Response of soil nutrients and their stoichiometric ratios to stand density in Pinus tabuliformis and Robinia pseudoacacia plantations in the loess region of western Shanxi Province, northern China
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摘要:目的 研究对比油松和刺槐林在不同密度下土壤养分及其化学计量比的变化规律及差异性，以加强黄土区人工林的林分管理和生态恢复建设。方法 以油松和刺槐人工林为研究对象，分别将其划分为高（2 000 ~ 2 700株/hm2）、中（1 100 ~ 1 600株/hm2）、低（800 ~ 1 100株/hm2）3组林分密度类型，每组挑选4个不同林分密度的林地，分别分层采取土样，测定土壤理化性质。结果 （1）双因素方差分析显示，林分类型对全磷含量（TP）、碳磷比（C∶P）、氮磷比（N∶P）均有显著影响，林分密度仅对TP有显著影响，林分类型与林分密度的交互作用对有机碳含量（SOC）、全氮含量（TN）、TP、C∶P、N∶P均有显著影响。（2）不同林分密度的油松林和刺槐林的SOC和TN表现为：高密度油松林（油H） > 中密度油松林（油M） > 低密度刺槐林（刺L） > 高密度刺槐林（刺H） > 低密度油松林（油L） > 中密度刺槐林（刺M），全P表现为：刺M > 油H > 刺L > 刺H > 油M > 油L；随林分密度增加，油松林各土层SOC和TN逐渐增加，TP变化相对稳定且无显著性差异，刺槐林各土层SOC和TN先减少后略有增加，TP则是先增加后减少；同一密度在不同林分类型下，油松林土壤养分含量在高密度和中密度时均优于刺槐林，低密度时则相反。（3）不同林分密度的油松和刺槐林的C:N比值表现为：油H > 刺H > 刺L > 油M > 刺M > 油L，C∶P和N∶P比值均表现为：油H > 油M > 刺L > 刺H > 油L > 刺M；随林分密度的增加，油松林土壤C∶P和N∶P逐渐增大，磷的有效性逐渐减小，刺槐林土壤C∶P和N∶P先减小后增大，磷的有效性先升高后降低，油松林土壤磷的有效性在高和中密度下低于同等密度的刺槐林，低密度下则相反；土壤SOC和TN分别在很大程度上决定了C∶P和N∶P水平；不同林分密度下土壤C∶N比较稳定，土壤氮含量较缺乏，林分生长过程受氮素的限制。（4）油松和刺槐林在不同林分密度下的土壤各养分含量呈现出“表聚现象”且随土层深度增加土壤SOC、TN、TP、C∶P、N∶P逐渐减小，C∶N无明显规律；随林分密度增加，油松林土壤属性变异强度先降低后升高，刺槐林则是缓慢升高；相比于油松林，林分密度对刺槐林土壤养分及其化学计量比的垂直变异影响较小，垂直变异更趋于平稳。（5）林分密度的变化会不同程度地改变土壤物理性质对土壤养分及其化学计量比的影响力度，不同林分密度下土壤密度对土壤养分含量及化学计量比的影响最大，非毛管孔隙次之。结论 综合来看，同一林分类型在不同密度下，油松林在中密度时土壤养分含量及其垂直变异、磷的有效性发挥、受氮素的限制等方面上均处于较优水平，而刺槐林则是在低密度时；同一密度在不同林分类型下，油松林在高密度和中密度的综合表现优于同等密度的刺槐林，低密度时则相反。Abstract:Objective This paper aims to study the changes and differences of soil nutrient and stoichiometry of Pinus tabuliformis and Robinia pseudoacacia plantations under different densities to strengthen the stand management and ecological restoration of artificial forests in the Loess Plateau of northern China.Method P. tabuliformis and R. pseudoacacia plantations were taken as research objects, and they were divided into three groups of stand density: high (2 000−2 700 plant/ha), medium (1 100−1 600 plant/ha) and low (800−1 100 plant/ha). Four kinds of stands with different densities were selected for each group, and soil samples were taken in layers respectively to measure the physical and chemical properties of soil.Result (1) Two-factor analysis of variance showed that the stand type had a significant effect on total P, C:P, N:P, the stand density only had a significant effect on total P, and the stand type and stand density had a jointly significant effect on organic carbon, total N, total P, C:P, N:P. (2) The organic carbon and total N of P. tabuliformis and R. pseudoacacia forests with different stand densities were as follows: high density P. tabuliformis forests (Pinus H) > medium density P. tabuliformis forests (Pinus M) > low density R. pseudoacacia forests (Robinia L) > high density R. pseudoacacia forests (Robinia H) > low density P. tabuliformis forests (Pinus L) > medium density R. pseudoacacia forests (Robinia M ), and the total P is as follows: Robinia M > Pinus H > Robinia L > Robinia H > Pinus M > Pinus L. With the increase of stand density, the contents of organic carbon and total N in all soil layers of P. tabuliformis forest showed gradual increase, while the changes of total P content were relatively stable and had no significant difference. The contents of organic carbon and total N in all soil layers of R. pseudoacacia forest first decreased and then slightly increased, while the contents of total P first increased and then decreased. Under the same density and different stand types, the soil nutrient content of P. tabuliformis forest was better than R. pseudoacacia forest at high density and medium density, but it was opposite at low density. (3) The C∶N ratios of P. tabuliformis and R. pseudoacacia forests with different stand densities were as follows: Pinus H > Robinia H > Robinia L > Pinus M > Robinia M > Pinus L and the C∶P and N∶P ratios were as follows: Pinus H > Pinus M > Robinia L > Robinia H > Pinus L > Robinia M. With the increase of stand density, the soil C∶P and N∶P in P. tabuliformis forest gradually increased, the availability of phosphorus gradually decreased, while the soil C∶P and N∶P in R. pseudoacacia forest decreased first and then increased, the availability of phosphorus first increased and then decreased. The availability of phosphorus in P. tabuliformis forest soil was lower than that in R. pseudoacacia forest with the same density under high and medium density, but the opposite was true under low density. Soil organic carbon and total N determined the levels of C:P and N:P respectively to a great extent. Under different stand densities, soil C:N was relatively stable, soil nitrogen content was relatively deficient, and growth process was limited by nitrogen. (4) The soil nutrient content of P. tabuliformis and R. pseudoacacia under different forest densities showed an “ surface aggregation phenomenon ” and soil organic carbon, total N, total P, C∶P, N∶P gradually decreased with the increase of soil depth. C∶N had no obvious law. With the increase of stand density, the variation intensity of soil properties of P. tabuliformis forest firstly decreased and then increased, while that of R. pseudoacacia forest increased slowly. Compared with P. tabuliformis forest, stand density had less influence on the vertical variation of soil nutrients and stoichiometry of R. pseudoacacia forest, and the vertical variation tended to be more stable. (5) The change of stand density will change the influence of soil physical properties on soil nutrient and its stoichiometric ratio to different extent. The effects of soil bulk density on soil nutrient content and stoichiometric ratio were the greatest under different stand densities, followed by non capillary porosity.Conclusion Generally, under different densities of the same stand type, P. tabuliformis forest is at a better level in soil nutrient content and its vertical variation, phosphorus availability and nitrogen limitation at medium density, while R. pseudoacacia forest was at low density in comparison. Under the same density and different stand types, the comprehensive performance of P. tabuliformis forest in high density and medium density was better than that of R. pseudoacacia forest with the same density, but it is opposite in low density.
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Keywords:
- stand density /
- Pinus tabuliformis /
- Robinia pseudoacacia /
- soil nutrient /
- stoichiometric ratio
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竹材具生长周期短、硬度强、韧性高、可降解的生物性材料。且在现有木材资源不能适应家具产业发展迫切需要的情况下，竹材是取代实木的最理想材料[1]，竹集成材作为保持了竹材优异的物理力学性能的竹制家具用材，具有良好的发展前景。众所周知，竹材容易受外界环境如光照、水、微生物等的侵害而发生变色、腐朽[2]，竹集成材亦如是。对竹集成材进行表面涂饰是最能够有效保护其性能的方法之一。
以水作为溶剂的水性漆与传统油性漆相比，不含挥发性有机物（volatile organic compounds，VOCs），具有绿色环保、节约资源的特性[3]。伴随着国家环保政策的不断完善和绿色环保理念的普及，水性漆在家具、室内装饰、建筑等领域将逐步替代传统涂料[4]。然而竹集成材水性漆涂饰面临着竹集成材密度大，纹孔少，横向渗透困难等问题[5]，使得水性漆漆膜附着力差，竹集成材水性漆涂饰工业化进度缓慢。为了克服这些问题，Lu[6]通过对毛竹表面进行过氧化氢表面预处理的方法，提高了水性漆在毛竹表面的附着力。此外其他研究人员通过使用湿热处理[7-8]、碱液浸泡处理[9]等方法，也在一定程度上提高了竹材表面的润湿性和粗糙度，改善了水性漆等流体在竹材内部的渗透效率，漆膜的附着力由此增强。涂饰工艺对涂料性能的发挥有着重要影响，是涂饰过程中的关键技术环节。但目前有关水性涂饰工艺的研究还着重于水曲柳、杨木等木质材料上[10-12]，对竹集成材涂饰工艺研究较少，且未有水性清漆和色漆对竹集成材硬度、附着力等漆膜性能影响方面的研究。
为了解决竹集成材水性涂装这些难题，本研究以家具中最为常用的毛竹集成材为基材，在省去预处理的基础上优化了竹集成材水性涂饰工艺，提高了水性涂饰工艺的效率，系统地探究了竹集成材清漆与色漆涂饰性能的影响及竹集成材水性漆漆膜的附着机理，为竹家具的水性化涂装提升提供理论支持和科学依据。
1. 材料与方法
1.1 材 料
选取含水率为11%的毛竹集成材，制成尺寸为100 mm（长） × 100 mm（宽） × 10 mm（厚）的试样18块，并对试样在室温和湿度为（65 ± 3）%的环境下进行打磨。选用涂料为自制水性底漆和商业水性面漆（分为清漆与色漆两种类型，主要成分为水性聚氨酯树脂，底漆固体含量为39.2%，面漆固体含量为34.6%）。
1.2 基材涂饰
依次用80目、120目、180目和240目砂纸对基材进行顺纹打磨并用羊毛刷除尘。涂饰前底漆与面漆分别添加5% 和8%的去离子水进行调配。调配底漆涂布量为80 g/m2，面漆涂布量为120 g/m2，在室温下均匀地喷涂底漆3遍、面漆1遍，每遍喷涂干燥之后再次顺纹打磨1遍（图1）。涂饰完后基材后在室温下干燥8 h。
1.3 测试方法
将无差别的18个样品分为A、B和C这3组，每组6个，按照字母加数字的方式编号成A1 ~ A6、B1 ~ B6和C1 ~ C6。
1.3.1 漆膜硬度、附着力、光泽度测试
选取A组试样进行漆膜的硬度测试。根据ISO 15184—1998 《色漆和清漆 铅笔法测定漆膜硬度》标准测试。选取B组试样进行漆膜的附着力测定。根据ISO 2409—2013《色漆和清漆交叉切割试验》中的检测标准，按照规定的步骤，使用QFH漆膜划格仪依次对每个试样进行测定。参照ISO 2813—2014《色漆和清漆在20°、60°和85°非金属色漆漆膜镜面光泽的测定》使用60°光泽度仪对C组和对照试样进行光泽度测试。
1.3.2 表面粗糙度测试
参照GB/T 12472—2003《产品几何量技术规范（GPS） 表面结构 轮廓法 木制件表面粗糙度参数及其数值》，使用TR240便携式表面粗糙度仪测试试样的表面粗糙度，将触针的运动转变为电信号，测量出各粗糙度参数。设置取样长度为2.5 mm，为了提高准确率，在每一块试件上选取4 个点测试，并对测试结果进行记录。
1.3.3 色度值测试
使用SP60色差仪按照国际照明委员会CIE标准色度系统对C组试样基材涂饰前后的颜色变化进行定量的度量。CIE由L*、a*、b*这3个数值进行评估。L*表示亮度；a*表示红绿，数值变化由正到负，表示颜色从红（正）到绿（负）；b*表示黄蓝，数值变化由正到负，表示颜色从黄（正）到蓝（负）。总色差值ΔE表示颜色知觉差异，数值越小则表示颜色变化越小。ΔE由公式（1）确定：
ΔE=√ΔL∗2+Δa∗2+Δb∗2 (1) 式中：ΔL*、Δa* 和Δb*分别为涂饰前后的L*、a*和b*差值。
1.3.4 扫描电镜（scanning electron microscope，SEM）分析
使用场发射环境扫描电镜（FEG-ESEM，XL30ESEMFEG，FEI Company，USA）观察并记录基材涂饰前后的表面形态。将加速电压设置为7 kV后，着重对涂饰后基材与漆膜界面结合处的形态进行观察。
1.3.5 傅里叶变换红外光谱（Fourier transform infrared spectroscopy，FTIR）分析
用溴化钾压片法分别测定涂饰前后试样的FTIR。设置光谱分辨率为4 cm−1，在500 ~ 4 000 cm−1范围内，利用傅里叶变换红外光谱仪（Nicolet6700傅里叶红外光谱仪，Thermo Scientific, Waltham, USA）扫描得到清漆、色漆、竹集成材、清漆和色漆涂饰后的基材的5种FTIR。测试完成后，将所有5个样品的光谱绘制成图表，分析每个样品的特征峰的变化，并据此探究水性漆与竹集成材的结合机理。
2. 结果与讨论
2.1 漆膜硬度与附着力
漆膜硬度代表了涂饰在基材上的漆膜的机械强度，反映了漆膜对来自外界的碰擦、刺划等机械作用的耐受能力[13]。从表1可以看出：清漆的漆膜硬度为1H，而色漆的漆膜硬度为2H。这是因为漆膜的硬度是由成膜物质的性能所决定的，色漆中含有较高硬度的颜料，因而色漆的硬度优于清漆。但两者的硬度均能够满足GB/T 3324—2017《木家具通用技术条件》中室内装饰、实木地板的使用要求[14]。此外，我们发现清漆和色漆的漆膜硬度均比之前研究的水性漆涂饰水曲柳所得的硬度高[12]，这充分说明了水性漆采用喷涂的涂饰工艺能在竹集成材上产生能媲美在木材上的效果。
表 1 水性漆漆膜的硬度与附着力Table 1. Hardness and adhesion of film of waterborne paint清漆 Varnish 色漆 Color paint 试件 Sample 硬度 Hardness 附着力 Adhesion 试件 Sample 硬度 Hardness 附着力 Adhesion A1 1H 0级 Grade 0 B1 2H 1级 Grade 1 A2 1H 0级 Grade 0 B2 2H 1级 Grade 1 A3 1H 0级 Grade 0 B3 2H 1级 Grade 1 A4 1H 0级 Grade 0 B4 2H 1级 Grade 1 A5 1H 0级 Grade 0 B5 2H 1级 Grade 1 A6 1H 0级 Grade 0 B6 2H 1级 Grade 1 平均值 Average value 1H 0级 Grade 0 平均值 Average value 2H 1级 Grade 1 漆膜附着力是指导家具涂装工艺优化方向的关键数据，也是影响漆膜性能的重要指标之一[15-16]。由表1可知：清漆漆膜的附着力比色漆漆膜的附着力更高，可达为最高的0级，这是由于色漆由于含有颜料，其固含量高于清漆，所以清漆具有更高的渗透能力，因而清漆能更好地填充在基材的细胞腔里。从SEM图中也能清晰地看到涂饰前后的差别。在未涂饰基材图（图2a、2b）中可以看到有较大的导管存在基材的横切面上，而纵切面上较多的则是裸露的细胞腔，基材表面裸露的细胞腔为水性漆在基材表面良好的附着性能提供了一定的基础。基材涂饰清漆和色漆后（图2c、2d），沟槽状的细胞腔和细胞胞间层中都有成膜物填充，因而达到较强的附着力。且从图2c、2d中也能看出：因清漆的渗透性能更好，使得在相同涂布量下，色漆的漆膜厚度明显高于清漆。此外，竹集成材水性清漆涂饰的漆膜附着力与之前研究的木材水性漆涂饰的附着力相当[12]。这也再次证明了使用“三低一面”的喷涂涂饰工艺能达到较好的漆膜性能。
2.2 光泽度
漆膜的光反射能力是通过漆膜的光泽度来衡量的,在一定范围内，随着竹材基材的表面光泽度增加，视觉效果变好[17]。涂饰前后基材的光泽度一般区分为垂直竹材纹理的光泽度值（gloss value of vertical bamboo texture，GZT）和平行竹材纹理的光泽度值（gloss value of parallel bamboo texture，GZL）。由图3可得涂饰后试样光泽度明显高于未涂饰试样，这是因为水性漆成膜物的光泽度比竹材自身的光泽度高。清漆涂饰后的平均GZT和GZL分别为19.83和21.24，色漆涂饰后的分别为21.39和22.93，均比未涂饰时提高了5倍以上，大大提升了竹集成材的装饰效果。且色漆因颜料填料含量较高，成膜物质在竹材表面固着占比更多，从而使得色漆光泽度均高于清漆。通过进一步对比发现试样的GZL均高于GZT，这是因为竹材大多数细胞是轴向排列的，在平行纹理方向，大部分细胞被剖开，细胞腔呈沟槽状暴露出来，因此成膜物容易填充到腔径大的细胞腔中；细胞壁的相对含量在垂直纹理方向上较多，因此成膜物很难渗透到具有纳米级孔的细胞壁中，导致平行纹理方向上成膜物的含量高于垂直纹理方向上的含量，因此其光泽度也显著增加[18-19]。
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图 3 基材涂饰前后光泽度GZT为光泽度仪垂直于木材纹理方向时所测得的光泽度值；GZL为光泽度仪平行于木材纹理方向时所测得的光泽度值。 GZT is the glossiness value measured when glossmeter is perpendicular to the direction of wood texture. GZL is the glossiness value measured when glossmeter is parallel to the direction of wood texture.Figure 3. Glossiness of substrate before and after painting2.3 表面粗糙度
表面粗糙度是指竹材在加工的过程中表面留下的各种不同程度的微观加工痕迹或不平度，常被用来评价竹材表面的质量，将会直接影响竹材的涂饰效果以及涂料的用量，常用轮廓算数平均偏差Ra、轮廓算数均方偏差Rq、微观不平度十点高度Rz和轮廓最大高度Ry表示[20]。本实验主要采用Ra表征试样的表面粗糙度，Ra的值越小，说明其表面越光滑平整。不同涂饰情况对应试样的表面粗糙度和电镜图见图4和图5。涂饰后的Ra值均小于未涂饰的Ra值，从SEM图也可以清楚地看出基材裸露的细胞腔被水性漆覆盖，表面粗糙度降低。且清漆涂饰后的Ra值比色漆涂饰后的Ra值小。这是因为色漆中含有颜料颗粒（图5b），可能影响成膜的交联程度，这导致涂饰色漆后表面粗糙度高于涂饰清漆后的表面粗糙度。
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图 4 涂饰前后试样表面粗糙度平均值Ra为评定轮廓的算数平均偏差； Rz为微观不平度十点高度，是指在取样长度内5 个最大的轮廓峰高的平均；Rq为评定轮廓的算数均方偏差；Ry为轮廓最大高度，是指在取样长度内，轮廓峰顶线和轮廓谷底线之间的距离。Ra is the arithmetical mean deviation of assessed profile; Rz is the height of ten points of micro unevenness, which refers to the average of five maximum contour peak heights within the sampling length; Rq is the root mean square deviation of the assessed profile; Ry is the maximum height of profile, which refers to the distance between the contour peak line and the contour bottom line within the sampling length.Figure 4. Surface roughness of substrate before and after painting2.4 色度值
色差是指两种颜色之间的差异。色差值是色差的数值表达。色差和色差值受涂料成分、涂饰工艺等因素的影响[21]。涂膜前后的色度值变化如图6所示。涂饰清漆前L*值为72.38，涂饰清漆后降低至64.37；a*值由原来的7.03增加到10.12；b*值由24.48增加到30.64。结果表明，涂层后基材表面明度略有下降，红色和黄色指数略有增加。ΔE较小为10.56，说明涂饰清漆前后竹集成材的表面颜色相差不大。这是因为水性清漆不含颜料，在竹集成材表面固化后是透明的，能较好地保持竹集成材本身的颜色。而涂饰色漆后L*值降低至34.74；a*值增加到12.03；b*值降低至18.30。说明涂层后基材表面明度有一定程度的下降，红色和蓝色指数略有增加。ΔE值较大，为38.46，这表明竹集成材表面的色彩特征因色漆中颜料的颜色发生了较大程度的改变。
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图 6 涂饰前后色度值对比L*表示亮度；a*表示红绿；b*表示黄蓝。 L* indicates lightness, a* indicates red and green, and b* indicates yellow and blue.Figure 6. Comparison of chromaticity values before and after painting2.5 FTIR分析
图7显示了各试样的FTIR，可以看出：3 436 cm−1处吸收峰是由−OH伸缩振动引起的，与其他谱线相比，竹材谱线在这一位置的峰值明显最强，且涂饰后色漆和清漆在1 724 cm−1处（C=O的拉伸振动特征峰）的强度分别较纯色漆与清漆小得多，在1 143 cm−1处（酯基中C−O伸缩振动峰）的峰值比竹材谱线的更强，说明水性漆中的极性分子（如羧基、羟基）与基材中的羟基结合后，水性底漆中的羧基与基材中的羟基发生了酯化反应，两者之间形成了氢键使结合更加稳固[22-23]。此外色漆在2 921 cm−1（−CH2反对称伸缩振动峰）、1 724 cm−1（C=O的拉伸振动特征峰）、1 460 cm−1（−CH2弯曲振动峰）、1 143 cm−1（C−O伸缩振动）处的峰值均比清漆所在的峰值高，这是由于色漆中相应的基团的占比比清漆中的高。所以水性底漆除物理结合外，还会与基材发生化学反应，使成膜物能很好地附着在竹集成材表面。
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图 7 水性漆与竹集成材涂饰前后的红外表征Figure 7. Infrared characterization of waterborne paint and bamboo laminated lumber before and after painting3. 结 论
本研究所获得的清漆的漆膜硬度为1H，色漆的漆膜硬度为2H。涂饰后，水性漆与竹集成材以机械互锁的物理形式和化学反应结合的形式使成膜物质能很好地附着在基材表面。由于色漆中含有颜料，清漆的附着性能优于色漆，可达最高的0级，与木材水性涂饰的附着性能相当。而颜料颗粒的存在影响了成膜的交联程度，使得色漆的表面粗糙度高于清漆。清漆和色漆涂饰后基材的光泽度提高了5倍以上，且平行纹理方向上的光泽度高于垂直纹理方向上。因色漆含有颜料，清漆涂饰前后总色差值较低，较好地保持了竹集成材本身优美的颜色。因此，本水性涂饰工艺在竹集成材上能获得较好的漆膜性能和较强的附着力，并能在很大程度上提升了竹集成材的装饰效果，为竹材及其制品的水性化涂装提供了重要的理论和技术支持。
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图 1 不同林分密度下2种人工林各土层土壤养分含量
不同大写字母表示同土层不同林分间差异显著，不同小写字母表示同林分不同土层间差异显著（P < 0.05）。油H. 高密度油松林；油M. 中密度油松林；油L. 低密度油松林；刺H. 高密度刺槐林；刺M. 中密度刺槐林；刺L. 低密度刺槐林。下同。Different uppercase letters indicate significant differences between varied forest stands in the same soil layer, and different lowercase letters indicate significant differences between varied soil layers in the same forest stands（P < 0.05）. 油H, high density Pinus tabuliformis plantation; 油M, medium density P. tabuliformis plantation; 油L, low density P. tabuliformis plantation; 刺H, high density Robinia pseudoacacia plantation; 刺M, medium density R. pseudoacacia plantation; 刺L, low density R. pseudoacacia plantation. The same below.
Figure 1. Soil nutrient contents in different soil layers of two plantations with varied stand densities
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图 2 不同林分密度下土壤属性的垂直分异
Figure 2. Vertical differentiation of soil properties under different stand densities
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图 3 不同林分密度下2种人工林各土层C、N、P化学计量比
Figure 3. Stoichiometric ratios of soil carbon （C）, nitrogen （N）, phosphorus （P） in different soil layers of 2 plantations with different stand densities
表 1 样地基本概况
Table 1 Basic information of the sample plots
林分类型
Stand type密度划分
Density division林分密度/（株·hm−2）
Stand density/
（plant·ha−1）土壤类型
Soil type坡向
Slope aspect坡度
Slope degree/（°）海拔
Altitude/m平均树高
Average tree height/m郁闭度
Canopy density油松
Pinus tabuliformisH 2 050，2 240，2 400，2 650 褐土
Cinnamon soil半阴坡
Semi-shady slope22 ~ 25 1 320 8.6 0.70 M 1 250，1 310，1 360，1 525 褐土
Cinnamon soil半阴坡
Semi-shady slope19 ~ 26 1 120 8.9 0.56 L 875，950，1 000，1 050 褐土
Cinnamon soil半阴坡
Semi-shady slope16 ~ 20 1 140 8.1 0.56 刺槐
Robinia pseudoacaciaH 2 050，2 155，2 350，2 675 褐土
Cinnamon soil半阴坡
Semi-shady slope21 ~ 27 1 110 7.0 0.46 M 1 175，1 350，1 410，1 525 褐土
Cinnamon soil半阴坡
Semi-shady slope21 ~ 24 1 040 8.2 0.60 L 900，975，1 010，1 075 褐土
Cinnamon soil半阴坡
Semi-shady slope16 ~ 19 1 130 10.1 0.50 注：H. 高密度；M. 中密度；L. 低密度。下同。Notes: H, high density; M, medium density; L, low density. The same below. 
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表 2 林分类型与林分密度对碳氮磷及其化学计量比的双因素方差分析
Table 2 Results of two-way ANOVA on the effects of stand type and stand density on organic carbon, nitrogen and phosphorus concentrations and their stoichiometric ratios
变异来源
Source of variation林分类型
Stand type林分密度
Stand density林分类型 × 林分密度
Stand type × stand densitydf F P df F P df F P SOC 1 3.54 0.063 2 2.59 0.079 2 5.49 < 0.01 TN 1 3.65 0.058 2 1.52 0.222 2 4.64 < 0.05 TP 1 20.67 < 0.001 2 5.16 < 0.01 2 13.21 < 0.001 C∶N 1 0.388 0.535 2 1.49 0.230 2 0.60 0.550 C∶P 1 6.30 < 0.05 2 2.61 0.078 2 5.34 < 0.01 N∶P 1 7.97 < 0.01 2 1.63 0.201 2 5.27 < 0.01 注：SOC. 土壤有机碳含量；TN. 全氮含量；TP. 全磷含量。下同。Notes: SOC, soil organic carbon content; TN, total nitrogen content; TP, total phosphorus content. The same below.
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表 3 碳氮磷含量及其化学计量比与土壤物理性质的相关性
Table 3 Correlations between organic carbon, nitrogen and phosphorus contents as well as their stoichiometric ratios and environmental factors
林分密度
Stand density土壤养分及其化学计量比
Soil nutrient and their
stoichiometric ratio土壤物理性质 Soil physical property 土壤密度
Soil density毛管孔隙度
Capillary porosity总孔隙度
Total porosity非毛管孔隙度
Noncapillary porosity含水率
Moisture contentH SOC − 0.566** 0.013 0.396* 0.359* 0.370* TN − 0.720** 0.268 0.316 0.332 0.124 TP − 0.369* 0.251 0.249 − 0.054 0.038 C∶N − 0.073 − 0.219 0.225 0.153 0.249 C∶P − 0.553** − 0.003 0.379* 0.377* 0.365* N∶P − 0.643** 0.173 0.219 0.341* 0.154 M SOC − 0.347* − 0.021 0.22 0.430** 0.308 TN − 0.421** 0.105 0.335* 0.485** 0.222 TP 0.197 − 0.284 − 0.056 0.046 0.238 C∶N − 0.178 − 0.078 0.058 0.188 0.262 C∶P − 0.405** 0.061 0.264 0.446** 0.226 N∶P − 0.457** 0.172 0.335* 0.474** 0.094 L SOC − 0.660** − 0.016 0.474** 0.552** 0.678** TN − 0.336* − 0.233 0.102 0.472** 0.701** TP − 0.243 0.329* 0.28 0.039 0.309* C∶N − 0.537** 0.131 0.528** 0.361* 0.318* C∶P − 0.642** − 0.066 0.438** 0.573** 0.663** N∶P − 0.308* − 0.281 0.059 0.483** 0.689** 注：*表示显著相关（P < 0.05），**表示极显著相关（P < 0.01）。Notes: * represents significant correlation （P < 0.05），** represents extremely significant correlation （P < 0.01）.
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