Automated Author Profile

Long, Teng

China West Normal University

Current S-Index

2.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.0

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

69.2%

Average FAIR Score per dataset

Total Citations

3

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Predicting range shifts of Davidia involucrata Ball. under future climate change (Version: 3)

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one-third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high-latitude regions. Similarly, at least one-fifthof the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.

Authors

  • Long, Teng ;
  • Tang, Junfeng ;
  • W. Pilfold, Nicholas ;
  • Zhao, Xuzhe ;
  • Dong, Tingfa
3 Citations0 Mentions69% FAIR2.4 Dataset Index
10.5061/dryad.cnp5hqc562022