Three-dimensional plant architecture and sunlit–shaded patterns: a stochastic model of light dynamics in canopies

Abstract

Background and AimsDiurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day.MethodsHigh-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit–shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from.Key ResultsFor a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data.ConclusionsThe model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.

Rate of photosynthetic induction in fluctuating light varies widely among genotypes of wheat

“…We simulated the impact of observed variability in photosynthetic induction kinetics on diurnal carbon gain for different sunfleck lengths and canopy positions, using a modeling approach similar to that of Taylor and Long (2017), in which we simulated photosynthetic induction kinetics using genotype-median kinetic parameters for V cmax induction from Equation 2 for each of the 10 genotypes studied. To assess the role of sunfleck length and canopy position, we calculated irradiance based on expressions given by Retkute et al (2018) and de Pury and Farquhar (1997). We chose this approach, rather than the sample ray tracing model output for a single variety and location as used by Taylor and Long (2017), because aspects of canopy light environment probably differ greatly among genotypes, canopy positions, planting densities, and geographic locations.…”

A Holistic Approach to Study Photosynthetic Acclimation Responses of Plants to Fluctuating Light

“…No prior knowledge of the underlying biological processes is required Dependent on high amounts of input data Stegemann et al, 1999;Louarn et al, 2015 Mechanistic Systems are broken down into smaller components whose interactions with one another are clearly defined Can be generalized and used to predict outcomes outside of the range of the input data Knowledge of the workings of the systems components is required Farquhar et al, 1980;Kirschbaum et al, 1997;Pearcy et al, 1997 Dynamic Models mainly consisting of ordinary of partial differential equations that capture changes over time Can incorporate changes in concentrations over time as well as kinetic and regulatory information Large models often lead to a combinatorial explosion in parameter estimation Farquhar et al, 1980;Porcar-Castell et al, 2006;Retkute et al, 2015 Guerriero et al, 2014;Retkute et al, 2018 The advantages and limitations of each are discussed and examples of where each type of model has been applied are provided.…”

Photosynthetic Acclimation to Fluctuating Irradiance in Plants

“…The duration and amplitude of sunflecks depends on wind speed (Tang et al, 1988;Roden, 2003), canopy structure (Peressotti et al, 2001;Kaiser et al, 2018b), plant biomechanical properties (Burgess et al, 2016, and position within the canopy (Pearcy et al, 1990). These fluctuations may be simulated with detailed 3D reconstructions of canopies coupled with physically based ray tracing algorithms, but challenges remain in the realistic simulation and measurement of plant movements by wind (Burgess et al, 2016;Retkute et al, 2018;Gibbs et al, 2019). The statistical properties of sunflecks were reviewed by Kaiser et al (2018b) showing that sunflecks are generally short (<2 s).…”