1. Introduction
The distribution and interaction of species are closely related to
climate (Nogues-Bravo & Rahbek, 2011), and global climate change is a
major challenge facing mankind and the biological world in the 21st
century (Bertrand et al., 2011). According to the Intergovernment Panel
on Climate Change (IPCC), average global temperatures have risen by
about 1.5℃ compared with pre-industrial levels. And the rising global
average temperature poses a serious threat to the sustainability of the
global ecosystem and alters global biodiversity patterns (Dawson,
Jackson, House, Prentice, & Mace, 2011). If species can find niches to
satisfy their needs, their habitats will expand or shrink as the climate
changes. However, if climate-friendly habitats disappear or are affected
by landscape barriers, some less diffuse species will become extinct as
a result of climate warming.
Amphibians are at higher risk of extinction than other groups of
vertebrates(Stuart et al., 2004; Wake & Vredenburg, 2008), with 41
percent at risk, and due to their complex life history and unique
physiological structure, their distribution and diffusion are greatly
affected by climate and landscape, and their ability to cope with
climate change is weak, which may be one of the reasons for the decline
of the global amphibians population (Lambers, 2015; Sinervo et al.,
2010).
In order to study the response of species to climate change, SDMs (SDMs)
is usually chosen to simulate the distribution area of species. SDMs can
calculate the relationship between the existence point of species and
local climate variables, perform function fitting through different
algorithms, and then project the function to a specific research area
and time, and finally obtain the distribution of the target species’
adaptive area (Elith, 2009; Guisan & Thuiller, 2010). Although the SDMs
has some shortcomings, for example, it cannot fully take into account
the interactions between species (Pearson & Dawson, 2003), SDMs is
still one of the effective methods for predicting species distribution,
assessing the risk of species extinction, planning and construction of
protected areas (Li et al., 2014; Preston, Rotenberry, Redak, & Allen,
2010). SDMs are often used to predict the distribution of endangered or
narrow species, and there are relatively few studies on the prediction
of widespread species (Yang, Tang, & Luo, 2020).
B. gargarizans is one of the most widely
distributed
amphibians in China, and compared with other amphibians, it has a
relatively low sensitivity to environmental factors, so it is a great
sentinel species for revealing amphibian responses to temperature
changes in this study. And the study of the genealogical geography ofB. gargarizans shows that the differentiation of the subspecies
of B. gargarizans is mainly caused by dominant dispersion rather
than vicariance, and showed a trend of dispersion from west to east (Fu,
Weadick, Zeng, Wang, & Hu, 2005; Hu et al., 2007). Relevant studies
show that in the future, the ecological niche of a large number of
amphibians in China will migrate to the west or north, and the
fragmentation of the distribution area will be serious year by year.
(Duan, Kong, Huang, Varela, & Ji, 2016). Although the genealogical
geography of B. gargarizans is relatively thorough, its spatial
distribution prediction has not been carried out in depth. Starting from
the distribution area of B. gargarizans , this study aims to
clarify the current and future trend of the B. gargarizans ’s
dispersion under the context of climate change, so as to provide certain
data support for the response model of amphibians to climate change.
The Maxent model was selected to simulate the current and future spatial
distribution of B. gargarizans under the background of global
climate change and the migration of the centroid point, in order to
solve the following problems: i) to simulate the current and future
distribution of B. gargarizans in China; ii) to predict the
change of suitable habitat of B. gargarizans in different parts
of China under climate change; iii) to predict the distribution
barycenter migration of B. gargarizans in China under climate
change, and reveal the mechanism of amphibian response to climate
change.