PhycoCanopy: An R Shiny tool for exploring primary production in macroalgal canopies

Abstract

Macroalgal canopies are considered important for coastal food webs and may have a role in carbon sequestration. Until recently, measures of canopy photosynthesis have been relatively rare, and simulations have sometimes omitted key aspects (e.g. self-shading, photosynthesis in air). PhycoCanopy offers a way of exploring how different algal parameters and environmental settings can affect net canopy photosynthesis. The model uses the approach of dividing the canopy into vertical layers, calculating the available light for photosynthesis in each layer with respect to attenuation by the water column and the canopy. A total of 23 parameters can be varied to investigate the consequences of changes in key processes such as the tidal cycle, position of algae relative to the low tide mark and photosynthesis in air. Predicted net photosynthesis can vary within a day as the timing of tides interacts with the light level at different times. The model offers a means of exploring the sensitivity of different parameters and building a fuller understanding of canopy photosynthesis. PhycoCanopy allows users to visualize net canopy photosynthesis and to make predictions in situations where parameters are well characterized. The results give an integrated insight into net photosynthesis, particularly as intertidal observations cannot be maintained continuously over the tidal cycle. The model also demonstrates important covariates, such as the area of algal thallus m−2 (thallus area index, TAI), that should be measured to interpret observed variation in canopy photosynthesis.