Temperature Dependence Of Soil Respiration Research Articles

Beyond a deterministic representation of the temperature dependence of soil respiration

Soil CO2 efflux represents a complex interplay of biological and physical processes that result in the production and transfer of CO2 from soils to the atmosphere. Temperature has been widely recognized as a critical factor regulating soil CO2 efflux and is commonly utilized in deterministic empirical models to predict this important flux for the carbon cycle. This study introduces the Bernstein copula-based cosimulation (BCC) as a data-driven probabilistic approach to model the temperature-soil CO2 efflux relationship. The BCC accounts for the joint probability distribution and temporal dependence of soil CO2 efflux, which are often overlooked in deterministic models. The BCC was implemented as a proof of concept using two years of data on soil CO2 efflux conditioned by soil temperature in a temperate forest. The BBC accurately reproduced the original probability distribution, temporal dependency, and temperature-soil CO2 efflux relationship. Our findings show that a deterministic method, such as the commonly employed exponential relationship between soil CO2 efflux and temperature, is limited for comprehensively capturing the intricate nature of the temperature-soil CO2 efflux relationship. This is due to the confounding and interacting effects of environmental drivers beyond temperature, which are not fully accounted for in such a deterministic approach. Furthermore, the BCC revealed that the probability density between the joint cumulative probability of temperature and soil CO2 efflux is not constant, which raises the concern that deterministic approaches introduce incorrect assumptions for estimating temperature-soil CO2 relationship. In conclusion, we propose that probabilistic approaches hold promise for effectively depicting dependency relationships for soil CO2 efflux modeling, and for improving predictions of the effects of weather variability and climate change.

Responses of aboveground litterfall respiration to unexpected snowfall events in Ailao subtropical forests in Southwest China

Soil respiration, the second largest CO2 flux in terrestrial ecosystems, involves the microbial respiration of litter from aboveground sources, belowground litter and root respiration, from rhizodeposition. In the subtropical forests of the Ailao Mountain, a chamber with automated CO2 efflux was set up with two treatments: a control treatment with litterfall to measure the total soil respiration (RT) and a litter removal treatment to measure aboveground litterfall respiration (RL). This study aimed to examine the responses of RL to unexpected heavy snowfall events and soil temperature (ST), soil moisture (SM), rainfall (RF), total litterfall (TL), litter water content (LWC), nitrate nitrogen (NO3−-N), and ammonium nitrogen (NH4+-N). The period of the study was divided into two: before the heavy snowfall event (BS) and during and after the heavy snowfall event (AS). The rate of RL was slightly decreased in AS (1.18 ± 0.03 μmol CO2 m−2 s−1) compared with that in BS (1.19 ± 0.02 μmol CO2 m−2 s−1). The relationships between RL and ST, SM, RF, and LWC, respectively, were all statistically significant (p < 0.05) in both periods. However, the relationships between RL and TL and NH4+-N, respectively, were not statistically significant for either period. The relationship between RL and NO3−-N was statistically significant for AS but not for BS. The relationship between RL and RF was statistically significant from 2011 to 2018. The temperature dependence of soil respiration was higher in BS than in AS, and the effect of litter removal was 2.55 % and 2.32 % for AS and BS respectively. The results indicate that current global terrestrial models underestimate RL trends for the feedback of global climate change in subtropical forests.

Separating the temperature response of soil respiration derived from soil organic matter and added labile carbon compounds

Broadly, soil organic C can be characterised as either labile (highly available and soluble) or stable (physiochemically protected) carbon. Previous studies have attributed differences in the temperature response of these C pools to overall availability or chemical complexity. Here, we estimated the decomposition of the labile pool as the difference of CO2 from soils with added highly available C substrates (arginine, glucose, glutamine, lysine, and maltose) and yeast extract, and CO2 from soil without added C. We also measured the temperature response of the decomposition of soil organic matter (SOM), which encompasses both labile and stable C (no added C). Soil was incubated for five hours using a temperature gradient block consisting of 18 discrete temperatures (~8–52 °C). We also tested to see if temperature responses differed between three contrasting soils (allophanic, gley, and organic/degraded peat). We applied macromolecular rate theory (MMRT) to the RS data to calculate the temperature optimum (Topt) and the inflection temperature (Tinf).The decomposition of SOM had an exponential, Arrhenius-like behaviour. In contrast, respiration of the five labile C compounds had a clear and similar Topt of around 37 °C and Tinf of 22 °C. The temperature response of the more labile C and of the SOM pools did not significantly vary between the three very different soils, suggesting that these responses might be independent of soil properties.Our findings provide support for the hypothesis that the overall temperature dependence of soil respiration is reliant on sorption/desorption and diffusion to microbes – a process that exhibits Arrhenius behaviour, and the biological decomposition of C by these soil microbes that exhibits MMRT behaviour. The overall response to temperature is governed by substrate availability as biological processes dominate when substrate is non-limiting, and physiochemical processes dominate when substrate availability is limiting.

Rapid laboratory measurement of the temperature dependence of soil respiration and application to changes in three diverse soils through the year

Determining the temperature dependence of soil respiration is needed to test predictive models such as Arrhenius-like functions and macro-molecular rate theory (MMRT). We tested a method for rapid measurement of respiration using a temperature gradient block, cooled at one end (~2 °C) and heated at the other (~50 °C) that accommodated 44 tubes containing soil incubated at roughly 1 °C increments. Gas samples were taken after 5 h incubation and analysed for CO2. The temperature gradient block allowed rapid assessment of temperature dependence of soil respiration with the precision needed to test models and explore existing theories of how temperature and moisture interact to control biochemical processes. Temperature response curves were well fitted by MMRT and allowed calculation of the temperature at which absolute temperature sensitivity was maximal (Tinf). We measured temperature response of three soils at seven moisture contents and showed that the absolute rate and sensitivity of respiration was partly dependent on adjusted moisture content. This result implied that comparisons between soils need to be made at a common moisture content. We also measured potential changes in the temperature dependence (and sensitivity) of respiration for three different soils collected at one site throughout a year. Tinf ranged from 43 to 51 °C for the three soils. Tinf and temperature sensitivity were not dependent on soil type collected but was partly dependent on time of year of collection. Temporal changes in temperature response suggested that the microbial communities may tune their metabolisms in response to changes in soil temperatures.

Temperature Dependence of Soil Respiration Modulated by Thresholds in Soil Water Availability Across European Shrubland Ecosystems

Soil respiration (SR) is a major component of the global carbon cycle and plays a fundamental role in ecosystem feedback to climate change. Empirical modelling is an essential tool for predicting ecosystem responses to environmental change, and also provides important data for calibrating and corroborating process-based models. In this study, we evaluated the performance of three empirical temperature–SR response functions (exponential, Lloyd–Taylor and Gaussian) at seven shrublands located within three climatic regions (Atlantic, Mediterranean and Continental) across Europe. We investigated the performance of SR models by including the interaction between soil moisture and soil temperature. We found that the best fit for the temperature functions depended on the site-specific climatic conditions. Including soil moisture, we identified thresholds in the three different response functions that improved the model fit in all cases. The direct soil moisture effect on SR, however, was weak at the annual time scale. We conclude that the exponential soil temperature function may only be a good predictor for SR in a narrow temperature range, and that extrapolating predictions for future climate based on this function should be treated with caution as modelled outputs may underestimate SR. The addition of soil moisture thresholds improved the model fit at all sites, but had a far greater ecological significance in the wet Atlantic shrubland where a fundamental change in the soil CO2 efflux would likely have an impact on the whole carbon budget.

Soil respiration and carbon loss relationship with temperature and land use conversion in freeze–thaw agricultural area

Soil respiration (Rs) was hypothesized to have a special response pattern to soil temperature and land use conversion in the freeze–thaw area. The Rs differences of eight types of land use conversions during agricultural development were observed and the impacts of Rs on soil organic carbon (SOC) loss were assessed. The land use conversions during last three decades were categorized into eight types, and the 141 SOC sampling sites were grouped by conversion type. The typical soil sampling sites were subsequently selected for monitoring of soil temperature and Rs of each land use conversion types. The Rs correlations with temperature at difference depths and different conversion types were identified with statistical analysis. The empirical mean error model and the biophysical theoretical model with Arrhenius equation about the Rs sensitivity to temperature were both analyzed and shared the similar patterns. The temperature dependence of soil respiration (Q10) analysis further demonstrated that the averaged value of eight types of land use in this freeze–thaw agricultural area ranged from 1.15 to 1.73, which was lower than the other cold areas. The temperature dependence analysis demonstrated that the Rs in the top layer of natural land covers was more sensitive to temperature and experienced a large vertical difference. The natural land covers exhibited smaller Rs and the farmlands had the bigger value due to tillage practices. The positive relationships between SOC loss and Rs were identified, which demonstrated that Rs was the key chain for SOC loss during land use conversion. The spatial–vertical distributions of SOC concentration with the 1.5-km grid sampling showed that the more SOC loss in the farmland, which was coincided with the higher Rs in farmlands. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze–thaw agricultural area. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze–thaw agricultural area.

Soil respiration after tillage under different fertiliser treatments – implications for modelling and balancing

Temperature-driven models of soil respiration (SR) are crucial for estimating C-balances of arable soils. However, model construction may be severely influenced by tillage operations. The impact of tillage on the temperature dependence of SR was studied to reveal the temporal patterns of model quality of temperature-driven SR-models. To obtain SR, CO2 fluxes were measured with a dynamic chamber technique in treatments of an energy crop rotation amended with biogas residues (BR) and mineral fertiliser (MF). Measurements were performed with short intervals during the first three days after tillage operations, then with extending intervals between measurements up to 35 days after tillage. Additionally, soil concentrations of hot-water extractable organic carbon (HWC) were determined before and during the experiment. Overall, in all treatments individual CO2 fluxes were affected by the extent of soil disturbance and fertiliser treatment. The highest tillage-induced fluxes where observed after disking in MF treatment. Tillage also induced an immediate increase of HWC, indicating additional labile C and a fast response of microbial activity. However, the change of HWC lasted only one day and approximated the pre-tillage values within a week. Even though BR soil had a higher HWC content, the increased C mineralisation in one repetition of MF suggests that buried plant residues might have a higher influence on SR after tillage than the type of fertiliser. Directly after soil disturbance by tillage it was impossible to construct temperature-driven models for SR in all treatments. Assuming that the coefficient of determination is appropriate with R2≥0.5 and the model quality is good with NRMSE≤0.15, the qualities of the models increased continuously with time, but were unsatisfying for at least two weeks. During this time, SR showed a high sensitivity to changing environmental influences like precipitation and soil moisture or available C for microbial turnover, rather than temperature. The treatment BR showed a less sensitive pattern, which might be attributed to an altered soil structure and microbial activity of soil after long-term application of an organic fertiliser like BR. Therefore, temperature-driven models for the prediction of soil derived CO2 emissions should be applied carefully for the days and weeks after tillage and verification by measurements in shorter intervals is advisable.

Does soil moisture overrule temperature dependence of soil respiration in Mediterranean riparian forests?

Abstract. Soil respiration (SR) is a major component of ecosystems' carbon cycles and represents the second largest CO2 flux in the terrestrial biosphere. Soil temperature is considered to be the primary abiotic control on SR, whereas soil moisture is the secondary control factor. However, soil moisture can become the dominant control on SR in very wet or dry conditions. Determining the trigger that makes soil moisture as the primary control factor of SR will provide a deeper understanding on how SR changes under the projected future increase in droughts. Specific objectives of this study were (1) to investigate the seasonal variations and the relationship between SR and both soil temperature and moisture in a Mediterranean riparian forest along a groundwater level gradient; (2) to determine soil moisture thresholds at which SR is controlled by soil moisture rather than by temperature; (3) to compare SR responses under different tree species present in a Mediterranean riparian forest (Alnus glutinosa, Populus nigra and Fraxinus excelsior). Results showed that the heterotrophic soil respiration rate, groundwater level and 30 cm integral soil moisture (SM30) decreased significantly from the riverside moving uphill and showed a pronounced seasonality. SR rates showed significant differences between tree species, with higher SR for P. nigra and lower SR for A. glutinosa. The lower threshold of soil moisture was 20 and 17% for heterotrophic and total SR, respectively. Daily mean SR rate was positively correlated with soil temperature when soil moisture exceeded the threshold, with Q10 values ranging from 1.19 to 2.14; nevertheless, SR became decoupled from soil temperature when soil moisture dropped below these thresholds.

On the ‘temperature sensitivity’ of soil respiration: Can we use the immeasurable to predict the unknown?

The temperature dependence of soil respiration (RS) is widely used as a key characteristic of soils or organic matter fractions within soils, and in the context of global climatic change is often applied to infer likely responses of RS to warmer future conditions. However, the way in which these temperature dependencies are calculated, interpreted and implemented in ecosystem models requires careful consideration of possible artefacts and assumptions. We argue that more conceptual clarity in the reported relationships is needed to obtain meaningful meta-analyses and better constrained parameters informing ecosystem models. Our critical assessment of common methodologies shows that it is impossible to measure actual temperature response of RS, and that a range of confounding effects creates the observed apparent temperature relations reported in the literature. Thus, any measureable temperature response function will likely fail to predict effects of climate change on Rs. For improving our understanding of RS in changing environments we need a better integration of the relationships between substrate supply and the soil biota, and of their long-term responses to changes in abiotic soil conditions. This is best achieved by experiments combining isotopic techniques and ecosystem manipulations, which allow a disentangling of abiotic and biotic factors underlying the temperature response of soil CO2 efflux.

Spatial and temporal patterns of soil respiration over the Japanese Archipelago: a model intercomparison study

We used terrestrial ecosystem models to estimate spatial and temporal variability in and uncertainty of estimated soil carbon dioxide (CO2) efflux, or soil respiration, over the Japanese Archipelago. We compared five carbon-cycle models to assess inter-model variability: Biome-BGC, CASA, LPJ, SEIB, and VISIT. These models differ in approaches to soil carbon dynamics, root respiration estimation, and relationships between decomposition and environmental factors. We simulated the carbon budget of natural ecosystems over the archipelago for 2001–2006 at 1-day time steps and 2-min (latitude and longitude) spatial resolution. The models were calibrated using measured flux data to accurately represent net ecosystem CO2 exchange. Each model successfully reproduced seasonal changes and latitudinal gradients in soil respiration. The five-model average of estimated total soil respiration of Japanese ecosystems was 295 Tg C year−1, with individual model estimates ranging from 210 to 396 Tg C year−1 (1 Tg = 1012 g). The differences between modeled estimates were more evident in summer and in warmer years, implying that they were mainly attributable to differences in modeling the temperature dependence of soil respiration. There was a large discrepancy between models in the estimated contribution of roots to total soil respiration, ranging from 3.9 to 48.4%. Although model calibration reduced the uncertainty of flux estimates, substantial uncertainties still remained in estimates of underground processes from these terrestrial carbon-cycle models.

Carbon dioxide in soil profiles: Production and temperature dependence

The temperature dependance of soil respiration has most commonly been addressed using surface flux data, despite the fact that surface flux measurements implicate CO2 transport and storage effects that may preclude robust assessments of the temperature dependence of soil respiration. Here we examine whether soil respiration might be assessed using soil profile CO2 production inferred from soil CO2 concentration profiles. Over the 9‐month study period, we observed marked similarities in the temperature response of CO2 production across four study sites of contrasting vegetation cover and land use.

反応速度論を用いた土壌呼吸速度のモデル化

Experiments of soil respiration are made using a soil sample mixed with a proper amount of compost in laboratory scale, Considering CO2 generation and diffusion processes, it is explained that the rate of soil respiration does not depend on the oxygen concentration in the soil because the size of moist compost particles is as small as 44μm on average. It means that the rate of soil respiration does not depend on the depth from the surface but depends on time only. Based on the above idea, an analytical solution of the unsteady diffusion equation is obtained and a method for estimating the rate of soil respiration by applying the experimental results of CO2 concentration in the soil is discussed. Following a manner of chemical kinetics, it is found out that the rate of soil respiration is proportional to the mass of compost introduced and the Q10 value representing the temperature dependence of soil respiration is about 2.5 on average, which is smaller than the value 3.0 obtained by Monteith et al.The theory of estimation of soil respiration and the procedure to make up an experimental equation proposed here will be useful to get the basic information before investigating the prevention of snow mold.

On the Temperature Dependence of Soil Respiration

From previously published measurements of soil respiration rate (R) and temperature (T) the goodness of fit of various R vs T relationships was evaluated. Exponential (Q 10 ) and conventional Arrhenius relationships between T and R cannot provide an unbiased estimate of respiration rate. Nor is a simple linear relationship appropriate. The relationship between R and T can, however, be accurately represented by an Arrhenius type equation where the effective activation energy for respiration varies inversely with temperature. An empirical equation is presented which yields an unbiased estimator of respiration rates over a wide range of temperatures. When combined with seasonal estimates of Gross Primary Productivity (GPP) the empirical relationship derived provides representative estimates of the seasonal cycle of net ecosystem productivity and its effects on atmospheric CO 2 (...)