This work aims at analyzing the composition and spatio/temporal distribution of marine litter amounts found at the sea-floor in a region of the central Mediterranean. Inspired by common multi-species distribution modeling problems, we propose a suitable Bayesian multivariate approach to model litter data inferring possible environmental covariates while controlling for correlation between different litter categories and providing a method for residual ordination. A combined environmental information coming from multiple sources at different spatio/temporal scales is considered to investigate environmental drivers that might affect dynamics of marine litter assemblages at local scale.

Bayesian mixed latent factor model for multi-response marine litter data with multi-source auxiliary information

Crescenza Calculli
;
Alessio Pollice;Marco V. Guglielmi;Porzia Maiorano
2019

Abstract

This work aims at analyzing the composition and spatio/temporal distribution of marine litter amounts found at the sea-floor in a region of the central Mediterranean. Inspired by common multi-species distribution modeling problems, we propose a suitable Bayesian multivariate approach to model litter data inferring possible environmental covariates while controlling for correlation between different litter categories and providing a method for residual ordination. A combined environmental information coming from multiple sources at different spatio/temporal scales is considered to investigate environmental drivers that might affect dynamics of marine litter assemblages at local scale.
9788891915108
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/248114
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