Spectroscopic measurements of soybeans used to parameterize physiological traits in the AgroIBIS ecosystem model

Friday, 19 December 2014
Aditya Singh1, Shawn Serbin2, Christopher J Kucharik1 and Philip A Townsend3, (1)University of Wisconsin Madison, Madison, WI, United States, (2)Brookhaven National Laboratory, Upton, NY, United States, (3)University of Wisconsin, Madison, WI, United States
Ecosystem models such AgroIBIS require detailed parameterizations of numerous vegetation traits related to leaf structure, biochemistry and photosynthetic capacity to properly assess plant carbon assimilation and yield response to environmental variability. In general, these traits are estimated from a limited number of field measurements or sourced from the literature, but rarely is the full observed range of variability in these traits utilized in modeling activities. In addition, pathogens and pests, such as the exotic soybean aphid (Aphis glycines), which affects photosynthetic pathways in soybean plants by feeding on phloem and sap, can potentially impact plant productivity and yields. Capturing plant responses to pest pressure in conjunction with environmental variability is of considerable interest to managers and the scientific community alike. In this research, we employed full-range (400-2500 nm) field and laboratory spectroscopy to rapidly characterize the leaf biochemical and physiological traits, namely foliar nitrogen, specific leaf area (SLA) and the maximum rate of RuBP carboxylation by the enzyme RuBisCo (Vcmax) in soybean plants, which experienced a broad range of environmental conditions and soybean aphid pressures. We utilized near-surface spectroscopic remote sensing measurements as a means to capture the spatial and temporal patterns of aphid impacts across broad aphid pressure levels. In addition, we used the spectroscopic data to generate a much larger dataset of key model parameters required by AgroIBIS than would be possible through traditional measurements of biochemistry and leaf-level gas exchange. The use of spectroscopic retrievals of soybean traits allowed us to better characterize the variability of plant responses associated with aphid pressure to more accurately model the likely impacts of soybean aphid on soybeans. Our next steps include the coupling of the information derived from our spectral measurements with the AgroIBIS model to project the impacts of increasing aphid pressures on yields expected with continued global change and altered environmental conditions.