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?