Abstract:

Species distribution models (SDMs) have been extensively used in simulations of geographical distribution of animal and plant species during the past 20 years. Taking the simulation of plant species distribution as an example, we used both the digitized and library databases including the China National Knowledge Infrastructure (CNKI), the VIP Chinese Journal Database (VIP) and the Web of Science (WoS) to compile available literatures published from 2000 to 2018. The number of publications, SDMs used, target plant species, data sources, and the purpose of studies about using various SDMs to simulate plant species distribution in China was statistically investigated. In total 366 publications were collected. Further analysis and synthesis showed that the application of SDMs in simulating Chinese plant species distribution has developed rapidly since 2011, especially during the past five years. SDMs have been used in studies of ecology, Chinese traditional medicine, agriculture, and forestry. The Maximum Entropy Model (MaxEnt) is the most widely used model among 33 commonly used SDMs. A half of the studies use climate data only, and another half of the studies use both climate, soil and topography data. The source of both environmental data and plant distribution data are diverse, derived from international and domestic databases. In these studies, researchers have simulated the distribution of 562 plant species, in which 52.7% are woody species and 41.8% are herbaceous species, including a large number of Chinese medicinal plants, fruit trees, garden plants, and crops. Studies aim mainly on two aspects, i.e. the impact of climate change on plant species distribution and their predicted pattern in the past, present, and future climate scenarios, and the assessment of the potential distribution of plant species and biodiversity trends (including the risk of invasive species). In future studies, more attention should be paid to both the basic science on the modelling of potential distribution of plant species and the impact from climate change, and the applied science on the prediction of suitable distribution area of plant species in order to popularize their plantation. More applications of SDMs in multiple disciplines and in multiple industries such as ecology, forestry, crop science and Chinese traditional medicine should be further developed. Joint simulations and inter-comparisons using multiple plant species, more SDMs and multiple data sources of environmental data, as well as the development of new and mechanism SDMs are encouraged. The extension of model applications in new research fields is also needed.

Key words: species distribution models, climate change, biodiversity conservation, potential distribution area, Maximum Entropy Model