Tracking changes in soil organic carbon across the heterogeneous agricultural landscape of the Lower Fraser Valley of British Columbia.

Increasing soil organic carbon (SOC) can improve the capacity of agricultural systems to both adapt to and mitigate climate change. Despite its importance, the current understanding of the magnitude or even the direction of SOC change in agricultural landscapes is limited. While changes in land use/land cover (LULC) and climate are among the main drivers of changes in SOC, their relative importance for the spatiotemporal assessment of SOC is unclear. This study evaluated LULC and SOC dynamics using archived and recent soil samples, remote sensing, and digital soil mapping in the Lower Fraser Valley of British Columbia, Canada. We combined both pixel- and object-based analysis of Landsat satellite imagery to assess LULC changes from 1984 to 2018. We achieved an overall accuracy of 81% and kappa coefficient of 0.77 for LULC classification using a random forest model. For predicting SOC for the same time period, we applied soil and vegetation indices derived from Landsat images, topographic indices, historic soil survey variables, and climate data in a random forest model. The SOC prediction of 2018 resulted in a coefficient of determination (R2) of 0.67, concordance correlation coefficient (CCC) of 0.76, and normalized root mean square error (nRMSE) of 0.12. For 1984, the SOC prediction accuracies were 0.46, 0.58, and 0.18 for R2, CCC, and nRMSE, respectively. We detected SOC loss in 61%, gain in 12%, while 27% remained unchanged across the study area. Although we detected large losses of SOC due to LULC change, the majority of the SOC losses across the landscape were attributed to areas that were remained in the same type of agricultural production since 1984. Climate variability did not, however, have a strong effect on SOC changes. These results can inform decision making in the study area to support sustainable LULC management for enhancing SOC sequestration.

A population survey of members of the phylum Bacteroidetes isolated from salt marsh sediments along the east coast of the United States.

The population diversity of cultured isolates of the phylum Bacteroidetes was investigated from salt-marsh sediments. A total of 44 isolates that belonged to this phylum were isolated either from high-dilution plates or from end-dilution most-probable-number (MPN) tubes. The majority of the isolates came from Virginia, with others isolated from salt marshes in Delaware and North Carolina. All the isolates were aerobic Gram-negative, catalase positive small rods that formed uniform colonies; most had either yellow or orange pigmentation. Riboprinting of 40 isolates revealed they were genotypically diverse, consisting of 33 different riboprint patterns; there were four riboprint groups with two or more members. The isolates could be divided into 23 different fatty acid methyl ester (FAME) profiles at the species level with 14 of the profiles being unique to single isolates. One group of 10 isolates was closely related, suggesting this group may be well adapted for life in salt marshes. Thirteen of the isolates were selected for sequencing of the small-subunit ribosomal RNA gene representing a diverse group of isolates that fell within the classes Sphingobacteria and Flavobacteria. Only one of the isolates was >97% similar at the 16S rDNA to a described species of Cytophaga marinoflava; the other isolates were 94 to 96.5% related to undescribed isolates mostly within the class Flavobacteria. There was good concordance between the FAME dendrogram and a phylogenetic tree based on comparison of 16S sequences. There were no obvious temporal or spatial distribution patterns to the isolates, suggesting that this group of bacteria is inherently diverse.

A formula for comparison of selected sport ball compressibility.

The purpose of this study was to develop a formula to determine and compare the compressibility of selected sport balls. Six balls (basketball, volleyball, soccer ball, baseball, handball, golf ball) were dropped ten times from each of four different heights onto a smooth solid surface overlaid with a white sheet of typing paper, overlaid with a sheet of carbon paper. The diameter of the area of contact of each ball imprinted onto the typing paper was measured in millimetres with calipers. From the data, the distance (d) that each ball compressed for each velocity (v) was calculated. It was found that a linear relationship existed between velocity at impact and the distance for each ball studied. The compressibility coefficient (c) for each ball was calculated and a formula was developed to determine the distance each ball would compress at a given velocity. When velocity is measured in metres per second and the distance a ball compresses is measured in millimetres, the formula to determine d for selected balls, in order of compressibility is: basketball d = 3.07v, volleyball d = 2.90v, soccer ball d = 2.80v, baseball d = 0.77v, handball d = 0.53v, and golf ball d = 0.17v.

The computer-based anesthetic monitors: the Duke Automatic Monitoring Equipment (DAME) system and the microDAME.

From 1972 to 1983 the Duke University Department of Anesthesiology designed, built, and maintained most of its own operating room patient monitoring equipment. Construction of a new hospital facility in 1980 provided the opportunity to design and test a new computer-based system, the Duke Automatic Monitoring Equipment (DAME) System. The system consist of microcomputer-based instrumentation on monitoring carts, which communicate with a central minicomputer that allows selection of different software monitoring packages based on the needs of the patient. Multiple problems, including frequent total monitoring failures during surgery, plagued the DAME System in its first year of operation. Despite resolution of many of these problems, user acceptance was poor because of the large size and weight of the monitoring carts, the inadequate quality of displayed physiological waveforms, and inability to overcome the difficulties of the man-machine interface. Because the remaining problems could not be rectified with the existing monitoring carts, a new generation of monitors was designed. The smaller, multiprocessor microDAME was designed to be as automatic and user tolerant as possible. It would omit much of the flexibility that had proved undesirable in the DAME system. When the microDAME was nearly completed, however, departmental research in that area ceased. It remains for others to apply our experiences to further improve operating room patient monitors.