Spatial analyses of pedosphere carbon stock and sequestration potential in Louisiana\u27s watersheds

This dissertation research aimed to quantify current soil organic carbon (SOC) stocks across Louisiana’s landscape, examine the spatial relationships between SOC and terrain factors at the watershed and river basin scales, and predict SOC changes in surface soils during future climate change. Using Louisiana as an example, a spatially-explicit modeling framework was developed that is conducive to watershed-scale prediction of soil carbon stock and change. SOC densities at the watershed scale were estimated using the USDA NRCS Soil Geographic Database (STATSGO). Louisiana watersheds and National Land Cover Database (NLCD) were used to aggregate total soil carbon and estimate average soil carbon density. Watershed drainage densities and slopes were quantified with 1:24 K Digital Elevation Models (DEM) data and the Louisiana hydrographic water features. Potential changes in SOC under 0.5° x 0.5° high-resolution climate change projections in Louisiana were simulated using a RothC model at a watershed scale under three greenhouse gas emissions scenarios (A1FI, A2, B2) based on the HadCM3 climate model. LIDAR and DEM datasets were used to assess the spatial distribution of potential inundated coastal areas; estimate the current wetland areas, SOC storage, and nitrogen contents at risk in Louisiana, classified by the National Wetlands Inventory (NWI) and DEM datasets. The research found that SOC density ranged from 22 to 108 tons/ha in the upper 30-cm soil at the watershed scale, with the highest density in emergent herbaceous wetlands. Among Louisiana’s 12 river basins, the Barataria, Terrebonne, and Lake Pontchartrain Basins in southeast Louisiana showed the highest SOC density. SOC density was positively correlated with watershed drainage density (r2=0.43), but negatively correlated with watershed slope gradient (r2=0.52) and elevation (r2=0.50). The modeling study on climate change effects showed that SOC storage in the top 30-cm soil layer of Louisiana forests, croplands, and grasslands would significantly decrease under all climate change scenarios. Coastal areas in southeastern Louisiana have some freshwater and estuarine wetland ecosystems that store a large quantity of organic carbon. Much of these areas have elevations less than 100 centimeters and are, therefore, prone to inundation of sea level rises during future climate change

Efficient callus induction and indirect plant regeneration from various tissues of Jatropha curcas

The Jatropha curcas is considered as an important energy plant due to the fact that its seed contains high oil content. Nowadays focus is being placed on J. curcas callus induction and plant regeneration. In this study, explants epicotyl, hypocotyl, petiole and cotyledon of 8-day-old seedlings of J. curcas were utilized for callus induction on media supplied with 1 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D), naphthyl acetic acid (NAA) or indolebutyric acid (IBA) and 0.1 mg/L kinetin (Kin), and the results demonstrated that the combination of 1 mg/L NAA and 0.1 mg/L Kin was the best medium for callus induction and growth. In addition, induced calli were transferred to regeneration medium containing different combination of auxins and cytokinins, and the data showed that the medium containing 1 mg/L thidiazuron (TDZ) and 1 mg/L Kin combined with 0.1 mg/L IBA was propitious to plant regeneration compared with other combinations.Keywords: Callus induction, indolebutyric acid, Jatropha curcas, kinetin, naphthyl acetic acid, plant regeneration, thidiazuro

A parallel numerical algorithm by combining MPI and OpenMP programming models with applications in gravity field recovery

Satellite gravimetry missions have enabled the calculation of high-accuracy and high-resolution Earth gravity field models from satellite-to-satellite tracking data and gravitational gradients. However, calculating high maximum degree/order (e.g., 240 or even higher) gravity field models using the least squares method is time-consuming due to the vast amount of gravimetry observations. To improve calculation efficiency, a parallel algorithm has been developed by combining Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) programming models to calculate and invert normal equations for the Earth gravity field recovery. The symmetrical feature of normal equations has been implemented to speed up the calculation progress and reduce computation time. For example, the computation time to generate the normal equation of an IGGT_R1 test version of degree/order 240 was reduced from 88 h to 27 h by considering the symmetrical feature. Here, the calculation was based on the high-performance computing cluster with 108 cores in the School of Geodesy and Geomatics, at Wuhan University. Additionally, the MPI parallel Gaussian-Jordan elimination method was modified to invert normal equation matrices and scaled up to 100 processor cores in this study while the traditional method was limited in a certain number of processors. Furthermore, the Cholesky decomposition from the ScaLAPACK library was used to compare with the parallel Gauss-Jordan elimination method. The numerical algorithm has effectively reduced the amount of calculation and sped up the calculation progress, and has been successfully implemented in applications such as building the gravity field models IGGT_R1 and IGGT_R1C.</p