Inferring fine scale wild species distribution from spatially aggregated data
Résumé
In spatial ecology, huge amount of aggregated and non-aggregated spatial data offer possibilities to map wild species distribution. However, this requires to properly handle the difference in spatial resolution between the different data sources. Such issue is often referred as the change of support (COS) problem. In this paper, we develop a hierarchical approach that allows (1) to handle COS for a mixture of zero-inflated positive continuous data and (2) to combine fine scale data and aggregated data. We assess the framework through simulations and apply it on real data for the common sole of the Bay of Biscay.
Domaines
Statistiques [math.ST]| Origine | Fichiers produits par l'(les) auteur(s) |
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