The Risk Assessment Of Information Diffusion Model Applied To Biological Invasion

This artical use the distribution data of Spartina alterniflora and the ocean environmental monitoring data of Ningde Sansha Bay,from April to October during 2014 and 2015.Run preliminary risk assessment of Spartina alterniflora and Karenia mikimotoi and the results are given. Collectting Ningde area determined invasionspecieSpartina, through the literature research, to archive the basic ecological characteristicsof Spartina alterniflora. Colletting water quality and phytoplankton identification data from April to October in 2014 and 2015 of Ningde Sansha Bay ocean, compared with national ocean bureau a wide range of the phytoplankton in Fujian in 2010,find out Ningde may be invasive plankton algae species of Karenia mikimotoi. By literature survey to explore the best breeding conditions of Karenia mikimotoiand the resultsare set for the risk assessment model as a reference standard and the maximum value for further work. At the same time, the sampling of seawater samples, obtain the corresponding laboratory data, Sansha Bay area of Ningde basic environmental state and eutrophic conditions to make a preliminary evaluation. Collectting research progress in risk assessment and risk assessment models in common use, choose the most suitable model of this study-- information diffusion model, which has many related research in geological disasters, disaster forestry, agriculture and meteorological disasters risk assessment while rare report in the ecological risk assessment field. The main advantage of the information diffusion model is particularly important and necessary that it needs the original data in a small number.The main conclusions of the study are:(1) the dominant species of phytoplankton in the Ningde. There are 34 species of phytoplankton in the sea area of Ningde, which belong to 63 genera and 4 species. In this survey, 40 species of phytoplankton were collected and divided into 22 genera. A significant seasonal variation exists: spring and summer diatom species increased, while dinoflagellate in autumn.The main dominant species were Skeletonemacostatum and Prorocentrum donghaiense.(2) Ningde sea water temperature constant in 12 ℃- 35℃, soluble phosphate and inorganic nitrogen content change with in larger, reached seawater quality standard IV. Water quality eutrophication appear the local difference: the eastern rim of Dong Chong Peninsula is in moderate eutrophication, for a long time; Northeastern seawater does not appear eutrophication; eutrophication of waters along the coast of northern waters is serious; eutrophication time of Sansha Bay mouth focused on April, other timefor noneutrophication or intermittently eutrophication.(3)There are 34 species of alien invasive species in the sea area of Ningde, which are mainly marine ballast water and the intention to introduce into the Ningde sea area. Among them, Karenia mikimotoiwhich has strong damage on aquaculture is harmful algae; Spartina alterniflorais dominant in Fujian mangrove areas, and mangrove decreases all the time.The monitoring work needs to be further strengthened.(4) The information diffusion model has good practicability and applicability in the risk assessment of biological invasion. For Spartina alterniflora area prediction and Karenia mikimotoi,a possible outbreak of prediction, accords with actual situation, own important reference value. Further optimization and development of the model is to improve the scope of the model and to provide a better reference.According to information diffusion model and the relationship and effect of alien marine organisms risk assessment, thisstudy established a mathematical model by using the multiplicative relationship.participating factorswere standardized referring to the formula in paper, to calculate the invasion risk comprehensive index. In the case of lacking data, this paper firstly uses the information diffusion model in fuzzy mathematics to establish the risk assessment model in the field of marine environmental risk assessment. Although the preliminary evaluation results of the model have not reached 90%, the model still needs to be improved, but it is a new method for risk assessment.