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One of the critical variables that determine the rate of any reaction is temperature. For biological systems, the effects of temperature are convoluted with myriad (and often opposing) contributions from enzyme catalysis, protein stability, and temperature-dependent regulation, for example. We have coined the phrase "macromolecular rate theory (MMRT)" to describe the temperature dependence of enzyme-catalyzed rates independent of stability or regulatory processes. Central to MMRT is the observation that enzyme-catalyzed reactions occur with significant values of ΔCp(‡) that are in general negative. That is, the heat capacity (Cp) for the enzyme-substrate complex is generally larger than the Cp for the enzyme-transition state complex. Consistent with a classical description of enzyme catalysis, a negative value for ΔCp(‡) is the result of the enzyme binding relatively weakly to the substrate and very tightly to the transition state. This observation of negative ΔCp(‡) has important implications for the temperature dependence of enzyme-catalyzed rates. Here, we lay out the fundamentals of MMRT. We present a number of hypotheses that arise directly from MMRT including a theoretical justification for the large size of enzymes and the basis for their optimum temperatures. We rationalize the behavior of psychrophilic enzymes and describe a "psychrophilic trap" which places limits on the evolution of enzymes in low temperature environments. One of the defining characteristics of biology is catalysis of chemical reactions by enzymes, and enzymes drive much of metabolism. Therefore, we also expect to see characteristics of MMRT at the level of cells, whole organisms, and even ecosystems.

There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international ‘4p1000’ initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long‐term experiments and space‐for‐time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.

The increase in enzymatic rates with temperature up to an optimum temperature (Topt) is widely attributed to classical Arrhenius behavior, with the decrease in enzymatic rates above Topt ascribed to protein denaturation and/or aggregation. This account persists despite many investigators noting that denaturation is insufficient to explain the decline in enzymatic rates above Topt. Here we show that it is the change in heat capacity associated with enzyme catalysis (ΔC(‡)p) and its effect on the temperature dependence of ΔG(‡) that determines the temperature dependence of enzyme activity. Through mutagenesis, we demonstrate that the Topt of an enzyme is correlated with ΔC(‡)p and that changes to ΔC(‡)p are sufficient to change Topt without affecting the catalytic rate. Furthermore, using X-ray crystallography and molecular dynamics simulations we reveal the molecular details underpinning these changes in ΔC(‡)p. The influence of ΔC(‡)p on enzymatic rates has implications for the temperature dependence of biological rates from enzymes to ecosystems.

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Our current understanding of the temperature response of biological processes in soil is based on the Arrhenius equation. This predicts an exponential increase in rate as temperature rises, whereas in the laboratory and in the field, there is always a clearly identifiable temperature optimum for all microbial processes. In the laboratory, this has been explained by denaturation of enzymes at higher temperatures, and in the field, the availability of substrates and water is often cited as critical factors. Recently, we have shown that temperature optima for enzymes and microbial growth occur in the absence of denaturation and that this is a consequence of the unusual heat capacity changes associated with enzymes. We have called this macromolecular rate theory -MMRT (Hobbs et al., 2013, ACS Chem. Biol. 8:2388). Here, we apply MMRT to a wide range of literature data on the response of soil microbial processes to temperature with a focus on respiration but also including different soil enzyme activities, nitrogen and methane cycling. Our theory agrees closely with a wide range of experimental data and predicts temperature optima for these microbial processes. MMRT also predicted high relative temperature sensitivity (as assessed by Q 10 calculations) at low temperatures and that Q 10 declined as temperature increases in agreement with data synthesis from the literature. Declining Q 10 and temperature optima in soils are coherently explained by MMRT which is based on thermodynamics and heat capacity changes for enzyme-catalysed rates. MMRT also provides a new perspective, and makes new predictions, regarding the absolute temperature sensitivity of ecosystems -a fundamental component of models for climate change.

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Denitrification is an important soil process for assessing nitrogen cycling and controlling nitrogen pollution in the environment. Numerous studies of denitrification rates in soils have been reported over the last decade, many with sampling protocols that are more reliable than in the past. In this paper, we review denitrification rates for agricultural and forest soils that have been reported in the literature, discuss factors that appear to be important in controlling the amount of denitrification that occurs in these soils, and summarise modelling approaches that have been used to predict annual denitrification rates. Most studies of in situ denitrification in upland soils have been conducted in agricultural grassland and forest ecosystems, with a paucity of studies reported from other ecosystems. A large range of annual, in situ, denitrification rates have been reported (0–239 kg N/ha.year), with the highest rates typically occurring in irrigated, nitrogen-fertilised soils. However, most annual denitrification rates reported in the literature appear to be fairly low, with over half of the rates in forest soils being <1 kg N/ha.year (mean of 1.9 kg N/ha.year). Rates of denitrification in agricultural soils tend to be higher than in forest soils, with 85% of rates reported being >1 kg N/ha.year, and a mean rate of 13 kg N/ha.year. Numerous soil, site, and management factors have been reported to affect the denitrification process in situ. The literature indicates that the highest rates of denitrification can be expected in nitrogen-fertilised soils, or where site management increases soil nitrate availability. Where nitrate is non-limiting, denitrification rates appear to be highest in irrigated loam soils. The review suggests that it is difficult to predict denitrification rates based on our current understanding, and that pilot studies should still be conducted if soil nitrogen balances are required.