B23F-0288:
Modulation of Leaf Economic Traits and Rates by Soil Properties, at Global Scale

Tuesday, 16 December 2014
Vincent Maire, Organization Not Listed, Washington, DC, United States, Ian J. Wright, Macquarie University, Sydney, Australia, Peter B. Reich, University of Minnesota Morris, Morris, MN, United States, Batjes Niels, ISRIC - World Soil Information, Wageningen, Netherlands, Peter M. van Bodegom, Free University of Amsterdam, Amsterdam, Netherlands, Radika Bhaskar, Brown University, Providence, RI, United States, Louis S Santiago, University of California Riverside, Chino, CA, United States, David Ellsworth, University of Western Sydney, Penrith, Australia, Ulo Niinemets, Estonian University of Life Sciences, Tartu, Estonia and Will Cornwell, University of New South Wales, Sydney, Australia
Abstract:
Photosynthesis can be construed as an economic process that optimises the costs of acquisition, transport and utilisation of two substitutable photosynthetic resources: water and nitrogen. The influence of soil fertility on photosynthetic rates and leaf ‘economic’ traits related with H2O and N costs is poorly quantified in higher plants in comparison with the effects of climate. We set out to address this situation by quantifying the unique and shared contributions to global leaf-trait variation from soils and climate.

Using a trait dataset comprising 1509 species from 288 sites, with climate and soil data derived from global datasets, we quantified the effects of soil and climate properties on photosynthetic traits: light-saturated photosynthetic rate (Aarea), stomatal conductance to water vapour (gs), leaf N and P (Narea and Parea) and specific leaf area (SLA). We used mixed regression models, multivariate analyses and variance partitioning.

Along a first dimension of soil fertility, soil pH covaried positively with measures of base status and climatic aridity, and negatively with soil organic C content. Along this dimension from low to high soil pH, Narea, Parea and Aarea increased and SLA decreased.

Along an independent dimension of soil fertility, gs declined and Parea increased with soil available P (Pavail). Overall, soil variables were stronger predictors of leaf traits than were climate variables, except for SLA. Importantly, soils and climate were not redundant information to explain leaf trait variation but were not additive either. Shared effects of soil and climate dominated over their independent effects on Narea and Parea, while unique effects of soils dominated for Aarea and gs.

Three environmental variables were key for explaining variation in leaf traits: soil pH and Pavail, and climatic aridity. Although the reliability of global soils datasets lags behind that of climate datasets our results nonetheless provide compelling evidence that both can now be taken into account in broad-scale analyses, and that effects uniquely attributable to soil properties are important determinants of leaf photosynthetic traits and rates. Understanding what soils tell us (that climate does not) is an important step to progress towards more reliable modelling of global vegetation function.

Back to: Optimality Concepts for Terrestrial Ecosystem Modeling Posters
<< Previous Abstract | Next Abstract >>