Integrating future scenario-based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA

Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario-based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long-term (1981– 2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km2 of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km2 (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) andmay result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystemservices is preferred. The 30-mLandsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. Themain goal of this study is to develop a 30-mgrassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based onMODIS and Landsat (r=0.91)was developed, and a 30-mMODIS equivalent GSN mapwas generated. Finally, a 30-mgrassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass productionmap andwill be useful for regional ecosystemstudy and local land management practices

Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States

Growing cellulosic feedstock crops (e.g., switchgrass) for biofuel is more environmentally sustainable than cornbased ethanol. Specifically, this practice can reduce soil erosion and water quality impairment from pesticides and fertilizer, improve ecosystem services and sustainability (e.g., serve as carbon sinks), and minimize impacts on global food supplies. The main goal of this study was to identify high-risk marginal croplands that are potentially suitable for growing cellulosic feedstock crops (e.g., switchgrass) in the US Great Plains (GP). Satellitederived growing season Normalized Difference Vegetation Index, a switchgrass biomass productivity map obtained from a previous study, US Geological Survey (USGS) irrigation and crop masks, and US Department of Agriculture (USDA) crop indemnity maps for the GP were used in this study. Our hypothesis was that croplands with relatively low crop yield but high productivity potential for switchgrass may be suitable for converting to switchgrass. Areas with relatively low crop indemnity (crop indemnity \u3c$2 157 068) were excluded from the suitable areas based on low probability of crop failures. Results show that approximately 650 000 ha of marginal croplands in the GP are potentially suitable for switchgrass development. The total estimated switchgrass biomass productivity gain from these suitable areas is about 5.9 million metric tons. Switchgrass can be cultivated in either lowland or upland regions in the GP depending on the local soil and environmental conditions. This study improves our understanding of ecosystem services and the sustainability of cropland systems in the GP. Results from this study provide useful information to land managers for making informed decisions regarding switchgrass development in the GP

Influence of management and precipitation on carbon fluxes in Great Plains grasslands

Suitable management and sufficient precipitation on grasslands can provide carbon sinks. The net carbon accumulation of a site from the atmosphere, modeled as the Net Ecosystem Productivity (NEP), is a useful means to gauge carbon balance. Previous research has developed methods to integrate flux tower data with satellite biophysical datasets to estimate NEP across large regions. A related method uses the Ecosystem Performance Anomaly (EPA) as a satellite-derived indicator of disturbance intensity (e.g., livestock stocking rate, fire, and insect damage). To better understand the interactions among management, climate, and carbon dynamics, we evaluated the relationship between EPA and NEP data at the 250 m scale for grasslands in the Central Great Plains, USA (ranging from semi-arid to mesic). We also used weekly estimates of NEP to evaluate the phenology of carbon dynamics, classified by EPA (i.e., by level of disturbance impact). Results show that the cumulative carbon balance over these grasslands from 2000 to 2008 was a weak net sink of 13.7 g C m−2 yr−1. Overall, NEP increased with precipitation (R2 = 0.39, P \u3c 0.05) from west to east. Disturbance influenced NEP phenology; however, climate and biophysical conditions were usually more important. The NEP response to disturbance varies by ecoregion, and more generally by grassland type, where the shortgrass prairie NEP is most sensitive to disturbance, the mixed-grass prairie displays a moderate response, and tallgrass prairie is the least impacted by disturbance (as measured by EPA). Sustainable management practices in the tallgrass and mixed-grass prairie may potentially induce a period of average net carbon sink until a new equilibrium soil organic carbon is achieved. In the shortgrass prairie, management should be considered sustainable if carbon stocks are simply maintained. The consideration of site carbon balance adds to the already difficult task of managing grasslands appropriately to site conditions. Results clarify the seasonal and interannual dynamics of NEP, specifically the influence of disturbance and moisture availability

Evaluation of Carbon Fluxes and Trends (2000e2008) in the Greater Platte River Basin: A Sustainability Study for Potential Biofuel Feedstock Development

This study evaluates the carbon fluxes and trends and examines the environmental sustainability (e.g., carbon budget, source or sink) of the potential biofuel feedstock sites identified in the Greater Platte River Basin (GPRB). A 9-year (2000e2008) time series of net ecosystem production (NEP), a measure of net carbon absorption or emission by ecosystems, was used to assess the historical trends and budgets of carbon flux for grasslands in the GPRB. The spatially averaged annual NEP (ANEP) for grassland areas that are possibly suitable for biofuel expansion (productive grasslands) was 71e169 g C m2 year1 during 2000e2008, indicating a carbon sink (more carbon is absorbed than released) in these areas. The spatially averaged ANEP for areas not suitable for biofuel feedstock development (less productive or degraded grasslands) was 47 to 69 g C m2 year1 during 2000e2008, showing a weak carbon source or a weak carbon sink (carbon emitted is nearly equal to carbon absorbed). The 9-year pre-harvest cumulative ANEP was 1166 g C m2 for the suitable areas (a strong carbon sink) and 200 g C m2 for the non-suitable areas (a weak carbon sink). Results demonstrate and confirm that our method of dynamic modeling of ecosystem performance can successfully identify areas desirable and sustainable for future biofuel feedstock development. This study provides useful information for land managers and decision makers to make optimal land use decisions regarding biofuel feedstock development and sustainability

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes ( Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rn were measured with a Bowen ratio–energy balance (BREB) technique in a sagebrush (Artemisia spp.)–steppe ecosystem in northeast Idaho, USA, during 1996–1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996–1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday (R2= 0.79, n = 66, P \u3c 0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of Fday (R2= 0.82, n = 66, P \u3c 0.0001). Cross-validation indicated that regression tree predictions of Fday were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted Rn quite well (R2 = 0.75–0.77, n = 66) with the regression tree model being slightly more robust in cross-validation. Temporal mapping of Fday and Rn is possible with these techniques and would allow the assessment of NEE in sagebrush–steppe ecosystems. Simulations of periodic Fday measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict Fday. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models

Monitoring Drought Impact on Annual Forage Production in Semi-Arid Grasslands: A Case Study of Nebraska Sandhills

Land management practices and disturbances (e.g. overgrazing, fire) have substantial effects on grassland forage production. When using satellite remote sensing to monitor climate impacts, such as drought stress on annual forage production, minimizing land management practices and disturbance effects sends a clear climate signal to the productivity data. This study investigates the effect of this climate signal by: (1) providing spatial estimates of expected biomass under specific climate conditions, (2) determining which drought indices explain the majority of interannual variability in this biomass, and (3) developing a predictive model that estimates the annual biomass early in the growing season. To address objective 1, this study uses an established methodology to determine Expected Ecosystem Performance (EEP) in the Nebraska Sandhills, US, representing annual forage levels after accounting for non-climatic influences. Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Dierence Vegetation Index (NDVI) data were used to approximate actual ecosystem performance. Seventeen years (2000–2016) of annual EEP was calculated using piecewise regression tree models of site potential and climate data. Expected biomass (EB), EEP converted to biomass in kg*ha-1*yr-1, was then used to examine the predictive capacity of several drought indices and the onset date of the growing season. Subsets of these indices were used to monitor and predict annual expected grassland biomass. Independent field-based biomass production data available from two Sandhills locations were used for validation of the EEP model. The EB was related to field-based biomass production (R2 = 0.66 and 0.57) and regional rangeland productivity statistics of the Soil Survey Geographic Database (SSURGO) dataset. The Evaporative Stress Index (ESI), the 3- and 6-month Standardized Precipitation Index (SPI), and the U.S. Drought Monitor (USDM), which represented moisture conditions during May, June and July, explained the majority of the interannual biomass variability in this grassland system (three-month ESI explained roughly 72% of the interannual biomass variability). A new model was developed to use drought indices from early in the growing season to predict the total EB for the whole growing season. This unique approach considers only climate-related drought signal on productivity. The capability to estimate annual EB by the end of May will potentially enable land managers to make informed decisions about stocking rates, hay purchase needs, and other management issues early in the season, minimizing their potential drought losses

Airborne electromagnetic imaging of discontinuous permafrost

The evolution of permafrost in cold regions is inextricably connected to hydrogeologic processes, climate, and ecosystems. Permafrost thawing has been linked to changes in wetland and lake areas, alteration of the groundwater contribution to stream flow, carbon release, and increased fire frequency. But detailed knowledge about the dynamic state of permafrost in relation to surface and groundwater systems remains an enigma. Here, we present the results of a pioneering ~1,800 line-kilometer airborne electromagnetic survey that shows sediments deposited over the past ~4 million years and the configuration of permafrost to depths of ~100 meters in the Yukon Flats area near Fort Yukon, Alaska. The Yukon Flats is near the boundary between continuous permafrost to the north and discontinuous permafrost to the south, making it an important location for examining permafrost dynamics. Our results not only provide a detailed snapshot of the present-day configuration of permafrost, but they also expose previously unseen details about potential surface – groundwater connections and the thermal legacy of surface water features that has been recorded in the permafrost over the past 1,000 years. This work will be a critical baseline for future permafrost studies aimed at exploring the connections between hydrogeologic, climatic, and ecological processes, and has significant implications for the stewardship of Arctic environments

Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands

The ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of its changes to climate variability. The current study validates the applicability of this approach for assessment of seasonal and interannual climate impacts on forage production in the western United States semi-arid grasslands. Using a piecewise regression tree model, we developed the Expected Ecosystem Performance (EEP), a proxy for annual forage production that reflects climatic influences while minimizing impacts of management and disturbances. The EEP model establishes relations between seasonal climate, site-specific growth potential, and long-term growth variability to capture changes in the growing season greenness measured via a time-integrated Normalized Difference Vegetation Index (NDVI) observed using a Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting 19 years of EEP were converted to expected biomass (EB, kg ha-1 year-1) using a newly-developed relation with the Soil Survey Geographic Database range production data (R2= 0.7). Results were compared to ground-observed biomass datasets collected by the U.S. Department of Agriculture and University of Nebraska-Lincoln (R2 = 0.67). This study illustrated that this approach is transferable to other semi-arid and arid grasslands and can be used for creating timely, post-season forage production assessments. When combined with seasonal climate predictions, it can provide within-season estimates of annual forage production that can serve as a basis for more informed adaptive decision making by livestock producers and land managers