Publication details

The cichlid-Cichlidogyrusnetwork: a blueprint for a model system of parasite evolution

Authors

CRUZ-LAUFER Armando J. ARTOIS Tom SMEETS Karen PARISELLE Antoine VANHOVE Maarten Pieterjan

Year of publication 2021
Type Article in Periodical
Magazine / Source Hydrobiologia
MU Faculty or unit

Faculty of Science

Citation
Web https://doi.org/10.1007/s10750-020-04426-4
Doi http://dx.doi.org/10.1007/s10750-020-04426-4
Keywords Cichlid parasites; Dactylogyridae; Monogenea; Host-parasite network; Taxonomic bias; Data reporting
Description Species interactions are a key aspect of evolutionary biology. Parasites, specifically, are drivers of the evolution of species communities and impact biosecurity and public health. However, when using interaction networks for evolutionary studies, interdependencies between distantly related species in these networks are shaped by ancient and complex processes. We propose using recent interacting host-parasite radiations, e.g. African cichlid fishes and cichlid gill parasites belonging toCichlidogyrus(Dactylogyridae, Monogenea), as macroevolutionary model of species interactions. The cichlid-Cichlidogyrusnetwork encompasses 138 parasite species and 416 interactions identified through morphological characteristics and genetic markers in 160 publications. We discuss the steps required to develop this model system based on data resolution, sampling bias, and reporting quality. In addition, we propose the following steps to guide efforts for a macroevolutionary model system for species interactions: first, evaluating and expanding model system outcome measures to increase data resolution; second, closing knowledge gaps to address underreporting and sampling bias arising from limited human and financial resources. Identifying phylogenetic and geographic targets, creating systematic overviews, enhancing scientific collaborations, and avoiding data loss through awareness of predatory journal publications can accelerate this process; and third, standardising data reporting to increase reporting quality and to facilitate data accessibility.

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