Placement of P in a fraction of the soil volume stimulates root growth in the P‐fertilized soil. Previous research on the degree of root proliferation as related to the proportion of soil fertilized with P was conducted with soils containing similar low levels of initial resin‐exchangeable P, Csi, and hence did not evaluate the influence of Csi on the degree of root proliferation in a P‐fertilized fraction of the soil. These measurements were made as part of research to determine the fractional volume of soil to fertilize with P to maximize P uptake. The objective of this research was to investigate the influence of initial soil Csi value and rate of P added on root distribution between P‐fertilized and unfertilized soil when the P‐fertilized volume is constant. Pot experiments were conducted in a controlled‐climate facility where maize (Zea mays L.) was grown on three soils varying in Csi levels and with three rates of applied P, from 50 to 300 mg kg−1, added to 0.20 of the volume of each soil. Root density, cm cm−3, in the P‐fertilized soil volume, RDF, and a comparable 0.20 volume of unfertilized soil, RDU, was measured and compared with Csi in the P‐fertilized soil, CsiF, and in the unfertilized soil, CsiU. There was a curvilinear relation between CsiF/CsiU and RDF/ROU that was described by the equation y = 1.20 + 2.74 log x (r2 = 0.97), where y is RDF/RDU and x is CsiF/CsiU. Hence, as soil Csi level increased, RDF/RDU decreased, and as rate of P applied increased, RDF/RDU increased. The relation between CsiF/CsiU and RDF/RDU can be used to predict root growth rates to use in the fertilized and unfertilized soil when using a mechanistic nutrient‐uptake model to calculate the effect of P placement on P uptake.

Quantitative estimation of the magnitude and variability of gross primary productivity (GPP) is required to study the carbon cycle of the terrestrial ecosystem. Using ecosystem models and remotely-sensed data is a practical method for accurately estimating GPP. This study presents a method for assimilating high-quality leaf area index (LAI) products retrieved from satellite data into a process-oriented Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM) to acquire accurate GPP. The assimilation methods, including the Ensemble Kalman Filter (EnKF) and a proper orthogonal decomposition (POD)-based ensemble four-dimensional (4D) variational assimilation method (PODEn4DVar), incorporate information provided by observations into the model to achieve a better agreement between the model-estimated and observed GPP. The LPJ-POD scheme performs better with a correlation coefficient of r = 0.923 and RMSD of 32.676 gC/m 2 /month compared with the LPJ-EnKF scheme (r = 0.887, RMSD = 38.531 gC/m 2 /month) and with no data assimilation (r = 0.840, RMSD = 45.410 gC/m 2 /month). Applying the PODEn4DVar method into LPJ-DGVM for simulating GPP in China shows that the annual amount of GPP in China varied between 5.92 PgC and 6.67 PgC during 2003-2012 with an annual mean of 6.35 PgC/yr. This study demonstrates that integrating remotely-sensed data with dynamic global vegetation models through data assimilation methods has potential in optimizing the simulation and that the LPJ-POD scheme shows better performance in improving GPP estimates, which can provide a favorable way for accurately estimating dynamics of ecosystems.

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Rail transit has been playing a vital role in comprehensive transportation system, there goes without saying that rail transit will stimulate economic growth of the regions alongside railway lines, its coverage and development pattern will exert widespread and far-reaching impact on the area where railway travels through. In Xi’an-Yinchuan High-speed Railway construction setting, firstly, building an accessibility model based on the GIS platform and comparing analysis of traffic accessibility changes in the study area before and after the opening of the high-speed rail. Secondly, relying on the railway network and economic relations to establish comprehensive indicators System, build a coupling model of rail transit and regional economy in Shanxi-Gansu-Ningxia. Finally, predicting the coupling relationship between economy and transportation after the opening of high-speed rail. The experimental results show that the accessibility of cities along the line changes greatly before and after the completion of the high-speed rail. The high-speed rail line obviously promotes the economic development of the old revolutionary areas and surrounding cities along the line, and provides guiding suggestions for further improving the rapid railway network.