PhD students Veronarindra Ramananjato & Nancia Raoelinjanakolona, along with colleagues, have a new publication in the American Journal of Anthropology, about a toolkit to improve data quality of multi-researcher datasets for analyzing morphological variation in mouse lemurs: https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.24836
Photograph by Veronarindra Ramananjato
Highlights(copied from the article)
Morphological variation is commonly used to infer environmental adaptations and phylogenetic relationships in animal taxa, but multi-researcher datasets can hamper analyses due to inter-observer biases.
Our filtering pipeline markedly improved data quality for downstream analyses and highlights key steps in data quality assessment for generating reliable results.
Across species, mouse lemurs are sexually dimorphic (with larger females), do not follow Rensch's rule for sexual size dimorphism or Bergmann's rule (as larger mouse lemur taxa live in warmer and wetter climates) but are concordant with Allen's rule with regard to having shorter tails in colder environments.