title: Animal vocal sequences: not the Markov chains we thought they were.
abstract: Many animals produce vocal sequences that appear complex. Most researchers assume that these sequences are well characterized as Markov chains (i.e. that the probability of a particular vocal element can be calculated from the history of only a finite number of preceding elements). However, this assumption has never been explicitly tested. Furthermore, it is unclear how language could evolve in a single step from a Markovian origin, as is frequently assumed, as no intermediate forms have been found between animal communication and human language. Here, we assess whether animal taxa produce vocal sequences that are better described by Markov chains, or by non-Markovian dynamics such as the 'renewal process' (RP), characterized by a strong tendency to repeat elements. We examined vocal sequences of seven taxa: Bengalese finches Lonchura striata domestica, Carolina chickadees Poecile carolinensis, free-tailed bats Tadarida brasiliensis, rock hyraxes Procavia capensis, pilot whales Globicephala macrorhynchus, killer whales Orcinus orca and orangutans Pongo spp. The vocal systems of most of these species are more consistent with a non-Markovian RP than with the Markovian models traditionally assumed. Our data suggest that non-Markovian vocal sequences may be more common than Markov sequences, which must be taken into account when evaluating alternative hypotheses for the evolution of signalling complexity, and perhaps human language origins.
authors.affiliation: National Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA arik@nimbios.org.
authors.forename: Arik
authors.initials: A
authors.lastname: Kershenbaum
authors.affiliation: Hubbs SeaWorld Research Institute, San Diego, CA 92109, USA.
authors.forename: Ann E
authors.initials: AE
authors.lastname: Bowles
authors.affiliation: Department of Psychology, University of Tennessee, Knoxville, TN, USA.
authors.forename: Todd M
authors.initials: TM
authors.lastname: Freeberg
authors.affiliation: Department of Physics and the Center for Neural Engineering, Penn State University, University Park, PA, USA.
authors.forename: Dezhe Z
authors.initials: DZ
authors.lastname: Jin
authors.affiliation: Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Sciencepark 904, 1098 XH, Amsterdam, The Netherlands Pongo Foundation, Papenhoeflaan 91, 3421 XN, Oudewater, The Netherlands.
authors.forename: Adriano R
authors.initials: AR
authors.lastname: Lameira
authors.affiliation: Department of Biological Sciences, Florida International University, Miami, FL, USA.
authors.forename: Kirsten
authors.initials: K
authors.lastname: Bohn
mesh_terms: D000818:Animals; D005075:Biological Evolution; D008322:Mammals / Q000502:physiology*; D008390:Markov Chains; D015233:Models, Statistical; D046109:Passeriformes / Q000502:physiology*; D013018:Sound Spectrography; D013045:Species Specificity; D014828:Vocalization, Animal / Q000502:physiology*
keywords: language evolution; renewal process; vocal complexity