The marine plastic litter pollution is a worldwide growing environmental concern. Despite its negative effects on marine ecosystems, the phenomenon is still not well-known at global and local scale. This work aims at assessing the spatio-temporal distribution of plastic litter amounts found at the sea-floor in a region of the central Mediterranean (Ionian sea). Inspired by species distribution models, we propose a two-parts model to accommodate the excess of zeros and the spatio-temporal correlation characterizing abundance monitoring data. A common spatial effect that links the plastic abundances and the probabilities of occurrences is implemented with the Stochastic Partial Differential Equation approach extended to a non-stationary barrier model. The INIA methodology allows to efficiently perform Bayesian inference to fit complex spatio-temporal models including effects of environmental covariates and enables to investigate the assemblages of plastic litter over the study region.

An inla spatio-temporal model for zero-inflated marine plastic litter abundance

Calculli Crescenza
;
Pollice Alessio;Sion Letizia;Maiorano Porzia
2019

Abstract

The marine plastic litter pollution is a worldwide growing environmental concern. Despite its negative effects on marine ecosystems, the phenomenon is still not well-known at global and local scale. This work aims at assessing the spatio-temporal distribution of plastic litter amounts found at the sea-floor in a region of the central Mediterranean (Ionian sea). Inspired by species distribution models, we propose a two-parts model to accommodate the excess of zeros and the spatio-temporal correlation characterizing abundance monitoring data. A common spatial effect that links the plastic abundances and the probabilities of occurrences is implemented with the Stochastic Partial Differential Equation approach extended to a non-stationary barrier model. The INIA methodology allows to efficiently perform Bayesian inference to fit complex spatio-temporal models including effects of environmental covariates and enables to investigate the assemblages of plastic litter over the study region.
978-88-97413-34-9
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/248125
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