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Population Status And Dispersal Trend Simulation Of Asian Openbill In China

Posted on:2018-12-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y LeiFull Text:PDF
GTID:2370330545457754Subject:Physical geography
Abstract/Summary:PDF Full Text Request
The ecological impact of new distribution species on local ecosystem is uncertain.Monitoring its distribution pattern is important for management and conservation of species.Asian openbill(Anastomus oscitans),a newly recorded species in China,have spread to Yunnan,Guizhou,Guangxi and Sichuan provinces in recent years,the population and occurrence sites are gradually increasing,however,its population dynamics,dispersal reason,trend and suitable distribution area were still lack understanding.In this study,the spatial distribution,population size and partial population dynamics of Aisan openbill in China.were studied by field investigation and data collection.Using the ecological niche model MaxEnt to compare the changes of the suitable area in different periods,and to analyze the relationship between species and envioronmental variables on two different spatial scales,global scene and China scene.Our results showed that:1)We found Asian openbill majority occurrence sites distribute in Yunnan,Guang xi,Guizhou three provinces,total number of population is 2135 ind by synchronous investigation.Among them,Yunnan is a major distribution of provines,accounting for 89.18%,Changqiao lake,located in Mengzi city,has the Maximum population size of all distribution sites,accounting for the total number of 50.4%.It means eastern of Yunnan has been the mainly distribution area;During 2013 to 2014 investigation data of Cao hai reserve,the maximum number increased to 602 ind from 427 ind in summer of 2013 and 2014,showed a rapidly increasing trend and its population trend exhibited significant seasonal fluctuation because of population size are more from May to October and decreased in November to April.2)Using MaxEnt model to analyze suitable area in global distribution sites before 2006,the results showed that the Indian Peninsula and Indochina Peninsula are the main suitable habitats for Aisan openbill,and are suitable for the annual average temperature of 25?,the coldest month minimum temperature above 0 ?,The annual temperature changes in the range of 10-20 ? and accompanied by a certain degree of human activity in the low latitude plains living in China,the distribution of a small area.In the same way,the analysis of the distribution of all species distribution in the current world is carried out.The results show that the current Asian jar stork has obvious diffusion trend in South Asia,Southeast Asia and even Oceania.Species suitable habitat temperature,temperature difference and other factors to increase the range of response,very low value on the suitability has increased.3)Only use occurrence data in China to built model then we found,Asian openbill distribution habitat in China prefer to live in annual average temperature of about 16 ?,besides the temperature and precipitation has significantly seasonal fluctuating environment conditions.We confirmed that the real niche of Asia openbill has been shift by comparing the difference between new distribution and original distribution on environment variables.Under future climate background,suitable area will increase entirely in 2050,especially in the middle part of Sichuan,the southern part of the Yangtze river and the Yun-Gui plateau.The suitable area slightly reduce in 2080,Guangdong coastal,Hainan island and Taiwan island is more stable.Overall,Asian Openbill have a tendency to dispearsal to the Chengdu plain,eastern coastal and islands.According to the results of the study,we propose to protect the Asian openbill due to its biological control of the invasive species like Golden apple snail,and recommend that the government departments establishing a consisted monitoring network to provide more basic data for the ecological impact and disease prevention.
Keywords/Search Tags:Asian openbill, MaxEnt model, Ecological niche, Suitable area prediction
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