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Dynamic And Prediction To Number Of Rhombomys Opimus Population

Posted on:2005-08-22Degree:MasterType:Thesis
Country:ChinaCandidate:J HuangFull Text:PDF
GTID:2120360125459188Subject:Zoology
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Rhomboms Opimus is one of major harmful mice in desert of Middle Asia. It mainly distributes in Xinjiang, Inner Mongolia and Gansu Province in China. And it mainly distributes in Junggar Basin, Yili valley, Hami Basin and Qijiaojing mountains valley in Xinjiang. Studies on ecology about Rhomboms Opimus have been reported, such as ecology observation and experiment of prevention and management (Li Chuanxun,1966) ;the cluster analysis of body length and body weight and the age of male Rhomboms Opimus by the least distance method (Zhao Tianbiao, 1993);population spatial pattern conditions of Rhombomys opimus in Tengernor, Damaoqi of Inner Mongolia (Zhang Zhongbin,1997), study on spatial pattern of hole groups of Rhomboms Opimus (Zhao Tianbiao,1997);studies on the spatial pattern of the population of Rhomboms Opimus and Meriones Meridianus (Zhao Tianbiao,1999); home range choose of Rhomboms Opimus (Dai Kun,1999);investigation of reproductive habits of Rhomboms Opimus population from Tenggenaoer, Dmaoqi of Inner Mongolia (Zhao Tianbiao,2000);the distribution of Rhomboms Opimus in China (Zhou Lizhi,2000);the choice of habitat of Rhombomys opimus in Tengernor, Damaoqi of Inner Mongolia (Zhao Tianbiao,2002);divide male Rhomboms Opimus nigrescens into five age groups with body length, body weight and the rate of molar chewing part and teeth quality (Zhao Tianbiao,1993,2002)。But the research about dynamic and prediction to number of Rhombomys Opimus population has never been showed. The Ganjiahu wilderness H.persicum State Natural Reserve in Jinhe County lies in the north of Xinjiang, west in Junggar Basin. Climate is subtemperature zone inland-desert climate, winter is length and hyperborean, summer is torrid and less rainfall, spring and autumn have a little much rainy. From April in 2002 to October in 2003, we conducted 9 times wildness fieldwork, 30 plots have been set in the way of 100mX100m, traps was distributed according to 5X20, the total number of traps amount to 9364. Measure as plots-area with traps, which last 72 hours and was checked every morning and dusk while the bait were be replaced, was taken to capture Rhombomys opimus. All have been measured with common biology methods, dissecting and recording number of embryos and womb spots, keeping the bone of head. Dividing age groups, making life table, measuring the stable age structure, finding out the relation between female reproductive peculiarity and the number dynamic of Rhombomys opimus population, predicting the reasonably near future trend on number dynamic and it's cause, deducing the number dynamic of Rhombomys opimus population in the latest years, verifying it's dynamic trend, finding out the cause, making the prediction equation. we provide reference for prediction. The results are as follows: 1.We use body weight excluding viscera as main index, and reference many factors, such as the body weight, body length, the variation of molar teeth chewing, what the growing degree of womb spots, whether the female is pregnant, how many little sizes and the womb spots in different period; whether the male's testicle has descended, the degree of it's distension, etc. We divide them into 5 age groups. In this way, the variation of body which caused by the pregnancy of female and the testicle distension of male can be avoided. Body weight excluding viscera can increase with age, its difference in different age groups has significant distinction. Therefore body weight excluding viscera is more fit for the dividing to age group for Rhombomys opimus. It is an accepted method. Compared with Zhao Tianbiao's method, it has difference some extent(1993,2000).2.In spring, summer and autumn of 2002 and 2003,the value of rm of Rhombomys opimus population were above zero, the value ofλwas above 1, this showed the population was increasing, but the extent was decreasing. The stable structure, which were calculated by the formula ofΣmxlxe-rmx=1 and Cx=mxlx/Σ(mxlx), showed it's increased in spring, stable in summer, stable but tur...
Keywords/Search Tags:Rhombomys opimus, number dynamic, prediction, Leslie matrix
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