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土壤养分影响林木生长、林分生产力[1-2]。在土耳其地中海地区,黎巴嫩雪松(Cedrus libani Rich.)的树高与土壤pH值呈负相关,而与土壤Mn、Cu和K含量呈正相关[3];湖北江汉平原栽培的杨树,其胸径和树高生长受土壤Zn和N含量的显著影响[4]。在用材林造林决策和经营管理过程中,获取最大的立地生产力是重要的目标之一[5]。立地指数常作为评价立地生产力大小的指标[6],其受土壤养分的影响因树种而异:如无梗花栎(Quercus petraea (Mattuschka) Liebl.)的立地指数与土壤Mg、S含量以及K/P2O5和Mg/K密切相关,而与C/N相关不显著[7];韩国西海岸生长的黑松(Pinus thunbergii Parl.),其立地指数受土壤Ca-P含量的显著影响[8];西班牙西北部土壤速效K含量与辐射松(P. radiata D. Don)立地指数间呈显著正相关[9]。对于同一树种而言,影响立地指数的养分因子因栽培区域而异:如苏格兰东北部的北美云杉(Picea sitchensis (Bong.) Carrière),其立地指数受表层土壤全N和全P含量的显著影响[10];而在阿拉斯加东南部,土壤有机C含量与北美云杉立地指数间呈显著正相关[11]。研究土壤养分与立地指数间的关系对于造林决策、无林地立地生产力估算等具有重要意义[12]。
西南桦(Betula alnoides Buch.-Ham. ex D. Don)是热带、南亚热带地区的一个速生珍贵用材树种,其木材材质优良,用途广泛,市场需求大。目前,西南桦在广西、云南等省区均大规模种植,其人工林面积已逾15.0万hm2[13]。在西南桦人工林快速发展过程中,由于立地选择不当、经营管理粗放等诸多原因,造成大量西南桦林分生产力低下。尽管影响西南桦林分生产力的因素复杂多样,林地土壤养分状况无疑是一个至关重要的因素。广西大青山林区为西南桦栽培最早的地区,本研究以其西南桦人工林为研究对象,设置典型样地开展林木生长调查与土壤养分测定,系统分析其林地土壤养分状况,探讨西南桦的土壤适应性,揭示土壤养分与立地生产潜力间的关系,为西南桦造林地选择、养分管理提供参考。
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考虑不同年龄、坡向、坡位等因素,在热带林业实验中心的青山、白云和伏波3个实验场西南桦人工林内分别设置17、14、16块600 m2的典型样地,并进行海拔、坡向等立地因子调查及常规生长测定。各样地的地形因子和林分年龄见表 1。
表 1 西南桦人工林样地概况
Table 1. General situations of the plots in Betula alnoides plantations
样地号
Plot No林龄
Age/a海拔
Altitude/mSA SP SG/(°) SI b1 14 670 SHA U 28.0 20 b2 14 670 SHA U 16.0 18 b3 14 670 SHA U 28.0 18 b4 17 460 SSHA M 36.0 20 b5 17 460 SSHA M 37.0 24 b6 17 455 SSHA M 39.0 22 b7 17 564 SSUN M 14.0 20 b8 17 485 SUN M 31.0 18 b9 17 485 SUN M 32.0 16 b10 17 390 SSUN L 37.0 18 b11 17 390 SSUN L 28.0 18 b12 17 400 SUN M 22.0 16 b13 17 400 SUN L 28.0 20 b14 17 405 SUN L 34.0 22 f1 14 460 SSUN L 39.0 22 f2 14 460 SHA L 34.0 26 f3 14 460 SHA L 26.0 24 f4 14 460 SHA L 24.0 26 f7 24 600 SSUN U 36.0 22 f8 24 600 SHA U 32.0 18 f9 24 600 SHA U 42.0 20 f11 13 640 SUN U 28.0 16 f12 13 640 SUN U 31.0 20 f13 13 640 SSUN M 32.0 28 f14 13 640 SHA U 37.0 20 f15 13 640 SSHA U 34.0 22 f16 15 440 SSUN M 31.0 18 f18 15 440 SSUN M 31.0 18 f21 16 480 SHA M 28.0 20 f23 16 480 SHA M 32.0 20 q1 12 230 SHA U 14.0 18 q2 12 230 SHA U 9.0 18 q3 12 230 SHA U 23.0 18 q4 13 190 SHA U 15.0 18 q5 13 190 SHA U 22.0 20 q6 13 190 SHA U 26.0 18 q7 20 260 SSUN U 23.0 20 q8 20 240 SSUN U 21.0 18 q9 20 250 SUN U 25.0 20 q10 20 250 SUN U 21.0 20 q11 20 250 SUN U 21.0 18 q12 20 240 SUN U 18.0 18 q14 12 523 SSUN M 37.0 16 q15 12 500 SSUN M 37.0 16 q16 12 550 SSUN M 34.0 20 q17 12 550 SUN M 32.0 22 q18 12 550 SUN M 31.0 20 注:SA、SP、SG、SI分别表示坡向、坡位、坡度和立地指数;b、f、q分别表示白云、伏波和青山实验场;SUN、SSUN、SHA、SSHA分别表示阳坡、半阳坡、半阴坡和阴坡;U、M、L分别表示上、中和下坡位。
Note:SA, SP, SG, SI represent slope aspect, slope position, slope gradient and site index; b, f, and q represent Baiyun, Fubo and Qingshan Experimental Stations; SUN, SSUN, SHA and SSHA represent sunny, semi-sunny, shade and semi-shade slopes; and U, M and L represent upper, middle and lower slopes, respectively.在每个样地的对角线上设置3个5 m×5 m的样方,每个样方挖取1个土壤剖面,取030 cm土壤约1 kg带回实验室,按国家林业局土壤养分分析标准制样并测定土壤pH值及有机质、全N、全P、全K、有效N、有效P、速效K、交换性Mg、活性Al的含量[14]。
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依据全国第二次土壤普查养分分级标准进行土壤养分分级[15]。
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每个样地的立地指数来自文献[16]中的“广西热林中心西南桦人工林立地指数表”。根据样地调查资料,每个样地选取5株优势木或亚优势木求其平均高,查表获得其立地指数(表 1)。
西南桦喜温凉气候,偏低海拔立地会因为温度高而影响西南桦生长[17],由表 1亦可以看出,海拔小于300 m的11个样地,其立地指数普遍偏小。300 m以上海拔较适宜西南桦生长,因此,在分析土壤养分特征与立地生产力的关系时仅针对海拔300 m以上的样地。35个样地的立地指数介于16 m与28 m之间,其均值约为20 m。据此将立地分为两类:大于20为高产组,小于或等于20为低产组(表 2)。采用独立样本t检验比较高产组和低产组之间各土壤养分的均值及其差异显著性。数据处理与分析均采用SPSS 22.0软件进行。
表 2 广西大青山中高海拔35个西南桦人工林样地的立地分组
Table 2. Site group division for 35 plots in Betula alnoides plantations of medium to high altitudes at Daqing Mountain, Guangxi
立地分组
Site groups样地数
Plot number样地号
Plots code立地指数(均值SD)
SI (Mean SD)显著性
Sig.HPS 11 b5, b6, b14, f1, f2, f3, f4, f7, f13, f15, f17 23.64±2.16 LPS 24 b1, b2, b3, b4, b7, b8, b9, b10, b11, b12, b13, f8, f9, f11, f12, f14, f16, f18, f21, f23, q14, q15, q16, q18 18.50±1.59 0.000 注:HPS和LPS分别表示高产和低产立地,下同。
Note: HPS and LPS represent site with high and low productivity, respectively. The same below. -
依据全国第二次土壤普查养分分级标准,广西大青山西南桦人工林地土壤为强酸性;其有机质、有效N、全N含量高;速效K、全P、交换性Mg缺乏;有效P、全K甚缺(表 3)。各土壤化学性质指标变异系数的变化范围为0.041.02,pH值的变异性最弱,全K含量的变异性最强(表 3)。
表 3 广西大青山西南桦人工林47个样地土壤化学性质特征
Table 3. Chemical properties of soils in 47 sampling plots of Betula alnoides plantations at Daqing Mountain, Guangxi
因子
Regimes最小值
Min最大值
Max均值
Mean标准差
S.D变异系数CV pH (H2O) 3.93 4.67 4.21 0.19 0.04 OM /(g·kg-1) 16.54 89.40 37.60 13.87 0.37 AN /(mg·kg-1) 64.38 324.27 134.61 52.36 0.39 AP /(mg·kg-1) 0.78 2.24 1.38 0.36 0.28 AK/ (mg·kg-1) 6.27 89.66 44.64 21.22 0.48 TN /(g·kg-1) 0.68 2.91 1.52 0.43 0.28 TP/ (g·kg-1) 0.11 0.69 0.34 0.13 0.37 TK/ (g·kg-1) 0.76 15.78 4.58 4.65 1.02 EMg /(cmol·kg-1) 0.07 1.03 0.27 0.18 0.66 AAL/ (g·kg-1) 15.77 57.75 35.22 12.54 0.36 注:OM、AN、AP、AK、TN、TP、TK、EMg、AAL分别表示有机质、有效N、有效P、速效K、全N、全P、全K、交换性Mg和活性Al含量;下同。
Note: OM, AN, AP, AK, TN, TP, TK, EMg and AAL refer to contents of organic matter, available nitrogen, available phosphorus, available potassium, total nitrogen, total phosphorus, total potassium, exchangeable magnesium and active aluminum, respectively. The same below.从表 3亦发现:大部分养分含量的最小值和最大值相差几倍至十几倍,仅以均值并不能全面反映出林地土壤各养分丰缺程度。进一步分析各样地土壤养分含量的分布频率(表 4)可知:90%以上样地属于强酸性土壤;绝大部分样地的土壤有机质、有效N、全N含量处于中等偏上水平;所有样地土壤有效P甚缺,全P、全K、速效K、交换性Mg含量中等偏下。
表 4 广西大青山西南桦人工林土壤养分指标分布频率
Table 4. Frequency distribution of soil nutrients in sampling plots of Betula alnoides plantations at Daqing Mountain, Guangxi
% 项目Item 丰Rich 高High 中Middle 低Low 缺Deficient 甚缺More deficient pH (H2O) (碱Alkali)0 (微碱Subalkaline)0 (中性Neutral)0 (微酸Micro acid)0 (酸Acid)8.5 (强酸Strongly acid)91.5 OM 38.3 29.8 29.8 2.1 0.0 0.0 AN 34.1 17.0 31.9 17.0 0.0 0.0 AP 0.0 0.0 0.0 0.0 0.0 100.0 AK 0.0 0.0 0.0 27.7 51.1 21.3 TN 6.4 42.6 42.6 6.4 2.1 0.0 TP 0.0 0.0 2.1 31.9 53.2 12.8 TK 0.0 0.0 4.3 14.9 10.6 70.2 EMg 0.0 0.0 2.1 14.9 38.3 44.7 -
由表 5可知:高产和低产组两类立地间土壤有机质和全K含量呈极显著差异(P<0.01),有效N含量差异显著(P<0.05),速效K含量在0.1水平上差异显著(P=0.076),其它养分指标均差异不显著(P≥0.05)。
表 5 高产与低产立地间土壤养分特征差异比较
Table 5. Comparison of soil nutrient status at high and low productivity sites
指标
Index立地分组
Site group均值
Mean标准差
SDt 显著性
Sig.pH(H2O) LPS
HPS4.14
4.190.18
0.19-0.825 0.416 OM/(g·kg-1) LPS
HPS31.70
45.726.51
14.673.018 0.005 AN/(mg·kg-1) LPS
HPS116.33
157.7727.49
62.282.102 0.043 AP/(mg·kg-1) LPS
HPS1.46
1.450.36
0.420.058 0.954 AK /(mg·kg-1) LPS
HPS41.18
56.9022.20
26.40-1.833 0.076 TN/(g·kg-1) LPS
HPS1.40
1.660.26
0.531.545 0.132 TP/(g·kg-1) LPS
HPS0.38
0.330.14
0.111.048 0.302 TK/(g·kg-1) LPS
HPS1.68
3.120.86
2.26-2.765 0.009 EMg/(cmol·kg-1) LPS
HPS0.21
0.200.12
0.120.168 0.868 AAL/(g·kg-1) LPS
HPS42.06
37.128.92
11.381.396 0.172
广西大青山西南桦人工林土壤养分特征及其与立地生产力的关系
Assessing Soil Nutrient Status and Its Relationship with Site Productivity of Betula alnoides Plantations in Daqingshan Mountains, Guangxi
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摘要:
目的 探讨西南桦人工林对土壤的适应性及土壤养分特征, 揭示土壤养分状况与立地生产力的关系, 为其造林地选择及人工林养分管理提供参考。 方法 在广西大青山林区西南桦人工林内设置47块600 m2的典型样地, 调查常规测树因子, 采集土壤样品, 测定10项常规土壤化学性质指标; 按照土壤养分分级标准评价土壤养分状况, 基于立地指数将样地分为高产和低产组, 进一步比较分析两组立地间各养分指标的差异性, 探讨土壤养分对立地生产力的影响。 结果 表明:广西大青山西南桦人工林地土壤绝大部分为强酸性, 有机质、有效N、全N含量中等偏上, 有效P甚缺, 其它养分含量中等偏下。高产和低产立地间土壤有机质和全K含量均呈极显著差异(P < 0.01), 有效N含量差异显著(P < 0.05)。 结论 西南桦对于低pH值、低P含量的土壤具有较强的适应性; 有机质、全K和有效N含量是影响广西大青山西南桦人工林立地指数的关键土壤养分因子。 Abstract:Objective The soil nutrient status in Betula alnoides plantation was investigated to assess the soil fitness of the species and reveal the relationship between soil nutrient regimes and site productivity so as to provide reference for site selection and soil nutrients management of B. alnoides plantation. Method Forty-seven plots with size of 600 m2 were established in B. alnoides plantations in Daqingshan Mountains, Guangxi. Three soil samples were collected in each plot and their soil chemical properties were analyzed, the soil nutritional status was evaluated according to the classification standard of soil nutrition. The plots were then divided into two site groups with high and low productivity based on their site index, and the differences in soil nutrition were further analyzed between the site groups. Result The soil in majority of B. alnoides plantation was strongly acidic. The soil organic matter and nitrogen contents were in upper-middle class, the available phosphorus was of heavy shortage, and the contents of other nutrients were in lower-middle class. The soil organic matter and total potassium contents were significantly different at the level of 0.01, and the available nitrogen content at the level of 0.05 between high and low productivity sites. Conclusion B. alnoides has strong adaptability to soils with low pH value and phosphorus contents. The organic matter, total potassium and available nitrogen contents are the key soil nutrient factors influencing the productivity of B. alnoides plantations in Daqingshan Mountains. -
Key words:
- Betula alnoides plantation
- / soil nutrient characteristics
- / soil fitness
- / site index
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表 1 西南桦人工林样地概况
Table 1. General situations of the plots in Betula alnoides plantations
样地号
Plot No林龄
Age/a海拔
Altitude/mSA SP SG/(°) SI b1 14 670 SHA U 28.0 20 b2 14 670 SHA U 16.0 18 b3 14 670 SHA U 28.0 18 b4 17 460 SSHA M 36.0 20 b5 17 460 SSHA M 37.0 24 b6 17 455 SSHA M 39.0 22 b7 17 564 SSUN M 14.0 20 b8 17 485 SUN M 31.0 18 b9 17 485 SUN M 32.0 16 b10 17 390 SSUN L 37.0 18 b11 17 390 SSUN L 28.0 18 b12 17 400 SUN M 22.0 16 b13 17 400 SUN L 28.0 20 b14 17 405 SUN L 34.0 22 f1 14 460 SSUN L 39.0 22 f2 14 460 SHA L 34.0 26 f3 14 460 SHA L 26.0 24 f4 14 460 SHA L 24.0 26 f7 24 600 SSUN U 36.0 22 f8 24 600 SHA U 32.0 18 f9 24 600 SHA U 42.0 20 f11 13 640 SUN U 28.0 16 f12 13 640 SUN U 31.0 20 f13 13 640 SSUN M 32.0 28 f14 13 640 SHA U 37.0 20 f15 13 640 SSHA U 34.0 22 f16 15 440 SSUN M 31.0 18 f18 15 440 SSUN M 31.0 18 f21 16 480 SHA M 28.0 20 f23 16 480 SHA M 32.0 20 q1 12 230 SHA U 14.0 18 q2 12 230 SHA U 9.0 18 q3 12 230 SHA U 23.0 18 q4 13 190 SHA U 15.0 18 q5 13 190 SHA U 22.0 20 q6 13 190 SHA U 26.0 18 q7 20 260 SSUN U 23.0 20 q8 20 240 SSUN U 21.0 18 q9 20 250 SUN U 25.0 20 q10 20 250 SUN U 21.0 20 q11 20 250 SUN U 21.0 18 q12 20 240 SUN U 18.0 18 q14 12 523 SSUN M 37.0 16 q15 12 500 SSUN M 37.0 16 q16 12 550 SSUN M 34.0 20 q17 12 550 SUN M 32.0 22 q18 12 550 SUN M 31.0 20 注:SA、SP、SG、SI分别表示坡向、坡位、坡度和立地指数;b、f、q分别表示白云、伏波和青山实验场;SUN、SSUN、SHA、SSHA分别表示阳坡、半阳坡、半阴坡和阴坡;U、M、L分别表示上、中和下坡位。
Note:SA, SP, SG, SI represent slope aspect, slope position, slope gradient and site index; b, f, and q represent Baiyun, Fubo and Qingshan Experimental Stations; SUN, SSUN, SHA and SSHA represent sunny, semi-sunny, shade and semi-shade slopes; and U, M and L represent upper, middle and lower slopes, respectively.表 2 广西大青山中高海拔35个西南桦人工林样地的立地分组
Table 2. Site group division for 35 plots in Betula alnoides plantations of medium to high altitudes at Daqing Mountain, Guangxi
立地分组
Site groups样地数
Plot number样地号
Plots code立地指数(均值SD)
SI (Mean SD)显著性
Sig.HPS 11 b5, b6, b14, f1, f2, f3, f4, f7, f13, f15, f17 23.64±2.16 LPS 24 b1, b2, b3, b4, b7, b8, b9, b10, b11, b12, b13, f8, f9, f11, f12, f14, f16, f18, f21, f23, q14, q15, q16, q18 18.50±1.59 0.000 注:HPS和LPS分别表示高产和低产立地,下同。
Note: HPS and LPS represent site with high and low productivity, respectively. The same below.表 3 广西大青山西南桦人工林47个样地土壤化学性质特征
Table 3. Chemical properties of soils in 47 sampling plots of Betula alnoides plantations at Daqing Mountain, Guangxi
因子
Regimes最小值
Min最大值
Max均值
Mean标准差
S.D变异系数CV pH (H2O) 3.93 4.67 4.21 0.19 0.04 OM /(g·kg-1) 16.54 89.40 37.60 13.87 0.37 AN /(mg·kg-1) 64.38 324.27 134.61 52.36 0.39 AP /(mg·kg-1) 0.78 2.24 1.38 0.36 0.28 AK/ (mg·kg-1) 6.27 89.66 44.64 21.22 0.48 TN /(g·kg-1) 0.68 2.91 1.52 0.43 0.28 TP/ (g·kg-1) 0.11 0.69 0.34 0.13 0.37 TK/ (g·kg-1) 0.76 15.78 4.58 4.65 1.02 EMg /(cmol·kg-1) 0.07 1.03 0.27 0.18 0.66 AAL/ (g·kg-1) 15.77 57.75 35.22 12.54 0.36 注:OM、AN、AP、AK、TN、TP、TK、EMg、AAL分别表示有机质、有效N、有效P、速效K、全N、全P、全K、交换性Mg和活性Al含量;下同。
Note: OM, AN, AP, AK, TN, TP, TK, EMg and AAL refer to contents of organic matter, available nitrogen, available phosphorus, available potassium, total nitrogen, total phosphorus, total potassium, exchangeable magnesium and active aluminum, respectively. The same below.表 4 广西大青山西南桦人工林土壤养分指标分布频率
Table 4. Frequency distribution of soil nutrients in sampling plots of Betula alnoides plantations at Daqing Mountain, Guangxi
% 项目Item 丰Rich 高High 中Middle 低Low 缺Deficient 甚缺More deficient pH (H2O) (碱Alkali)0 (微碱Subalkaline)0 (中性Neutral)0 (微酸Micro acid)0 (酸Acid)8.5 (强酸Strongly acid)91.5 OM 38.3 29.8 29.8 2.1 0.0 0.0 AN 34.1 17.0 31.9 17.0 0.0 0.0 AP 0.0 0.0 0.0 0.0 0.0 100.0 AK 0.0 0.0 0.0 27.7 51.1 21.3 TN 6.4 42.6 42.6 6.4 2.1 0.0 TP 0.0 0.0 2.1 31.9 53.2 12.8 TK 0.0 0.0 4.3 14.9 10.6 70.2 EMg 0.0 0.0 2.1 14.9 38.3 44.7 表 5 高产与低产立地间土壤养分特征差异比较
Table 5. Comparison of soil nutrient status at high and low productivity sites
指标
Index立地分组
Site group均值
Mean标准差
SDt 显著性
Sig.pH(H2O) LPS
HPS4.14
4.190.18
0.19-0.825 0.416 OM/(g·kg-1) LPS
HPS31.70
45.726.51
14.673.018 0.005 AN/(mg·kg-1) LPS
HPS116.33
157.7727.49
62.282.102 0.043 AP/(mg·kg-1) LPS
HPS1.46
1.450.36
0.420.058 0.954 AK /(mg·kg-1) LPS
HPS41.18
56.9022.20
26.40-1.833 0.076 TN/(g·kg-1) LPS
HPS1.40
1.660.26
0.531.545 0.132 TP/(g·kg-1) LPS
HPS0.38
0.330.14
0.111.048 0.302 TK/(g·kg-1) LPS
HPS1.68
3.120.86
2.26-2.765 0.009 EMg/(cmol·kg-1) LPS
HPS0.21
0.200.12
0.120.168 0.868 AAL/(g·kg-1) LPS
HPS42.06
37.128.92
11.381.396 0.172 -
[1] Nohrstedt H. Response of coniferous forest ecosystems on mineral soils to nutrient additions:A review of Swedish experiences[J]. Scandinavian Journal of Forest Research, 2001, 16(6):555-573. doi: 10.1080/02827580152699385 [2] Scholten T, Goebes P, Kühn P, et al. On the combined effect of soil fertility and topography on tree growth in subtropical forest ecosystems-a study from SE China[J]. Journal of Plant Ecology, 2017, 10(1):111-127. doi: 10.1093/jpe/rtw065 [3] Yasin K, Ali B M, Ouz H. Relationship of tree height with soil properties, soil and needle nutrients in cedar (Cedrus libani A. Rich.) plantations[J]. Research Journal of Biotechnology, 2014, 9(7):60-68. [4] Yu C B, Chen F, Luo Z J, et al. Evaluation of soil nutrient status in poplar forest soil by soil nutrient systematic approach[J]. Journal of Forestry Research, 2004, 15(4):298-300. doi: 10.1007/BF02844957 [5] Pietrzykowski M, Socha J, Doorn N S V. Scots pine (Pinus sylvestris L.) site index in relation to physico-chemical and biological properties in reclaimed mine soils[J]. New Forests, 2015, 46(2):247-266. doi: 10.1007/s11056-014-9459-z [6] Bravo F, Montero G. Site index estimation in Scots pine (Pinus sylvestris L.) stands in the High Ebro Basin (northern Spain) using soil attributes[J]. Forestry, 2001, 74(4):395-406. doi: 10.1093/forestry/74.4.395 [7] Bergès L, Chevalier R, Dumas Y, et al. Sessile oak (Quercus petraea Liebl.) site index variations in relation to climate, topography and soil in even-aged high-forest stands in northern France[J]. Annals of Forest Science, 2005, 62(5):391-402. doi: 10.1051/forest:2005035 [8] Kim H, Jeong S H, Kam D G, et al. Developing a site index model considering soil characteristics for Pinus thunbergii stands grown on the west coast of Korea[J]. Journal of the Korean Society for Applied Biological Chemistry, 2013, 56(2):173-180. doi: 10.1007/s13765-012-3255-2 [9] Afif-Khouri E, Cámara Obregón M A, Oliveira-Prendes J A, et al. Relationship among soil parameters, tree nutrition and site index of Pinus radiata D. Don in Asturias, NW Spain[J]. Forest Systems, 2010, 19(1):77-88. doi: 10.5424/fs/2010191-01169 [10] Blyth J F, Macleod D A. Sitka spruce (Picea sitchensis) in north-east Scotland. Ⅰ. Relationships between site factors and growth[J]. Forestry, 1981, 54(1):41-62. doi: 10.1093/forestry/54.1.41 [11] Ford E W, Farr W A, Chien L P. Preliminary analysis of four soil variables and their relation to site index of Sitka spruce in southeast Alaska[C]//Slaughter C W, Gasbarro T. Proceedings of the Alaska Forest Soil Productivity Workshop. Anchorage, AK, April 28-301988. General Technical Report, PNW-219. USDA. Pacific North Western Research and Experimental Station, 1988: 84-89. [12] Farrelly N, Dhubháin A' N, Nieuwenhuis M. Sitka spruce site index in response to varying soil moisture and nutrients in three different climate regions in Ireland[J]. Forest Ecology and Management, 2011, 262(12):2199-2206. doi: 10.1016/j.foreco.2011.08.012 [13] Wang C S, Zhao Z G, Hein S, et al. Effect of planting density on knot attributes and branch occlusion of Betula alnoides under natural pruning in southern China[J]. Forests, 2015, 6(4):1343-1361. [14] 国家林业局.森林土壤分析方法[S].北京: 中国标准出版社, 2000. [15] 全国土壤普查办公室, 全国第二次土壤普查暂行技术规程[S].北京: 农业出版社, 1979. [16] 唐诚.西南桦人工林生长模拟及立地质量评价[D].北京: 中国林业科学研究院, 2017. [17] 曾杰, 郑海水, 翁启杰.我国西南桦的地理分布与适生条件[J].林业科学研究, 1999, 12(05):479-484. doi: 10.3321/j.issn:1001-1498.1999.05.006 [18] Li W, Johnson C E. Relationships among pH, aluminum solubility and aluminum complexation with organic matter in acid forest soils of the Northeastern United States[J]. Geoderma, 2016, 271:234-242. doi: 10.1016/j.geoderma.2016.02.030 [19] 黄丽媛, 袁军, 吴泽龙, 等.油茶林地土壤铝的含量和化学形态分析[J].经济林研究, 2016, 34(3):79-83. [20] 杨继镐.广西南部林地土壤与适生树种[M].北京:中国林业出版社, 1995. [21] 杨承栋.我国人工林土壤有机质的量和质下降是制约林木生长的关键因子[J].林业科学, 2016, 52(12):1-12. doi: 10.11707/j.1001-7488.20161201 [22] Tian Y, Takanashi K, Toda H, et al. pH and substrate regulation of nitrogen and carbon dynamics in forest soils in a karst region of the upper Yangtze River basin, China[J]. Journal of Forest Research, 2013, 18(3):228-237. doi: 10.1007/s10310-012-0341-6 [23] 戴万宏, 黄耀, 武丽, 等.中国地带性土壤有机质含量与酸碱度的关系[J].土壤学报, 2009, 46(5):851-860. doi: 10.3321/j.issn:0564-3929.2009.05.013 [24] Curtin D, Peterson M E, Anderson C R. pH-dependence of organic matter solubility:Base type effects on dissolved organic C, N, P, and S in soils with contrasting mineralogy[J]. Geoderma, 2016, 271:161-172. doi: 10.1016/j.geoderma.2016.02.009 [25] Lu Y H, Sit P, Hung T F, et al. Regression models for impact of soil properties on site index class of Scots pine (Pinus sylvestris L.) stands in south-western Poland[J]. Sylwan, 2012, 156(8):563-571. [26] Subedi S, Fox T R. Predicting loblolly pine site index from soil properties using partial least-squares regression[J]. Forest Science, 2016, 62(4):449-456, doi: 10.5849/forsci.15-127 [27] Wang G G. White spruce site index in relation to soil, understory vegetation, and foliar nutrients[J]. Canadian Journal of Forest Research, 2011, 25(1):29-38. [28] 贝昭贤, 张秋芳, 郑蔚, 等.模拟增温对中亚热带杉木人工林土壤磷有效性的影响[J].生态学报, 2017, 38(3):1-8. doi: 10.3969/j.issn.1673-1182.2017.03.001 [29] Wang G G, Huang S M, Monserud R A, et al. Lodgepole pine site index in relation to synoptic measures of climate, soil moisture and soil nutrients[J]. Forestry Chronicle, 2004, 80(6):678-686. doi: 10.5558/tfc80678-6 [30] Brown J H. Growth and site index of white pine in relation to soils and topography in the glaciated areas of Ohio[J]. Northern Journal of Applied Forestry, 2007, 24(2):98-103. [31] Sharma R P, Brunner A, Eid T. Site index prediction from site and climate variables for Norway spruce and Scots pine in Norway[J]. Scandinavian Journal of Forest Research, 2012, 27(7):619-636. doi: 10.1080/02827581.2012.685749