Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

• DOI: 10.7717/peerj.6731
• Publication Date: 2019-04-09T03:46:03Z
• Authors: Lili Tang; Runxi Wang; Kate S. He; Cong Shi; Tong Yang; Yaping Huang; Pufan Zheng; Fuchen Shi
• Keywords: Species distribution

Background As global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity predicting species distribution based on observed at sites, but rarely consider those plant that could potentially inhabit absent from these areas (i.e., the dark diversity its distribution). Here, we estimated of vascular plants China picked up threatened result, applied maximum entropy (MaxEnt) model to project current future distributions their potential regions (those have species). Methods We used Beals probability index estimate available information explored which environmental variables had significant impacts by incorporating bioclimatic data into random forest (RF) model. collected occurrence ( Eucommia ulmoides , Liriodendron chinense Phoebe bournei Fagus longipetiolata Amentotaxus argotaenia Cathaya argyrophylla ) related can be predict distributions. In addition, MaxEnt modeling suitable under (2050 2070) scenarios. Results found every study region’s was lower than richness. areas, numbers ranging 0 215, with a generally increasing trend western east. RF results showed temperature more effect associated precipitation. The most were climatically 2070. Discussions this provide first ever patterns concentrated China, even though it provincial scale. A combination is an effective way shed light make diversity, such as projecting specific change. Besides, models (SDMs) may also value for ex situ conservation, ecological restoration, invasion prevention future.