Acclimation of leaf respiration consistent with optimal photosynthetic capacity

Han Wang; Owen K Atkin; Trevor F Keenan; Nicholas G Smith; Ian J Wright; Keith J Bloomfield; Jens Kattge; Peter B Reich; I Colin Prentice

doi:10.1111/gcb.14980

Acclimation of leaf respiration consistent with optimal photosynthetic capacity

Glob Chang Biol. 2020 Apr;26(4):2573-2583. doi: 10.1111/gcb.14980. Epub 2020 Feb 24.

Authors

Han Wang^{1

2}, Owen K Atkin^{3

4}, Trevor F Keenan^{5

6}, Nicholas G Smith⁷, Ian J Wright⁸, Keith J Bloomfield⁹, Jens Kattge^{10

11}, Peter B Reich^{12

13}, I Colin Prentice^{1

8

14}

Affiliations

¹ Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, China.
² Joint Centre for Global Change Studies, Tsinghua University, Beijing, China.
³ Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT, Australia.
⁴ Australian Research Council Centre of Excellence in Plant Energy Biology, Research School of Biology, The Australian National University, Canberra, ACT, Australia.
⁵ Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, USA.
⁶ Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
⁷ Department of Biological Sciences, Texas Tech University, Lubbock, TX, USA.
⁸ Department of Biological Sciences, Macquarie University, Sydney, NSW, Australia.
⁹ Department of Life Sciences, Imperial College London, Ascot, UK.
¹⁰ Max Planck Institute for Biogeochemistry, Jena, Germany.
¹¹ German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig, Leipzig, Germany.
¹² Department of Forest Resources, University of Minnesota, St. Paul, MN, USA.
¹³ Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia.
¹⁴ AXA Chair of Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, Ascot, UK.

PMID: 32091184
DOI: 10.1111/gcb.14980

Abstract

Plant respiration is an important contributor to the proposed positive global carbon-cycle feedback to climate change. However, as a major component, leaf mitochondrial ('dark') respiration (R_d ) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of R_d follows an optimal behaviour related to the need to maintain long-term average photosynthetic capacity (V_cmax ) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co-ordination theory to predict the acclimation of R_d to growth temperature via a link to V_cmax , and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co-ordination theory predicts that field-measured R_d and V_cmax accessed at growth temperature (R_d,tg and V_cmax,tg ) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for R_d and V_cmax respectively. Data-fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both R_d and V_cmax assessed at 25°C (R_d,25 and V_cmax,25 ) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for R_d acclimation to temperature that is simpler-and potentially more reliable-than the plant functional type-based leaf respiration schemes currently employed in most ecosystem and land-surface models.

Keywords: acclimation; carbon cycle; carboxylation capacity (Vcmax); climate change; co-ordination; land-surface model; leaf mass per area; leaf nitrogen; nitrogen cycle; optimality; photosynthesis.

Abstract

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