**1. Introduction**

Climate change is considered to be one of the most important driving factors of species distribution [1–3] According to the report of the sixth Coupled Model Intercomparison Project (CMIP6), the global temperature will continue to increase by the end of the 21st century [4]. The Qinghai–Tibetan Plateau (QTP), famous as the "third pole" in the world with high altitude and low temperature, is one of the most sensitive regions to climate change [5]. With global warming, many species shift their suitable habitats especially upward in altitude in order to adapt to changes in environmental conditions [6,7].

However, it remains unclear what influences climate change will have on alpine species at large regional scales and whether alpine species respond uniformly on the QTP. Two dominant and representative alpine trees (*Picea crassifolia* Kom, *Sabina przewalskii* Kom) and one dominant and representative alpine shrub (*Potentilla parvifolia* Fisch) on

**Citation:** Hu, H.; Wei, Y.; Wang, W.; Wang, C. The Influence of Climate Change on Three Dominant Alpine Species under Different Scenarios on the Qinghai–Tibetan Plateau. *Diversity* **2021**, *13*, 682. https:// doi.org/10.3390/d13120682

Academic Editor: Anatoliy A. Khapugin

Received: 1 December 2021 Accepted: 14 December 2021 Published: 19 December 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the QTP were used in this study, *Picea crassifolia* favors shady slopes, semi-shady slopes and humid valleys in the mountains with an altitude of 1750–3100 m (a.s.l), is endemic to China, and is distributed in the Qilian Mountains, Qinghai, Gansu, Ningxia, Inner Mongolia. *Sabina przewalskii* grows on sunny slopes of 2600–4000 m (a.s.l), is endemic to China, and is distributed in Qinghai, Gansu Hexi Corridor, and the north of Sichuan. *Potentilla parvifolia* favors dry hillside, rock crack, forest edge and forest with an altitude of 900–5000 m (a.s.l), and it is distributed in Heilongjiang, Inner Mongolia, Gansu, Qinghai, Sichuan and Tibet in China. Species on shady slopes are more sensitive to the magnitude of temperature fluctuations, and species on sunny slopes can tolerate larger temperature fluctuations [8]. The previous study was conducted on potential distribution for *Picea crassifolia*, *Sabina przewalskii* and *Potentilla parvifolia*, but they only focused on the potential distribution under different climate scenarios without considering the influence of geographical factors [9].

Species distribution models are popular methods in modeling the potential distributions of species in response to climate change in the past few decades [10]. Many species distribution models are used to predict potential distributions, such as maximum entropy (MaxEnt) [11]), random forests (RFs) [12], CLIMEX, and genetic algorithm for rule set production (GARP) [13]. Among them, MaxEnt is widely selected because it performs excellently with a small number of sample records compared to other models [14]. This research used MaxEnt to predict potential distribution for three species under different shared socio-economic pathways (SSPs) scenarios.

SSPs can be selected to predict greenhouse gas emission scenarios under different climate conditions [15]. SSPs consider the effects of land use and socio-economic with the development of regional climate change and are different from representative concentration pathways (RCPs) [16]. SSPs have a higher beginning point than RCP and the result of prediction is near to the true value [17]). SSP2.6 (Low forced scenario), SSP4.5 (Medium forced scenario), SSP7.0 (Medium-high forced scenario), SSP8.5 (High forced scenario) were selected to predict the potential distribution of three species during the period of the 2050s and 2070s in this study.

The aims of this research are: (1) to predict the potential distribution of three species under different climate scenarios; (2) to assess the key environment variables affecting the distribution of three species; (3) to analyze the area and elevation changes of the suitable habitat of three species in the future climate change. The results of this study will provide an important reference for the conservation of *Picea crassifolia*, *Sabina przewalskii*, *Potentilla parvifolia* and other dominant plant species on the QTP under climate change.

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

### *2.1. Study Area*

The Qinghai–Tibetan Plateau (QTP), located in western China, is famous as the "Roof of the World" with the highest and one of the most extensive plateaus on earth [18], It lies between 26◦ N to 39◦ N and 73◦ E to 104◦ E, and covers a total area of approximately 2.5 million km<sup>2</sup> with an average elevation above 4000 m (a.s.l). Alpine desert ecosystems, alpine meadow, alpine grassland, shrub and forest are distributed from the southwestern to the northeastern of QTP, which is characterized by low annual temperature differences, high daily temperature differences, low air temperature and strong solar radiation [19]). Climate change probably affect species on the QTP more than those in other regions with the same latitude [20,21]).

### *2.2. Occurrence Data*

As the accurate location information of species distribution is the basis of high precision simulation and prediction, the geographical distribution information of *Picea crassifolia*, *Sabina przewalskii* and *Potentilla parvifolia* were obtained from: (1) Chinese Virtual Herbarium (CVH, https://www.cvh.ac.cn/, accessed on 23 September 2021); (2) Global Biodiversity Information Facility (GBIF, http://www.gbif.org/, accessed on 24 September

2021); (3) Relevant literature reports (CNKI, Web of Science, https://www.cnki.net/ https://apps.webofknowledge.com/, accessed on 15 November 2021). Google Earth (http://ditu.google.cn/, accessed on 22 November 2021) was used to proofread specimen distribution information and the duplicate records were removed [22]. Finally, the 172 records of *Picea crassifolia* distribution data, 69 records of *Sabina przewalskii* distribution data and 146 records of *Potentilla parvifolia* distribution data were used (Figure 1). The longitude and latitude of the distribution data and the species name were entered into Excel and converted to csv format for modeling.

**Figure 1.** Locations of three species on the Qinghai–Tibetan Plateau.
