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A Study On Community Structure Of Insects And Weeds On Lawns In Nanjing

Posted on:2009-06-25Degree:MasterType:Thesis
Country:ChinaCandidate:H B GuoFull Text:PDF
GTID:2143360272988373Subject:Agricultural Entomology and Pest Control
Abstract/Summary:PDF Full Text Request
The population structure and distribution of the turf weed and the insect under different management lever or measures were surveyed. And the impact on between the occurrence of weed and insect communities and fertilizing, watering and grass mowing were studied and the peak period of occurrence of the weeds was set up. Moreover, the insect community structure in relation to environmental factors on Bermudagrass lawns were studied, and the main causes of the outbreak of dominant pest in bermudagrass lawn was revealed. The lawn pest was controlled using biological diversity from the ecological point of view.1. With sampling methods, twenty sampling plots in Nanjing were investigated in order to find out occurrence of weed species, infestation and distribution in turf. The results showed that the total of one hundred thirty-nine weed species, belonging to thirty-nine families, including twenty-four weed species of composite accounting for 17.27 percent, twenty-three weed species of poaceae accounting for 16.55 percent, 6 weed species of cyperaceae accounting for 4.32 percent, nine weed species of fabaceae accounting for 6.47 percent, eight weed species of scrophulariaceae total of 5.76% and other species accounts for about 50.0 percent of all weed species were recorded in Nanjing. The dominant population includes Poaceae, Compositae and Cyperaceae, and accountings for 38.13 percent of all weed species, accounting 58.80 percent of the total populations. The peak period of occurrence weed for full spring to the end of the summer. Moreover, it was founded that differences weed species in different types of turf, the distribution of one hundred thirty-two weed species accounting for 94.96 percent in warm-season turf more than seventy species of weeds about accounting for 50.36 percent in cool-season turf. The weed populations of different management levels in turf obviously, including 81 species in bermudagrass lawn, forty-seven species at least in tall fescue lawn; fivety-nine species in zoysia grass at fine-managed level. And ninety-eight species in most in bermudagrass lawn, eighty-two species in zoysia grass lawn and fifty-nine kinds in tall fescue lawn at poorly-managed level respectively.2. The obtained data were analyzed with canonical correspondence analysis (CCA). According to the analysis showed that the artificial management measures greatly reduce the number and species of weed. Soil fertilizer and watering conditions that affect the number of weeds were major environmental factors, the grass mowing was inhibited most high-weed species richness significantly, Digitaria sanguinalis, Cyperus rotundus, Cyperus difformis and others of richness were less effected. According to the different weed characteristics, 61 dominant lawn weed species were divided into three groups in Nanjing. First group of dominant weed species includes Eleusine indica, Digitaria sanguinalis, Cyperus rotundus and Cyperus difformis with low-cut resistance, resistance tramples and fast growth of the common characteristics. These weed species were not only negative correlated with turf grass growth (height), but also were positively correlated with water content in soil and fertilizing amount. The second group of dominant weed species includes Setaria glauca, Paspalum dilatatum, Imperata cylindrica var.majo, Medicago hispida, Trifolium repens. These weed species were not only negative correlated with water content in soil and fertilizing amount, but also were positively correlated with turf grass growth (height). The third group includes Erigeron annuus, Taraxacum mongolicum, Sonchus oleraceu and Artemisia lavandulaefolia were positively correlated with turf grass growth (height).3. One hundred-six insect species in turf, belonging to eleven orders, including twenty-four species of Coleoptera, according to the frequency, Oedaleu infernalis, Atractomorpha sinensis, Oxya chinensis, Teleogryllus emma, Gryllotalpa unispina, Cicadella viridis, Laodelphgax striatellus, Lygocoris lucorμm, Stephanitis nashi, Nabis stenoferus, Agetocera filicornis, Agrotis ypsilon, Predenia liture, Spodoptera depravata, Teretra japonica, Epiymiu sp. Chironomus sp., Calliphora vicina, Musca domestica, Lasius fuliginosus were the worst turf pest in Nanjing. Including forty-seven insect species in most in bermudagrass lawn, thirty species in tall fescue lawn; eighteen species at least in zoysia grass were recorded. According management lever, the number of insect at fine-managed level was less than poorly-managed level.4. Comparison to the seasonal dynamics and richness of weeds and insects in the same turf sampling, the result showed that the insects of occurrence time later than weeds, which the peak time of weeds growing since June to July, and insects in the peak period since August to September. Meanwhile, the number of occurrence weeds become to increase or reduce gradually was synchronized with insect species.5. The index of insect community diversity was reduced when the turf management lever raising. The grasshopper, leafhopper and Peanut-head bug were dominance pest species The dominant insect pests were grasshoppers (Acrididae), leafhoppers (Cicadellidae), and planthopper (Delphacidae) on poored-management in bermudagrass lawn, but Cicadella viridis, Laodelphgax striatellus, cutworms (Agrotis ypsilon) ,and Scarabaeid larvae on well-managed lawns. The CCA showed that soil physical characters (texture type and height of depositional horizon) were correlated with below-ground insect sub-community. Moreover, weed richness (number of weed species) and turf grass growth (height) were also correlated with carnivorous insect communities, but phytophagous insect communities were not correlated with turf habitat.
Keywords/Search Tags:Nanjing, turf weeds, turf insect, community, distribution rule, management measures, environmental factors, correlation
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