Deep learning models map rapid plant species changes from citizen science and remote sensing data.

ABSTRACT: Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model-Deepbiosphere-not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intens

SUBMITTER: Gillespie LE 

PROVIDER: S-EPMC11406280 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature