Simple equations for dynamic models of the effects of CO2 and O3 on light-use efficiency and growth of crops

Oijen, Marcel van; Dreccer, M. Fernanda; Firsching, K. H.; Schnieders, B.J.

doi:10.1016/j.ecolmodel.2004.05.002

Cited by 32 publications

(24 citation statements)

References 72 publications

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“…Besides being sensitive to light intensity, the calculated value of LUE depends on atmospheric CO 2 concentration and temperature, through their impact on a and P max (Farquhar et al 1980;Van Oijen et al 2004). Further, LUE is assumed to be decreased in case of drought.…”

Section: Coffee Growth and Productionmentioning

confidence: 99%

“…Equations for a and P max are derived from the limits of the Farquhar photosynthetic rate equations (Farquhar et al 1980) for very low and high light intensity, respectively. The derivation of the LUE-equation was described in detail by Van Oijen et al (2004) and examples of its successful application to growth modelling of various plant species were given by Höglind et al (2001), Van Oijen et al (2004), Van Oijen and Ewert (1999) and Rodriguez et al (1999). The equation yields the highest values for LUE (approaching the value of a) at low light intensity I 0 .…”

Section: Coffee Growth and Productionmentioning

confidence: 99%

“…Likewise, a model for Erythrina poeppigiana, a common shade-tree species for coffee, exists, but again with a focus on short-term radiation distribution (Nygren 1993). Notwithstanding the absence of ready-made coffee and shade-tree models, many algorithms developed for simple crop and forest models (for example, Van Oijen et al 2004, 2005 have general validity and may be used as elements in a coffee agroforestry model.…”

Section: Introductionmentioning

confidence: 99%

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Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results

et al. 2010

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Research on coffee agroforestry systems in Central America has identified various environmental factors, management strategies and plant characteristics that affect growth, yield and the impact of the systems on the environment. Much of this literature is not quantitative, and it remains difficult to optimise growing area selection, shade tree use and management. To assist in this optimisation we developed a simple dynamic model of coffee agroforestry systems. The model includes the physiology of vegetative and reproductive growth of coffee plants, and its response to different growing conditions. This is integrated into a plot-scale model of coffee and shade tree growth which includes competition for light, water and nutrients and allows for management treatments such as spacing, thinning, pruning and fertilising. Because of the limited availability of quantitative information, model parameterisation remains fraught with uncertainty, but model behaviour seems consistent with observations. We show examples of how the model can be used to examine tradeoffs between increasing coffee and tree productivity, and between maximising productivity and limiting the impact of the system on the environment. (Résumé d'auteur

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Section: Coffee Growth and Productionmentioning

confidence: 99%

Section: Coffee Growth and Productionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results

et al. 2010

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“…In addition, in this algorithm, actual LUE was calculated based on the assumption that LUE was influenced only by low or high temperatures and water shortages. However, in the real environment, LUE could also be influenced by many other factors, such as the eco-physiological processes in the vegetation, light intensity, and concentrations of CO 2 and O 3 in the atmosphere [56,57]. In addition, LUE shows obvious spatial heterogeneity and temporal variation under the combined influence of vegetation distribution and climate features [58][59][60].…”

Section: Future Workmentioning

confidence: 99%

Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

Sun

Xiao

et al. 2018

Remote Sensing

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Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP) and annual net primary production (NPP) are contained in MODerate Resolution Imaging Spectroradiometer (MODIS) products (MOD17), which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI) and

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“…This approach describes primary effects of ozone at the leaf biochemical level, but it is difficult to extrapolate their consequences to the plant or stand level. Consequently, for the purpose of plant growth models simpler approaches are needed that address ozone effects on light use efficiency as well as assimilate partitioning and overall rates and costs for detoxification and repair of enzymes (van Oijen et al 2004). Until now, only a few plant growth models consider impacts of ozone on plant growth (Weinstein et al 1991;Chen et al 1998;van Oijen et al 2004;Deckmyn et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Analysing the role of soil properties, initial biomass and ozone on observed plant growth variability in a lysimeter study

et al. 2009

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This simulation study is based on a lysimeter experiment with juvenile beech trees (Fagus sylvatica L.) which were grown under ambient or doubled ambient atmospheric ozone concentrations. The aim of the study was to analyze the role of differences in soil properties, differences in initial biomass and ozone impacts on observed plant growth variability at the eight lysimeters of this experiment. For this purpose, we established a new simulation model based on the Responsible Editor: Johan Six. model system Expert-N by coupling soil water and nitrogen transport models with the plant growth model PLATHO, which was already tested and applied for juvenile beech. In order to parameterize the soil model, for all lysimeters soil hydraulic parameters as well as carbon and nitrogen stocks were measured. Simulation results reveal that the observed decreased growth rates under elevated ozone are due to ozone impacts on plant growth, whereas the high plant growth variability between lysimeters is to a major part the consequence of differences in soil hydraulic properties. Differences in initial biomass are of minor importance to explain plant growth variability in this experiment.

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Simple equations for dynamic models of the effects of CO2 and O3 on light-use efficiency and growth of crops

Cited by 32 publications

References 72 publications

Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results

Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results

Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

Analysing the role of soil properties, initial biomass and ozone on observed plant growth variability in a lysimeter study

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