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.