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Carbon and water flux responses to physiology by environment interactions: a sensitivity analysis of variation in climate on photosynthetic and stomatal parameters
Authors:William L Bauerle  Alex B Daniels  David M Barnard
Institution:1. Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, 80523-1173, USA
Abstract:Sensitivity of carbon uptake and water use estimates to changes in physiology was determined with a coupled photosynthesis and stomatal conductance (g s) model, linked to canopy microclimate with a spatially explicit scheme (MAESTRA). The sensitivity analyses were conducted over the range of intraspecific physiology parameter variation observed for Acer rubrum L. and temperate hardwood C3 (C3) vegetation across the following climate conditions: carbon dioxide concentration 200–700 ppm, photosynthetically active radiation 50–2,000 μmol m?2 s?1, air temperature 5–40 °C, relative humidity 5–95 %, and wind speed at the top of the canopy 1–10 m s?1. Five key physiological inputs quantum yield of electron transport (α), minimum stomatal conductance (g 0), stomatal sensitivity to the marginal water cost of carbon gain (g 1), maximum rate of electron transport (J max), and maximum carboxylation rate of Rubisco (V cmax)] changed carbon and water flux estimates ≥15 % in response to climate gradients; variation in α, J max, and V cmax input resulted in up to ~50 and 82 % intraspecific and C3 photosynthesis estimate output differences respectively. Transpiration estimates were affected up to ~46 and 147 % by differences in intraspecific and C3 g 1 and g 0 values—two parameters previously overlooked in modeling land–atmosphere carbon and water exchange. We show that a variable environment, within a canopy or along a climate gradient, changes the spatial parameter effects of g 0, g 1, α, J max, and V cmax in photosynthesis-g s models. Since variation in physiology parameter input effects are dependent on climate, this approach can be used to assess the geographical importance of key physiology model inputs when estimating large scale carbon and water exchange.
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