The carbon-quality temperature hypothesis: Fact or artefact?

Climate warming can reduce global soil carbon stocks by enhancing microbial decomposition. However, the magnitude of this loss remains uncertain because the temperature sensitivity of the decomposition of the major fraction of soil carbon, namely resistant carbon, is not fully known. It is now believed that the resistance of soil carbon mostly depends on microbial accessibility of soil carbon with physical protection being the primary control of the decomposition of protected carbon, which is insensitive to temperature changes. However, it is still unclear whether the temperature sensitivity of the decomposition of unprotected carbon, for example, carbon that is not protected by the soil mineral matrix, may depend on the chemical recalcitrance of carbon compounds. In particular, the carbon-quality temperature (CQT) hypothesis asserts that recalcitrant low-quality carbon is more temperature-sensitive to decomposition than labile high-quality carbon. If the hypothesis is correct, climate warming could amplify the loss of unprotected, but chemically recalcitrant, carbon and the resultant CO2 release from soils to the atmosphere. Previous research has supported this hypothesis based on reported negative relationships between temperature sensitivity and carbon quality, defined as the decomposition rate at a reference temperature. Here we show that negative relationships can arise simply from the arbitrary choice of reference temperature, inherently invalidating those tests. To avoid this artefact, we defined the carbon quality of different compounds as their uncatalysed reaction rates in the absence of enzymes. Taking the uncatalysed rate as the carbon quality index, we found that the CQT hypothesis is not supported for enzyme-catalysed reactions, which showed no relationship between carbon quality and temperature sensitivity. The lack of correlation in enzyme-catalysed reactions implies similar temperature sensitivity for microbial decomposition of soil carbon, regardless of its quality, thereby allaying concerns of acceleration of warming-induced decomposition of recalcitrant carbon.

Could patterns of animal behaviour cause the observed differences in soil carbon between adjacent irrigated and unirrigated pastures?

Previous soil sampling from grazed pastures in New Zealand compared the changes of soil organic carbon (SOC) in adjacent irrigated and unirrigated portions of the same paddocks. It showed that irrigated portions had lower SOC stocks than unirrigated portions, with an average difference of 7.0 tC ha-1 or 0.6 tC ha-1 yr-1. These findings have formed the basis of an assessment for the net effect of conversion of New Zealand's grazed pastures to irrigation. However, since cattle could move freely between irrigated and unirrigated portions of the studied paddocks, there could have been different grazing intensities and/or excreta transfer between the irrigated and unirrigated portions of the same paddocks. Both these factors could have affected SOC stocks. In this study, we used the process-based model, CenW, to simulate the consequences of this possible carbon transfer via animal excreta and different grazing intensities. We found that the observed increase of 0.6 tC ha-1 yr-1 in SOC stock in the unirrigated portions could result from a transfer of 20% excreta from the irrigated to unirrigated portions (with an area ratio of 6:1) of a paddock and with the unirrigated portions being grazed only lightly with 2.0 tDM ha-1 in foliage biomass residuals remaining after grazing. That means that the observed higher SOC stocks in the unirrigated portions could potentially be attributable to the behaviour of grazing animals. We suggest that a realistic extent of carbon transfer and/or differences in grazing intensities could be sufficient to account for the observed differences in SOC stocks even if irrigation per se caused no differences in carbon stocks. It is therefore inappropriate to ascribe the change of SOC to irrigation effects based on experimental findings where SOC changes can be affected by the behaviour of grazing animals.

Global Research Alliance N2 O chamber methodology guidelines: Summary of modeling approaches.

Measurements of nitrous oxide (N2 O) emissions from agriculture are essential for understanding the complex soil-crop-climate processes, but there are practical and economic limits to the spatial and temporal extent over which measurements can be made. Therefore, N2 O models have an important role to play. As models are comparatively cheap to run, they can be used to extrapolate field measurements to regional or national scales, to simulate emissions over long time periods, or to run scenarios to compare mitigation practices. Process-based models can also be used as an aid to understanding the underlying processes, as they can simulate feedbacks and interactions that can be difficult to distinguish in the field. However, when applying models, it is important to understand the conceptual process differences in models, how conceptual understanding changed over time in various models, and the model requirements and limitations to ensure that the model is well suited to the purpose of the investigation and the type of system being simulated. The aim of this paper is to give the reader a high-level overview of some of the important issues that should be considered when modeling. This includes conceptual understanding of widely used models, common modeling techniques such as calibration and validation, assessing model fit, sensitivity analysis, and uncertainty assessment. We also review examples of N2 O modeling for different purposes and describe three commonly used process-based N2 O models (APSIM, DayCent, and DNDC).

Combining eddy covariance measurements with process-based modelling to enhance understanding of carbon exchange rates of dairy pastures.

Many temperate grasslands are used for dairying, and ongoing research aims to better understand these systems in order to increase animal production and soil organic carbon (SOC) stocks. However, it is difficult to fully understand management effects on SOC because most changes are slow and difficult to distinguish from natural variability, even if changes are important over years to decades. Eddy covariance (EC) measurements can overcome this problem by continuously measuring net carbon exchange from pastures, but net balances are very sensitive to even small systematic measurement errors. Combining EC measurements with detailed process-based modelling can reduce the risks inherent in total reliance on EC measurements. Modelling can also reveal information about the underlying processes that drive observed fluxes. Here, we describe carbon exchange patterns of five paddocks situated at four different locations in New Zealand and France where EC data and detailed physiological modelling were available. The work showed that respiration by grazing animals was often only incompletely captured in EC measurements. This was most problematic when fluxes were based on gap-filling, which could have estimated incorrect fluxes during grazing periods based on observations from periods without grazing. We then aimed to extract plant physiological insights from these studies. We found appreciable carbon uptake rates even at temperatures below 0 °C. After grazing, carbon uptake was reduced for up to 2 weeks. This reduction was larger than expected from reduced leaf area after grazing, but the factors contributing to that difference have not yet been identified. Detailed physiological models can also extrapolate findings to new management regimes, environmental conditions or plant attributes. This overcomes the limitation of experimental studies, which are necessarily restricted to actual site and weather conditions allowing models to make further progress on predicting management effects on SOC.

Modelling the effects of pasture renewal on the carbon balance of grazed pastures.

In New Zealand, pasture renewal is a routine management method for maintaining pasture productivity. However, knowledge of the renewal effects on soil organic carbon (SOC) stocks is still limited. Here we use a process-based model, CenW, to comprehensively assess the effects of pasture renewal on the carbon balance of a temperate pasture in the Waikato region of New Zealand. We investigated the effects of renewal frequency, length of fallow period, renewal timing, and the importance and quantification of age-related reductions in productivity. Our results suggest that SOC change depends on the combined effects of renewal on gross primary productivity (GPP), autotrophic and heterotrophic respiration, carbon removal by grazing and carbon allocation to roots. Pasture renewal reduces grazing removal proportionately more than GPP because newly established plants need to allocate more carbon to re-build their root system following renewal which limits foliage production. That lengthens the time before above-ground biomass has grown sufficiently to be grazed again. New plants have a lower ratio of autotrophic respiration to GPP, however, which partly compensates for the GPP loss during renewal. Our simulations suggested an average SOC loss of 0.16 tC ha-1 yr-1 if pastures were renewed every 25 years, but could gain an average of 0.3 tC ha-1 yr-1 if pastures were renewed every year. For maximizing pasture production, the optimal renewal frequency depends on the rate of pasture deterioration with more rapid deterioration rates favouring more frequent renewal. Additionally, the length of the fallow period, renewal timing, and associated environmental conditions are important factors that can affect SOC temporally, but the importance of those effects diminishes at the annual or longer time scales. A major uncertainty for a full understanding of the renewal effect on SOC lies in the rate of pasture deterioration with time since previous renewal.

Short-Term Temperature Response of Leaf Respiration in Different Subtropical Urban Tree Species.

Plant leaf respiration is one of the critical components of the carbon cycle in terrestrial ecosystems. To predict changes of carbon emissions from leaves to the atmosphere under a warming climate, it is, therefore, important to understand the thermodynamics of the temperature response of leaf respiration. In this study, we measured the short-term temperature response of leaf respiration from five different urban tree species in a subtropical region of southern China. We applied two models, including an empirical model (the Kavanau model) and a mechanistic model (Macromolecular Rate Theory, MMRT), to investigate the thermodynamic properties in different plant species. Both models are equivalent in fitting measurements of the temperature response of leaf respiration with no significant difference (p = 0.67) in model efficiency, while MMRT provides an easy way to determine the thermodynamic properties, i.e., enthalpy, entropy, and Gibbs free energy of activation, for plant respiration. We found a conserved temperature response in the five studied plant species, showing no difference in thermodynamic properties and the relative temperature sensitivity for different species at low temperatures (<42°C). However, divergent temperature response among species happened at high temperatures over 42°C, showing more than two-fold differences in relative respiration rate compared to that below 42°C, although the causes of the divergent temperature response remain unclear. Notably, the convergent temperature response at low temperatures could provide useful information for land surface models to improve predictions of climate change effects on plant respiration.