth traits and the leaf and wood characteristics of poplar plantations. The objectives of this study were to obtain the most suitable planting density and N fertilization level for obtaining optimum yield and wood quality. We hypothesized that the tree height and DBH increase with decreasing planting density and that increasing N fertilization improves the physiological processes of three poplar clones. Answering the hypotheses is very important to determine the most suitable planting density and N fertilization level for promoting growth and to provide new insights into the sustainable development and long-term productivity of poplar plantations.

2. Materials and Methods

2.1. Study Area and Experimental Design

The study was carried out at the Baicheng Forestry Center in Baicheng, Jilin Province, China (122°50′19″ E; 45°48′35″ N and elevation 100–200 m above sea level). This region has a temperate continental climate. The mean annual temperature is 5.2 °C and the mean annual frost-free period is ~144 days. The mean annual precipitation is 399.9 mm, with ~88% precipitation concentrated from May to September during the growing season [34]. Experimental plantations were established in March 2018 by planting 2-year-old cuttings.

The plant material comprised three poplar clones Populus simonii × P. nigra ‘Xiaohei’, ‘Xiaohei-14’, and ‘Bailin-3’. The experimental design was conducted using a split-split-plot design with density as the whole plot, clone type as the split plot, and N fertilization as the split-subplot. The five density levels consisted of line spacing × row spacing of 3 m × 2 m (1666 tree ha⁻¹; D2); 3 m × 3 m (1111 tree ha⁻¹, D3); 3 m × 4 m (833 tree ha⁻¹, D4); 3 m × 5 m (666 tree ha⁻¹, D5); and 3 m × 6 m (555 tree ha⁻¹, D6), and four N fertilization levels included 0 (N0), 100 (N1), 160 (N2), and 220 (N3) g N tree⁻¹ yr⁻¹, in the form of urea (Sinofert Holdings Co., Ltd., Beijing, China). Briefly, three replicate blocks were implemented, each consisting of five plots with five density treatments. Three subplots were established in each plot and each subplot was randomly assigned to one clone type with 144 trees being planted. Nitrogen was applied three times, on 30 May, 28 June, and 28 July 2021. Guard rows were planted throughout the surrounding area to lower edge effects in each plot.

2.2. Measurement of Growth Traits

Tree height and DBH were measured in November 2020 and November 2021, respectively. A laser vertex was used to measure tree height and the meter tap DBH, respectively.

2.3. Measurement of Leaf and Wood Properties

Four wood cores of each clone type (three trees from each treatment) were collected in a north–south direction at a height of 1.3 m and wrapped in paper tubes for laboratory analysis. The content of cellulose was determined according to the anthrone colorimetric method [35]. The content of hemicellulose was determined using the hydrochloric acid hydrolysis-DNS method and the content of lignin was determined using the ulfuric acid titration method [35].

The chlorophylls were extracted from needle samples of ~0.5 g using 10 mL 80% (v/v) aqueous solution of acetone [36]. After extraction, the suspensions were centrifuged at 1503× g for 2 min and the absorbance of the solution was measured (the absorbance at 470, 663, and 646 nm) to determine carotenoids, chlorophyll a, and chlorophyll b concentrations using a Unicam UV-330 spectrometer (Unicam, Cambridge, UK) [37].

The sample of 100 mg fresh leaf was hydrolyzed in 1 mL deionized water. For measuring soluble sugars, the homogenate was transferred to a 1.5 mL centrifuge tube and subjected to boiling at 95 °C for 15 min, and cooled using tap water, then centrifuged at 8000× g at 25 °C for 10 min. For measuring soluble proteins, the homogenate was centrifuged at 8000× g at 4 °C for 10 min. The solution concentration was estimated using soluble sugars and soluble proteins assay kits (Comin Biotechnology Co., Ltd., Suzhou, China), respectively [38].

2.4. Statistical Analysis

Three-way analysis of variance (ANOVA) was used to test the effects of the planting density, N fertilization, and clone type on the growth traits and the leaf and wood characteristics. Moreover, one-way ANOVA was used to test the differences in the same clone type and density among the five N fertilization levels and post hoc comparisons using Tukey’s test were conducted to determine which of the N fertilization levels differed. Before conducting ANOVA, the normality and homogeneity of variances of the data were tested, and the variance was squared or log-transformed if necessary. Correlation analysis was carried out for every trait, and regression analysis was used to analyze and establish the relational model between the planting densities in terms of growth traits and wood properties. A random forest model was employed to identify the primary credible predictors of the annual increments in tree height and DBH including growth traits and leaf and wood characteristics. The percent increase in mean squared error and the increase in node purity were calculated to determine the significance of the predictors. The cross-validated R² values and significance of the models were assessed with 1000 permutations of the response variables using the A3 package. Statistically significant differences were set at p < 0.05. All statistical analyses were carried out in R (4.0.2) software.

3. Results

3.1. Effect of Clone Type, Planting Density, and N Fertilization on Growth Traits

Three-way ANOVA indicated that the annual increments in DBH were significantly influenced by clone type, planting density, and N fertilization. As for the annual increment in tree height, this was significantly influenced by clone type and planting density, except for N fertilization (

Table 1. Three-way ANOVA results of the clone type, planting density, and nitrogen fertilization influences on growth traits and leaf and wood characteristics.

Parameters	Clone		Density		Nitrogen		Clone × Density		Clone × Nitrogen		Density × Nitrogen		Clone × Density × Nitrogen
	F	p	F	p	F	p	F	p	F	p	F	p	F	p
Height	147.89	<0.01	33.49	<0.01	0.76	ns	7.51	<0.01	2.95	0.01	2.08	0.02	1.37	ns
DBH	44.80	<0.01	151.13	<0.01	3.08	0.03	7.82	<0.01	1.43	ns	1.62	ns	1.46	ns
Hemicellulose	6.41	<0.01	2.34	ns	0.38	ns	1.32	ns	0.48	ns	0.90	ns	1.34	ns
Cellulose	5.59	<0.01	0.47	ns	0.03	ns	1.62	ns	0.86	ns	1.46	ns	0.91	ns
Lignin	4.39	0.01	0.66	ns	0.05	ns	2.05	ns	0.91	ns	1.07	ns	0.93	ns
Leaf length	42.53	<0.01	8.29	<0.01	1.46	ns	2.48	0.01	2.07	ns	2.35	0.01	2.47	<0.01
Leaf width	19.30	<0.01	10.01	<0.01	1.83	ns	0.50	ns	3.65	<0.01	1.77	ns	1.92	<0.01
Leaf mass per area	35.53	<0.01	35.93	<0.01	5.17	<0.01	1.35	ns	2.87	0.01	3.21	<0.01	2.58	<0.01
N content	21.99	<0.01	19.89	<0.01	10.69	<0.01	16.36	<0.01	8.88	<0.01	2.68	0.01	4.60	<0.01
Chlorophyll a	1.86	ns	1.58	ns	1.70	ns	2.21	0.03	1.98	ns	1.81	ns	1.21	ns
Chlorophyll b	10.02	<0.01	12.71	<0.01	1.64	ns	8.08	<0.01	7.72	<0.01	4.55	<0.01	4.27	<0.01
Carotenoids	18.45	<0.01	4.27	<0.01	1.81	ns	5.50	<0.01	2.11	ns	2.76	<0.01	3.68	<0.01
Chlorophyll	0.94	ns	8.03	<0.01	5.89	<0.01	7.11	<0.01	3.56	<0.01	4.37	<0.01	4.58	<0.01
Soluble sugar	6.39	<0.01	12.78	<0.01	43.07	<0.01	16.71	<0.01	7.03	<0.01	8.37	<0.01	6.53	<0.01
Soluble protein	47.42	<0.01	19.03	<0.01	11.17	<0.01	15.31	<0.01	10.30	<0.01	8.42	<0.01	11.22	<0.01

ns indicate p ≥ 0.05.

). The clone ‘Bailin-3’ had the highest annual increments in tree height (2.85 ± 0.31m) and DBH (2.93 ± 0.59 cm), and clone ‘Xiaohei-14’ had the middle annual increments in tree height (2.43 ± 0.3 m) and DBH (2.63 ± 0.67 cm), whereas clone ‘Xiaohei’ showed the lowest annual increments in tree height (2.34 ± 0.32 m) and DBH (2.47 ± 0.64 cm) (

Table 2. Means of the growth traits and wood characteristics according to the clone type, planting density, and nitrogen fertilization.

Factors	Height Increment (m)	DBH Increment (cm)	Hemicellulose (%)	Cellulose (%)	Lignin (%)
Clone
Xiaohei	2.34 ± 0.32 c	2.47 ± 0.64 c	15.45 ± 1.41 ab	17.83 ± 2.8 ab	49.39 ± 4.28 b
Xiaohei-14	2.43 ± 0.30 b	2.63 ± 0.67 b	15.81 ± 1.23 a	18.85 ± 4.22 a	51.67 ± 2.60 a
Bailin-3	2.85 ± 0.31 a	2.93 ± 0.59 a	15.08 ± 1.02 b	16.69 ± 2.28 b	51.17 ± 3.23 a
Planting density
D2	2.27 ± 0.42 C	1.91 ± 0.45 D	15.60 ± 1.02	17.67 ± 3.64	51.00 ± 3.57
D3	2.59 ± 0.39 B	2.48 ± 0.37 C	15.22 ± 1.45	17.67 ± 2.22	50.75 ± 2.83
D4	2.54 ± 0.29 B	2.7 ± 0.44 B	15.88 ± 1.33	17.47 ± 3.41	51.13 ± 3.56
D5	2.59 ± 0.30 B	2.87 ± 0.41 B	15.44 ± 1.34	17.92 ± 3.47	50.32 ± 3.64
D6	2.76 ± 0.32 A	3.43 ± 0.50 A	14.99 ± 0.92	18.51 ± 3.73	50.29 ± 4.23
Nitrogen fertilization
N0	2.51 ± 0.32	2.50 ± 0.64 b	15.47 ± 1.34	17.97 ± 3.19	50.71 ± 3.46
N1	2.55 ± 0.38	2.71 ± 0.67 ab	15.45 ± 1.58	17.95 ± 3.97	50.65 ± 4.00
N2	2.57 ± 0.44	2.79 ± 0.69 a	15.43 ± 0.96	17.39 ± 2.56	51.09 ± 2.90
N3	2.55 ± 0.39	2.72 ± 0.61 ab	15.36 ± 1.05	18.07 ± 3.48	50.34 ± 3.92

Different lowercase letters in the same column (the same parameter) indicate significant differences among different clone types by Tukey’s HSD test (p < 0.05); different uppercase letters in the same column (the same parameter) indicate significant differences among different planting density by Tukey’s HSD test (p < 0.05); and different italic lowercase letters in the same column (the same parameter) indicate significant differences among different nitrogen fertilization by Tukey’s HSD test (p < 0.05). D2: 3 m × 2 m (1666 tree ha⁻¹); D3: 3 m × 3 m (1111 tree ha⁻¹); D4: 3m × 4 m (833 tree ha⁻¹); D5: 3 m × 5 m (666 tree ha⁻¹); and D6: 3 m × 6 m (555 tree ha⁻¹, D6), and four N fertilization levels included 0 (N0), 100 (N1), 160 (N2), and 220 g N tree⁻¹ yr⁻¹ (N3).

). Regression analysis showed that the annual increments in tree height and DBH increased with decreasing planting density, regardless of clone type and N fertilization (Figure 1). Specifically, the annual increments in tree height and DBH were lowest in D2 (2.27 ± 0.42 m and 1.91 ± 0.45 cm) and highest in D6 (2.76 ± 0.32 m and 3.43 ± 0.5 cm). The annual increment in DBH was highest under 160 g N tree⁻¹ yr⁻¹. These results suggest that planting density can significantly increase the annual increments in tree height and DBH, regardless of the clone type and N fertilization treatments.

3.2. Effect of Clone Type, Planting Density, and N Fertilization on Wood Chemical Composition

Three-way ANOVA tests have shown that the cellulose, hemicellulose, and lignin contents were significantly influenced by clone type, but not by planting density and N fertilization (Table 1). The cellulose, hemicellulose, and lignin contents ranged from 17.39 to 18.85%, 14.99 to 15.81%, and 49.39 to 51.67%, respectively (Table 2; Figure 2). The hemicellulose and cellulose levels were higher in the clone ‘Bailin-3’ than in the clone ‘Xiaohei’, and the lignin content was lower in the clone ‘Bailin-3’ than in the clone ‘Xiaohei’ (Table 2).

3.3. Effect of Clone Type, Planting Density, and N Fertilization on Leaf Characteristics

Three-way ANOVA indicated that the clone type and planting density significantly influenced leaf length, leaf width, leaf mass per area, N, chlorophyll b, carotenoids, chlorophyll, soluble sugar, and soluble protein content, and N fertilization significantly influenced leaf mass per area, N, chlorophyll, soluble sugar, and soluble protein content (Table 1). Leaf length, leaf mass per area, chlorophyll b, and carotenoids content were significantly lower in the clone ‘Bailin-3’ than in the clones ‘Xiaohei’ and ‘Xiaohei-14’, whereas leaf width and N and soluble protein content were significantly higher in the clone ‘Bailin-3’ compared with the clone ‘Xiaohei’ (

Table 3. Means of the leaf characteristics according to clone type, planting density, and nitrogen fertilization level.

Factors	Leaf Length (mm)	Leaf Width (mm)	Leaf Mass per Area (g cm−2)	N Content (mg g−1)	Chlorophyll a (mg g−1)	Chlorophyll b (mg g−1)	Carotenoids (mg g−1)	Chlorophyll (mg g−1)	Soluble Sugar (mg g−1)	Soluble Protein (mg g−1)
Clone
Xiaohei	65.09 ± 5.11 a	39.15 ± 2.45 b	0.16 ± 0.03 a	8.37 ± 0.53 c	1.26 ± 0.10	0.42 ± 0.04 a	0.26 ± 0.03 a	1.67 ± 0.14	273.41 ± 19.62 b	5.54 ± 1.56 b
Xiaohei-14	65.05 ± 4.46 a	39.38 ± 3.08 b	0.16 ± 0.03 a	8.86 ± 0.72 a	1.27 ± 0.13	0.44 ± 0.10 a	0.27 ± 0.03 a	1.71 ± 0.18	280.74 ± 25.79 a	5.79 ± 1.3 b
Bailin-3	60.10 ± 5.94 b	41.6 ± 2.67 a	0.14 ± 0.03 b	8.60 ± 0.50 b	1.26 ± 0.14	0.40 ± 0.07 b	0.25 ± 0.03 b	1.68 ± 0.18	278.09 ± 23.76 ab	6.57 ± 1.92 a
Planting density
D2	61.88 ± 5.12 B	38.38 ± 2.58 B	0.13 ± 0.02 B	8.18 ± 0.56 C	1.24 ± 0.11 B	0.40 ± 0.07 B	0.26 ± 0.03 AB	1.64 ± 0.16 B	269.28 ± 15.51 C	5.75 ± 1.11 B
D3	61.96 ± 4.27 B	39.56 ± 2.60 B	0.14 ± 0.02 B	8.57 ± 0.60 B	1.26 ± 0.12 A	0.41 ± 0.05 B	0.27 ± 0.03 A	1.67 ± 0.16 B	273.95 ± 25.84 BC	4.97 ± 1.58 C
D4	64.88 ± 5.90 A	40.9 ± 2.83 A	0.17 ± 0.02 A	8.79 ± 0.53 A	1.28 ± 0.13 A	0.45 ± 0.11 AB	0.26 ± 0.04 AB	1.73 ± 0.16 AB	288.58 ± 26.88 A	6.32 ± 1.62 AB
D5	65.13 ± 6.24 A	40.69 ± 2.66 A	0.15 ± 0.03 A	8.57 ± 0.66 B	1.22 ± 0.14 B	0.40 ± 0.06 B	0.25 ± 0.03 B	1.66 ± 0.17 B	277.54 ± 28.37 BC	6.12 ± 1.81 AB
D6	62.61 ± 6.03 AB	40.85 ± 3.19 A	0.17 ± 0.03 A	8.88 ± 0.44 A	1.31 ± 0.11 A	0.45 ± 0.05 A	0.26 ± 0.03 AB	1.76 ± 0.16 A	277.18 ± 32.87 B	6.70 ± 1.70 A
Nitrogen fertilization
N0	62.34 ± 5.30	39.58 ± 2.42	0.15 ± 0.03 b	8.59 ± 0.7 ab	1.25 ± 0.11	0.41 ± 0.08	0.26 ± 0.03	1.66 ± 0.16	263.18 ± 26.53 c	5.55 ± 1.32 c
N1	63.61 ± 5.22	39.73 ± 2.98	0.16 ± 0.03 ab	8.62 ± 0.6 ab	1.26 ± 0.13	0.42 ± 0.09	0.27 ± 0.03	1.69 ± 0.18	279.24 ± 26.51 b	5.87 ± 2.12 b
N2	62.70 ± 6.67	40.37 ± 3.29	0.15 ± 0.03 ab	8.68 ± 0.62 a	1.25 ± 0.14	0.42 ± 0.07	0.26 ± 0.03	1.69 ± 0.16	279.48 ± 24.70 b	6.32 ± 1.53 a
N3	64.62 ± 5.53	40.68 ± 2.92	0.16 ± 0.03 a	8.48 ± 0.52 b	1.28 ± 0.12	0.43 ± 0.05	0.26 ± 0.03	1.71 ± 0.17	287.31 ± 25.26 a	6.19 ± 1.56 ab

Different lowercase letters in the same column (the same parameter) indicate significant differences among different clone types by Tukey’s HSD test (p < 0.05); different uppercase letters in the same column (the same parameter) indicate significant differences among different planting density by Tukey’s HSD test (p < 0.05); and different italic lowercase letters in the same column (the same parameter) indicate significant differences among different nitrogen fertilization by Tukey’s HSD test (p < 0.05). D2: 3 m × 2 m (1666 tree ha⁻¹); D3: 3 m × 3 m (1111 tree ha⁻¹); D4: 3m × 4 m (833 tree ha⁻¹); D5: 3 m × 5 m (666 tree ha⁻¹); and D6: 3 m × 6 m (555 tree ha⁻¹, D6), and four N fertilization levels included 0 (N0), 100 (N1), 160 (N2), and 220 g N tree⁻¹ yr⁻¹ (N3).

). The leaf length and soluble sugar were significantly increased from D2 to D4, and then subsequently decreased (Table 3). The leaf width, leaf mass per area, N content, chlorophyll a, chlorophyll b, and carotenoids content were significantly increased from D2 to D4, and decreased in D5, and then subsequently increased in D6 (Table 3). The soluble sugar and soluble protein contents significantly increased with N fertilization levels. For instance, the soluble sugar content was significantly lower in the N0 and N1 treatments than in the N4 under D3 and D6 of the clone ‘Xiaohei’, and the soluble protein content was significantly lower in the N0 treatment than in the N4 treatment under D3, D4, D5, and D6 of the clone ‘Xiaohei’ (Figure 3). The leaf length, leaf width, chlorophyll a, chlorophyll b, and carotenoids in the clone ‘Bailin-3’ were more easily affected by planting density than in the clones ‘Xiaohei’ and ‘Xiaohei-14’ (Figure 4). Specifically, the leaf length, leaf width, chlorophyll a, chlorophyll b, and carotenoids content were significantly higher under the D4 and D6 treatments than under D2 of the clone ‘Bailin-3’ (Figure 4).

3.4. Correlations among Growth Traits, Wood Properties, and Leaf Physiological Characteristics

Pearson correlations revealed that the annual increment in tree height had a significant positive relationship with leaf width, and with N, chlorophyll, and soluble protein content and had a significant negative relationship with leaf length and wood density. The annual increment in DBH had a significant positive relationship with leaf width, and N, chlorophyll a, chlorophyll b, and soluble protein content. In addition, wood properties had no significant relationship with leaf physiological characteristics and growth traits (Figure 5). The random forests modeling indicated that the chlorophyll, soluble protein, and N content were the best predictors of the annual increment in tree height, and the soluble protein and N content were the best predictors of the annual increment in DBH (Figure 6a,b).

4. Discussion

4.1. Effects of Clone Type, Planting Density, and N Fertilization on Growth Traits

Choosing high-yield clones for afforestation plays an important role in meeting industry demands for increased productivity and sustained wood supplies [39,40,41]. Different tree species have distinct biological characteristics, and poplar genotypes with excellent genetic material have been widely used to improve tree growth and wood production [42,43,44]. Previous studies have indicated differences in survival, growth, and productivity between different poplar clones under various growing conditions [45,46]. In this study, clone type significantly affected the growth traits, and the clone ‘Bailin-3’ had the highest annual increments in tree height and DBH.

Determining appropriate planting density and the amount of fertilizer application is important for the growth and development of trees, especially for intensive management of fast-growing and high-yield plantations [45,47]. In this study, the planting density had a significant influence on the DBH and tree height of the poplars, and this result agreed with other studies which also found that the growth traits showed a significant increase with decreasing planting density [48,49,50]. The reduced tree growth at high planting density may be attributed to the competition among individual trees for resources such as water, light, and nutrients [9,51]. The individual stem dimensions were significantly influenced by the planting density, and the mean DBHs of the trees planted at low density (494 tree ha⁻¹) were about twice as large as those which were planted at high density (4444 tree ha⁻¹) in 9-year poplar plantations [5]. Similarly, the present study showed that the DBH of poplars varied from 13.2 cm to 19.8 cm, with the highest at 416 tree ha⁻¹ and the lowest at 2500 tree ha⁻¹. Our results also found that the annual increments in tree height and DBH increased with decreasing density from 1666 tree ha⁻¹ to 555 tree ha⁻¹. Overall, there is a linear relationship between the DBH and planting density. Furthermore, planting density was more important than N fertilization level for supporting the growth and development of poplar. In this study area, the mean annual precipitation is only 399.9 mm and the soils have a sandy loam texture. Therefore, we conclude that water is the main limiting factor for poplar growth on this site. N fertilization had a weak but significant influence on the DBH, and the annual increment in DBH was highest at levels under 160 g N tree⁻¹ yr⁻¹, but not under 220 g N tree⁻¹ yr⁻¹; there is not a linear relationship between the annual increment in DBH and the N fertilization amount. These results also indicate that the combination of an appropriate initial density and a reasonable amount of fertilization is an effective strategy for promoting growth in poplar plantations.

Tree height is not always a variable dependent on silviculture, and soil quality has also been identified as the most important factor determining tree height growth; therefore, competition for soil resources may be the primary factor contributing to decreased tree height growth in high density stands [52]. A higher planting density in Picea obovate plantations significantly decreased the height growth of suppressed trees due to an earlier commencement of competition for resources [53]. Tree height growth has a tendency to increase as the planting density decreases, which is similar to what occurred in this study, but this trend is not consistent. Some studies suggested that planting density had minimal or limited influence on tree height growth [54]. In this study, the annual increment in tree height was significantly affected by planting density, but not by N fertilization, which demonstrates that initial density is more important than N fertilization on poplar growth, especially for tree height.

4.2. Effects of the Clone Type, Planting Density, and N Fertilization on Wood and Leaf Characteristics

Our results showed that the clone type significantly affected leaf and wood characteristics (e.g., leaf mass per area, and chlorophyll, soluble sugar, soluble protein, cellulose, hemicellulose, and lignin content), while planting density and N fertilization only had a significant effect on leaf characteristics, but not on wood characteristics (cellulose, hemicellulose, and lignin content). This is consistent with the results in previous studies, which showed that there is significant variation in chemical composition among poplar clones, while information about the impacts of silvicultural management practices on these traits is less readily available [55,56]. The impact of planting density on growth traits is larger than that of the wood chemical composition [12]; the wood chemical composition was mainly determined by its genetic background and was scarcely influenced by the planting density in the triploid Chinese white poplar [49]. These results show that the growth traits and chemical composition of trees may be genetically independent, and wood chemical composition was also almost unaffected by silvicultural treatment, which is beneficial for combination selection to obtain high productivity without a change in wood quality.

Correlation coefficients play an important role in comprehending the relationship between different measurement parameters [57]. Our results also showed that the growth traits (annual increments in tree height and DBH) had a significant positive relationship with leaf width, and chlorophyll and soluble protein content and had no significant relationship with the wood chemical composition (cellulose, hemicellulose, and lignin content). An appropriate decrease in initial density and application of nitrogen fertilizer fostered tree growth by promoting the leaf development, increasing chlorophyll content, and improving water and nutrients allocation [27,58,59]. The correlation between the growth traits and wood chemical composition was generally weak in tests conducted on P. simonii × P. nigra, P. × tomentosa, and Pinus massoniana plantations [12,35,49]. Additionally, there was a weak positive correlation between the growth traits and basic wood density of trees in the P. tometosa plantation [49]. These results further support the argument that the growth traits and chemical composition of trees may exhibit genetic independence, which is conducive for combination selection.

To improve the growth and yield production of poplar plantations under intensive management, it is essential to implement appropriate planting density and fertilizer application, especially in water-limited areas [12,32,60]. The hypothesis was partially supported by our findings that the tree height and DBH increase with decreasing planting density, but do not increase with N fertilization levels. We recommend that an appropriate reduction in initial density and reasonable N fertilization for poplar silviculture could be beneficial for improving growth traits and leaf characteristics. For instance, the clone ‘Bailin-3’ with 555 tree ha⁻¹ under 160 g N tree⁻¹ yr⁻¹ showed excellent growth traits in this study area.

5. Conclusions

This study has carried out an evaluation of the effects of clone type, planting density, and N fertilization on growth traits and leaf and wood characteristics of poplar plantations. The clone type significantly affected all observed indicators. Planting density and N fertilization had a significant effect on growth traits and leaf characteristics, but not on wood characteristics. N fertilization had a weak but significant effect on DBH, but not on tree height. The clone ‘Bailin-3’ exhibited the highest growth rate and the largest leaf width, N content, and soluble protein content. A decrease in planting density resulted in an increase in tree height and DBH, and 3 m × 6 m spacing (555 tree ha⁻¹) gave rise to the largest tree height and DBH. The annual increments in tree height and DBH were positively correlated with leaf width, and chlorophyll, soluble protein, and N content. In addition, the chlorophyll, soluble protein, and N content were the best predictors of the annual increments in tree height and DBH. Our results demonstrate that selecting clone ‘Bailin-3’ with 555 tree ha⁻¹ under 160 g N tree⁻¹ yr⁻¹ is recommended for the poplar silviculture of larger diameter timber production, and offer valuable guidance for the sustainable development and long-term productivity of poplar plantations.