Joint Global Change Research Institute

About: Joint Global Change Research Institute is a facility organization based out in Riverdale Park, Maryland, United States. It is known for research contribution in the topics: Greenhouse gas & Climate change. The organization has 197 authors who have published 934 publications receiving 62390 citations.

Management opportunities for enhancing terrestrial carbon dioxide sinks

Abstract: The potential for mitigating increasing atmospheric carbon dioxide concentrations through the use of terrestrial biological carbon (C) sequestration is substantial. Here, we estimate the amount of C being sequestered by natural processes at global, North American, and national US scales. We present and quantify, where possible, the potential for deliberate human actions – through forestry, agriculture, and use of biomass-based fuels – to augment these natural sinks. Carbon sequestration may potentially be achieved through some of these activities but at the expense of substantial changes in land-use management. Some practices (eg reduced tillage, improved silviculture, woody bioenergy crops) are already being implemented because of their economic benefits and associated ecosystem services. Given their cumulative greenhouse-gas impacts, other strategies (eg the use of biochar and cellulosic bioenergy crops) require further evaluation to determine whether widespread implementation is warranted.

Estimating crop net primary production using national inventory data and MODIS-derived parameters

Abstract: National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux between land and atmosphere. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale as well as national and continental scales. Existing satellite-based NPP products tend to underestimate NPP on croplands. An Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP over large multi-state regions. The method is documented here and evaluated for corn ( Zea mays L.) and soybean ( Glycine max L. Merr.) in Iowa and Illinois in 2006 and 2007. The method includes a crop-specific Enhanced Vegetation Index (EVI), shortwave radiation data estimated using the Mountain Climate Simulator (MTCLIM) algorithm, and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that corresponds to the Cropland Data Layer (CDL) land cover product. Results from the modeling framework captured the spatial NPP gradient across croplands of Iowa and Illinois, and also represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 917 g C m −2 yr −1 and 409 g C m −2 yr −1 , respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Site comparisons with flux tower data show AgI-LUE NPP in close agreement with tower-derived NPP, lower than inventory-based NPP, and higher than MOD17A3 NPP. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.