ORCID Profile
0000-0002-2484-8191
Current Organisation
University of Twente
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Publisher: Springer Science and Business Media LLC
Date: 06-2018
Publisher: Wiley
Date: 28-02-2009
DOI: 10.1002/HYP.7166
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 06-2018
Publisher: Wiley
Date: 08-2014
DOI: 10.1111/GCB.12664
Abstract: Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax ) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space-borne measurements of sun-induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top-of-canopy SIF measurements from space are sensitive to Vcmax at the ecosystem level, and present an approach to invert Vcmax from SIF data. We use the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal Vcmax and SIF which are used to solve the inverse problem. We evaluate our Vcmax estimation method at six agricultural flux tower sites in the midwestern US using spaced-based SIF retrievals. Our Vcmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 μmol m(-2) s(-1) , respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying Vcmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed Vcmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time-resolved Vcmax estimates from SIF are used, with R(2) for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space-based SIF data as a proxy for photosynthetic capacity and suggest the potential for global, time-resolved estimates of Vcmax .
Publisher: Elsevier BV
Date: 11-2014
Publisher: Wiley
Date: 09-02-2017
DOI: 10.1111/NPH.14437
Abstract: Sun‐induced fluorescence ( SIF ) in the far‐red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light‐use efficiency and gross primary production ( GPP ). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F 760 ) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen–phosphorous ( NP ). Using the soil–canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient‐induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF ) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration ( C ab) and maximum carboxylation capacity ( V cmax )) affected the observed linear relationship between F 760 and GPP . We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F 760 . Changes in canopy structure mainly control the GPP –F 760 relationship, with a secondary effect of C ab and V cmax . In order to exploit F 760 data to model GPP at the global/regional scale, canopy structural variability, bio ersity and functional traits are important factors that have to be considered.
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 09-2019
Publisher: Cold Spring Harbor Laboratory
Date: 05-02-2020
DOI: 10.1101/2020.02.05.935064
Abstract: Semi-arid grasslands and other ecosystems combine green and senescent leaves featuring different biochemical and optical properties, as well as functional traits. Knowing how these properties vary is necessary to understand the functioning of these ecosystems. However, differences between green and senescent leaves are not considered in recent models representing radiative transfer, heat, water and CO 2 exchange such as the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE). Neglecting the contribution of senescent leaves to the optical and thermal signal of vegetation limits the possibilities to use remote sensing information for studying these ecosystems as well as neglecting their lack of photosynthetic activity increases uncertainty in the representation of ecosystem fluxes. In this manuscript we present senSCOPE as a step towards a more realistic representation of mixed green and senescent canopies. senSCOPE is a modified version of SCOPE model that describes a canopy combining green and senescent leaves with different properties and function. The model relies on the same numerical solutions than SCOPE, but exploits the linear nature of the scattering coefficients to combine optical properties of both types of leaf. Photosynthesis and transpiration only take place in green leaves and different green and senescent leaf temperatures are used to close the energy balance. Radiative transfer of sun-induced fluorescence (SIF) and absorptance changes induced by the xanthophyll cycle action are also simulated. senSCOPE is evaluated against SCOPE both using synthetic simulations, forward simulations based on observations in a Mediterranean tree-grass ecosystem, and inverting dataset of ground measurements of reflectance factors, SIF, thermal radiance and gross primary production on a heterogeneous and partly senescent Mediterranean grassland. Results show that senSCOPE outputs vary quite linearly with the fraction of green leaf area, whereas SCOPE does not respond linearly to the effective leaf properties, calculated as the weighted average of green and senescent leaf parameters. Inversion results and pattern-oriented model evaluation show that senSCOPE improves the estimation of some parameters, especially chlorophyll content, with respect SCOPE retrievals during the dry season. Nonetheless, inaccurate knowledge of the optical properties of senescent matter still complicates model inversion. senSCOPE brings new opportunities for the monitoring of canopies mixing green and senescent leaves, and for improving the characterization of the optical properties of senescent material.
No related grants have been discovered for Christiaan van der Tol.