| 黑土区农田土壤节肢动物群落与土壤理化性质的关系 |
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| 引用本文： | 卢萍,徐演鹏,谭飞,杨忠岐,林英华. 黑土区农田土壤节肢动物群落与土壤理化性质的关系[J]. 中国农业科学, 2013, 46(9): 1848-1856. DOI: 10.3864/j.issn.0578-1752.2013.09.012 |
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| 作者姓名： | 卢萍 徐演鹏 谭飞 杨忠岐 林英华 |
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| 作者单位： | 1.中国林业科学研究院森林生态环境与保护研究所/国家林业局森林保护学重点实验室，北京 100091
2.中国林业科学研究院湿地研究所，北京 100091；3东北林业大学野生动物资源学院，哈尔滨 150040 |
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| 基金项目： | 国家自然科学基金项目（31071904） |
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| 摘 要： | 【目的】分析外源性碳、氮干扰下农田土壤动物群落特征和土壤主要性质之间的相互关系，探索外源性碳、氮转化与土壤动物相互作用。【方法】2011年5—9月，采用手拣法、改良干漏斗法（Modified Tullgren）和湿漏斗法（Baermann）对吉林黑土区不同外源碳、氮干扰处理小区，即0.5倍、1.0倍、1.5倍和2.0倍（C0.5、C1.0、C2.0、N0.5、N1.0、N1.5、N2.0）和对照小区（不施肥，CK）土壤节肢动物群落进行调查，并对土壤主要性质进行分析。【结果】研究时段，共收集到农田土壤节肢动物70 485头（未知111头），隶属8纲20目3亚目87科（总科）。农田土壤节肢动物个体数、类群数、群落多样性受采样时间与外源碳、氮干扰影响显著（P＜0.01）。与对照小区（CK）相比，施入外源碳增加了土壤有机碳与全氮含量、土壤C/N值以及土壤节肢动物个体数、类群数与多样性，但施入外源氮仅使土壤全氮含量和土壤中小型节肢动物的个体数增加。土壤节肢动物个体数与类群数分别与研究区域土壤温度、土壤湿度、土壤有机碳以及土壤呼吸强度存在显著的相关关系。等节虫兆科和长足虻科与土壤温度和土壤全氮含量呈正相关性；中气门亚目、甲螨亚目和棘虫兆科与土壤有机碳和土壤呼吸强度呈正相关性。冗余分析显示，土壤温度、土壤湿度以及土壤C/N对黑土区农田节肢动物主要类群作用最显著，农田土壤节肢动物主要类群较好的解释了土壤主要理化性质的变化。【结论】农田土壤节肢动物群落组成与多样性与采样时间、干扰种类相关，并受土壤温度、土壤湿度和土壤C/N影响；农田土壤节肢动物是反映土壤主要性质变化的敏感指示物。
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| 关 键 词： | 优势类群 群落多样性 营养功能群 主成分分析 |
| 收稿时间： | 2012-12-30 |
Relationship Between Cropland Soil Arthropods Community and Soil Properties in Black Soil Area |
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| LU Ping,XU Yan-Peng,TAN Fei,YANG Zhong-Qi,LIN Ying-Hua. Relationship Between Cropland Soil Arthropods Community and Soil Properties in Black Soil Area[J]. Scientia Agricultura Sinica, 2013, 46(9): 1848-1856. DOI: 10.3864/j.issn.0578-1752.2013.09.012 |
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| Authors: | LU Ping XU Yan-Peng TAN Fei YANG Zhong-Qi LIN Ying-Hua |
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| Affiliation: | 1.Key Laboratory of Forest Protection, State Forestry Administration/Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091;2.Institute of Wetland Research, Chinese Academy of Forestry, Beijing 100091;3.College of Wildlife Resource, Northeast University of Forestry, Harbin 150040 |
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| Abstract: | 【Objective】The characteristic of cropland soil arthropods community and soil properties under the disturbance of exogenous carbon and nitrogen was studied, to elucidate the effect of those disturbances on soil animal community.【Method】Using hand-sorting, modified Tullgren and Baermann’s methods, the cropland soil arthropods were collected from nine treatments, separately, i.e. Control (CK), exogenous carbon (C0.5, C1.0, C1.5, C2.0) and exogenous nitrogen (N0.5, N1.0, N1.5, N2.0) in the black soil area of Jilin during May to September of 2011, and the physic and chemistry character of the soil was also analyzed.【Result】A total of 70 485 individuals (111 unidentified） were collected, which belonged to eight classes, twenty orders, three suborders and 87 super-families. The individuals, groups and diversity of cropland soil arthropods were significantly affected by the sampling time and exogenous carbon and nitrogen. To compare to the control treatment(CK), soil organic carbon, soil total nitrogen, the C/N value of soil, individuals, group and diversity showed an increase in application exogenous carbon, while only soil total nitrogen, cropland individuals of soil meso-micro arthropods in application exogenous nitrogen. The number of individuals and groups were significantly correlated to soil moisture, soil temperature, soil organic carbon and soil respiration. Isotomidae and Dolichopodidae were both positively correlated to soil temperature and soil total nitrogen, while Mesostigmata, Oribatida and Onychiuridae positively correlated to soil organic carbon and soil respiration. The Redundancy analysis (RDA) showed that the dominant groups were significant effected by soil moisture, soil temperature and the C/N value of soil. The soil properties were much well explained by the dominant of cropland soil arthropod groups.【Conclusion】The composition and diversity of cropland soil arthropods were related to the sampling time and the types of exogenous, and affected by soil moisture, soil temperature and C/N value of soil. The cropland soil arthropod was sensitively indicator to inflect the changes in soil properties. |
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| Keywords: | dominant group community diversity guilt principal component analysis |
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