Application Of Niche Models In The Risk Assessment Of Invasive Alien Species

The world trade globalization has greatly promoted with the accelerating of the global economy integration, which provide a pathway for the alien species to invade, disseminate and spread around the world. The biological invasion has caused irreversible ecological disaster and enormous economic losses in many countries in the world. The geography and climate of China are tremendously diverse, and almost all kind of species can found suitable places to live in our country. Due to the vast, diverse ecological environment, it is particularly important to strengthen the defense against the biological invasion in our country. In order to promote the international trade and avoid using quarantine measures as a disguised mean by the trade protectionism, the World Trade Organization (WTO) has made some provisions to guarantee the measures being used appropriately, the Sanitary and Phytosanitary measures agreement (SPS) is one of the most important representatives. China, as one of WTO member, we must obey the agreement as we take active quarantine measures to protect the health of plant, animal and human in our country against the invasion of the alien species. A scientific reason must be provided to support decision when the measures did not agree with the international standards. The risk analysis is the centre of the scientific basis.The quantitative risk assessment of invasive alien species (IAS) is the developing trend all over the world, and currently this quantification is mainly embodied in the establish risk, spread risk and social impact of IAS. The suitability analysis lays the foundation of establish risk of IAS. It is very difficult to eradicate the IAS once it had successfully invaded, so we could not to test the suitability of the IAS in the novel region by introducing the species into this area. Fortunately we can predict the potential geographic distribution of IAS in the target region by using mathematical models. The niche based models were commonly employed to predict the habitat suitable maps of species, which can provide essential technical support for the policy-maker when they formulate the corresponding measures.The principle of ecological niche modeling was based on that there is a special niche - the set of environmental factors that determine where a species can or cannot maintain populations - for each specific species. We can deduce the ecological niche requirement of a species from the species' distribution information, and then project the niche requirement onto the novel area the species never been found before to predict the suitable maps of the species. Typically, applying niche models needs two types of data, one is the distribution of the species, the other is the environmental data. The locations of species distribution can be obtained from field survey, consulting the literature and searching the occurrence database of species, such as GBIF (Global Biodiversity Information Facility). The choice of environment variables has a direct effect on the final result. We select the predict variables which determine the species geographical distribution mostly based on the ecological niche factors analysis (ENFA) results. Receive operating characteristic curve (ROC) analysis was employed to evaluate the performance of different models, and based on the assessment results we chose the best model to give the final prediction suitable maps of the IAS. The habitat suitable maps were scaled by combining the Boyes index curve and the true positive rate. Thus we proposed a framework of the risk assessment of IAS based on ecological niche modeling.Using this risk assessment framework, we analyzed the potential geographic distribution of Radopholus similis (R.similis), Phatophthora sojae (P.sojae) and Synchytrium endobioticum (S.endobioticum) in China with 6 common used niche models: BIOCLIM, DOMAIN, ENFA, GARP, Mahalanobis and Maxent. The results showed that all of the 6 models can be used to predict the distribution of species with acceptable results, but the performance of different models varied dramatically. From the cases studied in this paper, the performance of Maxent is on top of the range with easy use and fast speed. From the results predicted by the models, the suitable areas of R.similis concentrates in the south of China, such as Hainan, Fujian, Guangdong, Guangxi, Yunnan, Taiwan provinces and areas, the high risk regions of P.sojae including the Heilongjiang, Jilin, Liaolning, Beijing, Hebei, Shandong, Jiangsu, Zhejiang, Anhui, Hubei, Jiangxi provinces, the potential distribution of S.endobioticum would lie in Guangxi, Guizhou, Sichuan, Gansu, Shanxi, Hubei and Jiangsu provinces.Using the ecological niche models to predict the distribution of species, we assumed that the niche requirement of species is conserved, which means that the niche of the species in the original region is the same or very similar to that of in the invaded area. But this presumption was not always correct in all conditions, the niche of species may shift some time. The niche of IAS tends to shift due to following two reasons: one is the fundamental niche of IAS can be changed as a result of the fast evolution of invasive species, the other is the realized niche of IAS can be alternated by lacking of natural enemies and competitors, and existing lots of empty niches. It is difficult to obtain the direct evidence of niche shift of IAS by traditional experiment. We proposed a method to gain an indirect evidence of niche shift of IAS by applying the niche models. Using Ageratum conyzoides (A.conyzoides) - one of regional distress invasive weed in China - as a case study, we analyzed the niche shift phenomenal of A.conyzoides. The results showed that the niche of tropical ageratum has shifted after invaded in China.The framework of risk assessment of IAS based on niche modeling has provided an essential technical support and useful tool for us to struggle with invasive species. We also investigated the possibility of applying the niche models in studying the niche shift of IAS during the invading process.