Funding sources used to support the research include a US National Science Foundation (NSF) HBCU&#8722;EiR (No. 1900885), a US Department of Agriculture (USDA) Agricultural Research Service (ARS) 1890s Faculty Research Sabbatical Program (No. 58-3098-9-005), a USDA NIFA grant (No. 2021-67020-34933), and a USDA Evans&#8722;Allen Grant (No. 1017802). We thank assistance received from staff members at the TSU&#39;s Main Campus Agriculture Research and Extension Center (AREC) in Nashville, Tennessee.

1. Temperature monitoring and programming
<ol>
	<li>Identify a sampling zone within a research plot. Install one or a few automatic temperature probes in soils at 10 cm depth. Connect the weather station to a computer via the data transmission cable and open the software on the computer.</li>
	<li>Click on the Launch/ Properties toolbar button to configure the logger for the external sensors being used.</li>
	<li>On the Properties screen, set the logger/station name (i.e., Soil incubation exp.) and the data collection interval (i.e., 60 min). Then, on the Properties screen, click Enabled on the external sensor ports being used and select the sensor/unit from the dropdown button for each sensor port (i.e., Port A; &#34;Enabled&#34;: Temperature &#730;C). Finally, click on OK to save the settings.</li>
	<li>Monitor the probes&#39; reading weekly to avoid malfunction and download the dataset once a month. Obtain a complete record for several months covering the growing season (i.e., April to September).</li>
	<li>Conduct data analysis of the temperature records. Obtain the mean hourly temperature of the growing season by averaging all observations.
	<ol>
		<li>Obtain the mean temperature of each hour on a daily basis by averaging temperatures of the same hour across all days during the growing season.</li>
	</ol>
	</li>
	<li>In the sophisticated chamber, launch the software and click on the Profile button on the main menu screen to create a new file. In the file name input line, enter &#34;SW low&#34;. By clicking on the Instant Change option, enter 15.9 &#176;C as an initial temperature as obtained in step 1.5, and enter 2 on the Minutes row to maintain the temperature for 2 min and click on the Done button. Then, under the Ramp Time option, enter 15.9 &#176;C as the target set point and on the Hours row enter 850 h to sustain the temperature. Fianlly, click on the Done button.
	<ol>
		<li>Repeat the above step in the second chamber by adding 5 &#176;C to each temperature node and create a new file name &#34;SW high&#34;.</li>
		<li>Repeat step 1.4 in the third chamber by adding 23 additional steps corresponding to 23 observed hourly soil temperatures as obtained in step 1.5.1. At the last step, called JUMP, set 42 repeated loops (Jump Count 42). This leads to the scenario of gradual warming or GW low.</li>
		<li>Repeat the above step in the fourth chamber with 5 &#176;C added to each temperature node. This will allow a simulation of varying temperatures for 42 days at a higher temperature level (i.e., GW high).</li>
	</ol>
	</li>
	<li>Conduct a preliminary run for 24 h and output the temperatures recorded by the four chambers. Plot the temperatures recorded by the chambers against those as programmed (Figure 2A-D).
	<ol>
		<li>If the temperatures achieved in the chamber match the temperatures as programmed by a temperature difference &#60;0.1 &#176;C during the 24 h (Figure 2A,B,E,F), the chambers are suitable for the soil incubation experiment.</li>
		<li>If the criteria were not satisfied in any of these chambers, repeat another 24 h test or seek a new chamber.</li>
	</ol>
	</li>
</ol>
2. Soil collection and homogenizing
<ol>
	<li>Near the temperature probe area, collect five soil samples at 0-20 cm depth and put them into one plastic bag after removing the surface litter layer.</li>
	<li>Mix the sample thoroughly by twisting, pressing, and mingling the materials in the bag until no individual soil sample is visible.</li>
	<li>Store the samples in a cooler filled with ice packs and transport the samples to the lab immediately.</li>
	<li>Remove the roots in each core, sieve it through a soil sieve of 2 mm, and thoroughly mix and homogenize the sample prior to the following analysis.</li>
</ol>
3. Laboratory incubation
<ol>
	<li>Prior to incubation, weigh 10.0 g of fresh soil, oven-dry it for 24 h at 105 &#176;C, and weigh the dry soil. Derive the difference between fresh and dry soil samples and calculate the ratio of difference over dry soil weight to determine the soil moisture content in a spreadsheet.</li>
	<li>Use the derived moisture content to calculate the soil microbial biomass carbon (MBC), extracellular enzyme activity (EEA), and soil heterotrophic respiration as described in the following steps. These data will help understand the treatment effects on soil respiration and the underlying microbial mechanisms.</li>
	<li>Prior to incubation, weigh the field moist soil subsample (10 g) and quantify the soil MBC by chloroform fumigation-K2SO4 extraction and potassium persulfate digestion methods18.</li>
	<li>Prior to incubation, weigh the subsample of field moist soil (1.0 g) and measure soil hydrolytic and oxidative EEA19.</li>
	<li>Weigh 16 field moist soil subsamples (15.0 g equivalent of dry weight) in 16 polyvinyl chloride (PVC) cores (5 cm diameter, 7.5 cm tall) sealed with glass fiber paper on the bottom.</li>
	<li>Place the PVC cores in Mason jars (~1 L) lined with a bed of glass beads to ensure that the cores do not absorb moisture.</li>
	<li>Place four jars in each of the four chambers as described in step 1.4. Turn on the chambers and launch the program simultaneously in four chambers.</li>
	<li>During the incubation, at 2 h, days 1, 2, 7, 14, 21, 28, 35, and 42, take all jars in each of four chambers and use a portable CO2 gas analyzer to measure soil respiration rate (Rs) by putting the analyzer&#39;s collar to the top of each jar.</li>
	<li>Destructively collect all jars at the end of incubation (i.e., day 42) and quantify soil MBC as described in step 3.3.</li>
	<li>Destructively collect all jars at the end of incubation (i.e., day 42) and quantify soil enzyme activity as described in step 3.4.</li>
</ol>
4. Warming effect comparison
<ol>
	<li>By assuming a constant respiration rate (Rs) between two consecutive collections, use the respiration rate times the duration to derive the cumulative respiration (Rc).</li>
	<li>Conduct a three-way repeated measures analysis of variance (ANOVA) to test the main and interactive effects of time, temperature (warming), and temperature mode (warming scenario) on Rs and Rc. In addition, conduct a two-way ANOVA to test warming and warming scenario effects on MBC and EEA.</li>
</ol>

The author has nothing to disclose.

The constant temperature control method has been applied widely (Table 1). However, the magnitude and temporal pattern of temperature implemented in these procedures poorly simulate soil temperature observed in the field condition. Despite the emerging efforts imitating the diurnal pattern in the past, such studies were scarce and failed to clarify the equipment and procedure; neither did they validate the temperature simulation regarding accuracy and reliability16,17. As the community strived to improve its understanding of soil warming responses, optimizing the soil incubation procedure with realistic temperature and feasible control is imperative. Nevertheless, such new methods have not been developed, and thus, a standard method for future incubation experiments is still out of reach. In the face of the increasing complexity of global temperature change in magnitude, amplitude, seasonality, duration, and extremality, a comprehensive procedure is in high demand.
Here, a method for manipulating a diurnal temperature change procedure was presented, relying upon the sophisticated chamber, to offer the capacity to establish constant, linear, and nonlinear temperature change and subsequently various warming scenarios for meeting future research needs. There are four critical steps within the protocol. The first is to determine soil temperature in the field condition. Because the soil type and depth of interest as well as the land use type can vary from one study to another, the number of temperature probes needed for the specific research site should be modified to best fit the actual conditions as much as possible.&#160;In general, soil depth for temperature probes shall meet the most research needs at 0-20 cm, and the number of probes to represent the soil temperature should be limited to one to three. The key is to achieve a long-term continuous and consecutive temperature record in at least one typical soil location.
The second critical step is to set up the program to achieve the targeted temperature magnitude and pattern in the chamber. Because of the high sensitivity and accuracy of chamber (Figure 4), it is feasible to program for an accurate representation of temperature as observed in the field condition. Although the current protocol only presented the observed hourly temperature as targeted in the chamber, a more frequent soil temperature monitoring, such as 30 min, 15 min, or even shorter, can be achieved through this procedure. Nevertheless, a test of the target and chamber temperatures must be conducted over 24 h, and prior to experiment, the test results must meet the criteria of less than 0.1 &#176;C between the target and chamber temperatures at all time points. The more frequent the temperature observation is selected to simulate, the more steps are needed to set up the program in the chamber prior to the experiment.
The third critical step is to conduct the incubation itself. To reduce the influence of soil heterogeneities63, homogenizing soil samples is key, and at least three replicates for each treatment are recommended. Prior to incubation, a pre-incubation treatment is required, and the current procedure can facilitate pre-treatment by programming the temperature and duration before the official start of the experiment. This is advantageous for one to reduce the experimental disturbance and orchestrate the entire incubation seamlessly. The last critical step is to include both constant temperature and varying temperature treatments so that a comparison can be made as to the soil warming responses.
This protocol can be easily modified to allow one to manipulate the magnitude, amplitude, and duration of temperature change. For example, extreme temperatures during a heat wave in summer and sudden frost in early spring due to climate change, can be represented using this procedure, in addition to its capacity to account for their varying duration and intensity. Simulating the regular and irregular temperatures in combination also allow one to simulate long-term complex temperature change effects as projected in the future. As summarized in Table 2, those warming scenarios that have been studied in many distinct studies can be accomplished collectively in one study. This protocol is expected to provide a sophisticated method to simulate temperature in soil incubation studies. With hope for a wide application, the adoption of this protocol will help identify or validate a more accurate method for future soil warming studies based on laboratory incubation.
An important limitation of the procedure is that the chamber used in the current protocol has a relatively small volume, thus is only able to accommodate nine incubation jars in each chamber. Though a smaller jar will increase the capacity of the chamber, a big volume of chamber is recommended. A new model (e.g., TestEquity 1007) will offer eight times more capacity and is thus recommended for large scale experiments. Despite the improvement of temperature control procedure in soil incubations, the potential complications with moisture and soil homogenization will not be relieved by adopting the current protocol.
We demonstrate significant advantages of the sophisticated temperature control procedure. It provides a reliable and affordable temperature control strategy to obtain accurate temperature simulation and offers a feasible way to improve soil incubation experiment required for a better understanding of soil warming responses. Although the constant temperature control is widely accepted and logistically easy to operate, the artifacts of long-term constant temperature on soil microbial communities may divert efforts to capture the genuine soil responses. The other reported laboratory warming methods are largely less controllable and replicable. The current protocol is superior due to its easy operation, high accuracy and replicability of temperature simulation, explicit programing, and capacity to combine various temperature change scenarios in a single experiment. The feasibility of temperature control with high accuracy will allow researchers to explore various temperature change scenarios.

Global surface temperature is expected to increase this century by 1.8-6.4 &#176;C1,2. Global warming may increase CO2 flux from soil to the atmosphere, resulting in positive feedback with warming3,4,5,6. Because microbial communities play a critical role in regulating soil respiratory responses to warming7,8, the changes in microbial respiration and the underlying microbial mechanisms with warming have been a research focus. Though soil warming experiments deployed in the field condition, via a heating cable9 and an open top chamber10, were advantageous in capturing natural soil features such as temperature11, their high cost for installation and maintenance have limited their application. Alternatively, soil incubation experiments subject to different temperatures are a favorable choice. The primary advantage of soil incubation in a laboratory is that the well-controlled environmental conditions (e.g., temperature) are able to disentangle the one-factor effect from other confounding factors in a field experimental setting12,13. Despite differences between growth chamber and field experiments (e.g., plant growth), translation from lab results to the field are readily available14. Incubating soil samples in a laboratory setting could help improve our mechanistic understanding of soil response to warming15.
Our literature review identified several temperature control methods and, consequently, distinct temperature change modes in past soil incubation studies (Table 1). First, instruments used to control temperature are mostly through an incubator, growth chamber, water bath, and in a rare case, heating cable. Given these instruments, three typical temperature change patterns have been generated (Figure 1). These include the most implemented mode, constant temperature (CT), linear change (LC) with a non-zero constant temperature change rate, and nonlinear change (NC) featured with a diurnal type of temperature. For a case of CT pattern, the temperature may vary in magnitude over time, though constant temperature remains for a certain time period during the incubation (Figure 1B). For LC, the rate of temperature change could vary in different studies at more than two orders of magnitude (e.g., 0.1 &#176;C/day vs. 3.3 &#176;C/h; Table 1); For NC cases, most relied upon the intrinsic capacity of instruments used, thus leading to various modes. Despite that a type of diurnal temperature change was claimed through a heating cable or incubator16,17; however, the chamber temperatures in these experiments were not validated. Other major review results in Table 1 include the range of incubation temperature of 0-40 &#176;C, with most between 5-25 &#176;C; the duration of experiments ranged from a few hours (&#60;1 day) to nearly 2 years (~725 days). Also, soils subjected to incubations were collected from forest, grassland, and cropland ecosystems, with dominant mineral horizon, organic horizon, and even contaminated soil, located mostly in the US, China, and Europe (Table 1).
Given the three major temperature change modes, several distinct warming scenarios achieved in the past studies were summarized in Table 2. They include stepwise warming (SW), SW with varying magnitude (SWv), gradual warming linearly (GWl), gradual warming nonlinearly (GWn), and gradual warming diurnally (GWd).
In summary, past soil incubations usually captured the average air or soil temperature in a site. In many cases, as shown in Table 1, incubators or chambers were manually programmed at a fixed temperature but incapable of automatically adjusting temperature as desired, lacking the ability to control the mode and rate of temperature change with time (Eq. 1), and thus leading to difficulty to imitate diurnal temperature of the local soil. On the other hand, though attempted in two experiments16,17, we identified no studies that explicitly imitated gradual warming diurnally (GWd) in their incubation experiments (Table 1). Based on the literature review, the major obstacle lies in poor experimental design, particularly lacking a sophisticated instrument that enables implementation and validation of diurnal or other gradual warming scenarios.
<img alt="Equation 1" src="/files/ftp_upload/64081/64081eq01.jpg" style="margin: auto;" />&#160; &#160;(Eq. 1)
Where &#916;T is the quantity of temperature change, m is the mode of temperature change, r is the rate of temperature change, and t is the duration of change.
To improve the experimental rigor in soil incubation, an accurate and sophisticated temperature control method is presented in this study. Adopting a state-of-the-art environmental chamber, increasingly available and economically viable, the new design shall not only enable the accurate simulation of in situ soil temperature (e.g., diurnal pattern) but also, by accounting for possible temperature change extremes, provide a reliable way to minimize the artefacts of instrumental bias. The current soil incubation design should assist researchers to identify optimal strategies that meet their incubation and research needs. The overall goal of this method is to present soil biogeochemists with a highly operational approach to reform soil incubation design.

<table><tbody><tr><td>10 mL-Syringe</td><td>Fisher Scientific</td><td>14-826-13</td><td>for soil respiration measurement</td></tr><tr><td>Composer Software</td><td>TestEquity</td><td>Model #107</td><td>for incubation temperature setup</td></tr><tr><td>Environmental chamber</td><td>TestEquity</td><td>Model #107</td><td>for soil incubation</td></tr><tr><td>Environmental gas analyzer</td><td>PP Systems</td><td>EGM5</td><td>for soil respiration measurement</td></tr><tr><td>Filter paper</td><td>Fisher Scientific</td><td>1005-125</td><td>for soil incubation</td></tr><tr><td>Mason jar</td><td>Ball</td><td>15381-3</td><td>for soil incubation</td></tr><tr><td>Oven</td><td>Fisher Scientific</td><td>15-103-0520</td><td>for soil moisture measurement</td></tr><tr><td>Plastic Zipper Seal Storage Bag</td><td>Fisher Scientific</td><td>09-800-16</td><td>for soil collection</td></tr><tr><td>Plate reader</td><td>Molecular devices</td><td>FilterMax F5</td><td>for soil extracellular enzyme analysis</td></tr><tr><td>R Software</td><td>The R Foundation</td><td>R version 4.1.3 (2022-03-10)</td><td>For statistical computing</td></tr><tr><td>Refrigerator/Freezer</td><td>Fisher Scientific</td><td>13-991-898</td><td>for soil storation</td></tr><tr><td>Screwdriver</td><td>Fisher Scientific</td><td>19-313-447</td><td>for soil collection</td></tr><tr><td>Sharpie</td><td>Fisher Scientific</td><td>50-111-3135</td><td>for soil collection</td></tr><tr><td>Sieve</td><td>Fisher Scientific</td><td>04-881G&amp;nbsp;</td><td>for sieving soil sample</td></tr><tr><td>Silicone Septa</td><td>Duran Wheaton kimble</td><td>224100-070</td><td>for mason jars used for soil incubation</td></tr><tr><td>Soil auger</td><td>AMS</td><td>350.05</td><td>for soil collection</td></tr><tr><td>SpecWare Software</td><td>Spectrum Technologies</td><td>WatchDog E2700 (3340WD2)</td><td>for temperature collection interval setup</td></tr><tr><td>Temperature probe</td><td>Spectrum Technologies</td><td>WatchDog E2700 (3340WD2)</td><td>for soil temperature measurements</td></tr><tr><td>TOC/TN analyzer</td><td>Shimadzu</td><td>TOC-L series</td><td>for soil microbial biomass analysis</td></tr></tbody></table>

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.

The selected state-of-the-art chambers replicated the target temperature with high precision (Figure 2A,B,E,F) and met the technical requirement of the incubation experiment. Given the easy use and operation, this signified the technique to improve the temperature simulation in soil warming studies and in other applications such as plant studies. The procedure has been employed in our recent case study based on a switchgrass cropland in Middle-Tennessee.
Research results showed that relative to control treatment, warming led to significantly greater respiratory losses (Rs and Rc) in both warming scenarios (SW and GW), and GW doubled the warming-induced respiratory loss (Rc) relative to SW, 81% vs. 40% (Figure 3). On day 42, MBC and EEA were also significantly different between SW and GW, such that MBC was higher in SW than in GW (69% vs. 38%; Figure 4) and glycosidases and peroxidase (e.g., AG, BG, BX, CBH, NAG, AP, LAP) were significantly higher in GW than in SW scenarios (Figure 5).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64081/64081fig01.jpg" /> 
Figure 1: The illustration of temperature change mode in a soil warming experiment as conceptualized from Table 1. (A) Constant temperature (CT) adopted by most studies. (B) Constant temperature with varying magnitude (CTv). (C,D) Linear change (LC) with positive and negative rates. (E,F) Nonlinear change (NC) with irregular pattern and diurnal pattern. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/64081fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64081/64081fig02.jpg" /> 
Figure 2: Temperature targeted via programming and chamber temperature during a 24-h testing period. (A,B) Target temperature (grey line) and chamber temperature records (dashed line) under control and warming treatments of stepwise warming (SW); (C,D) Target temperature (grey line) and chamber temperature records (dashed line) under control and warming treatments of gradual warming (GW); (E, F) The temperature difference derived for records in panels C and D. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/64081fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64081/64081fig03.jpg" /> 
Figure 3: Mean (&#177; SE) cumulative soil respiration rate (Rc, &#181;g CO2-C&#183;gsoil-1) under control (hollow) and warming (dark) treatments in SW and GW in a 42-day soil incubation experiment. The insets show soil respiration rates (Rs, &#181;g CO2-C&#183;h-1&#183;gsoil-1) applied to estimate cumulative respiration, assuming Rs was constant until the following measurement. (A) Stepwise warming (SW) and (B) gradual warming (GW). N = 4 in each collection. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/64081fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64081/64081fig04.jpg" /> 
Figure 4: Mean (&#177; SE) MBC under control and warming treatments in SW and GW in a 42-day soil incubation experiment. MBC = microbial biomass carbon;&#160;N = 4 in each collection. S denotes significant effect of warming scenario (SW vs. GW), at p &#60; 0.05, based on a three-way repeated measures ANOVA. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/64081fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64081/64081fig05.jpg" /> 
Figure 5: Mean (&#177; SE) glycosidases and peroxidase (&#181;mol activity h-1&#183;gsoil-1) under control and warming treatments in SW and GW in a 42-day incubation experiment. BX =&#946;1,4-xylosidase; AP = Acid Phosphatase; LAP = Leucine Aminopeptidase; NAG =&#946;-1,4-N-acetyl-glucosaminidase; OX = Oxidative enzymes; PHO = Phenol oxidase; PER = Peroxidase. N = 4 in each collection. S denotes significant effect of warming scenario (SW vs. GW), at p &#60; 0.05, based on a three-way repeated measures ANOVA. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/64081fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Table 1: Literature review of temperature control methods and temperature change modes in soil incubation studies12,13,16,17,20,21,22,23,24,25,26,27,28,29,30,31,32, 
33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51, 
52,53,54,55,56,57,58,59,60,61,62. 
In total, 46 studies were included in the review. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/Table1-64081R2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Major temperature change modes and the corresponding warming scenarios based on a literature review (Table 1). Five modes and scenarios were established to represent a wide range of possible temperature change and warming conditions. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64081/Table 2-64081R2.xlsx" target="_blank">Please click here to download this Table.</a>

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Simulating Temperature in a Soil Incubation Experiment

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 ...

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A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Construction of a Low-cost Mobile Incubator for Field and Laboratory Use

Incubators are essential for a range of culture-based microbial methods, such as membrane filtration followed by cultivation for assessing drinking water quality. However, commercially available incubators are often costly, difficult to transport, not flexible in terms of volume, and/or poorly adapted to local field conditions where access to electricity is unreliable. The purpose of this study was to develop an adaptable, low-cost and transportable incubator that can be constructed using readily available components. The electronic core of the incubator was first developed. These components were then tested under a range of ambient temperature conditions (3.5 &#176;C - 39 &#176;C) using three types of incubator shells (polystyrene foam box, hard cooler box, and cardboard box covered with a survival blanket). The electronic core showed comparable performance to a standard laboratory incubator in terms of the time required to reach the set temperature, inner temperature stability and spatial dispersion, power consumption, and microbial growth. The incubator set-ups were also effective at moderate and low ambient temperatures (between 3.5 &#176;C and 27 &#176;C), and at high temperatures (39 &#176;C) when the incubator set temperature was higher. This incubator prototype is low-cost (&lt; 300 USD) and adaptable to a variety of materials and volumes. Its demountable structure makes it easy to transport. It can be used in both established laboratories with grid power or in remote settings powered by solar energy or a car battery. It is particularly useful as an equipment option for field laboratories in areas with limited access to resources for water quality monitoring.

This paper describes a method for building an adaptable, low-cost and transportable incubator for microbial testing of drinking water. Our design is based on widely available materials and can operate under a range of field conditions, while still offering the advantages of higher-end laboratory-based models.

Incubators are essential for a range of culture-based microbial methods, such as membrane filtration followed by cultivation for assessing drinking water ...

Manufacturing Simple and Inexpensive Soil Surface Temperature and Gravimetric Water Content Sensors

Quantifying temperature and moisture at the soil surface is essential for understanding how soil surface biota respond to changes in the environment. However, at the soil surface these variables are highly dynamic and standard sensors do not explicitly measure temperature or moisture in the upper few millimeters of the soil profile. This paper describes methods for manufacturing simple, inexpensive sensors that simultaneously measure the temperature and moisture of the upper 5 mm of the soil surface. In addition to sensor construction, steps for quality control, as well as for calibration for various substrates, are explained. The sensors incorporate a Type E thermocouple to measure temperature and assess soil moisture by measuring the resistance between two gold-plated metal probes at the end of the sensor at a depth of 5 mm. The methods presented here can be altered to customize probes for different depths or substrates. These sensors have been effective in a variety of environments and have endured months of heavy rains in tropical forests as well as intense solar radiation in deserts of the southwestern U.S. Results demonstrate the effectiveness of these sensors for evaluating warming, drying, and freezing of the soil surface in a global change experiment.

Accurately measuring temperature and water content of the upper 5 mm of the soil surface can improve our understanding of environmental controls on biological, chemical, and physical processes. Here we describe a protocol for manufacturing, calibrating, and conducting measurements with soil surface temperature and moisture sensors.

Quantifying temperature and moisture at the soil surface is essential for understanding how soil surface biota respond to changes in the environment. ...

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 ...

Simulation of Early Earth Hydrothermal Chimneys in a Thermal Gradient Environment

Deep sea hydrothermal vents are self-organizing precipitates generated from geochemical disequilibria and have been proposed as a possible setting for the emergence of life. The growth of hydrothermal chimneys in a thermal gradient environment within an early Earth vent system was successfully simulated by using different hydrothermal simulants, such as sodium sulfide, which were injected into an early Earth ocean simulant containing dissolved ferrous iron. Moreover, an apparatus was developed to sufficiently cool the ocean simulant to near 0 &#176;C in a condenser vessel immersed in a cold water bath while injecting a sulfide solution at hot to room temperatures, effectively creating an artificial chimney structure in a temperature gradient environment over a period of a few hours. Such experiments with different chemistries and variable temperature&#160;gradients resulted in a variety of morphologies in the chimney structure. The use of ocean and hydrothermal fluid simulants at room temperature resulted in vertical chimneys, whereas the combination of a hot hydrothermal fluid and cold ocean simulant inhibited the formation of robust chimney structures. The customizable 3D printed condenser created for this study acts as a jacketed reaction vessel that can be easily modified and used by different researchers. It will allow the careful control of injection rate and chemical composition of vent and ocean simulants, which should help accurately simulate prebiotic reactions in chimney systems with thermal gradients similar to those of natural systems.

The goal of this protocol is to form simulated hydrothermal chimneys via chemical garden injection experiments and introduce a thermal gradient across the inorganic precipitate membrane, using a 3D printable condenser that can be reproduced for educational purposes.

Deep sea hydrothermal vents are self-organizing precipitates generated from geochemical disequilibria and have been proposed as a possible setting for the ...

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 ...

Biochemistry

Identification of Novel Regulators of Plant Transpiration by Large-Scale Thermal Imaging Screening in Helianthus Annuus

Plant adaptation to biotic and abiotic stresses is governed by a variety of factors, among which the regulation of stomatal aperture in response to water deficit or pathogens plays a crucial role. Identifying small molecules that regulate stomatal movement can therefore contribute to understanding the physiological basis by which plants adapt to their environment. Large-scale screening approaches that have been used to identify regulators of stomatal movement have potential limitations: some rely heavily on the abscisic acid (ABA) hormone signaling pathway, therefore excluding ABA-independent mechanisms, while others rely on the observation of indirect, long-term physiological effects such as plant growth and development. The screening method presented here allows the large-scale treatment of plants with a library of chemicals coupled with a direct quantification of their transpiration by thermal imaging. Since evaporation of water through transpiration results in leaf surface cooling, thermal imaging provides a non-invasive approach to investigate changes in stomatal conductance over time. In this protocol, Helianthus annuus seedlings are grown hydroponically and then treated by root feeding, in which the primary root is cut and dipped into the chemical being tested. Thermal imaging followed by statistical analysis of cotyledonary temperature changes over time allows for the identification of bioactive molecules modulating stomatal aperture. Our proof-of-concept experiments demonstrate that a chemical can be carried from the cut root to the cotyledon of the sunflower seedling within 10 minutes. In addition, when plants are treated with ABA as a positive control, an increase in leaf surface temperature can be detected within minutes. Our method thus allows the efficient and rapid identification of novel molecules regulating stomatal aperture.

Identification of Novel Regulators of Plant Transpiration by Large-Scale Thermal Imaging Screening in Helianthus Annuus

We provide a method for identifying modulators of foliar transpiration by large-scale screening of a compound library.

Plant adaptation to biotic and abiotic stresses is governed by a variety of factors, among which the regulation of stomatal aperture in response to water ...

Simulating Temperature in a Soil Incubation Experiment

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