Fish eggs classification and modelling through spatio-temporal point processes

Abstract

Presence-only data represent “point locations where a species has been recorded as present”. Species distribution modelling (SDM) methods, including point processes, are used to analyse such data. We use point processes to classify taxonomically unknown events using local indicators of spatio-temporal association (LISTA) and to fit thinned inhomogeneous multitype Poisson process models before and after classification. The methods are applied to data on fish eggs belonging to Gadus morhua and Melanogrammus aeglefinus, collected near the Gulf of Maine between 1995 and 1999.