,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85547. In a 10-year study, we assessed the influence of five carbon (C) treatments on the labile C and nitrogen (N) pools of historically N enriched plots on the Shortgrass Steppe Long Term Ecological Research site located in northeastern Colorado. For eight years, we applied sawdust, sugar, industrial lignin, sawdust + sugar, and lignin + sugar to plots that had received N and water additions in the early 1970s. Previous work showed that past water and N additions altered plant species composition and enhanced rates of nutrient cycling; these effects were still apparent 25 years later. We hypothesized that labile C amendments would stimulate microbial activity and suppress rates of N mineralization, whereas complex forms of carbon (sawdust and lignin) could enhance humification and lead to longer-term reductions in N availability. Results indicated that of the five carbon treatments, sugar, sawdust, and sawdust + sugar suppressed N availability, with sawdust + sugar being the most effective treatment to reduce N availability. The year after treatments stopped, N availability remained less in the sawdust + sugar treatment plots than in the high-N control plots. Three years after treatments ended, reductions in N availability were smaller (40-60%). Our results suggest that highly labile forms of carbon generate strong short- term N sinks, but these effects dissipate within one year of application, and that more recalcitrant forms reduce N longer. Sawdust + sugar was the most effective treatment to decrease exotic species canopy cover and increase native species density over the long term. Labile carbon had neither short- nor long-term effects on exotic species. Even though the organic amendments did not contribute to recovery of the dominant native species Bouteloua gracilis, they were effective in increasing another native species, Carex eleocharis. These results indicate that organic amendments may be a useful tool for restoring some native species in the shortgrass steppe.,,

,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. In a 10-year study, we assessed the influence of five carbon (C) treatments on the labile C and nitrogen (N) pools of historically N enriched plots on the Shortgrass Steppe Long Term Ecological Research site located in northeastern Colorado. For eight years, we applied sawdust, sugar, industrial lignin, sawdust + sugar, and lignin + sugar to plots that had received N and water additions in the early 1970s. Previous work showed that past water and N additions altered plant species composition and enhanced rates of nutrient cycling; these effects were still apparent 25 years later. We hypothesized that labile C amendments would stimulate microbial activity and suppress rates of N mineralization, whereas complex forms of carbon (sawdust and lignin) could enhance humification and lead to longer-term reductions in N availability. Results indicated that of the five carbon treatments, sugar, sawdust, and sawdust + sugar suppressed N availability, with sawdust + sugar being the most effective treatment to reduce N availability. The year after treatments stopped, N availability remained less in the sawdust + sugar treatment plots than in the high-N control plots. Three years after treatments ended, reductions in N availability were smaller (40-60%). Our results suggest that highly labile forms of carbon generate strong short- term N sinks, but these effects dissipate within one year of application, and that more recalcitrant forms reduce N longer. Sawdust + sugar was the most effective treatment to decrease exotic species canopy cover and increase native species density over the long term. Labile carbon had neither short- nor long-term effects on exotic species. Even though the organic amendments did not contribute to recovery of the dominant native species Bouteloua gracilis, they were effective in increasing another native species, Carex eleocharis. These results indicate that organic amendments may be a useful tool for restoring some native species in the shortgrass steppe.,,

,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85547. In a 10-year study, we assessed the influence of five carbon (C) treatments on the labile C and nitrogen (N) pools of historically N enriched plots on the Shortgrass Steppe Long Term Ecological Research site located in northeastern Colorado. For eight years, we applied sawdust, sugar, industrial lignin, sawdust + sugar, and lignin + sugar to plots that had received N and water additions in the early 1970s. Previous work showed that past water and N additions altered plant species composition and enhanced rates of nutrient cycling; these effects were still apparent 25 years later. We hypothesized that labile C amendments would stimulate microbial activity and suppress rates of N mineralization, whereas complex forms of carbon (sawdust and lignin) could enhance humification and lead to longer-term reductions in N availability. Results indicated that of the five carbon treatments, sugar, sawdust, and sawdust + sugar suppressed N availability, with sawdust + sugar being the most effective treatment to reduce N availability. The year after treatments stopped, N availability remained less in the sawdust + sugar treatment plots than in the high-N control plots. Three years after treatments ended, reductions in N availability were smaller (40-60%). Our results suggest that highly labile forms of carbon generate strong short- term N sinks, but these effects dissipate within one year of application, and that more recalcitrant forms reduce N longer. Sawdust + sugar was the most effective treatment to decrease exotic species canopy cover and increase native species density over the long term. Labile carbon had neither short- nor long-term effects on exotic species. Even though the organic amendments did not contribute to recovery of the dominant native species Bouteloua gracilis, they were effective in increasing another native species, Carex eleocharis. These results indicate that organic amendments may be a useful tool for restoring some native species in the shortgrass steppe.,,

This dataset provides estimates of carbon pools, fluxes, and associated uncertainties across the contiguous USA (CONUS) at 0.5-degree resolution for all terrestrial land cover types. Carbon pools include labile carbon, foliar carbon, fine root, woody carbon, litter carbon, and soil organic carbon. Carbon fluxes include gross primary production (GPP), net primary production (NPP), net biome exchange, autotrophic respiration, and heterotrophic respiration. The modeled estimates are provided as monthly averages over the 16-year period, 2001 through 2016. The data were derived from the CARbon DAta MOdel fraMework (CARDAMOM) that included climate data, and above and below ground biomass maps of CONUS for the years 2005, 2010, 2015 and 2016 as input data sources to this model-data fusion framework. The input data were integrated into the CARDAMOM model to constrain on the terrestrial carbon and to specifically attribute changes of forest carbon stocks and spatial distributions of carbon emissions and removals across forested lands. United States Forest Service's Forest Inventory and Analysis (FIA) plot data were used to train models for the prediction of forest above-ground biomass (AGB).

,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. Carbon isotopes of elevated and ambient OTC plants were measured for use in isotope labeling and plant water-use-efficiency measures. Leaf N and C are associated parameters were also measured. This research was conducted at the Central Plains Experimental Range, near Nunn, CO; lat.40degrees 40 minutes N; long. 104 degrees 45 minutes W in the shortgrass steppe region of NE Colorado, USA and as a collaboration between SGS-LTER and USDA-ARS researchers.,,

,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. At the end of the 5-year OTC study, root cores were taken from ambient and elevated-CO2-chambered plots and unchambered controls and sectioned at 10cm intervals for root scanning and weighing. There was a trend for higher root weight under elevated CO2, which corresponded to greater root length, but only in the 0-10cm depth interval. This research was conducted at the Central Plains Experimental Range, near Nunn, CO; lat.40degrees 40 minutes N; long. 104 degrees 45 minutes W in the shortgrass steppe region of NE Colorado, USA and as a collaboration between SGS-LTER and USDA-ARS researchers.,,

Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.

Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.