Physical interpretation of isothermal remanent magnetization end‐members: New insights into the environmental history of Lake Hovsgul, Mongolia

Abstract

Acquisition curves of isothermal remanent magnetization for 1057 samples of core KDP‐01 from Lake Hovsgul (Mongolia) are decomposed into three end‐members using non‐negative matrix factorization. The obtained mixing coefficients also decompose hysteresis loops, back‐field, and strong‐field thermomagnetic curves into their related end‐member components. This proves that the end‐members represent different mineralogical fractions of the Lake Hovsgul sedimentary environment. The method used for unmixing offers a new possibility to apply rock magnetism in paleoecological and paleoclimatic studies. For Lake Hovsgul, it indicates that a low‐coercivity component with a covarying paramagnetic phase represents a coarse‐grained magnetite fraction from terrigenous influx probably via fluvial transport. A second component with coercivities close to 50 mT is identified as a magnetite fraction related to magnetosomes of magnetotactic bacteria. The third component has coercivities near 85 mT and is identified as greigite of biotic or abiotic origin common in suboxic/anoxic sediments. Significant positive correlations between variations of intensity of all three mineralogical components along the core are found. A rapid drop in all end‐member concentrations by more than one order of magnitude at about 20 m depth testifies to a major change of the environmental or geological conditions of Lake Hovsgul. It possibly is related to the onset of MIS 10 marking the termination of arid climate conditions. Short intervals of high productivity are characterized by an abundance of magnetite magnetosomes and may highlight glacial‐interglacial transition intervals. For the rest of the core, greigite magnetization substantially exceeds that of magnetite, indicating a predominantly anoxic environment.

A New Tool for Separating the Magnetic Mineralogy of Complex Mineral Assemblages from Low Temperature Magnetic Behavior

“…These approaches are increasingly undertaken to characterize changes in contributions to the total remanent magnetization and in magnetic grain size of sedimentary archives of various origins from past and present continents and oceans (e.g., Abrajevitch and Kodama, 2011;Lascu et al, 2012;Chen et al, 2014;Nie et al, 2014;Hyland et al, 2015;Fabian et al, 2016;Maxbauer et al, 2016c;Zhang et al, 2016). However, obtaining mineral compositions of an ensemble of components via these methods is only possible indirectly through a series of assumptions or a priori knowledge.…”

“…Remanence acquisition or demagnetization curves and fielddependence of induced magnetization probed through hysteresis loops and first-order reversal curve (FORC) distributions are the dominant magnetic data currently being numerically unmixed to characterize the magnetic mineral components (Robertson and France, 1994;Carter-Stiglitz et al, 2001;Egli, 2003Egli, , 2013Fabian, 2003;Heslop and Dillon, 2007;Lascu et al, 2010Lascu et al, , 2015Heslop, 2015;Church et al, 2016;Fabian et al, 2016;Maxbauer et al, 2016b;Zhang et al, 2016). While important and useful results have emerged, the currently applied methods present important limitations.…”

Resolving the Interpretation of Magnetic Coercivity Components From Backfield Isothermal Remanence Curves Using Unmixing of Non‐Linear Preisach Maps: Application to Loess‐Paleosol Sequences

“…The main advantage of the non-parametric method is that it overcomes the problems associated with selecting the number of components and types of mathematical functions to fit. Several studies have used this method to identify the main processes responsible for magnetic properties of loess-paleosol deposits (Necula et al, 2013(Necula et al, , 2015Nie et al, 2014), soils (Hu et al, 2020), lacustrine sediments (Fabian et al, 2016;Nie et al, 2017), or marine sediments (Just et al, 2012), as well as to diagnose remagnetization in natural samples (Dekkers, 2012). The disadvantages of this method are that the endmembers (EMs) provided may not represent single components (He et al, 2020;Heslop, 2015;Just et al, 2012), and that if the overlap of the coercivity distributions is significant, the recovery of the pure EMs and their corresponding abundances may fail (He et al, 2020;Heslop, 2015).…”

Benchmarking Component Analysis of Remanent Magnetization Curves With a Synthetic Mixture Series: Insight Into the Reliability of Unmixing Natural Samples

“…This endmember modeling technique could unmix a dataset without any presumption of model distributions, avoiding the challenge in selecting optimal model distributions for SS‐IRM unmixing. It has been demonstrated to be a powerful tool for samples with complicated properties (Dekkers, 2012; Fabian et al, 2016; Just et al, 2012). However, the endmember solution is not only inherently nonunique but also sensitive to the dataset under investigation (Weltje, 1997).…”