基于最小数据集的喀斯特不同类型人工林土壤质量评价

doi:10.12302/j.issn.1000-2006.202311032

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南京林业大学学报（自然科学版） ›› 2025, Vol. 49 ›› Issue (2): 134-142.doi: 10.12302/j.issn.1000-2006.202311032

基于最小数据集的喀斯特不同类型人工林土壤质量评价

程彩云¹(), 薛建辉¹^,²^,^*(), 马洁³

1.南京林业大学生态与环境学院,江苏南京 210037
2.江苏省中国科学院植物研究所,江苏南京 210014
3.江苏省舜德生态环境科技有限公司,江苏南京 210043

收稿日期:2023-11-26 接受日期:2024-03-05 出版日期:2025-03-30 发布日期:2025-03-28
通讯作者: *薛建辉(jhxue@cnbg.net),教授。
作者简介:
程彩云(caiyuncheng5280@foxmail.com)。
基金资助:
国家重点研发计划(2016YFC0502605)

Assessment of different Karst plantation types on soil quality based on a minimum data set

CHENG Caiyun¹(), XUE Jianhui¹^,²^,^*(), MA Jie³

1. College of Ecology and the Environment, Nanjing Forestry University, Nanjing 210037, China
2. Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
3. Jiangsu Shunde Ecological Environment Technology Co., Ltd., Nanjing 210043, China

Received:2023-11-26 Accepted:2024-03-05 Online:2025-03-30 Published:2025-03-28

摘要/Abstract

摘要：

【目的】评价喀斯特山地不同类型人工林植被恢复对土壤质量的影响,为该地区选择适宜的造林树种和改善林地土壤质量提供参考依据。【方法】以贵州省喀斯特山地营造的干香柏 (Cupressus duclouxiana,下称滇柏)纯林、刺槐(Robinia pseudoacacia)纯林和滇柏-刺槐混交林这3种类型人工林及未造林地(CK)为研究对象,对喀斯特山地不同类型人工林土壤理化性质和酶活性变化进行了研究,采用冗余分析、主成分分析(PCA)、全体数据集(TDS)、最小数据集(MDS)和灰色关联度(GRA)等方法评估土壤质量。【结果】①3种人工林地土壤含水率、孔隙度、有机质、全氮、碱解氮、全磷、速效磷质量分数均显著高于未造林地,容重、pH、全钾、速效钾质量分数均显著低于未造林地。②土壤脲酶、多酚氧化酶、蔗糖酶、碱性磷酸酶、过氧化氢酶这5种酶中,除碱性磷酸酶活性外,其余4种土壤酶活性均在滇柏-刺槐混交林土壤中最高。3种类型人工林土壤脲酶、碱性磷酸酶、过氧化氢酶活性均高于未造林地。③基于主成分分析法的最小数据集适合作为喀斯特山地人工林土壤质量评价的最小数据集提取方法,本研究选择的最小数据集包括土壤全氮、全钾、速效钾质量分数、非毛管孔隙度、碱性磷酸酶、多酚氧化酶活性。④基于MDS 建立的土壤质量评价结果与基于TDS和灰色关联度的评价结果相一致,土壤质量评价得分从大到小顺序均为滇柏-刺槐混交林>刺槐林>滇柏林>未造林地。总体上看,混交林土壤质量明显优于纯林。【结论】在喀斯特山地植被恢复和人工林营造中,可遵循适树适地的原则,以营造混合林为主,从而达到改善土壤综合质量,提高人工植被修复生态效益的目的。

关键词: 喀斯特山地, 土壤质量综合评价, 主成分分析法(PCA), 最小数据集(MDS)

Abstract:

【Objective】This study evaluated soil quality under different types of plantation vegetation restoration in Karst areas, aiming to provide guidance on selecting suitable tree species and improving soil quality. 【Method】Three types of plantation forests—Cupressus duclouxiana forest, Robinia pseudoacacia forest, and C. duclouxiana-R. pseudoacacia mixed forest—along with unplanted land (control) in Guizhou Province, were selected for the study. The soil physical, chemical, and enzymatic characteristics were analyzed. Redundancy analysis and principal component analysis (PCA) were used to assess soil fertility quality, while total data set (TDS), minimum data set (MDS), and gray correlation degree method (GRA) were employed to evaluate soil fertility. 【Result】(1) Compared with unplanted land, soil water content, porosity, organic matter, total nitrogen, alkali-hydrolyzed nitrogen, total phosphorus, and available phosphorus content were significantly higher in plantation forests. Conversely, soil bulk density, pH, total potassium, and available potassium were significantly lower. (2) Except for alkaline phosphatase, the activities of urease, polyphenol oxidase, sucrase, and catalase were the highest in the C. duclouxiana-R. pseudoacacia mixed forest. Urease, alkaline phosphatase, and catalase activities were higher in plantations than those in unplanted land. (3) The minimum data set derived from PCA was suitable for soil quality evaluation in Karst plantations. This data set included soil total nitrogen, total potassium, available potassium content, non-capillary porosity, alkaline phosphatase, and polyphenol oxidase activities. (4) Soil quality evaluations based on MDS align with those based on TDS and grey correlation degree. The soil quality order was as follows: C. duclouxiana-R. pseudoacacia mixed forest > R. pseudoacacia forest > C. duclouxiana forest > unplanted land. The mixed forest demonstrated significantly better soil quality than the pure forests. 【Conclusion】 During vegetation restoration and plantation development in Karst areas, following the principles of tree adaptation and site suitability, and focusing on constructing mixed forests, can enhance overall soil quality and improve the ecological benefits of artificial vegetation restoration.

Key words: Karst area, evaluation of soil quality, principal component analysis(PCA), minimum data set(MDS)

中图分类号:

S714

程彩云,薛建辉,马洁. 基于最小数据集的喀斯特不同类型人工林土壤质量评价[J]. 南京林业大学学报（自然科学版）, 2025, 49(2): 134-142.

CHENG Caiyun, XUE Jianhui, MA Jie. Assessment of different Karst plantation types on soil quality based on a minimum data set[J].Journal of Nanjing Forestry University (Natural Science Edition), 2025, 49(2): 134-142.DOI: 10.12302/j.issn.1000-2006.202311032.

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林分类型 forest type	地理位置 location	坡度/ (°) slope	海拔/m altitude	林分密度/ (株·hm^-2) stand density	平均树高/m average tree height	平均胸径/cm average DBH	平均地径/cm average ground diameter	群落盖度/% coverage
CD	105°48'58.3″E,26°15'44.6″N	18	1 410	2 155	8.1	8.13	2.7	95.6
RP	105°50'49.2″E,26°16'57.7″N	10	1 470	1 722	4.2	4.77	4.8	94.9
CR	105°51'09.0″E,26°17'03.4″N	12	1 480	2 100	7.6	9.31	8.0/6.4	97.3
CK	105°51'11.6″E,26°16'53.5″N	13	1 480	—	—	—	—	91.4

林分类型 forest type	含水率/% WC	容重/ (g·cm^-3) BD	总孔隙度/% STP	毛管孔隙度/% SCP	非毛管孔隙度/% NSCP
CD	40.75±5.38 a	0.87±0.06 b	53.15±1.98 b	41.62±2.04 b	11.53±2.80 a
RP	46.08±3.71 a	0.70±0.03 d	64.76±5.17 a	50.91±1.24 a	13.84±6.37 a
CR	44.90±11.05 a	0.76±0.02 c	63.11±5.70 a	50.69±2.61 a	12.42±4.99 a
CK	34.97±5.39 b	0.97±0.03 a	46.35±5.00 c	39.48±6.08 b	6.86±2.21 b

林分类型 forest type	pH	有机质质量分数/ (g·kg^-1) SOM mass fraction	全氮质量分数/ (g·kg^-1) TN mass fraction	碱解氮质量分数/ (mg·kg^-1) HN mass fraction	全磷质量分数/ (g·kg^-1) TP mass fraction	速效磷质量分数/ (mg·kg^-1) AP mass fraction	全钾质量分数/ (g·kg^-1) TK mass fraction	速效钾质量分数/ (mg·kg^-1) AK mass fraction
CD	7.28±0.11 a	50.43±2.28 bc	3.54±0.13 c	269.60±8.95 c	0.86±0.03 ab	7.28±0.53 b	5.80±0.41 b	155.51±7.59 b
RP	6.76±0.13 c	53.87±2.95 ac	4.52±0.11 b	308.00±6.68 b	0.80±0.02 b	6.81±0.28 b	6.23±0.85 ab	163.05±7.78 b
CR	6.75±0.13 c	59.77±2.71 a	4.98±0.02 a	347.2±6.33 a	0.99±0.03 a	9.01±0.16 a	6.09±0.36 ab	149.7±7.29 b
CK	7.59±0.10 a	37.55±2.39 b	3.08±0.02 d	245.00±4.82 d	0.58±0.04 c	5.51±0.18 c	7.54±0.35 a	171.15±5.22 a

林分类型 forest type	脲酶活性/ (mg·g^-1·d^-1) UR activity	多酚氧化酶活性/ (mg·g^-1·h^-1) PO activity	蔗糖酶活性/ (mg·g^-1·d^-1) SU activity	碱性磷酸酶活性/ (mmol·g^-1·h^-1) ALP activity	过氧化氢酶活性/ (mol·g^-1·min^-1) CA activity
CD	766.14±21.80 b	33.22±3.66 b	42.20±9.22 b	42.70±1.18 a	8.08±0.59 a
RP	855.49±43.19 ab	23.21±2.93 c	75.22±5.53 a	45.21±1.07 a	8.26±0.12 a
CR	905.24±43.072 a	43.65±1.02 a	87.07±0.99 a	44.74±0.48 a	8.40±0.08 a
CK	681.40±26.74 b	28.76±2.09 b	42.66±0.77 b	41.58±0.16 b	6.46±0.04 b

土壤指标 soil index	分组 group	主成分principal component
土壤指标 soil index	分组 group	1	2	3	4	5
WC	1	-0.621	-0.136	0.125	0.201	-0.391
BD	1	0.842	-0.028	-0.213	-0.056	-0.149
STP	1	-0.889	-0.004	0.381	-0.009	0.027
SCP	1	-0.839	0.156	0.042	0.094	0.038
NSCP	3	-0.520	-0.202	0.615	-0.130	0.000
pH	1	-0.757	-0.064	0.295	0.196	0.010
SOM	1	0.666	0.345	0.234	-0.179	-0.267
TN	1	0.949	-0.020	0.097	0.035	-0.072
HN	1	0.871	-0.250	0.210	0.064	-0.020
TP	1	0.496	0.403	0.136	0.260	0.180
AP	1	0.588	0.387	0.431	0.051	0.055
TK	5	-0.225	-0.409	0.145	-0.466	0.585
AK	4	-0.205	-0.355	-0.420	0.517	0.388
UR	1	0.621	0.086	0.093	-0.281	0.367
PO	4	0.298	0.350	0.426	0.512	0.270
SU	1	0.666	-0.297	0.057	0.227	0.138
ALP	2	-0.316	0.867	-0.201	-0.067	0.117
CA	2	0.435	-0.821	0.188	0.103	-0.147
特征值 eigenvalue		7.428	2.521	1.452	1.108	1.045
方差贡献率/% percent of variance		41.265	14.007	8.065	6.153	5.806
累积方差贡献率/% cumulative percent of variance		41.265	55.272	63.337	69.490	75.296

基于最小数据集的喀斯特不同类型人工林土壤质量评价

Assessment of different Karst plantation types on soil quality based on a minimum data set

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[1]	安玉亭,薛建辉,吴永波,胡浩. 喀斯特山地不同类型人工林土壤微量元素含量与有效性特征[J]. 南京林业大学学报（自然科学版）, 2013, 37(03): 65-70.
[2]	戎宇，刘成刚，薛建辉*. 喀斯特山地不同人工林土壤特性差异与综合评价[J]. 南京林业大学学报（自然科学版）, 2011, 35(02): 108-112.
[3]	刘成刚，戎宇，薛建辉*，姚健. 喀斯特山地不同人工林土壤酶活性与草本层结构特征的关系[J]. 南京林业大学学报（自然科学版）, 2011, 35(02): 99-102.
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[5]	张喜. 贵州喀斯特山地坡耕地立地影响因素及分区[J]. 南京林业大学学报（自然科学版）, 2003, 27(06): 98-102.
[6]	万福绪;张金池. 黔中喀斯特山区的生态环境特点及植被恢复技术[J]. 南京林业大学学报（自然科学版）, 2003, 27(01): 45-49.