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The cultivation of energy cane throughout the Southeastern United States may displace grazed pastures on organic soil (Histosols) to meet growing demands for biofuels. We combined results from a field experiment with a biogeochemical model to improve our understanding of how the conversion of pasture to energy cane during early crop establishment affected soil GHG (CO 2 , CH 4 , and N 2 O) exchange with the atmosphere. GHG fluxes were measured under both land uses during wet, hot and cool, dry times of year, and following a fertilization event. We also simulated the impact of changes in precipitation on GHG exchange. Higher fertilization of cane contributed to greater emission of N 2 O than pasture during warmer and wetter times of the year. The model predicted that energy cane emitted more nitrogen than pasture during simulated wetter than drier years. The modeled emission factor for N 2 O was 20 to 30-fold higher than the default value from IPCC (1%), suggesting that the default IPCC value could dramatically underestimate the consequences of this land conversion on the climate system. Predicted soil CH 4 and CO 2 fluxes were higher in pasture than energy cane, and this difference was not affected by increasing precipitation. Model simulations predicted that soils under first year cane emit more GHGs than pasture, particularly during wet years, but this difference disappeared two years after energy cane establishment. Our results suggest that management practices may be important in determining soil GHG emissions from energy cane on organic soils particularly during the first year of cane establishment. [ABSTRACT FROM AUTHOR]

Intensification, the process of intensifying land management to enhance agricultural goods, results in "intensive" pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO 2 and CH 4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO 2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH 4 emissions from subtropical pastures and reduced CH 4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures. • Intensification did not increase forage productivity in subtropical pastures. • Intensification increased forage productivity in temperate pastures. • Intensification reduced supporting and regulating services in pastures. • Intensification reduced CO 2 sink capacity and increased CH 4 emissions of subtropical pastures. • Intensification increased the global warming potential associated with C fluxes in pastures. [ABSTRACT FROM AUTHOR]

[Display omitted] • Assessed common metrics with data from 34 cropland, grazing & integrated systems. • Compared production and phenology metrics from eddy covariance, PhenoCam and Landsat. • Correlations among metrics varied across diverse U.S. agroecosystems. • Devised a metric assessment framework to streamline decision making for monitoring. Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, G CC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series. Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam G CC (70.4 days, p adj < 0.0001) and EC GPP (79.6 days, p adj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam G CC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m−2 yr−1. Based on our results, we developed a "metric assessment framework" that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales. [ABSTRACT FROM AUTHOR]