Using temperature-dependent changes in leaf scaling relationships to quantitatively account for thermal acclimation of respiration in a coupled global climate-vegetation model

• Published in: Global change biology 2008-11, Vol.14 (11), p.2709-2726
• Main Authors: ATKIN, OWEN K, ATKINSON, LINDSEY J, FISHER, ROSIE A, CAMPBELL, CATHERINE D, ZARAGOZA-CASTELLS, JOANA, PITCHFORD, JON W, WOODWARD, F. IAN, HURRY, VAUGHAN
• Format: Article
• Language: English
• Subjects: acclimation; Animal and plant ecology; Animal, plant and microbial ecology; Biological and medical sciences; Climate change; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Techniques; Global warming; leaf mass per unit area; leaf traits; Leaves; Methods and techniques (sampling, tagging, trapping, modelling...); modeling; nitrogen; Plant biology; respiration; scaling; temperature; Temperature effects
• ISSN: 1354-1013; 1365-2486
• DOI: 10.1111/j.1365-2486.2008.01664.x

The response of plant respiration (R) to temperature is an important component of the biosphere's response to climate change. At present, most global models assume that R increases exponentially with temperature and does not thermally acclimate. Although we now know that acclimation does occur, quantitative incorporation of acclimation into models has been lacking. Using a dataset for 19 species grown at four temperatures (7, 14, 21, and 28 °C), we have assessed whether sustained differences in growth temperature systematically alter the slope and/or intercepts of the generalized log-log plots of leaf R vs. leaf mass per unit leaf area (LMA) and vs. leaf nitrogen (N) concentration. The extent to which variations in growth temperature account for the scatter observed in log-log R-LMA-N scaling relationships was also assessed. We show that thermal history accounts for up to 20% of the scatter in scaling relationships used to predict R, with the impact of thermal history on R-LMA-N generalized scaling relationships being highly predictable. This finding enabled us to quantitatively incorporate acclimation of R into a coupled global climate-vegetation model. We show that accounting for acclimation of R has negligible impact on predicted annual rates of global R, net primary productivity (NPP) or future atmospheric CO₂ concentrations. However, our analysis suggests that accounting for acclimation is important when considering carbon fluxes among thermally contrasting biomes (e.g. accounting for acclimation decreases predicted rates of R by up to 20% in high-temperature biomes). We conclude that acclimation of R needs to be accounted for when predicting potential responses of terrestrial carbon exchange to climatic change at a regional level.