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 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.
Global surface temperature is expected to increase this century by 1.8-6.4 °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 °C/day vs. 3.3 °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 °C, with most between 5-25 °C; the duration of experiments ranged from a few hours (<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.
(Eq. 1)
Where ΔT 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.
1. Temperature monitoring and programming
2. Soil collection and homogenizing
3. Laboratory incubation
4. Warming effect comparison
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).
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. Please click here to view a larger version of this figure.
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. Please click here to view a larger version of this figure.
Figure 3: Mean (± SE) cumulative soil respiration rate (Rc, µg CO2-C·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, µg CO2-C·h-1·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. Please click here to view a larger version of this figure.
Figure 4: Mean (± SE) MBC under control and warming treatments in SW and GW in a 42-day soil incubation experiment. MBC = microbial biomass carbon; N = 4 in each collection. S denotes significant effect of warming scenario (SW vs. GW), at p < 0.05, based on a three-way repeated measures ANOVA. Please click here to view a larger version of this figure.
Figure 5: Mean (± SE) glycosidases and peroxidase (µmol activity h-1·gsoil-1) under control and warming treatments in SW and GW in a 42-day incubation experiment. BX =β1,4-xylosidase; AP = Acid Phosphatase; LAP = Leucine Aminopeptidase; NAG =β-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 < 0.05, based on a three-way repeated measures ANOVA. Please click here to view a larger version of this figure.
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. Please click here to download this Table.
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. Please click here to download this Table.
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. 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 °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.
The authors have nothing to disclose.
Funding sources used to support the research include a US National Science Foundation (NSF) HBCU−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−Allen Grant (No. 1017802). We thank assistance received from staff members at the TSU's Main Campus Agriculture Research and Extension Center (AREC) in Nashville, Tennessee.
10 mL-Syringe | Fisher Scientific | 14-826-13 | for soil respiration measurement |
Composer Software | TestEquity | Model #107 | for incubation temperature setup |
Environmental chamber | TestEquity | Model #107 | for soil incubation |
Environmental gas analyzer | PP Systems | EGM5 | for soil respiration measurement |
Filter paper | Fisher Scientific | 1005-125 | for soil incubation |
Mason jar | Ball | 15381-3 | for soil incubation |
Oven | Fisher Scientific | 15-103-0520 | for soil moisture measurement |
Plastic Zipper Seal Storage Bag | Fisher Scientific | 09-800-16 | for soil collection |
Plate reader | Molecular devices | FilterMax F5 | for soil extracellular enzyme analysis |
R Software | The R Foundation | R version 4.1.3 (2022-03-10) | For statistical computing |
Refrigerator/Freezer | Fisher Scientific | 13-991-898 | for soil storation |
Screwdriver | Fisher Scientific | 19-313-447 | for soil collection |
Sharpie | Fisher Scientific | 50-111-3135 | for soil collection |
Sieve | Fisher Scientific | 04-881G | for sieving soil sample |
Silicone Septa | Duran Wheaton kimble | 224100-070 | for mason jars used for soil incubation |
Soil auger | AMS | 350.05 | for soil collection |
SpecWare Software | Spectrum Technologies | WatchDog E2700 (3340WD2) | for temperature collection interval setup |
Temperature probe | Spectrum Technologies | WatchDog E2700 (3340WD2) | for soil temperature measurements |
TOC/TN analyzer | Shimadzu | TOC-L series | for soil microbial biomass analysis |