Levels of 2,3,7,8-Tetrachlorodibenzo- -dioxin (2,3,7,8-TCDD) in adipose tissue of U.S. Vietnam veterans seeking medical assistance

2,3,7,8-Tetrachlorodibenzo- -dioxin (2,3,7,8-TCDD) was detected in an earlier study in adipose tissue of U.S. veterans who were exposed to Agent Orange in Vietnam. The levels appear to be directly related to the intensity of exposure¹. We now report on a group of thirteen Vietnam veterans who were screened for 2,3,7,8-TCDD in adipose tissue. All the veterans had sought medical assistance and some had health effects that may be ascribed to exposure to 2,3,7,8-TCDD. Also included are control patients who were taken from the population of the U.S. 2,3,7,8-TCDD was detected in most of the adipose tissue samples at levels ranging from 2 to 14 ppt. No significant differences in the tissue levels of Vietnam veterans and the other persons were found in this preliminary study.     

WATER QUALITY OF AN INTENSWE AGRICULTURAL WATERSHED IN QUEBEC1

ABSTRACT: . Under a watershed based approach being examined by the Quebec Ministry of Agriculture to accelerate the adoption of conservation practices, a study on the impacts of agricultural practices on the St. Esprit watershed was initiated in the fall of 1993. The water quality of this 26 km² intensive agricultural watershed was studied over an 18 month period. Water samples taken at the outlet of the watershed were analyzed for nitrate, phosphate, suspended sediment, and atrazine. Water quality data were analyzed to establish seasonal trends in pollutant concentration and load in the watercourse. Spring snowmelt was identified as a significant period of pollutant material export. All pollutant materials displayed seasonal variability in the export process. Peak pollutant concentrations were associated with high flow events. Mean observed pollutant concentrations did not exceed drinking water quality standards.     

Automated detection of frog calls and choruses by pulse repetition rate

Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call-recognition method for anurans must be robust to the challenges of real-world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval-based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog (Pseudacris maculata) of temperate North American grasslands and the critically endangered variable harlequin frog (Atelopus varius) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open-source implementations of RIBBIT in Python and R to support its use for other taxa and communities.