Introduction
Artemisia annua L. also called as annual wormwood, or huang hua hao, or sweet Annie, or sweet wormwood, is an annual herb, belong to Asteraceae(Lin, Humphries, & Gilbert, 2011). Its dry aboveground part is a traditional Chinese medicine called Qinghao(Tang & Eisenbrand, 1992). Qinghaosu (also named artemisinin or atreannuin), known as the frontline treatment of malaria(L. H. Miller & Su, 2011), was isolated only from A. annua with none yield in 30 other species of Artemisia (Klayman, 1985). Additional,A. annua has strong allelopathy(Lydon, Teasdale, & Chen, 1997). During its growth process, some secondary metabolites could be released to affect their surrounding plants(Knudsmark Jessing, Duke, & Cedergreeen, 2014). Therefore, it is an important resource plant not only for medical purpose to cure human diseases, but also for agricultural purpose to exploit natural herbicide.
In 2017, there were still an estimated 219 million malaria cases and 435000 deaths globally(WHO, 2018). Reliable supply of artemisinin which is the core component of ACTs (artemisinin-based combination therapies)-the most effective antimalarial drugs- is an urgent need(Kayani, Kiani, Dilshad, & Mirza, 2018). Besides exploring new synthesis pathway of artemisinin, enlarging cultivated area of A. annua would be the best way to ease this urgency while its wild resource is limited. Meanwhile, climate change has shift the ranges of many species(Urban, 2015). So, projecting its potential distribution, predicting its range shift under different climate scenarios and understanding the relationship between its distribution and environmental factors are very necessary. Up to now, there are many researches on isolation(Klayman et al., 1984), pharmacological analysis(Efferth, 2006) and artificial synthesis(Farhi, Kozin, Duchin, & Vainstein, 2013) of artemisinin, climate suitability analysis and relationship between artemisinin content and climate factors. It is rare to see some related report or studies about the range shift of A. annua under future climate scenarios. Species distribution models (SDM)(Austin, 2007) and global climate model(Comer, Fenech, & Gough, 2007) make it possible for us to simulate and foresee the range change of species under different future climate scenarios.
With niche theory as its kernel, SDM is the synthesis of geographic information systems (GIS), ecology and statistics(Jane Elith & Franklin, 2013; A. Guisan et al., 2013). Based on species occurrences and environmental variables, SDMs could work out some results using specific algorithms. These results can be explained as species richness, habitat suitability or probability of species presence(J. Elith & Leathwick, 2009). Nowadays, SDM is widely used in many research fields, such as Conservation Biology, Invasion Biology, Biogeography, Lemology, and impact of climate change(Jane Elith & Franklin, 2013; J. Elith & Leathwick, 2009; J. Miller, 2010; Phillips, Anderson, & Schapire, 2006).
Many global climate models are developed to simulate the future climate for the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC)(Eyring et al., 2016). The past, current and future climate data could be accessed conveniently from the Coupled Model Intercomparison Project (CMIP), and facilitate large scale research on impact of climate change(Balaji et al., 2018).
In this study, by means of SDMs and climate data, we simulated the present and future potential distributions ofA. annua based on its occurrence records around the world. The following questions were addressed: (1) what is the potential distribution pattern of A. annua under present climate? (2) which bioclimatic variable is the dominant variable to shape the range of this species? (3) How do the future distributions shift under different future climate scenarios? (4) What can be inferred from these results for its plant plan and management?