Extending site-based observations to predict the spatial patterns of vegetation structure and composition
M. McNellie, I. Oliver, S. Ferrier, G. Newell, G. Manion, P. Griffioen, M. White, T. Koen, M. Somerville, P. Gibbons
The paper uses site-based floristic data and artificial neural networks to create spatially explicit models of vegetation structure and composition, along with uncertainty maps.
bioRxiv · Aug 1, 2019 · PreprintEcology