Mapping global marine biodiversity under sparse data conditions
D. Righetti, M. Vogt, N. Gruber, N. E. Zimmermann
The paper uses species distribution models to predict marine biodiversity under sparse data conditions, finding that optimized models can explain up to 91% of species richness variations.
bioRxiv · Feb 28, 2023 · PreprintEcology