| 付贞桢,魏有海,郭良芝,翁华,程亮,朱海霞,李玮,陈红雨.青海省春小麦田杂草群落组成及其多样性分析[J].干旱地区农业研究,2024,(2):254~263 |
| 青海省春小麦田杂草群落组成及其多样性分析 |
| Analysis of weed community composition and diversity in spring wheat fields in Qinghai Province |
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| DOI：10.7606/j.issn.1000-7601.2024.02.27 |
| 中文关键词: 春小麦田 杂草 群落组成 物种多样性 青海省 |
| 英文关键词:spring wheat fields weed community composition species diversity Qinghai Province |
| 基金项目:科技部第二次青藏高原综合科学考察研究资助项目(2019QZKK0303)；国家重点研发计划项目（2018YFD0200405） |
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| 中文摘要: |
| 为明确青海省春小麦田杂草发生种类及其群落特征，采用倒置“W”九点取样法对青海省东部农业区和柴达木盆地农业区春小麦田杂草种类、生活型、科属组成、群落结构及杂草多样性进行调查。统计分析发现：小麦田有85种杂草，隶属24科64属。其中，菊科和禾本科是数量最多的科别，杂草分别为16种和14种。从杂草的综合优势度来看，藜（Chenopodium album L.）、野燕麦(Avena fatua L.)、萹蓄(Polygonum aviculare L.)、苦苣菜(Sonchus oleraceus L.)、苣荬菜(Herba Sonchi Brachyoti)5种杂草为优势杂草，芦苇(Phragmites australis(Cav.)Trin.)、赖草(Leymus secalinus (Georgi) Tzvel.)、狗尾草(Setaria viridis(Linn.) Beauv.)、藏蓟（Cirsium eriophoroides）、荞麦蔓（Fagopyrum esculentum Moench.）、节裂角茴香（Hypecoum leptocarpum Hook.f.et Thoms. ）、猪殃殃（Galium spurium L. ）、大刺儿菜（Cirsium arvense var. setosum (willd.) Ledeb）、密花香薷（Elsholtzia densa Benth. ）、野油菜（Brassica juncea (L.) Czern. et Coss.）10种杂草为区域性优势杂草。此外有常见杂草22种，一般性杂草48种。东部农业区田间杂草物种丰富度较柴达木地区高，湟中区、大通县、互助县麦田杂草的物种丰富度依次为46、45、42；柴达木盆地的都兰县、德令哈市、乌兰县、格尔木市麦田杂草的物种丰富度依次为30、26、23、13，调查区以格尔木市的物种丰富度最小。比较杂草的生活型发现，同一地区越年生杂草、多年生杂草的发生数量和一年生杂草的数量基本接近50%；从杂草群落的相似性来看，东部农业区的湟中区、互助县、大通县杂草群落组成极为相似，而柴达木盆地绿洲农业区的都兰县、德令哈市、格尔木市、乌兰县杂草群落相似性程度高，杂草群落结构的相似性结果与区域小麦生产实际相吻合。群落结构组成和区域耕作制度、气候条件、土壤理化性质、田间管理水平等具有较大的相关性，建议加强杂草优势种和区域性优势杂草的防控和监测，因地制宜制定杂草绿色防控措施。 |
| 英文摘要: |
| To clarify the types and community characteristics of weeds in spring wheat fields in Qinghai Province, the inverted “W” nine\|point sampling method was used to investigate the types, life forms, family and genus composition, community structure, and diversity of weeds in spring wheat fields in the eastern agricultural areas of Qinghai Province and the Qaidam Basin. Statistical analysis revealed that there were 85 species of weeds in the wheat fields, belonging to 24 families and 64 genera. Among them, Asteraceae and Poaceae were the most abundant families, with 16 and 14 species of weeds, respectively. In terms of the comprehensive dominance of weeds, Chenopodium album L., Avena fatua L., Polygonum aviculare L., Sonchus oleraceus L., and Herba Sonchi Brachyoti were the dominant weeds, while Phragmites australis (Cav.) Trin., Leymus secalinus (Georgi) Tzvel., Setaria viridis (Linn.) Beauv., Cirsium eriophoroides, Fagopyrum esculentum Moench., Hypecoum leptocarpum Hook.f.et Thoms., Galium spurium L., Cirsium arvense var. setosum (Willd.) Ledeb., Elsholtzia densa Benth., and Brassica juncea (L.) Czern. et Coss. were the regional dominant weeds. In addition, there were 22 common weeds and 48 general weeds. The species richness of weeds in the fields of the eastern agricultural region was higher than that in the Qaidam region. The species richness of weeds in the wheat fields of Huangzhong District, Datong County, and Huzhu County was 46, 45, and 42, respectively. The species richness of weeds in wheat fields of Dulan County, Delingha City, Ulan County, and Geermu City in the Qaidam Basin was 30, 26, 23, and 13, respectively. The species richness in Geermu City was the smallest in the survey area. Comparison of different life forms of weeds, it was found that the number of perennial and annual weeds in the same area was almost 50%. From the perspective of community similarity, the communities in Huangzhong District, Huzhu County, and Datong County in the eastern agricultural region were extremely similar, while the communities in Dulan County, Delingha City, Geermu City, and Ulan County in the oasis agricultural region of the Qaidam Basin had a high degree of similarity. The similarity in weed community structure was consistent with the actual wheat production in the region, and the composition of community structure was related to regional cultivation systems, climate conditions, soil physical and chemical properties, and field management level. It is recommended to strengthen the control and monitoring of dominant weed species and regional dominant weeds, and develop green control measures for weeds according to local conditions. |
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