Rhodoliths and Rhodolith Beds in the Rock Record

  • Julio Aguirre
  • Juan C. Braga
  • Davide Bassi
Part of the Coastal Research Library book series (COASTALRL, volume 15)


Calcareous coralline algae (Rhodophyta; Corallinales, Hapalidiales, and Sporolithales; corallines hereafter) constitute one of the most widespread and successful groups of marine macrophytes. They occur as crusts partially coating hard or soft substrates, as laminar thalli growing directly on the seabed, or forming structures rolling freely on the substrate with an inner nucleus or without it. These latter structures are called rhodoliths. They can be one of the most abundant components in carbonate platform deposits, forming the so-called rhodalgal facies. In assessments of the rhodoliths, internal and external algal growth morphology, rhodolith external form, rhodolith inner arrangement, and assemblages of organisms forming the rhodoliths can provide valuable information for reconstructing palaeoenvironmental and palaeoclimatic conditions. Rhodoliths can occur massively concentrated in beds several meters thick. These concentrations are referred as rhodolith beds. These rhodolith beds may be the result of biotic (autochthonous rhodolith beds), abiotic (allochthonous rhodolith beds) concentrations or due to a mixture of processes (paraautochthonous rhodolith beds). Taphonomic and facies analyses, as well as faunal assemblages, can provide the information needed to confidently differentiate among them. The rock record offers unique information to envisage the founding conditions and the long-term maintenance of the rhodolith beds. In this chapter, we review and update the information on fossil rhodoliths and rhodolith beds, and discuss their value for palaeoenvironmental and palaeoclimatic reconstructions. Also, we discuss the sedimentary and the sequence stratigraphy contexts in which rhodolith beds are preferentially formed and developed.


Coralline Alga Benthic Foraminifer Algal Cover Water Energy Nodular Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the research projects CGL2013-47236-P, of the Ministerio de Ciencia e Innovación of Spain, and RNM-190 of the Junta de Andalucía. We thank David Nesbitt for the correction of the English text.


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© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Departamento de Estratigrafía y PaleontologíaUniversidad de GranadaGranadaSpain
  2. 2.Dipartimento di Fisica e Scienze della TerraUniversità di FerraraFerraraItaly

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