Abstract
OBJECTIVES: Body mass estimates for extinct animals are critical for informing hypotheses and analyses related to behavioral ecology, extinction risk, and locomotor modes. These estimates underpin reconstructions of behavioral ecology, especially for Madagascar's extinct subfossil lemurs. Previous estimates, based on femoral and humeral midshaft cortical areas, did not account for phylogenetic relatedness, potentially impacting their accuracy. This study updates body mass estimates for extinct lemurs using phylogenetically informed methods. MATERIALS AND METHODS: We analyzed 64 femora from 10 extinct lemur species. Each specimen was scanned using a Bruker SkyScan 1178 micro-CT scanner to obtain high-resolution images of femoral cortical areas. These data were combined to form a dataset comprising more than 125 subfossil lemur specimens across 15 identifiable species. Phylogenetically informed regression models (pGLS) incorporating femoral cortical surface area (FCSA) and femoral length (FL) as predictors were applied. Model fits were evaluated using Akaike information criterion (AIC) and adjusted R(2) values to determine the optimal predictors of body mass (BM). RESULTS: Natural log-transformed FCSA emerged as the best predictor of natural log-transformed BM among living primates. This pGLS regression equation was used to estimate body mass and lower and upper 95% prediction limits for all subfossil specimens, and weighted average BM estimates were obtained for each species. Our updated body mass estimates are consistently smaller than those previously reported. DISCUSSION: These estimates provide a more accurate basis for understanding extinct lemur life history traits, morphometrics, and ecological adaptations. These findings underscore the importance of incorporating evolutionary context in paleontological and ecological research.