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The Greenland Sea is an important breeding ground for harp seals (Pagophilus groenlandicus) and hooded seals (Cystophora cristata). An estimate of the annual seal pup
production is a critical factor in the abundance estimation needed for management of the species. Estimates of seal pup production are usually based on counts from aerial photographic surveys. However, due to the large extent of typical whelping regions, only a minor part of the complete area can be photographed. To estimate the total seal pup production, we propose a Bayesian hierarchical modelling approach motivated by viewing
the seal pup appearances as a realization of a log-Gaussian Cox process using covariate information from satellite imagery as a proxy for ice-thickness. For inference, we utilize the spatial partial differential equation (SPDE) module of the integrated nested Laplace
approximation (INLA) framework. In a case study using survey data from 2012, we compare our results with existing methodology in a comprehensive cross-validation study. The new proposed method improves local estimation performance and more accurately addresses the associated uncertainty.