Global photosynthetic capacity is optimized to the environment.

Autor: Smith NG; Department of Biological Sciences, Texas Tech University, Lubbock, TX, USA.; Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA., Keenan TF; Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.; Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, USA., Colin Prentice I; AXA Chair of Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, London, UK.; College of Forestry, Northwest A&F University, Yangling, China.; Department of Biological Sciences, Macquarie University, NSW, 2109, Australia.; Department of Earth System Science, Tsinghua University, Beijing., Wang H; Department of Earth System Science, Tsinghua University, Beijing., Wright IJ; Department of Biological Sciences, Macquarie University, NSW, 2109, Australia., Niinemets Ü; Department of Plant Physiology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Tartu, Estonia., Crous KY; Hawkesbury Institute for the Environment, Western Sydney University, Penrith, Australia., Domingues TF; Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto - University of São Paulo, São Paulo, Brazil., Guerrieri R; Center for Ecological Research and Forestry Applications, Universidad Autonoma de Barcelona, Cerdanyola, Barcelona, Spain.; School of Geosciences, University of Edinburgh, Edinburgh, UK., Yoko Ishida F; Centre for Tropical Environmental and Sustainability Science, College of Science and Engineering, James Cook University, Cairns, Australia., Kattge J; Max Planck Institute for Biogeochemistry, Jena, Germany.; German Center for Integrative Biodiversity Research Halle-Jena-Leipzig, Leipzig, Germany., Kruger EL; Department of Forest and Wildlife Ecology, University of Wisconsin - Madison, Madison, Wisconsin, USA., Maire V; Département des sciences de l'environnement, Université du Québec à Trois, Rivières, Trois Rivières, Canada., Rogers A; Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA., Serbin SP; Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA., Tarvainen L; Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden., Togashi HF; Department of Biological Sciences, Macquarie University, NSW, 2109, Australia., Townsend PA; Department of Forest and Wildlife Ecology, University of Wisconsin - Madison, Madison, Wisconsin, USA., Wang M; College of Forestry, Northwest A&F University, Yangling, China.; State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Northeast Normal University, Changchun, China., Weerasinghe LK; Research School of Biology, The Australian National University, Canberra, Australia.; Faculty of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka., Zhou SX; Department of Biological Sciences, Macquarie University, NSW, 2109, Australia.; The New Zealand Institute for Plant and Food Research Ltd, Hawke's, Bay, New Zealand.
Jazyk: angličtina
Zdroj: Ecology letters [Ecol Lett] 2019 Mar; Vol. 22 (3), pp. 506-517. Date of Electronic Publication: 2019 Jan 04.
DOI: 10.1111/ele.13210
Abstrakt: Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V cmax ), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal V cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured V cmax dataset for C 3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.
(© 2019 John Wiley & Sons Ltd/CNRS.)
Databáze: MEDLINE
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