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Modeling leaf maximum net photosynthetic rate of <Emphasis Type="Italic">Festuca pallescens</Emphasis>, the dominant perennial grass of Patagonian pine-based silvopastoral systems
Authors:Gonzalo Caballé  María Elena Fernández  Javier Gyenge  Alejandro Aparicio  Tomás Schlichter
Institution:1.Instituto Nacional de Tecnología Agropecuaria (INTA) EEA Bariloche,Bariloche,Argentina;2.Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET),Buenos Aires,Argentina
Abstract:The integrated relationship in a simple mechanistic model between the critical environmental factors controlling leaf photosynthesis of understory species would be a useful tool to optimize the management of the silvopastoral systems. Individual effect of leaf temperature, water stress and light environment over net maximum photosynthetic rate (Pmax) was evaluated on Festuca pallescens leaves grown in a silvopastoral system of two Pinus ponderosa canopy covers (350 and 500 trees ha−1) and natural grassland. The aim was to integrate individual functions for Pmax against these environmental factors into a multiplicative model. We measured pre-dawn water potential (ψ pd), leaf temperature and net photosynthetic rate (Pn), stomatal conductance (gs) and intercellular CO2 concentration (Ci) as a function of photosynthetic photon flux density (PPFD). The highest Pmax under non-limiting conditions was 20.4 μmol CO2 m−2 s−1 and was defined as standardized dimensionless Pmax s  = 1 for comparison of environmental factors. The leaf temperature function showed an optimum range between 20.2 and 21.8°C where Pmax s  = 1. Then, Pmax s declined by an average 1 μmol CO2 m−2 s−1 C−1 from the optimum to 4.7 and 38.5°C. Pmax s decreased at a rate of 9.49 μmol CO2 m−2 s−1 MPa−1 as water potential reaches −1.9 MPa and showed a lower slope as water potential decreased down to −4.3 MPa. The light environment was estimated from hemispherical photograph analysis. Pmax s was 20% higher in leaves of open control plants than under the maximum tree canopy cover. The simple multiplicative model accounted for 0.82 of the variation in Pmax. Such a simple mechanistic model is the first step towards a more effective decision support tool.
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