Environmental Sciences
; Geosciences, Multidisciplinary
; Water Resources
WOS研究方向:
Environmental Sciences & Ecology
; Geology
; Water Resources
英文摘要:
Intensive human land use and climate change have led to widespread ecological degradation which requires optimizing species distributions to achieve ecological restoration. In this paper, we combine predictive species distribution models (SDMs) with field investigations in the mountainous areas of northern China to determine where ecological restoration should be implemented. Using three species distribution models, i.e., generalized additive models (GAMs), generalized linear models, and classification tree models, we predict optimal species algorithms for ecological restoration. The results show that GAMs have more accurate predictive power to detect relationships between biogeographic factors and species distributions than the other two models based on cross-validation. In addition, the regionalization schemes designed in this study provide scientific guidance for ecological restoration by combining simulation results of SDMs with field investigations. By considering the suitability of different land use/cover types, restoration scenarios could be used to guide ecological restoration. The methodology proposed here provides a scientific basis for the restoration of species diversity, improved ecosystem services provision, and can be adopted in regions with extensive human disturbance and environmental change.
1.Peking Univ Shenzhen, Grad Sch, Lab Urban Future, Shenzhen 518055, Peoples R China 2.China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China
Recommended Citation:
Cai, Ailing,Wang, Jun,Wang, Yang,et al. Spatial optimizations of multiple plant species for ecological restoration of the mountainous areas of North China[J]. ENVIRONMENTAL EARTH SCIENCES,2019-01-01,78(10)