
In this paper, we discuss the advantages and drawbacks of the most classical approaches used in lichenometry. In particular, we perform a detailed comparison among methods based on the statistical analysis of either the largest lichen diameters recorded on geomorphic features or the frequency of all lichens. To assess the performance of each method, a careful comparison design with well-defined criteria is proposed and applied to two distinct data sets. First, we study 350 tombstones. This represents an ideal test bed because tombstone dates are known and, therefore, the quality of the estimated lichen growth curve can be easily tested for the different techniques. Secondly, 37 moraines from two tropical glaciers are investigated. This analysis corresponds to our real case study. For both data sets, we apply our list of criteria that reflects precision, error measurements and their theoretical foundations when proposing estimated ages and their associated confidence intervals. From this comparison, it clearly appears that two methods, the mean of the n largest lichen diameters and the recent Bayesian method based on extreme value theory, offer the most reliable estimates of moraine and tombstones dates. Concerning the spread of the error, the latter approach provides the smallest uncertainty and it is the only one that takes advantage of the statistical nature of the observations by fitting an extreme value distribution to the largest diameters.
[SDE] Environmental Sciences, 550, accuracy, [SDE.MCG]Environmental Sciences/Global Changes, lichenometry, extremes, comparison of methods, [SDE.MCG] Environmental Sciences/Global Changes, [SDE]Environmental Sciences, [SDE.ES] Environmental Sciences/Environment and Society, [SDE.ES]Environmental Sciences/Environment and Society, uncertainty
[SDE] Environmental Sciences, 550, accuracy, [SDE.MCG]Environmental Sciences/Global Changes, lichenometry, extremes, comparison of methods, [SDE.MCG] Environmental Sciences/Global Changes, [SDE]Environmental Sciences, [SDE.ES] Environmental Sciences/Environment and Society, [SDE.ES]Environmental Sciences/Environment and Society, uncertainty
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