To understand the temporal and spatial variability of switchgrass (Panicum virgatum) and restored prairie biomass yield and quality as a bioenergy feedstock at field-scale, a study was conducted at Marshall Farm (42.44° N, -85.32° W) and Lux Arbor Farm (42.48° N, -85.44° W) in southwest Michigan USA from 2018-2021. Switchgrass annual average biomass yield ranged from 4.3 to 9.1 Mg ha-1 over the study period. Restored prairie annual average biomass yield ranged from 2.4 to 4.9 Mg ha-1. Under similar field conditions, the monoculture switchgrass cropping system exhibited more temporal and spatial variability of biomass yield than the polyculture restored prairie. In contrast, the polyculture restored prairie exhibited more spatial variability of glucose and xylose content than monoculture switchgrass under similar field conditions. However, minimal spatial variability of glucose, xylose and lignin content was observed in switchgrass and restored prairie. The ratio of interannual temporal variance to spatial variance for glucose, xylose and lignin content of switchgrass at Marshall Farm was 12.2, 3.2 and 5.5, respectively. The ratio of interannual temporal variance to spatial variance for glucose, xylose and lignin content of switchgrass at Lux Arbor Farm was 52.4, 5.8 and 1.0 x 105, respectively. The ratio of interannual temporal variance to spatial variance for glucose, xylose and lignin content of restored prairie at Marshall Farm was 1.3, 1.7 and 9.1, respectively. The ratio of interannual temporal variance to spatial variance for glucose, xylose and lignin content of restored prairie at Lux Arbor Farm was 6.1, 4.3 and 18.8, respectively. Soil ammonium, magnesium, calcium, and phosphorus concentrations as well as the topographic wetness index were important to explain within-field spatial variability in biomass yield, glucose, xylose and lignin content of switchgrass and restored prairie at Lux Arbor Farm and Marshall Farm. Lastly, we evaluated near-infrared spectroscopy as a quick, non-destructive method for analyzing biomass quality. Compared to chemical analyses, near-infrared sprectroscopy had negative biases for glucose (switchgrass: -72.5 mg g-1, restored prairie: -78.5 mg g-1) and xylose content (switchgrass: -99.6 mg g-1, restored prairie: -91.4 mg g-1) and positive biases for lignin content (switchgrass: 32.6 mg g-1, restored prairie: 47.8 mg g-1). With bias correction, the agreement between near-infrared spectroscopy and chemical analysis was significantly improved. Near-infrared spectroscopy is therefore a promising rapid analytical tool for glucose, xylose, and lignin content of biomass. With expected increases in precipitation and temperature variability associated with future climate change, spatial and temporal variability in biomass quality will likely be exacerbated. Understanding the sources of this variability will facilitate the development of management practices at the field and biorefinery level to help address the issue. Identifying analytical methods to accurately assess variability in biomass quality will be an important step in this process.
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