Analyzing paleomagnetic data: To anchor or not to anchor?

Abstract

Paleomagnetic directions provide the basis for use of paleomagnetism in chronological andtectonic reconstructions and for constraining past geomagnetic field behavior over a variety of timescales.Crucial to paleomagnetic analysis is the separation and quantification of a characteristic remanentmagnetization (ChRM), which relates to a process of interest, from other remanence components. Principalcomponent analysis (PCA) of stepwise demagnetization data is employed routinely in these situations toestimate magnetic remanence direc tions and their uncertainties. A given ChRM is often assumed to trendtoward the origin of a vector demagnetization diagram and prevailing data analysis frameworks allowremanence directions to be estimated based on PCA fits that are forced to pass through the origin of suchdiagrams, a process referred to as “anchoring.” While this approach is adopted commonly, little attentionhas been paid to the effects of anchoring and the influence it has on both estimated remanence direc tionsand their associated uncertainties. In almost all cases, anchoring produces an artificially low uncertaintyestimation compared to an unanchored fit. Bayesian model selection demonstrates that the effectsof anchoring cannot typically be justified from a statistical standpoint. We present an alternative toanchoring that constrains the best fit remanence direction to pass through the origin of a vectordemagnetization diagram without unreasonably distorting the representation of the demagnetization data Show more