The carbon and nitrogen cycle impacts of reverting perennial bioenergy switchgrass to an annual maize crop rotation

Abstract

In the age of biofuel innovation, bioenergy crop sustainability assessment has determined how candidate systems alter the carbon (C) and nitrogen (N) cycle. These research efforts revealed how perennial crops, such as switchgrass, increase belowground soil organic carbon (SOC) and lose less N than annual crops, like maize. As demand for bioenergy increases, land managers will need to choose whether to invest in food or fuel cropping systems. However, little research has focused on the C and N cycle impacts of reverting purpose-grown perennial bioenergy crops back to annual cropping systems. We investigated this knowledge gap by measuring C and N pools and fluxes over 2 years following reversion of a mature switchgrass stand to an annual maize rotation. The most striking treatment difference was in ecosystem respiration (ER), with the maize-converted treatment showing the highest respiration flux of 2,073.63 (± 367.20) g C m −2 year −1 compared to the switchgrass 1,412.70 (± 28.72) g C m −2 year −1 and maize-control treatments 1,699.16 (± 234.79) g C m −2 year −1. This difference was likely driven by increased heterotrophic respiration of belowground This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Ecosystem‐scale biogeochemical fluxes from three bioenergy crop candidates: How energy sorghum compares to maize and miscanthus

“…The eddy covariance technique, as outlined in Moore et al (2020), was used to characterize ecosystem‐scale C, water (latent heat flux, LE) and energy (sensible heat flux, H) differences between maize, miscanthus and energy sorghum. Each flux tower supported an open path infrared gas analyzer (LI‐7500RS; LICOR Biosciences) for atmospheric gas concentration and a 3D sonic anemometer (81000RE; RM Young) for wind speed and direction, all recorded at 10 Hz.…”

“…Perennial crops offer the best trade‐off for biomass production and C sequestration due to their low N requirements (Heaton et al, 2009; Smith et al, 2013) and their extensive belowground allocation that provides a long‐term store of C (Anderson‐Teixeira et al, 2013; Robertson et al, 2017). However, if this C and N becomes disturbed through land‐use change, it can quickly leave the system and negate the sequestration benefits of the crops (Abraha et al, 2019; Gelfand et al, 2011; Moore et al, 2020; Zeri et al, 2011). Such consequences could make it difficult for land managers to rotate between food and fuel crops to keep pace with market demands while maximizing long‐term C storage in these agro‐ecosystems.…”

The effect of increasing temperature on crop photosynthesis: from enzymes to ecosystems

“…However, under longer term heat stress, NSC accumulation in leaves and stems (tomato and rice, Zhang et al , 2012 ; Zhang et al , 2018 ) decreases root to shoot biomass ratio (castor bean, Ribeiro et al , 2014 ), and the reduced carbon export rate from leaves suggests a reduction in carbohydrate export towards sinks (maize, Suwa et al , 2010 ). Carbohydrate accumulation in mesophyll cells has been linked to down-regulation of photosynthetic capacity via negative feedback on Rubisco content and activity ( Moore et al , 1999 ; Long et al , 2004 ). Yet any potential regulatory role for leaf carbohydrate accumulation observed during long-term heat stress remains unclear, due to the direct impact of temperature on Rubisco (see earlier).…”

21st‐century biogeochemical modeling: Challenges for Century‐based models and where do we go from here?

“…New PFT parameterizations in DayCent‐CABBI, a version of DayCent developed by the Center for Advanced Bioenergy and Bioproducts Innovation, have improved the model representation of perennial plant establishment and growth (Figure 3; Moore et al, in press). Model‐data agreement can be tuned with a comparable amount of success for both DayCent‐CABBI and DayCent‐Photo, the previous version of the model (Stenzel et al., 2019; Straube et al., 2018).…”