**1. Introduction**

Climate has been identified to be a main element affecting the large-scale distribution of various species [1,2]. Global climate change has been reported to result in shifts in the distribution of many species over the past 30 years, and may be the dominant factor leading directly to species extinction in the short run, or under the synergistic effect with additional drivers of extinction [2–4]. Forest ecosystems are affected by changes in rainfall and average temperature, as well as by changes in the frequency of extreme weather events, including droughts, cyclones, intense storms, and wildfires [5]. These effects of weather and climate can be broadly described as changes affecting species distribution [6] as well as the composition and structure [7,8] of forests. Climate also affects flowering and fruiting phenology [2], life-history traits [9–11], and habitat requirements [2,6]. Therefore, it is important to understand the effects of climate change on the suitable habitat for various species, so that forest managers are able to evaluate the climate change susceptibilities of ecosystems and species [12,13].

Species distribution modelling (SDM) is one approach used to model the potential geographical distribution and ecological requirements of a species. This method analyzes those environmental conditions of a species' known occurrence to predict potential suitable habitats in different locations and has been adopted among various disciplines, such as global change biology, biogeography, and conservation management [9,13,14]. Various SDMs, such as domain environmental envelope (DOMAIN), the generalized additive model (GAM), Maxent, and the Genetic Algorithm for Rule-set Production (GARP), have been widely used in predicting ecological requirements, distribution areas, invasive risks, and disease transmission for various species [15–17]. Briefly, these approaches are different from each other in terms of species records (absence/presence or presence-only) as well as the factors used to make predictions (mechanistic-physiological constrain or empirical-climatic approach) [18].

Each model is associated with drawbacks that limit the accuracy of predictions [19]. Consequently, the most reliably modeled potential distribution of a species could be identified through comparing predictions obtained from more than one algorithm [9,19]. Maxent and GARP provide two commonly used methods for predicting the distribution of species at different scales [20]. Therefore, evaluating the performances of GARP and Maxent will help to reveal the variations in the ability of these two models to accurately predict the future distribution of a plantation species.

*Euscaphis japonica* (Thunb.) Kanitz (Staphyleaceae) is a small widely distributed deciduous tree or shrub growing in open forests or mountainous valleys across Vietnam, Korea, Japan, and a majority of provinces in China, particularly from the south Yangtze River to Hainan [21]. The ripe red of the pericarp of fruits of this species cause it to be used in horticulture as an ornamental tree; the fruits stay on the branches from September until March in the following year [22,23]. Besides its attractive fruit, *E. japonica* extracts have abundant chemical compositions, including esters, terpenes, flavonoids, etc., and they have diverse pharmacological effects, including anti-inflammatory, anti-liver fibrosis, and anti-oxidation effects [24].

Over the past few decades, an unprecedented amount of damage caused by humans to forests has caused severe degeneration of the natural habitat of *E. japonica*. However, without knowing the climatic preference and potential geographical distribution of this species, developing a management strategy and practical measures that can be used to conserve or cultivate *E. japonica* resources will be difficult. Moreover, climate change has been reported to have significant implications for the habitat requirements of various species. Therefore, determining whether climate change will affect the suitability of habitat for this species presents another critical problem linked to its economic value and ecological significance. Nonetheless, the ecological requirements of *E. japonica* have rarely been investigated in existing studies, so that little is known about which areas should be prioritized for afforestation using *E. japonica* under climate change.

In this regard, we use Maxent and GARP to project the potential distribution patterns of *E. japonica*. The goals of this paper are to (a) examine the geographical distribution of *E. japonica*; (b) determine relevant environmental factors influencing its distribution; (c) discuss the variations of suitable habitat under projected climate change conditions; and (d) recommend conservation priority areas for future effective conservation. The results will contribute to identifying the appropriate geographical space available for this species in the future and help in the use, management, and cultivation of *E. japonica*.

### **2. Materials and Methods**
