@article {doi:10.1111/2041-210X.13078,
	title = {How to predict fine resolution occupancy from coarse occupancy data},
	journal = {Methods in Ecology and Evolution},
	year = {Submitted},
	abstract = {Abstract The area of occupancy (AOO) is a widely used index in conservation assessments, notably in criteria B2 of the International Union for Conservation of Nature (IUCN) red-list. However, IUCN guidelines require assessing AOO at finer resolution than is generally available. For this reason, extrapolation techniques have been proposed to predict finer AOO from coarser resolution data. Here, we apply 10 published downscaling models to the distributions of a large number of plant and bird species{\textquoteright} in contrasting landscapes. We further compare the output of two ensemble models, one relying on all 10 downscaling models and one a subset of five models that can be fit rapidly and robustly, with minimal oversight required. We further compare the accuracy of downscaled predictions with respect to species prevalence. Across all landscapes and taxa, the models predicted AOO consistently. Some, such as the power law and Hui models, were nonlinear with respect to species prevalence. Some models consistently over or under predicted, such as the Nachman and Poisson models. Furthermore, some models proved to give more variable predictions than other models, e.g. Nachman and power law. For these reasons, none of these models are suitable for downscaling if used individually. The Thomas model was also rejected, because it is too computationally intensive, even though its predictions are relatively unbiased. The most effective model, when used by itself, was the improved binomial model. However, the two ensemble models were able to provide accurate predictions of AOO with low variability compared to using any one single model. There was no significant loss in performance using the simpler ensemble model, and therefore this solution is the least computationally intensive and requires least user oversight. Our results show that downscaling models could be potential tools to reliably estimate AOO for conservation assessments. Under circumstances where there is no a priori reason to prefer one model over another then an ensemble of these models may be the best solution for batch analysis of IUCN status under criteria B2. Moreover, we foresee the use of downscaling for the production of other biodiversity indicators, such as for invasive species monitoring.},
	keywords = {area of occupancy, atlas, conservation assessment, red listing, scale},
	doi = {10.1111/2041-210X.13078},
	url = {https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13078},
	author = {Groom, Quentin J. and Marsh, Charles J. and Gavish, Yoni and Kunin, William E.}
}
