Effects of topography on simulated net primary productivity at landscape scale

Local topography significantly affects spatial variations of climatic variables and soil water movement in complex terrain. Therefore, the distribution and productivity of ecosystems are closely linked to topography. Using a coupled terrestrial carbon and hydrological model (BEPS-TerrainLab model), the topographic effects on the net primary productivity (NPP) are analyzed through four modelling experiments for a 5700 km(2) area in Baohe River basin, Shaanxi Province, northwest of China. The model was able to capture 81% of the variability in NPP estimated from tree rings, with a mean relative error of 3.1%. The average NPP in 2003 for the study area was 741 gCm(-2)yr(-1) from a model run including topographic effects on the distributions of climate variables and lateral flow of ground water. Topography has considerable effect on NPP, which peaks near 1350 m above the sea level. An elevation increase of 100 m above this level reduces the average annual NPP by about 25 gCm(-2). The terrain aspect gives rise to a NPP change of 5% for forests located below 1900 m as a result of its influence on incident solar radiation. For the whole study area, a simulation totally excluding topographic effects on the distributions of climatic variables and ground water movement overestimated the average NPP by 5%.     

Topographical imaging as a means of monitoring biodegradation of poly(hydroxyalkanoate) films

Poly(hydroxyalkanoates) (PHAs) are a class of bacterially-derived polymers that are naturally biodegradable through the action of extracellular depolymerase enzymes secreted by a number of different bacteria and fungi. In this paper we describe the development of topographical imaging protocols (by both scanning electron microscopy; SEM, and confocal microscopy; CM) as a means of monitoring the biodegradation of solution cast films of poly(3-hydroxybutanoate-co-3-hydroxyhexanoate) (P3HB/3HHx) and medium-chain-length (mcl-) PHA. Pseudomonas lemoignei and Comamonas P37C were used as sources for PHA depolymerase enzymes as these bacteria are known to degrade at least one of the polymers in question. SEM revealed the bacterial colonization of the film surfaces while CM permitted the comparative assessment of the roughness of the film surfaces upon exposure to the two bacterial strains. By dividing the total surface area of the film (A′) by the total area of the scan (A) it was possible to monitor biodegradation by observing differences in the topography of the film surface. Prior to inoculation, P3HB/3HHx films had an A′/A ratio of 1.06. A 24-h incubation with P. lemoignei increased the A′/A ratio to 1.47 while a 48- and 120-h incubation with Comamonas resulted in A′/A ratios of 1.16 and 1.33, respectively. These increases in the A′/A ratios over time demonstrated an increase in the irregularity of the film surface, indicative of PHA polymer breakdown. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Interpolating SRTM Elevation Data to Higher Resolution to Improve Hydrologic Analysis

The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) has been a valuable resource for hydrological analysis, providing elevation data at a consistent resolution on a near‐global scale. However, its resolution (three arc‐second or 90 m) is sometimes too low to obtain the desired level of accuracy and precision for hydrologic analysis. We evaluated the performance of several methods for interpolating SRTM three arc‐second data to a 30‐m resolution grid to better represent topography and derive terrain characteristics of the landscape. STRM data were interpolated to 30‐m DEMs on a common grid using spline, inverse distance weighting (IDW), kriging (KR), natural neighbor methods, and cubic convolution (CC) resampling. Accuracy of the methods was assessed by comparing interpolated and resampled 30‐m grids with the reference data. Slope, aspect, sinks, and stream networks were derived for the 30‐m grids and compared on a cell‐by‐cell basis to evaluate their performance in reproducing the derivatives. The comparisons identify spline and KR as the most accurate interpolation methods, of which spline is preferred because of its relative simplicity. IDW provided the greatest bias in all methods with artifacts evident in slope and aspect maps. The performance of CC projection directly to a 30‐m resolution was comparable to spline interpolation, thus is recommended as the most convenient method for interpolating SRTM to a higher resolution.