Abstract
Radiocarbon ((14)C) analysis of skeletal remains by accelerator mass spectrometry is an essential tool in multiple branches of science. However, bone (14)C dating results can be inconsistent and not comparable due to disparate laboratory pretreatment protocols that remove contamination. And, pretreatments are rarely discussed or reported by end-users, making it an 'elephant in the room' for Quaternary scientists. Through a questionnaire survey, I quantified consensus on the reliability of collagen pretreatments for (14)C dating across 132 experts (25 countries). I discovered that while more than 95% of the audience was wary of contamination and would avoid gelatinization alone (minimum pretreatment used by most (14)C facilities), 52% asked laboratories to choose the pretreatment method for them, and 58% could not rank the reliability of at least one pretreatment. Ultrafiltration was highly popular, and purification by XAD resins seemed restricted to American researchers. Isolating and dating the amino acid hydroxyproline was perceived as the most reliable pretreatment, but is expensive, time-consuming and not widely available. Solid evidence supports that only molecular-level dating accommodates all known bone contaminants and guarantees complete removal of humic and fulvic acids and conservation substances, with three key areas of progress: (i) innovation and more funded research is required to develop affordable analytical chemistry that can handle low-mass samples of collagen amino acids, (ii) a certification agency overseeing dating-quality control is needed to enhance methodological reproducibility and dating accuracy among laboratories, and (iii) more cross-disciplinary work with better (14)C reporting etiquette will promote the integration of (14)C dating across disciplines. Those developments could conclude long-standing debates based on low-accuracy data used to build chronologies for animal domestications, human/megafauna extirpations and migrations, archaeology, palaeoecology, palaeontology and palaeoclimate models.