This study aims to (1) develop quantitative approaches for the study of ichnological systems; (2) model, for the first time, ichnosites as networks; (3) analyze the response of ichnological systems to global dynamics, with particular regard to Late Paleozoic fluvial-influenced settings. In this regard, the modern peritidal environments of the Grado lagoon (Italy, Adriatic Sea), the Nurra ichnosite (Permian-Triassic; Italy) and the Pramollo ichnolagerstätte (Carboniferous-Permian; Italy) have been selected for developing, applying and testing network analysis for the study of ichnological systems. Results show that network theory is able to depict the traces-environment relationships both for modern and fossil ichnological systems. It is therefore suggested that network theory may have great potential for understanding Phanerozoic bioturbation patterns.

NETWORK THEORY IN ICHNOLOGY: FROM BEHAVIOURAL TOPOLOGY TO THE DEPOSITIONAL ENVIRONMENT

BAUCON, ANDREA
2014

Abstract

This study aims to (1) develop quantitative approaches for the study of ichnological systems; (2) model, for the first time, ichnosites as networks; (3) analyze the response of ichnological systems to global dynamics, with particular regard to Late Paleozoic fluvial-influenced settings. In this regard, the modern peritidal environments of the Grado lagoon (Italy, Adriatic Sea), the Nurra ichnosite (Permian-Triassic; Italy) and the Pramollo ichnolagerstätte (Carboniferous-Permian; Italy) have been selected for developing, applying and testing network analysis for the study of ichnological systems. Results show that network theory is able to depict the traces-environment relationships both for modern and fossil ichnological systems. It is therefore suggested that network theory may have great potential for understanding Phanerozoic bioturbation patterns.
12-feb-2014
Inglese
FELLETTI, FABRIZIO BRUNO
Università degli Studi di Milano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/170069
Il codice NBN di questa tesi è URN:NBN:IT:UNIMI-170069