Little is known on dinosaur population biology due to insufficient information on age-dependent fecundities and mortalities. So far, survivorship curves (hereafter SC) of only six dinosaurs (four tyrannosaurs, one ceratopsian, one hadrosaur) were erected from bone assemblages of aged specimens. They indicate high survival throughout most of their life with presumable higher mortalities after hatching and increasing mortalities towards its end. However, all studies ignored that assemblages must preserve stationary age distributions (i.e., the population’s age distribution is stable and its size is constant over time as overall population fecundities match mortalities, hereafter SAD population) to infer a reliable SC for a taxon.

To assess SCs of these dinosaurs, I built a simple population model with age-dependent fecundities and survival rates. Its few input parameters are maximum longevity, age at sexual maturation and maximum annual offspring number, on which information exists in these dinosaurs. As bone histological studies and scaling relationships provide estimates on its three parameters, my model is also applicable to other extinct taxa.

            Modelling suggests that bone assemblages did not preserve SAD populations. SCs determined for SAD populations of Albertosaurus sarcophagus, Gorgosaurus libratus, Dasplatosaurus torosus and Tyrannosaurus rex indicated that low mortalities follow high mortalities early in their life or that mortalities were rather constant throughout their life. In Psittacosaurus lujiatuensis modelling suggests low mortalities throughout most of its life that increase towards its end. The SC of Maiasaura peeblesorum was not questioned by my model as it is unable to capture sigmoidal or other composite SCs.

Analysed samples of age structures of dinosaurs and extant species were compiled from literature.

The paper related to this record presents an age-structured population model that is used to re-analyse samples regrading the survivorship curve's shape.

R-scripts used for analyses done in this paper are found here as well as supplementary information on results obtained. 

Please read the README file for instructions on how to run the R-scripts and adapt them for own analysis.