Model exploration of interactions between algal functional diversity and productivity in chemostats to represent open ponds systems across climate gradients

Abstract

Eukaryotic microalgae and prokaryotic cyanobacteria (often collectively described as algae) have been proposed as a promising commercially viable feedstock for biofuels and other bioproducts. Open pond algal monocultures are subjected to environmental fluctuations (i.e. temperature), limiting productivity as environmental conditions vary. An approach to overcome such limitation is the replacement of monocultures with customized polycultures that leverage diversity-productivity relationships by exploiting complementary but uninhabited ecological niches. Defining ecological niche complementarity requires an understanding of how traits and trade-offs interact across environmental gradients and for this reason numerical models represent valuable tools to explore the possible solution space prior to experimental design and verification. We have developed a trait-based, dynamic energy budget model (TB-DEB) of microalgal monocultures and polycultures, and simulated the growth of random and customized polycultures under environmental conditions (i.e. temperature, photoperiod) similar to those in operational algal ponds across the US. Each of the algal species selected as a polyculture component is defined by distinct combinations of literature-derived traits related to substrate uptake, light utilization and temperature optima. Members of the polycultures were categorized into algal functional guilds that were defined based on the interaction between thermal traits and pond thermal regimes. When compared to guilds defined by taxonomy, we demonstrate that grouping algal guilds by functional traits can be an effective approach towards improving biomass productivity in operational algal ponds. Simulations show that a polyculture represents the equivalent of a wider niche monoculture, leading to sustained productivity across seasons. Simulations also revealed that higher species diversity and higher functional diversity lead to higher system biomass. In all, results from this modeling study and earlier experimental studies highlight the idea that regardless of the functional group definition, systematic selection of species based on knowledge of physiology, ecology and the environment aiming at maximizing use of niche space through complementarity has positive impacts on system productivity.