Archive for Holocene

dough Nat’ [1 Oct 2025]

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , , , on November 1, 2025 by xi'an

The 01 October²⁵ issue of Nature contains a paper on a “doughnut-shaped representation of social and planetary boundaries towards meeting the needs of all people within the means of the living planet”. With the side description including a warning

“Red wedges show a shortfall below the social foundation or an overshoot beyond the ecological ceiling. The grey wedge indicates missing data. The centre of the plot represents total human deprivation (for the social indicators) and the pre-industrial Holocene baseline (for the ecological indicators). Values are proportional to the length of each wedge, which leads to a quadratic scaling of wedge area that may lead some readers to perceive small changes as more significant than they are.”

which compounds the shortcomings of the original if unmentioned Nightingale rose, as pointed out by Edward Tufte and (CHANCE colleague) Howard Wainer. (And add insult to injury by switching from a rose to the worst ever junk food!) Quiz time: how many dimensions are crammed into the proposed representation? And do they exceed the number of unhealthy ingredients in a doughnut?!

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locusts in a random forest

Posted in pictures, Statistics, University life with tags , , , , , , , , , , , on July 19, 2019 by xi'an

My friends from Montpellier, where I am visiting today, Arnaud Estoup, Jean-Michel Marin, and Louis Raynal, along with their co-authors, have recently posted on biorXiv a paper using ABC-RF (Random Forests) to analyse the divergence of two populations of desert locusts in Africa. (I actually first heard of their paper by an unsolicited email from one of these self-declared research aggregates.)

“…the present study is the first one using recently developed ABC-RF algorithms to carry out inferences about both scenario choice and parameter estimation, on a real multi-locus microsatellite dataset. It includes and illustrates three novelties in statistical analyses (…): model grouping analyses based on several key evolutionary events, assessment of the quality of predictions to evaluate the robustness of our inferences, and incorporation of previous information on the mutational setting of the used microsatellite markers”.

The construction of the competing models (or scenarios) is built upon data of past precipitations and desert evolution spanning several interglacial periods, back to the middle Pleistocene, concluding at a probable separation in the middle-late stages of the Holocene, which corresponds to the last transition from humid to arid conditions in the African continent. The probability of choosing the wrong model is exploited to determine which model(s) lead(s) to a posterior [ABC] probability lower than the corresponding prior probability, and only one scenario stands this test. As in previous ABC-RF implementations, the summary statistics are complemented by pure noise statistics in order to determine a barrier in the collection of statistics, even though those just above the noise elements (which often cluster together) may achieve better Gini importance by mere chance. An aspect of the paper that I particularly like is the discussion of the various prior modellings one can derive from existing information (or lack thereof) and the evaluation of the impact of these modellings on the resulting inference based on simulated pseudo-data.

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