Impacts of Distribution Data on Accurate Species Modeling: A Case Study of Litsea auriculata (Lauraceae).

ABSTRACT: Global warming has caused many species to become endangered or even extinct. Describing and predicting how species will respond to global warming is one of the hotspots of biodiversity research. Species distribution models predict the potential distribution of species based on species occurrence data. However, the impact of the accuracy of the distribution data on the prediction results is poorly studied. In this study, we used the endemic plant Litsea auriculata (Lauraceae) as a case study. By collecting and assembling six different datasets of this species, we used MaxEnt to perform species distribution modeling and then conducted comparative analyses. The results show that, based on our updated complete correct dataset (dataset 1), the suitable distribution of this species is mai

SUBMITTER: Tan C 

PROVIDER: S-EPMC11435344 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature