3. Arrhenius Kinetics Reaction Velocity = A e -Ea/RT where, A = pre-exponential factor, or y-intercept Ea = activation energy of the substrate R = universal gas constant T = temperature, o K

4. Boone et al (2003) Nature 396:570-572. Figure 1: Season time course of soil respiration. Figure 2. Relationship between soil temperature and rate of soil respiration. The different experimental treatments reflect modifications to the rate of substrate supply.

5. In the above energy diagram for the reaction A  B we have the following features: 1.Overall, the reaction is energetically favorable. In other words, the product, B, is at a lower energy level than the reactant, A. Energetically, the reaction will proceed with a net release of energy (i.e. goes downhill energetically as it goes from A  B) 2. However, for the reaction to proceed, there is an activation energy barrier that molecule A will have to overcome. Molecules of A will have to acquire enough energy to overcome E a in order for the reaction to proceed. This energy will come from the kinetic energy associated with molecular collisions Energy

6. Craine et al (2010) Nature Geoscience 3:854-857 Widespread coupling between the rate and temperature sensitivity of organic matter decay High Ea decomposes slowly Low Ea decomposes rapidly R 20 = microbial respiration rate @ 20 o C

7. Issue of substrate supply Low to high

8. What processes affect heterotrophic respiration? (1) activation energy of the substrate (e.g., Craine et al. 2010) (2) soil temperature & moisture (e.g., Lloyd & Taylor 1994 (3) substrate supply (e.g., Davidson and Janssens 2006) (4) O 2 concentration(e.g., Skopp et al. 1990) (5) C-use efficiency (e.g., Allison et al. 2010) (6) sorption – desorption dynamics(e.g., Hinsinger 2001) substrate supply O 2 concentration max. rate of reaction double Michaelis-Menton function

9. What processes affect heterotrophic respiration? (1) activation energy of the substrate (e.g., Craine et al. 2010) (2) soil temperature & moisture (e.g., Lloyd & Taylor 1994 (3) substrate supply (e.g., Davidson and Janssens 2006) (4) O 2 concentration(e.g., Skopp et al. 1990) (5) C-use efficiency (e.g., Allison et al. 2010) (6) sorption – desorption dynamics(e.g., Hinsinger 2001) substrate supply O 2 concentration max. rate of reaction double Michaelis-Menton function Arrhenius function reaction rate increases with T

10. A simple test: predicting exoenzyme activity [Davidson et al. 2011] 1.known substrate concentrations 2.constant temperature during incubation 36.5 o C 27.5 o C 4.5 o C 12.7 o C 23.7 o C aaaaa 50 40 30 20 10 0 reaction velocity (μmol hr -1 ) 0.04 0.03 0.02 0.01 0 reaction velocity (μmol hr -1 ) substrate concentration [Sx] 0 20000 40000 60000 80000 100000 120000 0 20000 40000 60000 80000 100000 substrate concentration [Sx]

11. A complex test: predicting heterotrophic respiration in a trenching expt. at the Harvard Forest [Davidson et al. 2011] substrate concentration @ reaction site O 2 concentration @ reaction site Sx total =soil C content p = solubility fraction D liq =difussivity in water Θ = soil moisture a =air filled porosity BD=bulk density PD=particle density D gas =diffusivity of O 2 in air

12. A complex test: predicting heterotrophic respiration in a trenching expt. at the Harvard Forest [Davidson et al. 2011] observations model model w/seasonality by allowing variation in α Sx of Vmax Sx = α Sx X e -EaSx/RT

15. Wieder et al. 2013 Nature Climate Change 3:909-912 Global soil carbon projections are improved by modelling microbial processes doi:10.1038/nclimate1951 Observations, global total = 1,259 Pg C. b, CLM4cn, global total = 691 Pg C (spatial correlation with observations (r) = 0.55, model-weighted root mean square error (r.m.s.e) = 7.1 kg C m−2). c, DAYCENT, global total = 939 Pg C (r = 0.53, r.m.s.e = 7.6). d, The CLM microbial model, global total = 1,310 Pg C (r = 0.71, r.m.s.e = 5.3).

16. Tarnocai et al. 2009 Global Biogeochemical Cycles0-30cm 191Total=3224x10 15 gC Circumarctic permafrost region0-100cm 496~32% of global total 0-300cm1024

17. Microbial C-use Efficiency: an emerging topic in terrestrial biogeochemistry Figure Source: Schimel and Weintraub (2003) Soil Biology and Biochemistry

18. Microbial C-use Efficiency: an emerging topic in terrestrial biogeochemistry Melillo et al (2003) Science 13:2173-2176 Soil Warming and Carbon-Cycle Feedbacks to the Climate System

19. Figure 1. Soil samples were collected from control plots at two soil warming studies at the Harvard Forest LTER site, amended with one of four substrates (glucose, glutamic acid, oxalic acid or phenol) and incubated at 5, 15 or 25 °C. Error bars represent one standard error. direct uptake, not temperature sensitive high efficiency direct uptake not temperature sensitive low efficiency indirect uptake via extracellular decomposition temperature sensitive Efficiency decreases with increasing temperature & molecular complexity [Ea] 30% decrease 60% decrease Frey et al. (2013) Nature Climate Change 3:395-398 The temperature response of soil microbial efficiency and its feedback to climate

20. Frey et al. (2013) Nature Climate Change 3:395-398 The temperature response of soil microbial efficiency and its feedback to climate a.Two years following there is little change in the microbial CUE of phenol in warmed compared to control plots b.18 years following experimental warming, phenol CUE “acclimates” in treatment relative to control plots * shifts in microbial physiology * shifts in microbial community composition

21. Allison et al (2010) Nature Geoscience 3:336 – 340 Soil-carbon response to warming dependent on microbial physiology Model simulates temperature sensitivity of microbial [growth, CUE] and exoenzyme activity

22. CUE  w/T when respiration more sensitive to T than biomass production Soil studies suggest CUE declines by at least 0.016 o C -1 Model Simulation [+5 o C] Warming + varying CUE CUE declines 0.31 to 0.23 Warming + constant CUE CUE remains at 0.31 Warming + acclimation thermal acclimation of microbial respiration [evolutionary adaptation, community shifts and physiological changes] simulated by reducing T sensitivity of CUE Allison et al (2010) Nature Geoscience 3:336 – 340 Soil-carbon response to warming dependent on microbial physiology M O D E L D Y N A M I C S microbial enzyme prod./ respirationbiomass activitySOC small transient    large transient  30%  long term - substrate limitation via SOC depletion intermediate  15%  transient