Soil organic carbon (SOC) concentration is a useful soil property with which to guide agricultural applications of chemical inputs. To enable this, simple, accurate, rapid and inexpensive methods are needed to produce maps of surface SOC concentrations. Researchers have investigated estimates of soil surface properties from remotely sensed information as a means of rapidly quantifying and monitoring some surface soil properties, such as SOC. The objective of this paper is to review the potential and limitations of remotely sensed data for mapping and evaluating SOC. Several statistical methods including simple regression models, the 'soil line' approach, principal component analysis and geostatistics have been applied to data to investigate the accuracy of such estimates. A review of the literature shows that predictive equations are not universal and require new regression models for every scene. An important benefit of remotely sensed data is to suggest a sampling strategy that can lead to improved representation of spatial heterogeneity in SOC.

The use of cover crops is a management technique that can potentially increase the amount of carbon (C) sequestered in soil. However, information on cover crop's role in increasing soil C comes mostly from small experimental plots, while the magnitude of C gains in large agricultural fields may vary spatially in response to topographic and soil

Active fractions of soil C such as particulate organic C (POC) and short‐term mineralizable C (SMC) respond faster than total organic C (TOC) to management induced changes in soil C. However, the active fractions of organic C can possibly have larger variability that decreases the detectability of management effects on soil C. The objectives of this study were to (i) assess the relative usefulness of TOC, POC, and SMC as criteria of management induced changes on soil C and (ii) investigate if using auxiliary soil and topographical information can aid in increasing the usefulness of these criteria in studies conducted across large spatial scales. Data were collected at locations with two contrasting topographical positions (slope and depression) within 10 agricultural fields in conventional and cover crop based row crop managements at the 0‐ to 20‐, 35‐ to 50‐, and 70‐ to 90‐cm depths. The results showed that to detect differences between the management systems with an acceptable type II error of 0.20, an 80% difference in TOC and a 50% difference in SMC were needed. The statistical power for POC was never in an acceptable range. The use of auxiliary soil and topography information via analysis of covariance decreased the sizes of the minimal detectable differences. Given the faster reaction to management of SMC as compared with TOC, and its lower variability as compared with POC, we recommend SMC as the preferred C fraction for detecting treatment induced differences in organic C stocks in agricultural field experiments, especially in deeper soil layers.

Supplying adequate amounts of soil N for plant growth during the growing season and across large agricultural fields is a challenge for conservational agricultural systems with cover crops. Knowledge about cover crop effects on N comes mostly from small, flat research plots and performance of cover crops across topographically diverse agricultural land is poorly understood. Our objective was to assess effects of both leguminous (red clover) and non-leguminous (winter rye) cover crops on potentially mineralizable N (PMN) and levels across a topographically diverse landscape. We studied conventional, low-input, and organic managements in corn-soybean-wheat rotation. The rotations of low-input and organic managements included rye and red clover cover crops. The managements were implemented in twenty large undulating fields in Southwest Michigan starting from 2006. The data collection and analysis were conducted during three growing seasons of 2011, 2012 and 2013. Observational micro-plots with and without cover crops were laid within each field on three contrasting topographical positions of depression, slope and summit. Soil samples were collected 4–5 times during each growing season and analyzed for and PMN. The results showed that all three managements were similar in their temporal and spatial distributions of NO3 —N. Red clover cover crop increased by 35% on depression, 20% on slope and 32% on summit positions. Rye cover crop had a significant 15% negative effect on in topographical depressions but not in slope and summit positions. The magnitude of the cover crop effects on soil mineral nitrogen across topographically diverse fields was associated with the amount of cover crop growth and residue production. The results emphasize the potential environmental and economic benefits that can be generated by implementing site-specific topography-driven cover crop management in row-crop agricultural systems.

members of the same organization that responded to a targeted email blast. Measures: We adapted the comprehension portion of ISO 9186-1: 2007 to test 38 standardized symbols developed for the medical device industry. Participants were asked to provide an open-ended response regarding the meaning of each symbol. Survey responses were categorized into five levels of comprehension: correct, wrong, opposite, don't know or no response. Symbols receiving response rates of ≥85% in the correct category were considered successful. Conversely, if responses categorized as opposite were ≥5%, symbols were considered 'critically confusing.' Main Results: Six of 38 symbols were classified as 'successful'; five of the six had text (in English) imbedded within. Three out of the 38 were categorized as 'critically confusing'; they were not only misunderstood, but, in fact, interpreted to mean the opposite of what was intended by ≥5% of participants surveyed. Conclusions: Given that the medical device industry in the US has requested permission from the US Food and Drug Administration (FDA) to use stand-alone symbols to better harmonize with EU Directives, the exploration of healthcare providers' comprehension of the same is an important and timely topic. Our work suggests that symbols commonly incorporated into the labeling of medical devices may not be readily understood at present. As such, policy decisions should be carefully considered. Limitations: Although we provided participants with a general context of use (i.e. these symbols are used on medical devices), the specific part of the hospital, or type of procedure where the symbol would be found was not noted. Further research to evaluate symbol comprehension with specific context (e.g. IVD, general procedure, etc.) is recommended.Run order was presented consistently throughout the experiment in the same booklet. We tested whether or not this impacted results in two ways: (a) by correlating run order with mean performance to see if there was a trend through the data (toward improvement or decline) and (b) by assuming repeated measures from subjects to test if the subject response changes with time. Neither of these analyses suggested significant effects because of run order.