Articles | Volume 11, issue 1
https://doi.org/10.5194/soil-11-51-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-11-51-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
14 Jan 2025
Original research article |
| 14 Jan 2025
| 14 Jan 2025
Mixed Signals: interpreting mixing patterns of different soil bioturbation processes through luminescence and numerical modelling
W. Marijn van der Meij
CORRESPONDING AUTHOR
Institute of Geography, University of Cologne, Zülpicher Straße 45, 50674 Cologne, Germany
Svenja Riedesel
Institute of Geography, University of Cologne, Zülpicher Straße 45, 50674 Cologne, Germany
Department of Physics, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Tony Reimann
Institute of Geography, University of Cologne, Zülpicher Straße 45, 50674 Cologne, Germany
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Cited articles
Bateman, M. D., Frederick, C. D., Jaiswal, M. K., and Singhvi, A. K.: Investigations into the potential effects of pedoturbation on luminescence dating, Quaternary Sci. Rev., 22, 1169–1176, https://doi.org/10.1016/S0277-3791(03)00019-2, 2003.
Bateman, M. D., Boulter, C. H., Carr, A. S., Frederick, C. D., Peter, D., and Wilder, M.: Preserving the palaeoenvironmental record in Drylands: Bioturbation and its significance for luminescence-derived chronologies, Sediment. Geol., 195, 5–19, https://doi.org/10.1016/j.sedgeo.2006.07.003, 2007.
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.: Julia: A Fresh Approach to Numerical Computing, SIAM Rev., 59, 65–98, https://doi.org/10.1137/141000671, 2017.
Bottinelli, N., Jouquet, P., Capowiez, Y., Podwojewski, P., Grimaldi, M., and Peng, X.: Why is the influence of soil macrofauna on soil structure only considered by soil ecologists?, Soil Till. Res., 146, 118–124, https://doi.org/10.1016/j.still.2014.01.007, 2015.
Bouché, M. B.: Strategies lombriciennes, Ecol. Bull., 25, 122–132, 1977.
Briones, M. J. I.: Soil fauna and soil functions: a jigsaw puzzle, Front. Environ. Sci., 2, 7, https://doi.org/10.3389/fenvs.2014.00007, 2014.
Brown, E. T., Colin, F., and Bourlès, D. L.: Quantitative evaluation of soil processes using in situ-produced cosmogenic nuclides, C.R. Geosci., 335, 1161–1171, https://doi.org/10.1016/j.crte.2003.10.004, 2003.
Creamer, R. E., Barel, J. M., Bongiorno, G., and Zwetsloot, M. J.: The life of soils: Integrating the who and how of multifunctionality, Soil Biol. Biochem., 166, 108561, https://doi.org/10.1016/j.soilbio.2022.108561, 2022.
De Alba, S., Lindstrom, M., Schumacher, T. E., and Malo, D. D.: Soil landscape evolution due to soil redistribution by tillage: a new conceptual model of soil catena evolution in agricultural landscapes, CATENA, 58, 77–100, https://doi.org/10.1016/j.catena.2003.12.004, 2004.
Duller, G. A. T.: Single-grain optical dating of Quaternary sediments: why aliquot size matters in luminescence dating, Boreas, 37, 589–612, https://doi.org/10.1111/j.1502-3885.2008.00051.x, 2008.
Furbish, D. J., Roering, J. J., Almond, P., and Doane, T. H.: Soil particle transport and mixing near a hillslope crest: 1. Particle ages and residence times, J. Geophys. Res.-Earth, 123, 1052–1077, https://doi.org/10.1029/2017JF004315, 2018a.
Furbish, D. J., Roering, J. J., Keen-Zebert, A., Almond, P., Doane, T. H., and Schumer, R.: Soil particle transport and mixing near a hillslope crest: 2. Cosmogenic nuclide and optically stimulated luminescence tracers, J. Geophys. Res.-Earth, 123, 1078–1093, https://doi.org/10.1029/2017JF004316, 2018b.
Gabet, E. J.: Gopher bioturbation: field evidence for non-linear hillslope diffusion, Earth Surf. Proc. Land., 25, 1419–1428, https://doi.org/10.1002/1096-9837(200012)25:13<1419::AID-ESP148>3.0.CO;2-1, 2000.
Gabet, E. J., Reichman, O. J., and Seabloom, E. W.: The effects of bioturbation on soil processes and sediment transport, Annu. Rev. Earth Pl. Sc., 31, 249–273, https://doi.org/10.1146/annurev.earth.31.100901.141314, 2003.
Galbraith, R. F. and Roberts, R. G.: Statistical aspects of equivalent dose and error calculation and display in OSL dating: An overview and some recommendations, Quat. Geochronol., 11, 1–27, https://doi.org/10.1016/j.quageo.2012.04.020, 2012.
Gliganic, L. A., May, J.-H., and Cohen, T. J.: All mixed up: Using single-grain equivalent dose distributions to identify phases of pedogenic mixing on a dryland alluvial fan, Quatern. Int., 362, 23–33, https://doi.org/10.1016/j.quaint.2014.07.040, 2015.
Gliganic, L. A., Cohen, T. J., Slack, M., and Feathers, J. K.: Sediment mixing in aeolian sandsheets identified and quantified using single-grain optically stimulated luminescence, Quat. Geochronol., 32, 53–66, https://doi.org/10.1016/j.quageo.2015.12.006, 2016.
Gray, H. J., Keen-Zebert, A., Furbish, D. J., Tucker, G. E., and Mahan, S. A.: Depth-dependent soil mixing persists across climate zones, P. Natl. Acad. Sci. USA, 117, 8750–8756, https://doi.org/10.1073/pnas.1914140117, 2020.
Halfen, A. F. and Hasiotis, S. T.: Neoichnological study of the traces and burrowing behaviors of the Western harvester ant Pogonomyrex Occidentalis (insecta: Hymenoptera: Formicidae): paleopedogenic and paleoecological implications, PALAIOS, 25, 703–720, https://doi.org/10.2110/palo.2010.p10-005r, 2010.
Hanson, P. R., Mason, J. A., Jacobs, P. M., and Young, A. R.: Evidence for bioturbation of luminescence signals in eolian sand on upland ridgetops, southeastern Minnesota, USA, Quatern. Int., 362, 108–115, https://doi.org/10.1016/j.quaint.2014.06.039, 2015.
Heimsath, A. M., Dietrich, W. E., Nishiizumi, K., and Finkel, R. C.: The soil production function and landscape equilibrium, Nature, 388, 358–361, https://doi.org/10.1038/41056, 1997.
Heimsath, A. M., Chappell, J., Spooner, N. A., and Questiaux, D. G.: Creeping soil, Geology, 30, 111–114, https://doi.org/10.1130/0091-7613(2002)030<0111:CS>2.0.CO;2, 2002.
Johnson, M. O., Mudd, S. M., Pillans, B., Spooner, N. A., Keith Fifield, L., Kirkby, M. J., and Gloor, M.: Quantifying the rate and depth dependence of bioturbation based on optically-stimulated luminescence (OSL) dates and meteoric 10Be, Earth Surf. Proc. Land., 39, 1188–1196, https://doi.org/10.1002/esp.3520, 2014.
Kaste, J. M., Heimsath, A. M., and Bostick, B. C.: Short-term soil mixing quantified with fallout radionuclides, Geology, 35, 243–246, https://doi.org/10.1130/G23355A.1, 2007.
Kraus, D., Brandl, R., Achilles, S., Bendix, J., Grigusova, P., Larsen, A., Pliscoff, P., Übernickel, K., and Farwig, N.: Vegetation and vertebrate abundance as drivers of bioturbation patterns along a climate gradient, PLoS ONE, 17, e0264408, https://doi.org/10.1371/journal.pone.0264408, 2022.
Kristensen, J. A., Thomsen, K., Murray, A., Buylaert, J.-P., Jain, M., and Breuning-Madsen, H.: Quantification of termite bioturbation in a savannah ecosystem: Application of OSL dating, Quat. Geochronol., 30, 334–341, https://doi.org/10.1016/j.quageo.2015.02.026, 2015.
Lee, K. E. and Foster, R. C.: Soil fauna and soil structure, Soil Res., 29, 745–775, https://doi.org/10.1071/sr9910745, 1991.
Madsen, A. T., Murray, A. S., Jain, M., Andersen, T. J., and Pejrup, M.: A new method for measuring bioturbation rates in sandy tidal flat sediments based on luminescence dating, Estuar. Coast. Shelf S., 92, 464–471, https://doi.org/10.1016/j.ecss.2011.02.004, 2011.
Meng, X., Kooijman, A. M., Temme, A. J. A. M., and Cammeraat, E. L. H.: The current and future role of biota in soil-landscape evolution models, Earth-Sci. Rev., 103945, https://doi.org/10.1016/j.earscirev.2022.103945, 2022.
Meyer, M. C., Gliganic, L. A., Jain, M., Sohbati, R., and Schmidmair, D.: Lithological controls on light penetration into rock surfaces – Implications for OSL and IRSL surface exposure dating, Radiat. Meas., 120, 298–304, https://doi.org/10.1016/j.radmeas.2018.03.004, 2018.
Michel, E., Néel, M.-C., Capowiez, Y., Sammartino, S., Lafolie, F., Renault, P., and Pelosi, C.: Making Waves: Modeling bioturbation in soils – are we burrowing in the right direction?, Water Res., 216, 118342, https://doi.org/10.1016/j.watres.2022.118342, 2022.
Miedema, R. and Slager, S.: Micromorphological Quantification of Clay Illuviation, J. Soil Sci., 23, 309–314, https://doi.org/10.1111/j.1365-2389.1972.tb01662.x, 1972.
Minasny, B., Stockmann, U., Hartemink, A. E., and McBratney, A. B.: Measuring and Modelling Soil Depth Functions, in: Digital Soil Morphometrics, edited by: Hartemink, A. E. and Minasny, B., Springer International Publishing, Cham, 225–240, https://doi.org/10.1007/978-3-319-28295-4_14, 2016.
Reimann, T., Román-Sánchez, A., Vanwalleghem, T., and Wallinga, J.: Getting a grip on soil reworking – Single-grain feldspar luminescence as a novel tool to quantify soil reworking rates, Quat. Geochronol., 42, 1–14, https://doi.org/10.1016/j.quageo.2017.07.002, 2017.
Richards, P.: Aphaenogaster ants as bioturbators: Impacts on soil and slope processes, Earth-Sci. Rev., 96, 92–106, https://doi.org/10.1016/j.earscirev.2009.06.004, 2009.
Rink, W. J., Dunbar, J. S., Tschinkel, W. R., Kwapich, C., Repp, A., Stanton, W., and Thulman, D. K.: Subterranean transport and deposition of quartz by ants in sandy sites relevant to age overestimation in optical luminescence dating, J. Archaeol. Sci., 40, 2217–2226, https://doi.org/10.1016/j.jas.2012.11.006, 2013.
Román-Sánchez, A., Laguna, A., Reimann, T., Giraldez, J., Peña, A., and Vanwalleghem, T.: Bioturbation and erosion rates along the soil-hillslope conveyor belt, part 2: Quantification using an analytical solution of the diffusion-advection equation, Earth Surf. Proc. Land., 44, 2066–2080, https://doi.org/10.1002/esp.4626, 2019a.
Román-Sánchez, A., Reimann, T., Wallinga, J., and Vanwalleghem, T.: Bioturbation and erosion rates along the soil-hillslope conveyor belt, part 1: Insights from single-grain feldspar luminescence, Earth Surf. Proc. Land., 44, 2051–2065, https://doi.org/10.1002/esp.4628, 2019b.
Ruiz, S., Or, D., and Schymanski, S. J.: Soil Penetration by Earthworms and Plant Roots–Mechanical Energetics of Bioturbation of Compacted Soils, PLoS ONE, 10, e0128914, https://doi.org/10.1371/journal.pone.0128914, 2015.
Sauzet, O., Cammas, C., Gilliot, J., and Montagne, D.: Long-term quantification of the intensity of clay-sized particles transfers due to earthworm bioturbation and eluviation/illuviation in a cultivated Luvisol, Geoderma, 429, 116251, https://doi.org/10.1016/j.geoderma.2022.116251, 2023.
Schiffers, K., Teal, L. R., Travis, J. M. J., and Solan, M.: An Open Source Simulation Model for Soil and Sediment Bioturbation, PLoS ONE, 6, e28028, https://doi.org/10.1371/journal.pone.0028028, 2011.
Sheather, S. J. and Jones, M. C.: A Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation, J. Roy. Stat. Soc. B Met., 53, 683–690, https://doi.org/10.1111/j.2517-6161.1991.tb01857.x, 1991.
Stewart, A. D. and Anand, R. R.: Anomalies in insect nest structures at the Garden Well gold deposit: Investigation of mound-forming termites, subterranean termites and ants, J. Geochem. Explor., 140, 77–86, https://doi.org/10.1016/j.gexplo.2014.02.011, 2014.
Stockmann, U., Minasny, B., Pietsch, T. J., and McBratney, A. B.: Quantifying processes of pedogenesis using optically stimulated luminescence, Eur. J. Soil Sci., 64, 145–160, https://doi.org/10.1111/ejss.12012, 2013.
Taylor, A. R., Lenoir, L., Vegerfors, B., and Persson, T.: Ant and Earthworm Bioturbation in Cold-Temperate Ecosystems, Ecosystems, 22, 981–994, https://doi.org/10.1007/s10021-018-0317-2, 2019.
Temme, A. J. A. M. and Van der Meij, W. M.: lorica_all_versions, GitHub [code], https://github.com/arnaudtemme/lorica_all_versions, last access: 11 September 2024.
Temme, A. J. A. M. and Vanwalleghem, T.: LORICA – A new model for linking landscape and soil profile evolution: development and sensitivity analysis, Comput. Geosci., 90, 131–143, https://doi.org/10.1016/j.cageo.2015.08.004, 2016.
Tyler, A. N., Carter, S., Davidson, D. A., Long, D. J., and Tipping, R.: The extent and significance of bioturbation on 137Cs distributions in upland soils, CATENA, 43, 81–99, https://doi.org/10.1016/S0341-8162(00)00127-2, 2001.
Van der Meij, W. M.: Mixed Signals - soil bioturbation simulation tool, Version v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.14603831, 2024.
Van der Meij, W. M. and Temme, A. J. A. M.: ChronoLorica v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.7875033, 2022.
Van der Meij, W. M., Reimann, T., Vornehm, V. K., Temme, A. J. A. M., Wallinga, J., van Beek, R., and Sommer, M.: Reconstructing rates and patterns of colluvial soil redistribution in agrarian (hummocky) landscapes, Earth Surf. Proc. Land., 44, 2408–2422, https://doi.org/10.1002/esp.4671, 2019.
Van der Meij, W. M., Temme, A. J. A. M., Wallinga, J., and Sommer, M.: Modeling soil and landscape evolution – the effect of rainfall and land-use change on soil and landscape patterns, SOIL, 6, 337–358, https://doi.org/10.5194/soil-6-337-2020, 2020.
Van der Meij, W. M., Temme, A. J. A. M., Binnie, S. A., and Reimann, T.: ChronoLorica: introduction of a soil–landscape evolution model combined with geochronometers, Geochronology, 5, 241–261, https://doi.org/10.5194/gchron-5-241-2023, 2023.
von Suchodoletz, H., Kühn, P., Wiedner, K., and Reimann, T.: Deciphering timing and rates of Central German Chernozem/Phaeozem formation through high resolution single-grain luminescence dating, Scientific Reports, 13, 4769, https://doi.org/10.1038/s41598-023-32005-9, 2023.
Wackett, A. A., Yoo, K., Amundson, R., Heimsath, A. M., and Jelinski, N. A.: Climate controls on coupled processes of chemical weathering, bioturbation, and sediment transport across hillslopes, Earth Surf. Proc. Land., 43, 1575–1590, https://doi.org/10.1002/esp.4337, 2018.
Wilkinson, M. T., Richards, P. J., and Humphreys, G. S.: Breaking ground: Pedological, geological, and ecological implications of soil bioturbation, Earth-Sci. Rev., 97, 257–272, https://doi.org/10.1016/j.earscirev.2009.09.005, 2009.
Wintle, A. G. and Murray, A. S.: A review of quartz optically stimulated luminescence characteristics and their relevance in single-aliquot regeneration dating protocols, Radiat. Meas., 41, 369–391, https://doi.org/10.1016/j.radmeas.2005.11.001, 2006.
Yates, L. A., Aandahl, Z., Brook, B. W., Jacobs, Z., Li, B., David, B., and Roberts, R. G.: A new OSL dose model to account for post-depositional mixing of sediments, Quat. Geochronol., 101502, https://doi.org/10.1016/j.quageo.2024.101502, 2024.
Zhang, A., Long, H., Yang, F., Zhang, J., Peng, J., Shi, Y., and Zhang, G.: Reconstructing Mollisol Formation Processes Through Quantified Pedoturbation, Geophys. Res. Lett., 51, e2024GL108189, https://doi.org/10.1029/2024GL108189, 2024.
Short summary
Soil mixing (bioturbation) plays a key role in soil functions, but the underlying processes are poorly understood and difficult to quantify. In this study, we use luminescence, a light-sensitive soil mineral property, and numerical models to better understand different types of bioturbation. We provide a conceptual model that helps to determine which types of bioturbation processes occur in a soil and a numerical model that can derive quantitative process rates from luminescence measurements.
Soil mixing (bioturbation) plays a key role in soil functions, but the underlying processes are...
