Section 4 Chapter I Notes

4.1 Outline

How do animals impact the physical evolution of soils and terrestrial landscapes?

Figure 1. Visualization of the categories of animal activity.

Animals work vertically. Vertical mixing of the soil is perhaps the most high-profile impact of soil dwelling animals.

Earthworm species may be epigeic (litter dwellers), endogeic (soil dwellers), and anecic (burrowing surface feeders), or some combination of the three (Hale et al., 2005).

Animals work laterally.

Animals introduce heterogeneity.

Animals introduce order.

Table 1. Gallery of some animal behaviors and the categories they belong to.

Case Studies of Animal Activity

The precise behaviors of animals is the subjects of entire disciplines. However, their importance to pedology, geomorphology, and agronomy is increasingly recognized.

Organism have been recognized as important factors pedogenetic factors since the time of the first pedologists. Darwin recognized the role of earthworms in hillslope formation, soil horizination, the burial of large coarse fragments, and the darkening of upper soil horizons (Darwin, 1881). Hans Jenny included organisms in the original clorpt model in 1941 Factors. Countless studies provide examples….

Using the framework established above (Figure 1), the animals of each study can be plotted on a quadrant.

Figure 2. Quadrant plot of animals with examples

Geomorphology…

Agronomy, soil health…

4.2 Numerical Models

Conceptual models alone are valuable for describing a number of processes, as justified above. However, quantitative, numerical models are a more powerful tool for answering questions and making predictions, and can inform and be informed by conceptual ones…

Numerical models are now being used across for many soils-applications. [connect this back to the list of important subjects established in the introduction: ecology, weathering, carbon, etc.] [These should be somewhat outside of the models discussed here, althought still relating to pedology in some regard to demonstrate the value more modeling can bring. for example: (Vanwalleghem et al., 2013), (Salvador-Blanes et al., 2007)]

Likewise, modeling the activity of soil fauna is increasing. Modeling soil fauna also bridges both sub-aqueous and sub-aerial soils. Greater emphasis was given to the numerical modeling of sub-aqueous soil turbation through feeding, burrowing, and burial than sub-aerial soils throughout the 20th century (Michel et al., 2022). However, as increasing attention is payed to the role of soil organisms in pedological studies, a more substantial body of work is emerging [this connects to the introduction]….

Before individual works and models are discussed, however, its is important to establish the braod-stokes and approaches of these models. Then, an analysis of specfic models will allow us to identify the key parameters and draw comparisons to the conceptual models above.

Characteristics of Numerical Models

Anomalous and Normal mixing

There are two broad approaches to modeling bioturbation in terrestrial and aquatic environments: anomalous mixing and normal mixing. Anomalous mixing models simulate the trajectory of individual sediment particles by capturing their discontinuous movement in “jumps” between periods of waiting (Michel et al., 2022). Jump length and waiting time, both organism-specific stochastic variables, are modeled to simulate mixing over short periods of time (Meysman et al., 2010 in Michel et al., 2022). Normal mixing is analogous with the diffusion process and is described by a diffusion-advection equation. Of interest to this review, if simulation time and jump counts are sufficiently large, anomalous mixing models coincide with the diffusive model (Michel et al., 2022) [further reading needed]. Further, the mathematics overlap, and the biodiffusion coefficient can be described as… [a function of jump length]. As soil development occurs over relativity long periods is the focus of this review, normal mixing is the primary approach explored here.

[Sources to further look into]

Meysman 2008: https://doi.org/10.1016/j.gca.2008.04.023
Meysman 2010: https://www.researchgate.net/publication/230736816_When_and_why_does_bioturbation_lead_to_diffusive_mixing
Marie 2007: https://doi.org/10.1016/j.jembe.2006.10.052

Local diffusion and Non-local mixing

Normal mixing is further described as the sum of two components: local and non-local mixing, each of which can be modeled. To illustrate the difference, imagine burying a marble at the bottom of a bucket of sand. To get the marble out, you have two options. Digging sand out and piling it up on the side is comparable to non-local mixing. Forcing your hand through the loosely packed sand, displacing it as you go, is similar to local mixing.

Formally, local mixing is the random displacement of material across distances over which the change in soil composition is minimal (Boudreau, 1986a). Because translocation distance is small and randomly determined, local mixing is approximately described by a diffusion-advection equation. Correspondingly, when soil is mixed, soil components will move diffusely across concentration gradients. Local mixing is common for most bioturbators and includes ingestion/egestion, pushing/shouldering of particles, and local digging/foraging… [citation to break these down]. Epi-, endo-, and epiendogeic earthworm species are all local mixers. More examples…

Non-local mixing represents the displacement of material in which the point of excavation is far from the point of deposition. Its characterized by translocation of excavated material to the soil surface followed by infilling from local material [???].

[Boudreau (1986a) suggests non-local mixing cannot be defined by diffusion. Keep reading.]

Non-local mixing is common for mound building and burrowing organisms like Anecic earthworm species and pocket gophers.

Both local and non-local mixing represent a substantial movement of material but differ in scale. Local mixing acts on a horizon to horizon scale. Non-local mixing acts on a profile scale. Given enough time and stability, either may completely ‘turn over’ the profile. Jarvis et al. (2010) found that models excluding non-local mixing significantly underestimate surface burial. Matisoff et al. (2011) also integrate a non-local mixing factor into their model.

Depth dependence

Most bioturbation models consider the observation made by scientists as far back as Charles Darwin that organism activity declines with depth (Darwin, 1881), with more contemporary authors attempting to quantify this decline (Vanwalleghem et al., 2013; among others). However, a degree of nuance is needed to understand when this observation is relevant to modeling. Depth dependence is relevant under the following conditions. 1) Organism activity does not encompass the entire profile. 2) The system is not in equilibrium, or too little time has passed for bioturbation to homogenize the soil profile. 3) The rate of mixing is large compared to soil erosion or production. 4) Material that is introduced to the profile decays, weathers, or is otherwise transformed at a rate neither too fast to be meaningfully redistributed by fauna nor to slow to reach equilibrium. If one or multiple of these conditions are met, a diffusion-depth function is needed. [are examples needed to illustrate this?] Boudreau (1986a) provides equations for when these conditions are met for specific radioisotopes.

When depth dependence is relevant, a function that describes the diffusion-depth relationship is derived. A diffusion-depth function requires three pieces of information: surface diffusion coefficient, maximum bioturbation depth, and the shape of the decline. There is a general consensus in the literature that the function’s shape is best described by an exponential function (Boudreau, 1986a; Jarvis et al. 2010; Román‐Sánchez et al., 2019; Kirkby, 1985). The remaining two parameters are the most influential parameters in diffusion models (Román‐Sánchez et al., 2019). They are determined through field observation, as suggested by Boudreau (1986a), or by fitting an equation to the vertical distributions of radioisotope tracers (Gray et al., 2020; Jarvis et al. 2010; Matisoff et al., 2011), for shorter timescales, or OSL-determined quartz grain ages, for longer timescales (Johnson et al. 2014; Román‐Sánchez et al., 2019).

[erosion is also kinda important to this relationship, but not as. Discuss how erosion is measured, briefly]

Attempts to broaden model application are challenged by the considerable variability in theses parameters across environments [Table X] and the relative costs of radioisotope tracer or OSL analysis. However, there may be future opportunities to estimate parameters. As discussed in the conceptual model section, holistically considering the impact of soil fauna on mixing may provide insights into alternative methods. Kirkby (1985) suggests the possibility of using a bulk density profile to estimate mixing intensity. Estimating animal or disturbance density may also play an important role.

Review of equations from the literature

Because determining the animal activity-depth ratio is critical to diffusive models, it is practical to break down the various modeling approaches by the method used to determine this relationship. Currently, optically stimulated luminescence (OSL) and isotope tracers are the most promising techniques.

Quick note on time step size, discussed further later. Since these are diffusive models, to maintain conservation of mass, we must choose a time step based on the Courant–Friedrichs–Lewy condition. Basically, the chosen time step must be sufficiently small so that a given layer will diffuse only to its immediate neighbors. It can be determined using the following equation \(C=a\frac{dt}{dz^2}\), where a is diffusivity, dt time step length, and dz layer depth where \(C<=1\).

Type 1: Optically Stimulated Luminescence Applications

At its most basic, bioturbation is descried be a simple diffusion equation (Johnson et al., 2014; Román‐Sánchez et al., 2019):

\[ \frac{dy}{dt} = \frac{d}{dz}(D(z)\frac{dA}{dz})+1 \]

Where a is soil grain age (yr) and D(z) is a biodiffusion function that describes the diffusion-depth relationship. Note, Johnson et al. (2014) and Román‐Sánchez et al. (2019) include a \(+ 1\) on the right side of the equation, a term specific to modeling soil grain age. D(z) may be linear, exponential, or constant. Although, as noted above, there is general consensus that this relationship is exponential. Johnson et al. (2014) applies the following two definitions of D(z), the former introduced in Kirkby (1985):

\[ D(z) = D(0)e^{-z/z_{b}} \]

\[ D(z)=-az+D(0) \]

where zb is a shape parameter [e-folding length scale] and a is the gradient of the slope. A linear model may also be adjusted to represent constant diffusion with depth by setting a equal to zero.

[figures here]

This model is an oversimplification of a soil-system, however, and surface erosion and deposition are relatively easily introduced. Conceptually, erosion and deposition represent the bulk advective movement of the profile. Erosion movies the profile upwards, and deposition moves the profile downwards. They are introduced to the diffusion-advection equation as T:

\[ \frac{dy}{dt} = \frac{d}{dz}(D(z)\frac{dA}{dz})+T\frac{dA}{dz}+1 \] Together with the diffusion function, this equation can then be solved analytically, as detailed in Román‐Sánchez et al., (2019), to determine the values of the parameters D(0), zb, and soil depth. T is best determined by other means, like cosmogenic nuclides in Johnson et al. (2014), as current diffusive models introduce too much uncertainty to estimate from age profiles directly (Román‐Sánchez et al., 2019).

Table X. Diffusion equation parameter values from the literature.
Source	Equation	D(0) (m2/yr)	zb (m)
Kirkby (1985)	\(D(z) = D(0)e^{-z/z_{b}}\)	\(10^{-4}-10^{-2}\)	0.50
Johnson et al. (2014)	\(D(z) = D(0)e^{-z/z_{b}}\)	\(9.81 * 10^{-5}\)	0.28
Román‐Sánchez et al. (2019)	\(D(z) = D(0)e^{-z/z_{b}}\)	\(1.2-8.4*10^{-2}\)	0.28 (from Johnson et al., 2014)

[(Kristensen et al. (2015) provides OLS age profiles beneath a termite mound. It may be worthwhile to consider trying to apply these equations to that data set for extra data. Althought I will need some statistics / “super-computing” practice, as the analytically solutions to these problems are very lengthy.]

[(Zhang et al., 2025) uses OSL to date krotovenas, finding they differ significantly from surrounding soil. Also, authors note the presence of a exponential decline in soil depth, likely attributed to bioturbation]

[this paragraph needs major work] Using OSL to estimate bioturbation model parameters permits making a few simplifying assumptions, providing an advantage over other methods. One, tracer decay can be neglected. Two, the impact of advective flow via water movement down the profile, besides illuviation of clay minerals, is minimal. It also permits analysis over much greater timescales than surface applied, fallout, and many natural radioisotope tracers allow. However, so far these models are limited to describing local mixing, or the cumulative impact of local and non-local mixing, not being able to represent the different mechanisms by which soil fauna mix soil. With these limitations/simplifications in mind, in the interest of comparison, the above equations can be changed to a more general form:

\[ \frac{dy}{dt} = \frac{d}{dz}(D(z)\frac{dyρ}{dz})+\frac{dz}{dt}\frac{dyρ}{dz} \]

Where y is the concentration (mass/volume) of some component, ρ is bulk density, and D(z) is a depth-diffusion function.

Type 2: Isotope Tracers

Jarvis et al. (2010) and Matisoff et al. (2011) apply similar equations derived in Boudreau (1986) for using radioisotope tracers. The following equation is the basic descirption of local mixing.

\[ \frac{dρy}{dt}=\frac{d}{dz}(D\frac{dρy}{dx})-wρy) \]

Where w is rate of downward soil displacement or soil velocity (m/s) (or burial velocity), ρ is bulk density, and D is the biodiffusion coefficient. Note, ρ is included in the derivative to account for varaitions in bulk density along the profile.

Type 3: Alternatives

[(Sauzet et al., 2023) uses image analysis to estimate an earthworm activity-depth relationship and use that relationship to explain clay redistribution. Their data is fairy different than other authors, although they did not sample the top several cm, where lots of activity takes place.

Key Parameters

Table Y. Summary of important parameters in animal activity modeling
Parameter	Description	Example

Conclusion

If you’re a pedologist doing descriptions, leave a column open for animals. Note what organisms are present? How deep do they go? What is the lateral distribution/abundance of krotovinas or tree throw mounds? What structure or texture change might be a product of bioturbation?

If you’re designing a study around bioturbation, consider what you are trying to measure. Consider what methods might be most applicable. And consider what kind of shared data is needed to maximize the value of your own.

References

Concepts

Baxter, Timothy, Sam Woor, Martin Coombes, and Heather Viles. “The Geomorphic Work of the European Mole ( Talpa europaea ): Long‐term Monitoring of Molehills Using Structure‐from‐motion Photogrammetry.” Earth Surface Processes and Landforms, October 13, 2024, esp.6008. https://doi.org/10.1002/esp.6008.

Cox, G. W., & Allen, D. W. (1987). Soil translocation by pocket gophers in a Mima moundfield. Oecologia 72, 207-210.

Grinnell, Joseph. “THE BURROWING RODENTS OF CALIFORNIA AS AGENTS IN SOIL FORMATIONl.” JOURNAL OF MAMMALOGY, 1923.

Hansen, R. M. (n.d.). MOVEMENT OF ROCKS BY NORTHERN POCKET GOPI-IERS. 49.

Miller, M. A. (1957). Burrows of the Sacramento Valley pocket gopher in flood-irrigated alfalfa fields. Hilgardia, 26(8), 431–452. https://doi.org/10.3733/hilg.v26n08p431

Nye, P. H. “Some Soil-Forming Processes in the Humid Tropics.” Journal of Soil Science 5, no. 1 (1954): 7–21. https://doi.org/10.1111/j.1365-2389.1954.tb02171.x.

Yeates, G. W., & Van Der Meulen, H. (1995). Burial of soil-surface artifacts in the presence of lumbricid earthworms. Biology and Fertility of Soils, 19(1), 73–74. https://doi.org/10.1007/BF00336350

Gabet, Emmanuel J., O.J. Reichman, and Eric W. Seabloom. “The Effects of Bioturbation on Soil Processes and Sediment Transport.” Annual Review of Earth and Planetary Sciences 31, no. 1 (May 2003): 249–73. https://doi.org/10.1146/annurev.earth.31.100901.141314.

Gabet, Emmanuel J. “Gopher Bioturbation: Field Evidence for Non-Linear Hillslope Diffusion.” Earth Surface Processes and Landforms 25, no. 13 (2000): 1419–28. https://doi.org/10.1002/1096-9837(200012)25:13<1419::AID-ESP1483.0.CO;2-1.

Jenny, H. (1941). Factors of Soil Formation A System of Quantitative Pedology. Dover Publications.

Johnson, D. L., and D. Watson-Stegner. “EVOLUTION MODEL OF PEDOGENESIS:” Soil Science 143, no. 5 (May 1987): 349–66. https://doi.org/10.1097/00010694-198705000-00005.

Models

Boudreau, B. P. “Mathematics of Tracer Mixing in Sediments; I, Spatially-Dependent, Diffusive Mixing.” American Journal of Science 286, no. 3 (March 1, 1986): 161–98. https://doi.org/10.2475/ajs.286.3.161.

Boudreau, B. P. “Mathematics of Tracer Mixing in Sediments; II, Nonlocal Mixing and Biological Conveyor-Belt Phenomena.” American Journal of Science 286, no. 3 (March 1, 1986): 199–238. https://doi.org/10.2475/ajs.286.3.199.

Boudreau, B. P., and D. M. Imboden. “Mathematics of Tracer Mixing in Sediments; III, The Theory of Nonlocal Mixing within Sediments.” American Journal of Science 287, no. 7 (September 1, 1987): 693–719. https://doi.org/10.2475/ajs.287.7.693.

Gray, Harrison J., Amanda Keen-Zebert, David J. Furbish, Gregory E. Tucker, and Shannon A. Mahan. “Depth-Dependent Soil Mixing Persists across Climate Zones.” Proceedings of the National Academy of Sciences 117, no. 16 (April 21, 2020): 8750–56. https://doi.org/10.1073/pnas.1914140117.

Jarvis, N. J., Taylor, A., Larsbo, M., Etana, A., & Rosén, K. (2010). Modelling the effects of bioturbation on the re-distribution of 137Cs in an undisturbed grassland soil. European Journal of Soil Science, 61(1), 24–34. https://doi.org/10.1111/j.1365-2389.2009.01209.x

Johnson, D. L., Domier, J. E. J., & Johnson, D. N. (2005a). Animating the biodynamics of soil thickness using process vector analysis: A dynamic denudation approach to soil formation. Geomorphology, 67(1–2), 23–46. https://doi.org/10.1016/j.geomorph.2004.08.014

Johnson, D. L., Domier, J. E. J., & Johnson, D. N. (2005b). Reflections on the Nature of Soil and Its Biomantle. Annals of the Association of American Geographers, 95(1), 11–31. https://doi.org/10.1111/j.1467-8306.2005.00448.x

Johnson, M. O., Mudd, S. M., Pillans, B., Spooner, N. A., Keith Fifield, L., Kirkby, M. J., & Gloor, M. (2014). Quantifying the rate and depth dependence of bioturbation based on optically‐stimulated luminescence (OSL) dates and meteoric 10 Be. Earth Surface Processes and Landforms, 39(9), 1188–1196. https://doi.org/10.1002/esp.3520

Matisoff, G., Ketterer, M. E., Rosén, K., Mietelski, J. W., Vitko, L. F., Persson, H., & Lokas, E. (2011). Downward migration of Chernobyl-derived radionuclides in soils in Poland and Sweden. Applied Geochemistry, 26(1), 105–115. https://doi.org/10.1016/j.apgeochem.2010.11.007

Michel, E., Néel, M.-C., Capowiez, Y., Sammartino, S., Lafolie, F., Renault, P., & Pelosi, C. (2022). Making Waves: Modeling bioturbation in soils – are we burrowing in the right direction? Water Research, 216, 118342. https://doi.org/10.1016/j.watres.2022.118342

Román‐Sánchez, A., Laguna, A., Reimann, T., Giráldez, J. V., Peña, A., & Vanwalleghem, T. (2019). Bioturbation and erosion rates along the soil‐hillslope conveyor belt, part 2: Quantification using an analytical solution of the diffusion–advection equation. Earth Surface Processes and Landforms, 44(10), 2066–2080. https://doi.org/10.1002/esp.4626

Salvador-Blanes, S., Minasny, B., & McBratney, A. B. (2007). Modelling long-term in situ soil profile evolution: Application to the genesis of soil profiles containing stone layers. European Journal of Soil Science, 58(6), 1535–1548. https://doi.org/10.1111/j.1365-2389.2007.00961.x

Kristensen, Jeppe Aa., Kristina J. Thomsen, Andrew S. Murray, Jan-Pieter Buylaert, Mayank Jain, and Henrik Breuning-Madsen. “Quantification of Termite Bioturbation in a Savannah Ecosystem: Application of OSL Dating.” Quaternary Geochronology 30 (October 2015): 334–41. https://doi.org/10.1016/j.quageo.2015.02.026.

Zhang, Aimin, Hao Long, Fei Yang, Jingran Zhang, Jun Peng, Keyang Gong, Yunpeng Hong, et al. “Revisiting Krotovina Formation Using Luminescence Dating − a Case Study from NE China.” CATENA 248 (January 2025): 108554. https://doi.org/10.1016/j.catena.2024.108554.

4.3 Annotated Bibliography

Beca, Gabrielle, Leonie E. Valentine, Mauro Galetti, and Richard J. Hobbs. “Ecosystem Roles and Conservation Status of Bioturbator Mammals.” Mammal Review 52, no. 2 (April 2022): 192–207. https://doi.org/10.1111/mam.12269.

Review on the global distrobution and conservation/endangered status of bioturbator mammals. Great map showing global abundance, mostly in subtropical and temperate grasslands. 22% of non-flying land-dwalling mammal species regularly perform bioturbation.
This data would be fascinating to look more into. Especially if there was invertebrate data to pair it with. As is, this is a good source for the widespread distribution of bioturbators, and shows that at least globally they are sensitive to moisture.
Present a table on with some examples of ecological roles. Could be useful.

Bétard, François. “Insects as Zoogeomorphic Agents: An Extended Review.” Earth Surface Processes and Landforms 46, no. 1 (2021): 89–109. https://doi.org/10.1002/esp.4944.

Blouin, M., M. E. Hodson, E. A. Delgado, G. Baker, L. Brussaard, K. R. Butt, J. Dai, et al. “A Review of Earthworm Impact on Soil Function and Ecosystem Services.” European Journal of Soil Science 64, no. 2 (April 2013): 161–82. https://doi.org/10.1111/ejss.12025.

Canti, M.G. “Earthworm Activity and Archaeological Stratigraphy: A Review of Products and Processes.” Journal of Archaeological Science 30, no. 2 (February 2003): 135–48. https://doi.org/10.1006/jasc.2001.0770.

Chang, Chih-Han, Marie L. C. Bartz, George Brown, Mac A. Callaham, Erin K. Cameron, Andrea Dávalos, Annise Dobson, et al. “The Second Wave of Earthworm Invasions in North America: Biology, Environmental Impacts, Management and Control of Invasive Jumping Worms.” Biological Invasions 23, no. 11 (November 2021): 3291–3322. https://doi.org/10.1007/s10530-021-02598-1.

Review the impacts of jumping worms on soils. Probably not usable in this review, unless as a case study of the contrast between two earthworm groups.

Chiriac, Luiza Silvia, and Dumitru T Murariu. “THE ECOLOGICAL ROLE OF SOME FUNCTIONAL GROUPS OF INVERTEBRATES – A REVIEW,” n.d.

Corenblit, Dov, Andreas C.W. Baas, Gudrun Bornette, José Darrozes, Sébastien Delmotte, Robert A. Francis, Angela M. Gurnell, Frédéric Julien, Robert J. Naiman, and Johannes Steiger. “Feedbacks between Geomorphology and Biota Controlling Earth Surface Processes and Landforms: A Review of Foundation Concepts and Current Understandings.” Earth-Science Reviews 106, no. 3–4 (June 2011): 307–31. https://doi.org/10.1016/j.earscirev.2011.03.002.

Review of the linkages between organisms and landscape evolution. Organims are constrained by env parameters, driving evolution, but simultaneously shape the landscape, creating a feedback process.
Animal architects are keystone species. A little heavy on genetics.
This will but useful in talking about time: how organisms and landscapes co-evolve.

Corenblit, Dov, Bruno Corbara, and Johannes Steiger. “Biogeomorphological Eco-Evolutionary Feedback between Life and Geomorphology: A Theoretical Framework Using Fossorial Mammals.” The Science of Nature 108, no. 6 (December 2021): 55. https://doi.org/10.1007/s00114-021-01760-y.

Corenblit, Dov, Eric Tabacchi, Johannes Steiger, and Angela M. Gurnell. “Reciprocal Interactions and Adjustments between Fluvial Landforms and Vegetation Dynamics in River Corridors: A Review of Complementary Approaches.” Earth-Science Reviews 84, no. 1–2 (September 2007): 56–86. https://doi.org/10.1016/j.earscirev.2007.05.004.

Eckmeier, Eileen, Renate Gerlach, Ernst Gehrt, and Michael W.I. Schmidt. “Pedogenesis of Chernozems in Central Europe — A Review.” Geoderma 139, no. 3–4 (May 2007): 288–99. https://doi.org/10.1016/j.geoderma.2007.01.009.

Eijsackers, H. “Earthworms as Colonizers of Natural and Cultivated Soil Environments.” Applied Soil Ecology 50 (October 2011): 1–13. https://doi.org/10.1016/j.apsoil.2011.07.008.

Feller, Christian, George G Brown, Eric Blanchart, Pierre Deleporte, and Sergey S Chernyanskii. “Charles Darwin, Earthworms and the Natural Sciences: Various Lessons from Past to Future.” Agriculture, Ecosystems & Environment 99, no. 1–3 (October 2003): 29–49. https://doi.org/10.1016/S0167-8809(03)00143-9.

Folgarait, Patricia J. “Ant Biodiversity and Its Relationship to Ecosystem Functioning: A Review.” Biodiversity and Conservation 7, no. 9 (September 1998): 1221–44. https://doi.org/10.1023/A:1008891901953.

Gabet, Emmanuel J., O.J. Reichman, and Eric W. Seabloom. “The Effects of Bioturbation on Soil Processes and Sediment Transport.” Annual Review of Earth and Planetary Sciences 31, no. 1 (May 2003): 249–73. https://doi.org/10.1146/annurev.earth.31.100901.141314.

Harit, Ajay, Rashmi Shanbhag, Ekta Chaudhary, Sougueh Cheik, and Pascal Jouquet. “Properties and Functional Impact of Termite Sheetings.” Biology and Fertility of Soils 53, no. 7 (October 2017): 743–49. https://doi.org/10.1007/s00374-017-1228-7.

Johnson, D. L., J. E. J. Domier, and D. N. Johnson. “Reflections on the Nature of Soil and Its Biomantle.” Annals of the Association of American Geographers 95, no. 1 (March 1, 2005): 11–31. https://doi.org/10.1111/j.1467-8306.2005.00448.x.

Jouquet, Pascal, Jens Dauber, Jan Lagerlöf, Patrick Lavelle, and Michel Lepage. “Soil Invertebrates as Ecosystem Engineers: Intended and Accidental Effects on Soil and Feedback Loops.” Applied Soil Ecology 32, no. 2 (June 2006): 153–64. https://doi.org/10.1016/j.apsoil.2005.07.004.

Lavelle, Patrick. “Soil Function in a Changing World: The Role of Invertebrate Ecosystem Engineers,” 1997. Maire, O, P Lecroart, F Meysman, R Rosenberg, J Duchêne, and A Grémare. “Quantification of Sediment Reworking Rates in Bioturbation Research: A Review.” Aquatic Biology 2, no. 3 (June 19, 2008): 219–38. https://doi.org/10.3354/ab00053.

Mason, Richard J., and Harry Sanders. “Invertebrate Zoogeomorphology: A Review and Conceptual Framework for Rivers.” WIREs Water 8, no. 5 (September 2021): e1540. https://doi.org/10.1002/wat2.1540.

Claims Zoomorphology as a field is specifically for fluvial landscapes / rivers? Reviews of the roles of various aquatic organisms in bioturbating and -eroding stream banks and beds. Interesting horizontal erosion framework.
Body size is a primary driver of organism impact: both magnitude and direction. Larger organisms occupy more space individually, so likely have more localized impacts (greater burrow spacing). I wonder if anyone has done a study comparing burrow spacing to organism size. However, organism size also determines the size of particles they can move.
What if I desribe the 4(ish) sections of my conceptual model, then took a moment to discuss why there is such diversity. There is also an opperunity to disucss direction (i.e. direciton of pedogenesis).
This is a good example of a conceptual model being put forward to help us understand organisms better. Good note on invasive species.

McBrearty, Sally. “Consider the Humble Termite: Termites as Agents of Post-Depositional Disturbance at African Archaeological Sites.” Journal of Archaeological Science 17, no. 2 (March 1990): 111–43. https://doi.org/10.1016/0305-4403(90)90054-9.

Meysman, F, J Middelburg, and C Heip. “Bioturbation: A Fresh Look at Darwin’s Last Idea.” Trends in Ecology & Evolution 21, no. 12 (December 2006): 688–95. https://doi.org/10.1016/j.tree.2006.08.002.

Muvengwi, Justice, and Edward T. F. Witkowski. “Cascading Effects of Termite Mounds in African Savannas.” New Zealand Journal of Botany 58, no. 3 (July 2, 2020): 167–93. https://doi.org/10.1080/0028825X.2020.1767162.

Nascimento, Diego Luciano, Mariane Chiapini, Pablo Vidal-Torrado, Jonathan D. Phillips, Francisco Sérgio Bernardes Ladeira, Diego Fernandes Terra Machado, Roberto Da Silva Camargo, and Everton Vinícius Valezio. “The Underestimated Role of Leaf-Cutting Ants in Soil and Geomorphological Development in Neotropical America.” Earth-Science Reviews 248 (January 2024): 104650. https://doi.org/10.1016/j.earscirev.2023.104650.

A review of the activities of leaf cutter ants (LCA) in neoamerica. Create both constructional (surface) and excavational (subsurface) landforms that both have impact landscape evolution (e.g. filled burrows contribute to soil creep). They perform both biomixing AND biosorting simultaneously, depending on the parent material.
Actions on the landscape are cumulative. Hundreds of colonies over thousands of years. Some intentional constructions: mounds are built to reduce flooding of burrows.
Really great figure that represents the different sources of downward-moving material.
This is great evidence of cumulative impacts to support a conceptual model.

Palmer, Bryony J., Leonie E. Valentine, Manda Page, and Richard J. Hobbs. “Translocations of Digging Mammals and Their Potential for Ecosystem Restoration: A Review of Goals and Monitoring Programmes.” Mammal Review 50, no. 4 (October 2020): 382–98. https://doi.org/10.1111/mam.12208.

Reviews historical to current translocations of digging mammals in Australia
Could be used a proof that they are recognized as important to ecosystem restoration.

Pawlik, Łukasz, Jonathan D. Phillips, and Pavel Šamonil. “Roots, Rock, and Regolith: Biomechanical and Biochemical Weathering by Trees and Its Impact on Hillslopes—A Critical Literature Review.” Earth-Science Reviews 159 (August 2016): 142–59. https://doi.org/10.1016/j.earscirev.2016.06.002.

Pawlik, Łukasz, and Pavel Šamonil. “Soil Creep: The Driving Factors, Evidence and Significance for Biogeomorphic and Pedogenic Domains and Systems – A Critical Literature Review.” Earth-Science Reviews 178 (March 2018): 257–78. https://doi.org/10.1016/j.earscirev.2018.01.008.

Review of the historical development of organism-driven soil creep. Great figures. Thorough information on the role of organisms

Reichman, O.J., and Eric W. Seabloom. “The Role of Pocket Gophers as Subterranean Ecosystem Engineers.” Trends in Ecology & Evolution 17, no. 1 (January 2002): 44–49. https://doi.org/10.1016/S0169-5347(01)02329-1.

Reinhardt, Liam, Douglas Jerolmack, Brad J. Cardinale, Veerle Vanacker, and Justin Wright. “Dynamic Interactions of Life and Its Landscape: Feedbacks at the Interface of Geomorphology and Ecology.” Earth Surface Processes and Landforms 35, no. 1 (January 2010): 78–101. https://doi.org/10.1002/esp.1912.

Schneider, Anne-Kathrin, and Boris Schröder. “Perspectives in Modelling Earthworm Dynamics and Their Feedbacks with Abiotic Soil Properties.” Applied Soil Ecology 58 (July 2012): 29–36. https://doi.org/10.1016/j.apsoil.2012.02.020.

Sharma, D. K., S. Tomar, and D. Chakraborty. “Role of Earthworm in Improving Soil Structure and Functioning.” Current Science 113, no. 06 (September 25, 2017): 1064. https://doi.org/10.18520/cs/v113/i06/1064-1071.

Stockmann, Uta, Budiman Minasny, and Alexander McBratney. “Advances in Agronomy Quantifying Processes of Pedogenesis.” In Advances in Agronomy, 113:1–74. Elsevier, 2011. https://doi.org/10.1016/B978-0-12-386473-4.00001-4.

Übernickel, Kirstin, Jaime Pizarro-Araya, Susila Bhagavathula, Leandro Paulino, and Todd A. Ehlers. “Reviews and Syntheses: Composition and Characteristics of Burrowing Animals along a Climate and Ecological Gradient, Chile.” Biogeosciences 18, no. 20 (October 18, 2021): 5573–94. https://doi.org/10.5194/bg-18-5573-2021.

A very thorough review (1000+ sources) on the behaviors and impacts of bioturbators, vertebrates and invertebrates, in Chile. Acknowledges prior studes are heterogenious in methods, hard to estimate impact on the landscape and do not cover other biomes besides NA. We need a way to estimate the aggreagate impact of animals on the landscape.
Covers variability in excavation rates, tunnel diameter (sorting implications?), burrow depth, geographic distribution. Touches on the need for seasonality.
This can be used for a lot. Great evidence for the variability and different axes of animal activity, and also highlights the need for more thorough, consistent data.

Uvarov, Alexei V. “Inter- and Intraspecific Interactions in Lumbricid Earthworms: Their Role for Earthworm Performance and Ecosystem Functioning.” Pedobiologia 53, no. 1 (November 2009): 1–27. https://doi.org/10.1016/j.pedobi.2009.05.001.

Viles, H. A., L. A. Naylor, N. E. A. Carter, and D. Chaput. “Biogeomorphological Disturbance Regimes: Progress in Linking Ecological and Geomorphological Systems.” Earth Surface Processes and Landforms 33, no. 9 (August 2008): 1419–35. https://doi.org/10.1002/esp.1717.

Wilkinson, Marshall T., Paul J. Richards, and Geoff S. Humphreys. “Breaking Ground: Pedological, Geological, and Ecological Implications of Soil Bioturbation.” Earth-Science Reviews 97, no. 1–4 (December 2009): 257–72. https://doi.org/10.1016/j.earscirev.2009.09.005.

Reviews the implications of biological action in soil / geology.
Good table w/ examples of bioturbation. Figure that outlines different kinds of mounding.

Zhang, Yanming, Zhibin Zhang, and Jike Liu. “Burrowing Rodents as Ecosystem Engineers: The Ecology and Management of Plateau Zokors Myospalax Fontanierii in Alpine Meadow Ecosystems on the Tibetan Plateau.” Mammal Review 33, no. 3–4 (September 2003): 284–94. https://doi.org/10.1046/j.1365-2907.2003.00020.x.

4.3.1 Part 2

Provides a quantitative framework, an equation, to describe the sediment flux by tree throw—based on tree root depth. Suggest a non-linear relationship between slope angle and sediment flux for creep by tree throw. Relativley independent of curvature.
Also, has a small part review of the impacts of various invertebrates (earthworms, ants, termites) and vertebrates (gophers, moles).

Gabet, Emmanuel J. “Gopher Bioturbation: Field Evidence for Non-Linear Hillslope Diffusion.” Earth Surface Processes and Landforms 25, no. 13 (2000): 1419–28. https://doi.org/10.1002/1096-9837(200012)25:13<1419::AID-ESP1483.0.CO;2-1.

Tests the hypothesis that in hillslope w/ bioturbators, gophers, the relationship between diffusivity and curvature is nonlinear. This is true, the relationship is non-linear, because of preferential transport of surface material downhill. Subsurface material movement was found to have no relationship with hillslope gradient.
This paper has some excellent statistics too.
An example of lateral actions.

Phillips, Jonathan D. “Changes, Perturbations, and Responses in Geomorphic Systems.” Progress in Physical Geography: Earth and Environment 33, no. 1 (February 2009): 17–30. https://doi.org/10.1177/0309133309103889.

Promotes a conceptual model for describing geomorphic disturbance considering timescale and branching end-state.
Mechanisms are described by… frequency, magnitude, duration, areal extent, speed of onset, spatial dispersion, temporal spacing
Landscape responses are described by… response (reaction time and relaxation time), resistance (strength or absorption), resilience, and recursion (feedback).
This can be used for conceptual model development.

Meng, Xia, Annemieke M. Kooijman, Arnaud J.A.M. Temme, and Erik L.H. Cammeraat. “The Current and Future Role of Biota in Soil-Landscape Evolution Models.” Earth-Science Reviews 226 (March 2022): 103945. https://doi.org/10.1016/j.earscirev.2022.103945.

A review of the roles or organisms in soil and landscape evolution. AND a review of the 19 landscape evolution models that contain biota parameters—up to 2020. They conclude that this modeling suite is insufficient for biological organisms. Largely because of a lack of data.
Role review is mostly focused on hydrology, soil-bedrock production, weathering, and sediment transport. Lacks discussion of the types of animal activities, and their outcomes.
This is a great piece of evidence that animal-soil-landscape modes are underrepresented, and that there is a need both for models and a more holistic understanding.

Baxter, Timothy, Sam Woor, Martin Coombes, and Heather Viles. “The Geomorphic Work of the European Mole ( Talpa europaea ): Long‐term Monitoring of Molehills Using Structure‐from‐motion Photogrammetry.” Earth Surface Processes and Landforms, October 13, 2024, esp.6008. https://doi.org/10.1002/esp.6008.

Uses image analysis to study molehills dynamics: how they change over time in shape, size, density, etc. Molehills are very dynamic in location, size density, and change in response to season and introduce variability in soils.
Clean review data on mole excavation rates but “difficult to compare because of differences in the design (i.e., time and spatial monitoring scale and method), local conditions (i.e., soil type and climate), reported metrics (i.e., volume vs. mass) and research focus of different studies.”
Note about the importance of disturbance regime. Moles reconstruct collapsed burrows. If burrows are frequently collapsed (e.g. by floods or human disturbance), moles will anually excavate more sediment than those in stable landscapes. This poses a challenge for measurement, because we then need both mound abundance and disturbance regime.
This is a great case study for lateral, random(?) animal activity.

Cox, G W, and D W Allen. “Soil Translocation by Pocket Gophers in a Mima Moundfield,” 1987.

Study on the horizontal and vertical movement of soil on and surrounding pocket gopher mounds. Results suggests a net movement of soils upwards and mound wards, creating larger and larger mounds. Questions remain: How is this opposed by erosion? Is there an equilibrium rate?
This is a great example of topography-behavior connections

Darwin, Charles. The Formation of Vegetable Mould through the Action of Worms: With Observations on Their Habits. 1st ed. Cambridge University Press, 1881. https://doi.org/10.1017/CBO9780511703850.

Obviously, Darwin’s very early work on pedology and bioturbation. He describes how organisms, mostly earthworms, aid in the formation of hillslopes, sort soils and create distinct textural horizons, bury large coarse fragments and ancient buildings, and contribute to the darkening of upper soil horizons.
Great paper for the introduction to pedology and bioturbators. Honestly even works as a case study.

Don, Johnson. “BIOMANTLE EVOLUTION AND THE REDISTRIBUTION OF EARTH MATERIALS AND ARTIFACTS.” Soil Science 149, no. 2 (February 1990): 84–102.

Early biomantle paper. Similar but a less fleshed out version of the others from 2005. Great figures for tree throw.
This I believe is the earliest mention of the biomantle.

Grinnell, Joseph. “THE BURROWING RODENTS OF CALIFORNIA AS AGENTS IN SOIL FORMATION.” JOURNAL OF MAMMALOGY, 1923.

Early work on the impacts of gophers on soil development, somewhat parallel to Darwin’s work on earthworms. Mentions the role of organism in mixing soil and in doing so enhancing substratum/soil chemical weathering.
This a good source for early soils-animals work.

Hansen, R. M. and Morris M. J. “MOVEMENT OF ROCKS BY NORTHERN POCKET GOPHERS.” Journal of Mammalogy 49 (August, 1968): 391-99.

Study on the differences in coarse fragment content (fine, 0.64-1.27, 1.27-2.54, and >2.54cm) of gopher inhabited topsoil, uninhabited topsoil, summer mounds, and winter casts. Author Suggests gophers cannot move fragments >5cm, average burrow diameter.
This is a great sorting case study / hypothesis.

Hartemink, A.E., Y. Zhang, J.G. Bockheim, N. Curi, S.H.G. Silva, J. Grauer-Gray, D.J. Lowe, and P. Krasilnikov. “Soil Horizon Variation: A Review.” In Advances in Agronomy, 160:125–85. Elsevier, 2020. https://doi.org/10.1016/bs.agron.2019.10.003.

A review of lateral horizon variability. Good figures of tree-throw induced variability.
This could be a good lateral variability reference. Need to reed further.

AND

Johnson, D.L., J.E.J. Domier, and D.N. Johnson. “Animating the Biodynamics of Soil Thickness Using Process Vector Analysis: A Dynamic Denudation Approach to Soil Formation.” Geomorphology 67, no. 1–2 (April 2005): 23–46. https://doi.org/10.1016/j.geomorph.2004.08.014.

Companion papers with similar content. Authors propose an alternative, processed based model of soil genesis that greatly emphasizes biological processes
Introduces the biomantle, the “skin of the earth”, where organisms live, die, and change the soil. Contains a brief history of the other paradigms of soil erosion, dating back to Darwin, Dokuchaev, Hans Jenny, and to more recent USDA scientists.
Introduces “bioturbation styles”, great table with upward biotransfers (non-local mixing), biomixing (local mixing), and cratering.
Also introduces the dynamic denudation framework, where stonelines develop and serve as permanent restrictive layers in the soil profile.
This is a watershed paper in bioturbation literature. Provide several examples of stonelines,

Johnson, D. L., and D. Watson-Stegner. “EVOLUTION MODEL OF PEDOGENESIS:” Soil Science 143, no. 5 (May 1987): 349–66. https://doi.org/10.1097/00010694-198705000-00005.

Provides a novel framework for soil evolution: one that describe soil as a function of progressive and regressive pedogensis. Progressive pedogensis includes horizonation processes, developmental up-building, and soil deepening. Regressive pedogensis includes haploidization processes, retardant up-building, and soil removal. Development up-building, versus retardant up-building, requires added material be pedogenetically assimilated into the profile. Often this depends on the rate of addition. The authors suggest positive and negative vectors for the following that together drive or oppose soil development.
The authors also introduce the idea of internal feedback processes endogenic soil properties dominate over exogenic, environmental factors. For example, a petrocalcic horizon may develop in soil with a Ca rich parent material under an arid climate. This petrocalcic horizon, a product of soil genesis, impacts future development though leaching or bioturbation. A threshold was crossed that put the soil down a unique pedogenetic pathway.
The authors also reference Jenny’s 1941 clopt model and use that elegant framework to describe their approach of soil genesis. It is a reminder of the utility of that basic equation and it’s many applications.
Couple references to check out: Yaalon (1971) and Ruellan (1971) soil feedback processes; Wilde (1946, p. 13) include dt in clorpt; Vreeken (1975a) soil landscape processes; Johnson et al. (1987b) dynamic rate model; Runge (1973) and Volobuyeve (1984) thermodyanics of soil end points

Johnson, Michelle O., Simon M. Mudd, Brad Pillans, Nigel A. Spooner, L. Keith Fifield, Mike J. Kirkby, and Manuel Gloor. “Quantifying the Rate and Depth Dependence of Bioturbation Based on Optically‐stimulated Luminescence (OSL) Dates and Meteoric 10 Be.” Earth Surface Processes and Landforms 39, no. 9 (July 2014): 1188–96. https://doi.org/10.1002/esp.3520.

Uses quarz grains to date the age of a termite mound and soil beneath. I can see there are no bioturbation rate calculations, although this data could be used.
Figure 5 of appendix looks visually very similar to what I modeled. my note: note the shape of C is very similar to what is described by a diffusion-advection model (w/ erosion). 100-150cm is the stoneline layer, the lower boundary of bioturbation, and explains the signifigant increase in age after.
Sorting case study too

Miller, Milton A. “Burrows of the Sacramento Valley Pocket Gopher in Flood-Irrigated Alfalfa Fields.” Hilgardia 26, no. 8 (January 1957): 431–52. https://doi.org/10.3733/hilg.v26n08p431.

A dated study on a number of topics, with valuable information on burrow depth and a decent dataset of soil displacement rates by different gopher species.
Great figure on burrow area w/ depth.

Nye, P. H. “Some Soil-Forming Processes in the Humid Tropics.” Journal of Soil Science 5, no. 1 (1954): 7–21. https://doi.org/10.1111/j.1365-2389.1954.tb02171.x.

Discusses the genesis of a catena of tropical soils in West Africa making reference to the role of soil fauna, here ants, earthworms, and termites, in the creation of stonelines in soils. The author compares the soil texture of termite mounds to that of the suspected termite-formed horizon and finds them similar. He makes notes about coarse fragment size relating to bedrock fracture density and the releative importance of clay illuviation in texture contrast development.

This is a good case study for animal sorting.

Román‐Sánchez, Andrea, Ana Laguna, Tony Reimann, Juan Vicente Giráldez, Adolfo Peña, and Tom Vanwalleghem. “Bioturbation and Erosion Rates along the Soil‐hillslope Conveyor Belt, Part 2: Quantification Using an Analytical Solution of the Diffusion–Advection Equation.” Earth Surface Processes and Landforms 44, no. 10 (August 2019): 2066–80. https://doi.org/10.1002/esp.4626.

Salvador-Blanes, S., B. Minasny, and A. B. McBratney. “Modelling Long-Term in Situ Soil Profile Evolution: Application to the Genesis of Soil Profiles Containing Stone Layers.” European Journal of Soil Science 58, no. 6 (2007): 1535–48. https://doi.org/10.1111/j.1365-2389.2007.00961.x.

Yeates, G. W., and H. Van Der Meulen. “Burial of Soil-Surface Artifacts in the Presence of Lumbricid Earthworms.” Biology and Fertility of Soils 19, no. 1 (January 1995): 73–74. https://doi.org/10.1007/BF00336350.

Study on the bural of of wire by Lumbricid earthworms in pasture and forest.
This is a valuable study focused on non-local mixing.