O'Sullivan Odhran S.

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O'Sullivan
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Odhran S.
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  • Preprint
    Macromolecular rate theory (MMRT) provides a thermodynamics rationale to underpin the convergent temperature response in plant leaf respiration
    ( 2017-10) Liang, Liyin L. ; Arcus, Vickery ; Heskel, Mary ; O'Sullivan, Odhran S. ; Weerasinghe, Lasantha K. ; Creek, Danielle ; Egerton, John J. G. ; Tjoelker, Mark ; Atkin, Owen K. ; Schipper, Louis A.
    Temperature is a crucial factor in determining the rates of ecosystem processes, e.g. leaf respiration (R) − the flux of plant respired CO2 from leaves to the atmosphere. Generally, R increases exponentially with temperature and formulations such as the Arrhenius equation are widely used in earth system models. However, experimental observations have shown a consequential and consistent departure from an exponential increase in R. What are the principles that underlie these observed patterns? Here, we demonstrate that macromolecular rate theory (MMRT), based on transition state theory for enzyme-catalyzed kinetics, provides a thermodynamic explanation for the observed departure and the convergent temperature response of R using a global database. Three meaningful parameters emerge from MMRT analysis: the temperature at which the rate of respiration would theoretically reach a maximum (the optimum temperature, Topt), the temperature at which the respiration rate is most sensitive to changes in temperature (the inflection temperature, Tinf) and the overall curvature of the log(rate) versus temperature plot (the change in heat capacity for the system, ∆Cp‡). On average the highest potential enzyme-catalyzed rates of respiratory enzymes for R is predicted to occur at 67.0±1.2 °C and the maximum temperature sensitivity at 41.4±0.7 °C from MMRT. The average curvature (average negative ∆Cp‡) was -1.2±0.1 kJ.mol-1K-1. Interestingly, Topt, Tinf and ∆Cp‡ appear insignificantly different across biomes and plant functional types (PFTs), suggesting that thermal response of respiratory enzymes in leaves could be conserved. The derived parameters from MMRT can serve as thermal traits for plant leaves that represents the collective temperature response of metabolic respiratory enzymes and could be useful to understand regulations of R under a warmer climate. MMRT extends the classic transition state theory to enzyme-catalyzed reactions and provides an accurate and mechanistic model for the short-term temperature response of R around the globe.
  • Article
    Implications of improved representations of plant respiration in a changing climate
    (Nature Publishing Group, 2017-11-17) Huntingford, Chris ; Atkin, Owen K. ; Martinez-de la Torre, Alberto ; Mercado, Lina M. ; Heskel, Mary ; Harper, Anna B. ; Bloomfield, Keith J. ; O'Sullivan, Odhran S. ; Reich, Peter B. ; Wythers, Kirk R. ; Butler, Ethan E. ; Chen, Ming ; Griffin, Kevin L. ; Meir, Patrick ; Tjoelker, Mark ; Turnbull, Matthew H. ; Sitch, Stephen ; Wiltshire, Andrew J. ; Malhi, Yadvinder
    Land-atmosphere exchanges influence atmospheric CO2. Emphasis has been on describing photosynthetic CO2 uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (Rd) and temperature dependencies. This allows characterisation of baseline Rd, instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates Rd to whole-plant respiration Rp, driven with meteorological forcings spanning uncertainty across climate change models. For pre-industrial estimates, new baseline Rd increases Rp and especially in the tropics. Compared to new baseline, revised instantaneous response decreases Rp for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new Rd estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how Rd aggregates to whole-plant respiration. Our analysis suggests Rp could be around 30% higher than existing estimates.