Valuing a Novel Biotechnology with Outcome Variability and Uncertainty: The Case of Mycorrhizal Biofertilizers

While phosphorus is an essential nutrient for plant growth, excess demand for phosphate fertilizers has contributed to extremely volatile fertilizer prices and caused billions of dollars in environmental damages. Over 80% of terrestrial plants have evolved to form symbiotic relationships with soil-dwelling fungi known as mycorrhiza, which help them to absorb phosphorus, and agricultural producers may be able to improve P-efficiency by encouraging this symbiosis. However, mycorrhiza cannot be directly observed and the magnitude of their effect on P absorption is context-dependent and subject to scientific debate. This paper estimates the value of the ecosystem services provided by mycorrhiza to agricultural operators through improved P-efficiency using a dynamic programming model with varying levels of state stochasticity and uncertainty. We compare several different management strategies under which an agricultural producer chooses to add fertilizer and/or a commercial mycorrhizal inoculum to maximize profit and yield. The first objective is to calibrate a deterministic dynamic programming model, wherein the biological and physical processes are well-understood. To this, stochasticity will added, including biological stochasticity for the biomass of mycorrhiza and the host plant. Lastly, distributions will be added to key parameters, representing uncertainty about the biomass of mycorrhiza, the stock of phosphorus, and the effects of symbiosis on plant biomass.