We thank Case Western Reserve University&#8217;s Squire Valleevue and Valley Ridge Farms, including A. Locci, C. Bond, and A. Alldridge, for help establishing the common garden. J. Hooks, L. Huffman, L. Gonzales, S. C. Leahy, B. Ochocki, A. Ubiles, C. Yu, X. Zhao, and N. M. Zimmerman provided field assistance. A.J.B. and J.H.B. were funded by startup funds from CWRU to J.H.B. G.A.D. was supported by a Summer Programs in Undergraduate Research grant from CWRU funded by the Howard Hughes Medical Institute. This work was also supported by National Science Foundation funding to J.H.B. (DEB 1250170).

1. Collect Field Soils to Produce Heterogeneous and Homogeneous Soil Treatments
<ol>
	<li>Identify two cooccurring plant species in similar habitats and soil types for study (e.g. Figure 1a). Determine amount of soil needed based on soil patch size to use in the experiment (e.g. one-third to one-half of the focal species' primary root zone, or volume encompassed by the root ball) and the number of patches needed for the experiment (see Protocol 2 and 3, below).
	<ol>
		<li>For Rumex spp. (Figure 1a), use soil patches of 10 cm x 10 cm x 18 cm (length x width x depth) for approximate root zone of 10 cm radius from base of plant to 18 cm depth (5,655 cm3 soil from this defined zone of root influence for one individual plant yields 3 soil patches of 1,800 cm3).</li>
	</ol>
	</li>
	<li>Survey field site to locate adult individuals of the two focal species. Avoid individuals whose root zone likely overlaps with the other focal species (e.g. Rumex individuals located within 0.25 m of the other species). Mark the number of individuals needed to obtain the required amount of soil with pin flags.
	<ol>
		<li>Mark 20 randomly chosen individuals of each Rumex spp. for 20 experimental units (2 species x 2 soil treatments x 5 replicates) that each require 3 soil patches from each focal species (as in Protocol 2, below).</li>
	</ol>
	</li>
	<li>Sterilize soil collecting equipment (shovels, gloves, transporting containers) with an approximately 1:10 mixture of bleach (5-10% NaClO) and water to remove all soil particles. Dry equipment before use to avoid bleach effects on soil biota. Label each piece of equipment with laboratory tape to indicate the focal species whose soil it will collect or transport to avoid cross-contamination (e.g. label one shovel for species A and a second shovel for species B).</li>
	<li>Check weather and soil conditions before beginning soil collection for recent precipitation events. Avoid collecting soils that are too wet (muddy or fully saturated) or collecting soil during a precipitation event to minimize soil compaction. Avoid collecting soils that are too dry (very hard and difficult to insert a shovel into) to aid in separating soil from roots.</li>
	<li>Collect field soil from marked individuals of the two focal species in replicate batches to avoid pseudoreplication (e.g. a single soil sample containing a rare pathogen being subsequently mixed across experimental replicates).
	<ol>
		<li>Dig up the complete root zone of an individual of species A (as defined in step 1.1) with the appropriately-labeled sterile shovel, remove visible coarse roots from the soil with the appropriately-labeled sterile gloves, and place soil in the appropriately-labeled sterile transport container (e.g. bucket). For an experiment with 4 experimental units in each block and 1 individual plant's root zone providing enough soil for 1 experimental unit (as in Section 1.2.1), repeat this procedure for 3 additional individuals of species A.</li>
		<li>Repeat Section 1.5.1 for species B.</li>
		<li>Transport the replicate soil collection from both species to the experimental site. Place soil in experimental units for block 1 of the experiment (as in Protocol 2 or 3, below), where a block contains an experimental unit from each treatment combination (i.e. each species x each soil treatment).</li>
		<li>Repeat Section 1.5.3.</li>
		<li>Repeat Sections 1.5.1-1.5.4 for the remaining blocks in the experiment. Collect soil from groups of individuals at least 1 m distant from previous collecting locations for each replicate collection to minimize pseudoreplication.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" fo:content-width="6in" src="/files/ftp_upload/51580/51580fig1highres.jpg" width="500" /> 
Figure 1. Example field experimental design manipulating plant-induced soil heterogeneity. (a) Soils are collected from the zone of root influence of conspecifics (&#945;) and heterospecifics (&#946;) in the field, following standard protocols for studying the effects of plant-soil feedbacks9. (b) Experimental treatments with heterogeneous soils composed of soils from plant A (&#945; soils) and soils from plant B ('&#946;' soils) are arranged in a grid, and homogenized soil treatments created with an equal mixture of soils from these two origins. In this example, grids of field soils are inserted into large-diameter pots sunken into the ground and the area around each grid is filled with coarse, sterilized sand. This figure has been modified from Brandt et al.10
2. An Example Field Experiment, Creating Grids of Heterogeneous and Homogeneous Soil to Measure Plant Population Responses
<ol>
	<li>Use soils from a replicate field soil collection (Protocol 1) to produce a heterogeneous treatment (i.e. alternating grid cells contain soil collected from species A or species B) and a homogeneous treatment (i.e. each grid cell contains a 1:1 mixture of soil from species A and B) (Figure 1b) for block 1 of the experiment in the following steps.
	<ol>
		<li>Sterilize soil handling equipment (trowels, gloves, plastic grid) with an approximately 1:10 mixture of bleach (5-10% NaClO) and water to remove all soil particles. Dry equipment before use to avoid bleach effects on soil biota. Label each piece of equipment with laboratory tape to indicate the focal species whose soil it will handle to avoid cross-contamination (e.g. label one trowel for species A and a second trowel for species B) and the plastic grid to indicate whether it will be used for the heterogeneous or homogeneous soil treatment.</li>
		<li>Place removable plastic grid into a pot sunken into the ground [or other plot or container large enough to accommodate the grid] to be filled with field collected soil (e.g. 1,800 cm3/grid cell as in step 1.1.1). Use a custom-constructed grid of the desired dimensions, e.g. a 2 x 3 grid with 6 cells of the size determined in step 1.1 (Figure 1b).
		<ol>
			<li>For the heterogeneous treatment of alternating soil patch types, place spadefuls of soil from species A into grid cells for &#945; soil and soils from species B into cells for &#946; soil (Figure 1b).</li>
			<li>For the homogeneous treatment, place alternating spadefuls of soils a and b into each grid cell, taking care to evenly distribute the two soil types and avoid the formation of layers of each soil type (Figure 1b). For the example soil patch of 1,800 cm3 (Section 1.1.1), place 900 cm3 of each soil type in each grid cell.</li>
			<li>Be sure to produce equal amounts of disturbance (i.e. break up soil clods to the same degree) when creating heterogeneous and homogeneous soil treatments to avoid confounding soil disturbance with soil heterogeneity.</li>
		</ol>
		</li>
		<li>If any empty area remains around the outside of the grid within the large pot used (as in Figure 1b), fill this area with sterile sand. Sterilize sand using any standard method (e.g. autoclaving, gamma-irradiation).</li>
		<li>Lift the plastic grid vertically out of the pot, leaving the soil patches intact. This allows roots from different individuals to interact in the soil and each plant to experience multiple patches, which is essential for allowing plant roots to grow into multiple soil patches (i.e. grid cells).</li>
		<li>Repeat Sections 2.1.2-2.1.4 for a second pair of experimental units to produce a complete experimental block (i.e. a grid of heterogeneous soil into which to plant each focal species and a grid of homogeneous soil into which to plant each focal species, for a total of 4 experimental units).</li>
	</ol>
	</li>
	<li>Repeat step 2.1 for remaining blocks in the experiment with the remaining soil replicate collections (Protocol 1). Randomize blocks, and plots within blocks, throughout the experimental area, using landscape fabric around the plots if desired, to keep shading from outside vegetation at a minimum (not shown).</li>
	<li>Plant seeds of focal species into each grid cell of each experimental pot (2 focal species x 2 soil treatments). Use pooled seed to avoid confounding plant genotypes or seed-surface microbial communities with the soil treatments. For example, plant seeds of each Rumex spp. into the pot for that species (Figure 1a) individually glued to plastic toothpicks with water-soluble glue in 12 planting positions (2 positions per grid cell) to clearly identify the planted individuals.</li>
	<li>Measure population responses of the experimental units, such as germination and survival, through a regular census of individual marked planting locations of seeds (e.g. using toothpicks as in step 2.3). Minimize disturbance of the soil for any response measured to avoid mixing soil among patches.
	<ol>
		<li>Determine the appropriate census intervals based on the expected rate of population responses for the focal species. For example, conduct weekly censuses for Rumex spp. that can germinate quickly.</li>
		<li>Continue the experiment for an appropriate duration based on the life history of the focal species. For example, continue the experiment for at least 2 years for short-lived perennial Rumex spp. to obtain data on all life stages.</li>
	</ol>
	</li>
</ol>
3. An Example Greenhouse Experiment, with Heterogeneous and Homogenized Soil in Pots to Measure Individual Plant Responses
<ol>
	<li>Use soils from a replicate field soil collection (Protocol 1) to produce a heterogeneous treatment (i.e. each half of a pot filled with soil collected from species A or species B) and a homogeneous treatment (i.e. pot contains a 1:1 mixture of soil from species A and B) (Figure 2a) for block 1 of the experiment in the following steps.
	<ol>
		<li>In the transport container (e.g. bucket) and before potting, mix the field collected soil from each species with sterile sand to produce a 1:1 mixture. Do this to mitigate soil compaction and improve drainage in the pots, which is especially helpful for washing roots, facilitating the separation of roots from soil. Sterilize sand using any standard method (e.g. autoclaving, gamma-irradiation).</li>
		<li>Be sure to produce equal amounts of disturbance (i.e. break up soil clods to the same degree) when mixing each batch of field soil with sand.</li>
	</ol>
	</li>
	<li>Sterilize soil handling equipment (trowels, gloves, plastic sheet) with an approximately 1:10 mixture of bleach (5-10% NaClO) and water to remove all soil particles. Dry equipment before use to avoid bleach effects on soil biota. Label each piece of equipment with laboratory tape to indicate the focal species whose soil it will handle to avoid cross-contamination (e.g. label one trowel for species A and a second trowel for species B) and each side of a stiff plastic sheet to indicate which soil type will be potted on each side of it in the heterogeneous soil treatment.</li>
	<li>Create a heterogeneous soil treatment using the field soil-sand mixtures from the two focal species (from Section 3.1.1).
	<ol>
		<li>Place the stiff plastic sheet in the center of a pot to divide it in half (Figure 2a). Use a pot sized such that half of it is equivalent in volume to the appropriate soil patch size (step 1.1). For example, use a pot with a 15 cm diameter and 18 cm depth for the Rumex spp. in Figure 1a (total volume of 3,181 cm3).</li>
		<li>Have two researchers simultaneously add the field collected soil from each species to the appropriate side of the pot (e.g. &#945; soil from species A) with appropriately-labeled trowels, to keep the sides even as the pot is filled.</li>
		<li>Remove the plastic divider by lifting it vertically out of the soil, leaving the soil patches intact. This allows the plants to experience both patches of soil within a pot, essential for the plants to experience heterogeneity.</li>
		<li>Repeat Sections 3.3.1-3.3.3 for 3 additional experimental units to produce a complete block of the heterogeneous soil treatment (2 species x 2 soil patch types in the heterogeneous treatment; Figure 2).</li>
	</ol>
	</li>
	<li>Create a homogeneous soil treatment using the field soil-sand mixtures from the two focal species (from Section 3.1.1).
	<ol>
		<li>Repeat Section 3.3.1. Have two researchers simultaneously add both &#945; and &#946; soils to both sides of the pot with appropriately-labeled trowels, evenly distributing both soil types within each patch and avoiding the creation of layers. Repeat Section 3.3.3.</li>
		<li>Repeat Section 3.4.1 for a second experimental unit to produce a complete block of the homogeneous soil treatment (one pot for each of the 2 focal species).</li>
	</ol>
	</li>
	<li>Repeat steps 3.2-3.4 for remaining blocks in the experiment with the remaining soil replicate collections (Protocol 1). Randomize blocks, and plots within blocks, across the greenhouse bench.</li>
</ol>
<img alt="Figure 2" fo:content-width="6in" src="/files/ftp_upload/51580/51580fig2highres.jpg" width="500" /> 
Figure 2. Example greenhouse experimental design manipulating plant-induced soil heterogeneity. (a) Soils collected from the zone of root influence of species A (&#945; soils) and species B (&#946; soils) in the field are placed in each half of a pot (heterogeneous treatment) or mixed throughout the pot (homogeneous treatment). (b) Plants of species A are then planted into the experiment in each soil patch type in the heterogeneous treatment and on one side of the homogeneous treatment. Here, only one species (A) is shown planted into this design. A fully reciprocal design would include plants of the second focal species (B) planted into each soil treatment and patch type within the heterogeneous treatment.
<ol start="6">
	<li>Plant seedlings of focal species A and B into each soil patch type in a factorial design (2 species x 3 soil patch types [&#945; soil, &#946; soil, and a homogeneous mixture of &#945; and &#946; soil]; Figure 2b).</li>
	<li>Measure any individual plant responses that indicate plant performance, such as plant size, biomass production, or functional traits. Appropriate traits to measure will depend on the focal species and the scientific questions of interest.
	<ol>
		<li>Continue the experiment until the plants appear large relative to soil patches (e.g. approximately 1.5x the width of the soil patch for rosette-forming forbs) to ensure the plant roots are growing into both soil patches. Experimental duration will thus depend on the growth rate of focal species.</li>
		<li>Harvest plants and/or measure responses before plants become pot-bound (i.e. root growth is limited by the confines of the pot and roots circle the bottom of the pot) if realistic responses to the soil environment are desired. For example, roots of pot-bound plants are unlikely to forage throughout the soil column in a similar manner to plants in the field.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

Plant-induced soil heterogeneity is highly likely in natural communities because plants have large and often species-specific effects on their soil environment and the subsequent plants that experience that soil (e.g. Petermann&#160;et al.13). However, our understanding of the role of this type of heterogeneity on plant communities is minimal10,14. Here, we present a method for manipulating plant-induced soil heterogeneity, using soil from different origins (i.e. zones of root influence of different species) in the field. The critical steps within the protocol to avoid confounding plant-induced soil heterogeneity with other variables that affect plant responses are: (1) avoiding pseudoreplication of soil samples collected from the field and placed into experimental units and (2) equalizing the amounts of soil disturbance for field soils placed into heterogeneous and homogeneous soil treatments. Pseudoreplication of soil samples could occur if heterogeneous and homogeneous treatments receive soil collected from different individual plants or collecting locations in the field, which can be avoided by collecting soil in replicate batches from well-spaced locations (step 1.5). Pseudoreplication can affect the study&#8217;s results if, for example, a rare pathogen occurs in the root zone of one plant in the field and that plant&#8217;s soil is only placed in one of the two soil treatments. Additionally, collecting locations in the field may differ in management, vegetation history, or soil properties; thus soil from each collecting location should be used in both experimental treatments, randomizing across potential confounding factors. Disturbance to field soils (i.e. breaking up of soil clods) increases soil compaction and can affect the interpretation of results. For example, if the homogeneous soil treatment receives greater disturbance than the heterogeneous treatment, then the effect of soil heterogeneity would be an effect of soil disturbance. Readers should also consider statistical power in their design of these experiments, which would affect the total amount of soil required (step 1.1) and the number of individuals of each focal species from which to collect soil in the field (step 1.2). Preliminary experiments could be used to determine the effect size and variance expected, and this information could then be used to design an experiment with sufficient replication15.
This protocol could be easily modified to accommodate other methods for studying plant-soil feedbacks (e.g. by using soils conditioned in the greenhouse16) and alternative experimental designs (e.g. different spatial or temporal scales, interspecific competition17). Additional experiments could also use alternative focal species. The selection of focal species has implications for both the study&#8217;s logistics and interpretation of results, but above all should be done to best address the investigator&#8217;s questions of interest. We show Representative Results for closely related pairs of species, which allowed us to control to some extent for growth form18 and an effect of phylogeny on plant-soil feedback responses (e.g. Burns and&#160;Strauss19). The size of focal species determines the scale of soil patches used and their life history may affect the duration of the experiment. Two focal species of different size might respond differently to the same scale of plant-induced soil heterogeneity if the smaller species cannot integrate across different soil patch types to the same degree as the larger species (e.g. the smaller species&#8217; root zone is restricted to a single soil patch). Additionally, using species with a clonal growth form is likely to produce different responses to soil heterogeneity than species that reproduce solely from seed (as reviewed in Reynolds and&#160;Haubensak14).
An important limitation of this method is that the mechanisms governing responses to soil heterogeneity (e.g. abiotic factors such as soil chemistry, biotic factors such as soil microbial communities) are not identified without further work. For example, our results suggest that homogeneous soil (i.e. mixed soil) can result in nonadditive effects at both the population and individual plant level, where plant responses in the homogeneous treatment were not intermediate relative to plant responses in the two soil types that composed the mixture. Soil mixing could occur in natural communities as a result of disturbances, such as rodents&#8217; digging, or as a result of overlapping zones of root influence as plants of different species grow into each other&#8217;s rooting zones. One possible mechanism for these findings is an effect of soil biota, which could contribute to nonadditive responses if communities of bacteria, fungi, or other organisms interact upon soil mixing, changing the biotic composition of the soil and thus the plant responses to that soil. Abiotic mechanisms could also result in nonadditive responses, if plant functional responses to abiotic drivers (e.g. nutrient levels) are nonlinear20. Additional experiments and sampling are thus necessary to identify the drivers of plant responses to these soil treatments, with implications for their application to natural communities. For example, the role of soil biotic factors in governing plant responses to plant-induced soil heterogeneity could be tested by using soils conditioned by focal species in the greenhouse compared with sterilized soils, which provide a negative control for testing the role of soil biota.
We demonstrate significant plant responses to plant-induced soil heterogeneity, suggesting that plants themselves influence the environmental heterogeneity that affects plant community assembly (Figure&#160;5). Heterogeneity can thus be intrinsic to the community composition, as opposed to the more extrinsic types of heterogeneity that studies of plant community assembly have more frequently considered3. The novel method presented here has potential to reconcile conflicting predictions from theory and results from experiments about the relationship between environmental heterogeneity and species coexistence, or diversity4,14. Theory predicts that environmental heterogeneity leads to increased species diversity (reviewed in Melbourne&#160;et al.3), however previous experiments directly manipulating soil nutrient heterogeneity have often found the opposite trend (reviewed in Lundholm4&#160;and&#160;Reynolds and Haubensak14), suggesting that other types of heterogeneity, such as those resulting from plant-soil feedbacks, should be examined. This method of manipulating plant-induced soil heterogeneity indicates specific mechanisms by which coexistence may be facilitated in homogeneous environments. For example, if resident plants have lower germination or higher mortality in homogeneous soils, as was found for some species (Figure&#160;3), then these more homogeneous environments may be more invasible, counter to the traditional predictions of theory. Further, coexistence predictions for each species pair in heterogeneous soils can be calculated7 using species responses to each soil patch type within the heterogeneous treatment, allowing researchers to determine for which species they might expect plant-induced soil heterogeneity to facilitate coexistence10.&#160;
<img alt="Figure 5" fo:content-width="5in" src="/files/ftp_upload/51580/51580fig5highres.jpg" width="500" /> 
Figure 5.&#160;Conceptual overview of the value of addressing plant-induced soil heterogeneity. (a) Traditional conceptualization of the influence of heterogeneity on coexistence and community assembly has focused on the effect of heterogeneity extrinsic to the community composition (e.g. landscape topology) on community assembly. (b) The new methods proposed here include the effects of plants on soil heterogeneity driven by plant-soil feedbacks, where plants influence the biota, chemistry, or structure of the soil in a manner that influences subsequent plant performance in that soil. This perspective acknowledges that heterogeneity intrinsic to community composition, including both biotic and abiotic effects, also influences assembly.
Manipulating heterogeneity that is intrinsic to the community allows rigorous testing of the potential for frequency-dependent coexistence that could result from biotic feedbacks, such as plant-soil feedbacks, and integrates our understanding of this mechanism with the greater body of coexistence theory9. Because this type of heterogeneity is dynamic over time, its influence on community assembly will depend on the length of time it takes for plant-soil feedbacks to develop and the length of plant-soil feedback legacy effects in communities. Thus, further empirical work is needed on the temporal scale over which these effects develop and degrade. Future applications that could emerge from this work thus include informing new theory that incorporates heterogeneity driven by intrinsic feedback processes (e.g. Fukami and&#160;Nakajima20) and further empirical tests of the role of these intrinsic processes in assembly (e.g. Brandt&#160;et al.10).

One of the primary goals of community ecology is to explain and predict the processes governing community assembly. However, plant communities are frequently more diverse than predicted by coexistence theory1, and restoration ecologists need to understand coexistence mechanisms to successfully restore diverse native communities2. Environmental heterogeneity is a theoretically important mechanism that can help explain high levels of community diversity, but experimental manipulations of heterogeneity are infrequent3 and focus on abiotic heterogeneity (e.g. reviewed in Lundholm4). Theory that incorporates heterogeneity typically assumes that heterogeneity is extrinsic to the assembling community. Extrinsic heterogeneity is governed by factors such as landscape typology, which are independent of the community composition. Extrinsic heterogeneity can result in coexistence through niche partitioning (reviewed in Melbourne&#160;et al.3, e.g. Pacala and Tilman5&#160;and&#160;Chesson6). However, much of the environmental heterogeneity relevant to plant communities may be intrinsic to the community, developing as the community assembles and depending on the identity of the species in the community. Intrinsic heterogeneity can result from biotic feedbacks, which can lead to coexistence through negative frequency-dependence (e.g. Bever&#160;et al.7). Here, we describe a novel method for manipulating plant-induced soil heterogeneity, a type of soil heterogeneity that is intrinsic to the community and arises from plant-soil feedbacks.
Plant-soil feedbacks (PSF) occur when plants influence the soil structure, chemistry, or biota in a manner that affects subsequent plant performance in that soil, and PSF have large mean effects on plant performance in native plant communities8. Studies of PSF have typically either collected soils from the field or conditioned soils experimentally, then asked how plants perform in conspecific soil relative to heterospecific or sterilized soil9. If plants perform better in conspecific soil relative to reference soils, then PSF are positive, while if plants perform better in reference soils, PSF are negative. Reciprocal negative PSF can lead to frequency-dependent coexistence between species7. While the mean effects of PSF are well-characterized8, the effects of spatial heterogeneity in PSF are poorly understood10.
Because PSF occur on the scale of individual plants7 and because plants are often nonrandomly distributed in space and time, PSF are likely to lead to soil heterogeneity, which we call plant-induced soil heterogeneity. Unlike many other forms of heterogeneity (e.g. landscape topology), this heterogeneity is intrinsic to the assembling community and may thus influence community assembly differently than more extrinsic forms of heterogeneity. In order to understand the influence of this form of heterogeneity on plant performance and coexistence, we need experimental methods that manipulate plant-induced soil heterogeneity. Here, we demonstrate such a method, which uses soils conditioned by two species to create a heterogeneous treatment with separate patches from two soil origins and a homogeneous treatment, which is a mixture of the two soil origins. This soil mixing could represent at least two plausible scenarios in the field: (1) disturbance (e.g. rodent, agriculture) which mixes soils of different origins or (2) plants of two species growing in close proximity, such that their zones of root influence intermingle and homogenize.
We present two example experiments that use plant-induced soil heterogeneity to answer key questions at different levels of ecological organization: (1) Do plant populations respond to plant-induced soil heterogeneity? and (2) Do individual plants respond to plant-induced soil heterogeneity? We describe a field experiment using 6 soil patches to address the first question and a greenhouse experiment using 2 soil patches to address the second question. Quantifying both population and individual plant responses to soil heterogeneity is essential to understanding how heterogeneity influences community assembly.

<table><tbody><tr><td>Shovel(s)</td><td>Any</td><td>NA</td><td>It is helpful to have at least two shovels, one for each species of soil origin.</td></tr><tr><td>Trowel(s)</td><td>Any</td><td>NA</td><td>It is necessary to have at least two trowels of identical size, one for each species of soil origin.</td></tr><tr><td>Gloves</td><td>Any</td><td>NA</td><td>Gardening gloves can be used.</td></tr><tr><td>Diluted bleach</td><td>Any</td><td>NA</td><td>We use an ~1:10 concentration of household bleach (containing 5-10% NaClO) to water to sterilize all equipment between soil collections.</td></tr><tr><td>Plastic grid(s)</td><td>Any</td><td>NA</td><td>CUSTOM. We used plastic sheeting from the construction of greenhouse walls to create the grid used in the field experiment. However any stiff plastic that can be manipulated can be used. It is helpful to have three grids to produce reciprocal heterogeneous treatments and a homogeneous treatment without needing to sterilize between each experimental unit.</td></tr><tr><td>Plastic dividers</td><td>Any</td><td>NA</td><td>CUSTOM. We used stiff sheets of plastic, cut to fit the pot minimum width, such that they can slide down to the bottom of the pot for the greenhouse experiment. It is helpful to have at least two dividers, one for heterogeneous and one for homogeneous treatments, if investigators want to randomize the order in which experimental units within a block are filled without needing to sterilize the divider in between each experimental unit.</td></tr><tr><td>Buckets or wheelbarrows</td><td>Any</td><td>NA</td><td>Any container for transporting soils.</td></tr><tr><td>Seeds</td><td>Any</td><td>NA</td><td>We collect seeds in the field by hand. Seeds can also be ordered from horticultural suppliers, if appropriate.</td></tr><tr><td>Plastic toothpicks</td><td>Soodhalter Plastics, Inc.</td><td>805KP</td><td>We plant individual seeds glued on toothpick in the field experiment to facilitate monitoring germination and survival of individuals.</td></tr><tr><td>Water soluble glue</td><td>Elmer&#039;s</td><td>Elmer&#039;s Glue-all</td><td>Any water soluble glue can be used to adhere seeds to plastic toothpicks.</td></tr><tr><td>Pots</td><td>Any</td><td>NA</td><td>Pot size will depend on experimental plants used and number of soil patches desired (&lt;em&gt;e.g.&lt;/em&gt; 2 or 6).</td></tr><tr><td>Sand</td><td>Any</td><td>NA</td><td>Coarse sand may be mixed with field soils to improve drainage in pots.</td></tr><tr><td>Lab tape&amp;nbsp;</td><td>Any</td><td>NA</td><td>Tape may be used to label equipment used in handling soils with the species of origin.</td></tr><tr><td>Pin flags</td><td>Any</td><td>NA</td><td>Flags can be used to identify individuals in the field prior to soil collection.</td></tr><tr><td>Landscape fabric</td><td>Any</td><td>NA</td><td>Landscape fabric can be used in the field to minimize the growth of plants outside experimental plots.</td></tr></tbody></table>

experimental protocol for manipulating plant-induced soil heterogeneity

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

Species responded to plant-induced soil heterogeneity in diverse ways at both the population and individual level (Figures 3 and 4), with implications for community assembly. To determine whether plant populations respond to plant-induced soil heterogeneity, a field experiment was established as in Protocol 2 using three congeneric pairs of species. Plant populations were censused weekly for three months and the total proportion of planted seeds that germinated and the total proportion of those seedlings that died in the first growing season (where mortality represents the inverse of survival) were calculated (Figure 3). We found significant plant population responses to plant-induced soil heterogeneity, suggesting that this experiment was successful in manipulating heterogeneity that influenced plant populations. Some species exhibited nonadditive responses to soil mixing, such that the response observed in the homogeneous treatment (&#945;&#946; soil patches) was not an intermediate response to the two soil types that were mixed to create that treatment (&#945;, or conspecific, soil patches and &#946;, or congener, soil patches). For example, Solanum carolinense had lower germination and Rumex crispus had greater mortality in a homogenized mixture of conspecific and congener's soils than in either soil type alone (Figure 3)10. These results provide potential mechanisms by which homogeneous soil environments might facilitate coexistence, where reduced germination or increased mortality of one species could provide open patches for other species to colonize.
<img alt="Figure 3" fo:content-width="6in" src="/files/ftp_upload/51580/51580fig3highres.jpg" width="500" /> 
Figure 3. Example results from a field experiment with heterogeneous and homogeneous soils. (a) Proportion germination and (b) proportion mortality of 3 pairs of congeneric species planted into patches of conspecific soil, congener soil, or a homogeneous mixture of the two soil types. Some species responded to soil mixing in a nonadditive manner; for example, Rumex crispus had greater mortality in the homogeneous treatment than in either conspecific or congener (R. obtusifolius) soil patches in the heterogeneous treatment. PLALAN = Plantago lanceolata, PLAMAJ = P. major, RUMCRI = R. crispus, RUMOBT = R. obtusifolius, SOLCAR = Solanum carolinense, and SOLDUL = S. dulcamara. *P&#60;0.05 from orthogonal contrasts of homogeneous vs. unmixed soil and conspecific vs. congener soil within each species in a mixed effects model with a binomial error distribution in the R Statistical Environment11. Mean proportions are presented (total count divided by total sample, for consistency with statistical methods12). This figure has been modified from Brandt et al.10 See Brandt et al.10 for detailed analysis methods.
To determine whether individual plants respond to plant-induced soil heterogeneity, a greenhouse experiment was established as in Protocol 3 using two congeneric pairs of species. Because we expected plants to respond to the soil patch type in which they were grown in addition to the pot-level soil heterogeneity, seedlings were planted into each patch type within the heterogeneous treatment (as in Figure 2b). The plants were grown for 2 months and then harvested to measure performance (total biomass) and functional traits (including specific leaf area (SLA), as shown in Figure 4). Significant plant responses to soil heterogeneity were observed, suggesting that this experiment was successful in manipulating a form of soil heterogeneity that influences plant performance. We observed a nonadditive response to soil mixing, in which species tended to have lower SLA, or thicker leaves, in a homogenized mixture of conspecific and congener's soil than in either soil type alone (P = 0.031 from an orthogonal contrast of homogeneous vs. unmixed soil in a mixed effects model with plant biomass as a covariate and block as a random effect; Figure 4). Specific leaf area was also lower in conspecific compared to congener soil patches (P = 0.004 from an orthogonal contrast of soil patch types in the heterogeneous soil treatment; Figure 4). These results suggest that plant resource acquisition strategies respond to plant-induced soil heterogeneity, which has implications for the effect of such heterogeneity on plant growth, fecundity, and species interactions.
<img alt="Figure 4" fo:content-width="6in" src="/files/ftp_upload/51580/51580fig4highres.jpg" width="500" /> 
Figure 4. Example results from a greenhouse experiment with heterogeneous and homogeneous soils. Specific leaf area (SLA), calculated as leaf area divided by dry mass, of 2 pairs of congeneric species grown in patches of conspecific soil, congener soil, or a homogeneous mixture of the two soil types. Overall, species responded to soil mixing in a nonadditive manner, where SLA was lower in the homogeneous treatment than in either conspecific or congener soil patches in the heterogeneous treatment. Mean traits &#177; 1 SE. PLALAN = Plantago lanceolata, PLAMAJ = P. major, RUMCRI = R. crispus, RUMOBT = R. obtusifolius.

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Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community&#8217;s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as ...

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18.6K Views.  Case Western Reserve University. Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community’s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Video: Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24&#160;hr&#160;after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

A rainfall simulator was used to apply a consistent rate of uniform rainfall to packed soil boxes in a study of the fate and transport of urea, a nonpoint source environmental contaminant. Under uniform soil and rainfall conditions, antecedent soil moisture content exerted strong control over urea loss in surface runoff.

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The ...

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled Earth-system processes. Such knowledge is imperative in improving predictions of hydro-biogeochemical cycles, especially under climate change scenarios. We present an experimental method, designed to capture sub-surface heterogeneity of an initially homogeneous soil system. This method is based on destructive sampling of a soil lysimeter designed to simulate a small-scale hillslope. A weighing lysimeter of one cubic meter capacity was divided into sections (voxels) and was excavated layer-by-layer, with sub samples being collected from each voxel. The excavation procedure was aimed at detecting the incipient heterogeneity of the system by focusing on the spatial assessment of hydrological, geochemical, and microbiological properties of the soil. Representative results of a few physicochemical variables tested show the development of heterogeneity. Additional work to test interactions between hydrological, geochemical, and microbiological signatures is planned to interpret the observed patterns. Our study also demonstrates the possibility of carrying out similar excavations in order to observe and quantify different aspects of soil-development under varying environmental conditions and scale.

This study presents an excavation method for investigating subsurface hydrological, geochemical, and microbiological heterogeneity of a soil lysimeter. The lysimeter simulates an artificial hillslope which was initially under homogeneous condition and had been subjected to approximately 5,000 mm of water over eight cycles of irrigation in an 18-month period.

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled ...

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The purpose of this manuscript is to provide detail on how to rapidly sample soil, rhizosphere, and endosphere of replicated field trials and analyze changes that may occur in the microbial communities due to sample type, treatment, and plant genotype. The experiment used to demonstrate these methods consists of replicated field plots containing two, pure, warm-season grasses (Panicum virgatum and Andropogon gerardii) and a low-diversity grass mixture (A. gerardii, Sorghastrum nutans, and Bouteloua curtipendula). Briefly, plants are excavated, a variety of roots are cut and placed in phosphate buffer, and then shaken to collect the rhizosphere. Roots are brought to the laboratory on ice and surface sterilized with bleach and ethanol (EtOH). The rhizosphere is filtered and concentrated by centrifugation. Excavated soil from around the root ball is placed into plastic bags and brought to the lab where a small amount of soil is taken for DNA extractions. DNA is extracted from roots, soil, and rhizosphere and then amplified with primers for the V4 region of the 16S rRNA gene. Amplicons are sequenced, then analyzed with open access bioinformatics tools. These methods allow researchers to test how the microbial community diversity and composition varies due to sample type, treatment, and plant genotype. Using these methods along with statistical models, the representative results demonstrate there are significant differences in microbial communities of roots, rhizosphere, and soil. Methods presented here provide a complete set of steps for how to collect field samples, isolate, extract, quantify, amplify, and sequence DNA, and analyze microbial community diversity and composition in replicated field trials.

Excavation of plant roots from the field as well as processing of samples into endosphere, rhizosphere, and soil are described in detail, including DNA extraction and data analysis methods. This paper is designed to enable other laboratories to use these techniques for the study of soil, endosphere, and rhizosphere microbiomes.

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The ...

Sampling Soils in a Heterogeneous Research Plot

Soils are highly heterogeneous. In general, the number of soil samples required for soil research has always been determined arbitrarily and the associated accuracy is unknown. Here, we present a detailed protocol for efficient and clustered soil sampling in a research plot and, relying on a pilot sampling using this design, for demonstrating soil spatial heterogeneity and informing reasonable sample sizes and associated accuracy for future study. The protocol mainly comprises four steps: sampling design, field collection, soil analysis, and geostatistical analysis. The step-by-step procedure is modified according to former publications. Two examples will be presented to demonstrate contrasting spatial distributions of soil organic carbon (SOC) and soil microbial biomass carbon (MBC) under different management practices. In addition, we present a strategy to determine the sample size requirement (SSR) given a certain level of accuracy based on the plot-level coefficient of variation (CV). The field sampling protocol and the quantitative determination of the sample size will assist researchers in seeking feasible sampling strategies to meet research needs and resources' availability.

The traditional soil-sampling procedure determines the number of soil samples arbitrarily. Here, we provide a simple yet efficient clustered soil-sampling design to demonstrate soil spatial heterogeneity and quantitatively determine the number of soil samples required and the associated sampling accuracy.

Soils are highly heterogeneous. In general, the number of soil samples required for soil research has always been determined arbitrarily and the ...

Investigation of Plant Interactions Across Common Mycorrhizal Networks Using Rotated Cores

Arbuscular mycorrhizal (AM) fungi influence plant mineral nutrient uptake and growth, hence, they have the potential to influence plant interactions. The power of their influence is in extraradical mycelia that spread beyond nutrient depletion zones found near roots to ultimately interconnect individuals within a common mycorrhizal network (CMN). Most experiments, however, have investigated the role of AM fungi in plant interactions by growing plants with versus without mycorrhizal fungi, a method that fails to explicitly address the role of CMNs. Here, we propose a method that manipulates CMNs to investigate their role in plant interactions. Our method uses modified containers with conical bottoms with a nylon mesh and/or hydrophobic material covering slotted openings, 15N fertilizer, and a nutrient-poor interstitial sand. CMNs are left either intact between interacting individuals, severed by rotation of containers, or prevented from forming by a solid barrier. Our findings suggest that rotating containers is sufficient to disrupt CMNs and prevent their effects on plant interactions across CMNs. Our approach is advantageous because it mimics aspects of nature, such as seedlings tapping into already established CMNs and the use of a suite of AM fungi that may provide diverse benefits. Although our experiment is limited to investigating plants at the seedling stage, plant interactions across CMNs can be detected using our approach which therefore can be applied to investigate biological questions about the functioning of CMNs in ecosystems.

Most plants within communities likely are interconnected by arbuscular mycorrhizal (AM) fungi, but mediation of plant interactions by them has been investigated primarily by growing plants with versus without mycorrhizas. We present a method to manipulate common mycorrhizal networks among mycorrhizal plants to investigate their consequences for plant interactions.

Arbuscular mycorrhizal (AM) fungi influence plant mineral nutrient uptake and growth, hence, they have the potential to influence plant interactions. The ...

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&ndash;Environment Interactions

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating a knowledge gap. To meet the challenge of improving crops to feed the growing global population, this gap must be bridged.
Physiological traits are considered key functional traits in the context of responsiveness or sensitivity to environmental conditions. Many recently introduced high-throughput (HTP) phenotyping techniques are based on remote sensing or imaging and are capable of directly measuring morphological traits, but measure physiological parameters mainly indirectly.
This paper describes a method for direct physiological phenotyping that has several advantages for the functional phenotyping of plant&#8211;environment interactions. It helps users overcome the many challenges encountered in the use of load-cell gravimetric systems and pot experiments. The suggested techniques will enable users to distinguish between soil weight, plant weight and soil water content, providing a method for the continuous and simultaneous measurement of dynamic soil, plant and atmosphere conditions, alongside the measurement of key physiological traits. This method allows researchers to closely mimic field stress scenarios while taking into consideration the environment&#8217;s effects on the plants&#8217; physiology. This method also minimizes pot effects, which are one of the major problems in pre-field phenotyping. It includes a feed-back fertigation system that enables a truly randomized experimental design at a field-like plant density. This system detects the soil-water-content limiting threshold (&#952;) and allows for the translation of data into knowledge through the use of a real-time analytic tool and an online statistical resource. This method for the rapid and direct measurement of the physiological responses of multiple plants to a dynamic environment has great potential for use in screening for beneficial traits associated with responses to abiotic stress, in the context of pre-field breeding and crop improvement.

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&#8211;Environment Interactions

This high-throughput, telemetric, whole-plant water relations gravimetric phenotyping method enables direct and simultaneous real-time measurements, as well as the analysis of multiple yield-related physiological traits involved in dynamic plant&#8211;environment interactions.

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating ...

Inoculation Strategies to Infect Plant Roots with Soil-Borne Microorganisms

The rhizosphere harbors a highly complex microbial community in which plant roots are constantly challenged. Roots are in close contact with a wide variety of microorganisms, but studies on soil-borne interactions are still behind those performed on aboveground organs. Although some inoculation strategies for infecting model plants with model root pathogens are described in the literature, it remains difficult to get a comprehensive methodological overview. To address this problem, three different root inoculation systems are precisely described that can be applied to gain insights into the biology of root-microbe interactions. For illustration, Verticillium species (namely, V. longisporum and V. dahliae) were employed as root invading model pathogens. However, the methods can be easily adapted to other root colonizing microbes - both pathogenic and beneficial. By colonizing the plant xylem, vascular soil-borne fungi such as Verticillium spp. exhibit a unique lifestyle. After root invasion, they spread via the xylem vessels acropetally, reach the shoot, and elicit disease symptoms. Three representative plant species were chosen as model hosts: Arabidopsis thaliana, economically important oilseed rape (Brassica napus), and tomato (Solanum lycopersicum). Step-by-step protocols are given. Representative results of pathogenicity assays, transcriptional analyses of marker genes, and independent confirmations by reporter constructs are shown. Furthermore, the advantages and disadvantages of each inoculation system are thoroughly discussed. These proven protocols can assist in providing approaches for research questions on root-microbe interactions. Knowing how plants cope with microbes in the soil is crucial for developing new strategies to improve agriculture.

This protocol presents a detailed summary of strategies to inoculate plant roots with soil-borne microbes. Exemplified for the fungi Verticillium longisporum and Verticillium dahliae, three different root infection systems are described. Potential applications and possible downstream analyses are highlighted, and advantages or disadvantages are discussed for each system.

The rhizosphere harbors a highly complex microbial community in which plant roots are constantly challenged. Roots are in close contact with a wide ...

Simulating Temperature in a Soil Incubation Experiment

The study of warming impact on soils requires a realistic and accurate representation of temperature. In laboratory incubation studies, a widely adopted method has been to render constant temperatures in multiple chambers, and via comparisons of soil responses between low- and high-temperature chambers, to derive the warming impact on soil changes. However, this commonly used method failed to imitate both the magnitude and amplitude of actual temperatures as observed in field conditions, thus potentially undermining the validity of such studies. With sophisticated environmental chambers becoming increasingly available, it is imperative to examine alternative methods of temperature control for soil incubation research. This protocol will introduce a state-of-the-art environmental chamber and demonstrate both conventional and new methods of temperature control to improve the experimental design of soil incubation. The protocol mainly comprises four steps: temperature monitoring and programming, soil collection, laboratory incubation, and warming effect comparison. One example will be presented to demonstrate different methods of temperature control and the resultant contrasting warming scenarios; that is, a constant temperature design referred to as stepwise warming (SW) and simulated in situ temperature design as gradual warming (GW), as well as their effects on soil respiration, microbial biomass, and extracellular enzyme activities. In addition, we present a strategy to diversify temperature change scenarios to meet specific climate change research needs (e.g., extreme heat). The temperature control protocol and the recommended well-tailored and diversified temperature change scenarios will assist researchers in establishing reliable and realistic soil incubation experiments in the laboratory.

Laboratory soil warming experiments usually employ two or more constant temperatures in multiple chambers. By presenting a sophisticated environmental chamber, we provide an accurate temperature control method to imitate the magnitude and amplitude of in situ soil temperature and improve the experimental design of soil incubation studies.

The study of warming impact on soils requires a realistic and accurate representation of temperature. In laboratory incubation studies, a widely adopted ...

JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning

The global loss of biodiversity has motivated many studies that experimentally vary plant species richness and examine the consequences for ecosystem functioning. Such experiments generally show a positive relationship between above- and below-ground biodiversity and the functioning of terrestrial ecosystems. Moreover, this relationship tends to strengthen over time, seen as enhanced functioning of diverse plant communities and reduced functioning of low-diversity plant communities. Differences in multitrophic community assembly and biotic interactions in high- versus low-diversity plant communities are hypothesized to affect plant performance by altering consumer community structure and function and driving plastic or micro-evolutionary responses of plant species in the plant communities. To resolve this complex interplay of community history, we separated these effects into plant and soil history. Plant history refers to all plant-level responses to past abiotic and biotic selection pressures experienced in their communities, while soil history relates to all abiotic and biotic soil properties developed as a legacy of plant-soil interactions under variable plant diversity. We set up a biodiversity experiment in an Ecotron, a terrestrial mesocosm facility that allows controlling environmental conditions above- and below-ground, to test whether the strengthening biodiversity-ecosystem functioning relationship is due to soil history, plant history, or a combination of both. We established a plant diversity gradient consisting of 1, 2, 3, and 6 grassland plant species and factorially nested with soil history and plant history treatments for each level of plant species richness. Representative results demonstrate the successful establishment of target treatments in the Ecotron experiment, observing the effects of plant and soil history on initial plant development and final plant growth. Additionally, we provide a case study for data analysis of individual response variables. We outline research objectives and methods to comprehensively assess the multifunctional responses to the experimental treatments necessary to ultimately address the overarching hypothesis.

Here we present a study established in the iDiv Ecotron, terrestrial mesocosm chambers with controlled environmental conditions above- and below-ground, to study the independent and interactive effects of plant history and soil history on ecosystem functioning of grassland communities along a plant diversity gradient.

The global loss of biodiversity has motivated many studies that experimentally vary plant species richness and examine the consequences for ecosystem ...

Enhancing CO2 Sequestration: A Soil Biota Approach to Boost Mineral Weathering

Design and Construction of an Experimental Setup to Enhance Mineral Weathering through the Activity of Soil Organisms

Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies on accelerating the natural process of mineral weathering in soils by manipulating the abiotic variables that govern this process, in particular mineral grain size and exposure to acids dissolved in water. EW mainly aims at reducing atmospheric CO2 concentrations by enhancing inorganic carbon sequestration. Until now, knowledge of EW has been mainly gained through experiments that focused on the abiotic variables known for stimulating mineral weathering, thereby neglecting the potential influence of biotic components. While bacteria, fungi, and earthworms are known to increase mineral weathering rates, the use of soil organisms in the context of EW remains underexplored. 
 This protocol describes the design and construction of an experimental setup developed to enhance mineral weathering rates through soil organisms while concurrently controlling abiotic conditions. The setup is designed to maximize weathering rates while maintaining soil organisms' activity. It consists of a large number of columns filled with rock powder and organic material, located in a climate chamber and with water applied via a downflow irrigation system. Columns are placed above a fridge containing jerrycans to collect the leachate. Representative results demonstrate that this setup is suitable to ensure the activity of soil organisms and quantify their effect on inorganic carbon sequestration. Challenges remain in minimizing leachate losses, ensuring homogeneous ventilation through the climate chamber, and avoiding flooding of the columns. With this setup, an innovative and promising approach is proposed to enhance mineral weathering rates through the activity of soil biota and disentangle the effect of biotic and abiotic factors as drivers of EW.

Author Spotlight: Unraveling the Role of Earthworms in Enhancing Mineral Weathering for CO2 Removal 

Here we present the construction and operation of an experimental setup to enhance mineral weathering through the activity of soil organisms while concurrently manipulating abiotic variables known to stimulate weathering. Representative results from the functioning of the setup and sample analyses are discussed together with points for improvement.

Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies ...