## 5 Conclusions  
In this study, regression tree models were developed to estimate weekly mean daily NEP for grassland and cropland of the U.S. Great Plains for the period 2000-2008. In collecting applicable, supporting flux tower data for the study area and time frame, the final sample for mapping NEP across select grassland and cropland in the U.S. Great Plains consisted of 76 site years of flux tower data. The modeling methodology used in this study exhibited the capability for quantifying NEP at the regional level. However, a more robust flux tower network for model sampling would have been ideal for this study and several areas were identified as possible candidates for future flux tower development to better serve environmental model developers and the carbon cycle science community. The models were applied to create weekly NEP maps at 250 m resolution for much of the cropland and grassland ecosystems in the U.S. Great Plains. Heavily used spatial inputs in the mapping models were weekly NDVI, weekly PAR, and time of year inputs (Week or DOY). The resulting map products were scaled and summarized at various temporal and spatial units and the two different land cover types were considered in a statistical, comparative analysis. Grass and cropland NEP magnitudes were similar when comparing inter-annual values. Corn and alfalfa had the strongest C stock of all the crops in this study. Grasslands showed stronger C sink tendencies (139 g\(\cdot\)m\({}^{-2}\cdot\)year\({}^{-1}\)) more at the 2000-2008 NEP equilibrium than non-irrigated croplands across the moisture and productivity gradients of the Great Plains. Grassland 2000-2008 equilibrium NEP was expected to occur near 373 mm of annual precipitation from the 30-year climate record. Non-irrigated crop 2000-2008 equilibrium NEP was expected at an annual 30-year climate precipitation of 629 mm. Typically, grasslands are subject to minimal management and the soil is generally left alone, apart from occasional weed control, animal grazing, and cutting. Croplands, meanwhile, are commonly managed to control pests and weeds from the time the seed is drilled into the soil until harvest, followed by tilling, and applications of fertilizer. Higher spring and fall C retention levels in cropland soils might be observed if a cover crop was introduced to minimize soil exposure and erosion. The maps and statistics presented in this study provide a framework and basic overview of C fluctuations in the U.S. Great Plains throughout the 2000-2008 time frame. This effort is expected to be continued and to be expanded to include cropland and grassland for the entire conterminous U.S. and possibly include NEP estimates for additional years and/or other land cover types, such as forests and shrublands. Understanding and being able to visualize the carbon cycling as a function of land cover and land use will help drive decision making in the area of land management and promote natural resource sustainability. **Supplementary Materials:** The following are available online at www.mdpi.com/2072-4292/8/11/944/s1, Table S1: A complete list of the grassland and cropland flux towers used in the development of the NEP models. Table S2: Regression tree mapping model for crop NEP. Table S3: Regression tree mapping model for grass NEP. Table S4: Crop type and grass mean weekly NEP (data for Figure 11). Figure S1: A flow chart of the NEP regression tree model development. Starting in the upper left, (A) the flux tower NEP records (dependent variable) and the input spatial data (independent variables) are spatially linked to associate each flux tower site with the input values at each point. This information is stored in a data base (B) for ingestion into model training. The fully developed model is then applied on a pixel-by-pixel basis to estimate NEP by reading in the full set of spatial independent variables and following the model rules (C). The results are the weekly NEP maps (D). Figure S2: Majority land cover of the U.S. Great Plains during 2000-2008.