Decline of photosynthetic capacity with leaf age and position in two tropical pioneer tree species

Abstract. The influence of seasonal phenology on canopy photosynthesis in tropical evergreen forests remains poorly understood, and its representation in global ecosystem models is highly simplified, typically with no seasonal variation of canopy leaf properties taken into account. Including seasonal variation in leaf age and photosynthetic capacity could improve the correspondence of global vegetation model outputs with the wet-dry season CO 2 patterns measured at flux tower sites in these forests. We introduced a leaf litterfall dynamics scheme in the global terrestrial ecosystem model ORCHIDEE based on seasonal variations in net primary production (NPP), resulting in higher leaf turnover in periods of high productivity. The modifications in the leaf litterfall scheme induce seasonal variation in leaf age distribution and photosynthetic capacity. We evaluated the results of the modification against seasonal patterns of three long-term in-situ leaf litterfall datasets of evergreen tropical forests in Panama, French Guiana and Brazil. In addition, we evaluated the impact of the model improvements on simulated latent heat (LE) and gross primary productivity (GPP) fluxes for the flux tower sites Guyaflux (French Guiana) and Tapajós (km 67, Brazil). The results show that the introduced seasonal leaf litterfall corresponds well with field inventory leaf litter data and times with its seasonality. Although the simulated litterfall improved substantially by the model modifications, the impact on the modelled fluxes remained limited. The seasonal pattern of GPP improved clearly for the Guyaflux site, but no significant improvement was obtained for the Tapajós site. The seasonal pattern of the modelled latent heat fluxes was hardly changed and remained consistent with the observed fluxes. We conclude that we introduced a realistic and generic litterfall dynamics scheme, but that other processes need to be improved in the model to achieve better simulations of GPP seasonal patterns for tropical evergreen forests.

Abstract. Mixed-species tree plantations, composed of high-value native rain forest timbers, are potential forestry systems for the subtropics and tropics that can provide ecological and production benefits. Choices of rain forest tree species for mixtures are generally based on the concept that assemblages of fast-growing and light-demanding species are less productive than assemblages of species with different shade tolerances. We examined the hypothesis that mixtures of two fast-growing species compete for resources, while mixtures of shade-tolerant and shade-intolerant species are complementary. Ecophysiological characteristics of young trees were determined and analyzed with a physiology-based canopy model (MAESTRA) to test species interactions. Contrary to predictions, there was evidence for complementary interactions between two fast-growing species with respect to nutrient uptake, nutrient use efficiency, and nutrient cycling. Fast-growing Elaeocarpus angustifolius had maximum demand for soil nutrients in summer, the most efficient internal recycling of N, and low P use efficiency at the leaf and whole-plant level and produced a large amount of nutrient-rich litter. In contrast, fast-growing Grevillea robusta had maximum demand for soil nutrients in spring and highest leaf nutrient use efficiency for N and P and produced lownutrient litter. Thus, mixtures of fast-growing G. robusta and E. angustifolius or G. robusta and slow-growing, shade-tolerant Castanospermum australe may have similar or even greater productivity than monocultures, as light requirement is just one of several factors affecting performance of mixed-species plantations. We conclude that the knowledge gained here will be useful for designing large-scale experimental mixtures and commercial forestry systems in subtropical Australia and elsewhere.

-The objective of this work was to evaluate a generalized response function to the atmospheric CO 2 concentration [f(CO 2 )] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO 2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO 2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO 2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R 2 ), and the root mean square error (RMSE). The f(CO 2 ) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO 2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO 2 emissions for the next generation of climate scenarios for the 21 st century.Index terms: Oryza sativa, global warming, modeling, photosynthesis. Função de resposta a CO 2 na eficiência de uso da radiação em arroz para cenários de mudanças climáticasResumo -O objetivo deste trabalho foi avaliar uma função de resposta generalizada à concentração de CO 2 atmosférico [f (CO 2 )] pela eficiência de uso de radiação (RUE) em arroz. Os dados experimentais de RUE, em diferentes concentrações de CO 2 , foram coletados de ensaios sobre o arroz realizados em diferentes locais do mundo. Os dados de RUE foram normalizados de modo que todos os valores de RUE, na atual concentração de CO 2 , foram iguais a 1. A função de resposta foi obtida pelos valores de RUE normalizados versus a concentração de CO 2 , ajustados à função de Morgan-Mercer-Flodin (MMF), com uso do método de Marquardt para estimar os coeficientes do modelo. O ajuste da função foi medido pelo desvio-padrão dos coeficientes estimados, o coeficiente de determinação (R²) e a raiz do quadrado médio do erro (RQME). A f(CO 2 ) descreve uma resposta não linear sigmoidal da RUE em arroz, em função da concentração do CO 2 atmosférico, o que tem significado ecofisiológico e, portanto, é uma função robusta que pode ser facilmente acoplada a modelos de simulação de arroz, além de abranger as emissões de CO 2 para a próxima geração de cenários climáticos para o século 21.Termos para indexação: Oryza sativa, aquecimento global, modelagem, fotossíntese.