New media (S1 and S2) were formulated that provide a high degree of selectivity and detection of fluorescent pseudomonads on initial plating. The selectivity of the S-type media was based on a detergent, sodium lauroyl sarcosine, and an antibiotic, trimethoprim. A total of five soils from different geographical locations and one sewage sludge sample were examined. On S1 medium, isolates from two soils with low fluorescent pseudomonad populations exhibited a high frequency of arginine dihydrolase (78%) and oxidase-positive (95%) phenotypes, but no fermentative isolates were recovered. Medium S2 was more defined and selective than S1, but lower numbers of fluorescent pseudomonads were recovered on S2. In soils in which fluorescent pseudomonads represent a small proportion of the total population, S1 medium consistently recovered high percentages of fluorescent phenotypes (82.5%).

Nonpoint sources of pollution that contribute fecal bacteria to surface waters have proven difficult to identify. Knowledge of pollution sources could aid in restoration of the water quality, reduce the amounts of nutrients leaving watersheds, and reduce the danger of infectious disease resulting from exposure to contaminated waters. Patterns of antibiotic resistance in fecal streptococci were analyzed by discriminant and cluster analysis and used to identify sources of fecal pollution in a rural Virginia watershed. A database consisting of patterns from 7,058 fecal streptococcus isolates was first established from known human, livestock, and wildlife sources in Montgomery County, Va. Correct fecal streptococcus source identification averaged 87% for the entire database and ranged from 84% for deer isolates to 93% for human isolates. To field test the method and the database, a watershed improvement project (Page Brook) in Clarke County, Va., was initiated in 1996. Comparison of 892 known-source isolates from that watershed against the database resulted in an average correct classification rate of 88%. Combining all animal isolates increased correct classification rates to ≥95% for separations between animal and human sources. Stream samples from three collection sites were highly contaminated, and fecal streptococci from these sites were classified as being predominantly from cattle (>78% of isolates), with small proportions from waterfowl, deer, and unidentified sources (≈7% each). Based on these results, cattle access to the stream was restricted by installation of fencing and in-pasture watering stations. Fecal coliforms were reduced at the three sites by an average of 94%, from prefencing average populations of 15,900 per 100 ml to postfencing average populations of 960 per 100 ml. After fencing, <45% of fecal streptococcus isolates were classified as being from cattle. These results demonstrate that antibiotic resistance profiles in fecal streptococci can be used to reliably determine sources of fecal pollution, and water quality improvements can occur when efforts to address the identified sources are made.

Microbial source tracking (MST) uses various approaches to classify fecal-indicator microorganisms to source hosts. Reproducibility, accuracy, and robustness of seven phenotypic and genotypic MST protocols were evaluated by use of Escherichia coli from an eight-host library of known-source isolates and a separate, blinded challenge library. In reproducibility tests, measuring each protocol's ability to reclassify blinded replicates, only one (pulsed-field gel electrophoresis; PFGE) correctly classified all test replicates to host species; three protocols classified 48-62% correctly, and the remaining three classified fewer than 25% correctly. In accuracy tests, measuring each protocol's ability to correctly classify new isolates, ribotyping with EcoRI and PvuII approached 100% correctclassification but only 6% of isolates were classified; four of the other six protocols (antibiotic resistance analysis, PFGE, and two repetitive-element PCR protocols) achieved better than random accuracy rates when 30-100% of challenge isolates were classified. In robustness tests, measuring each protocol's ability to recognize isolates from nonlibrary

Land applications of manure from confined animal systems and direct deposit by grazing animals are both major sources of bacteria in streams. An understanding of the overland transport mechanisms from land applied waste is needed to improve design of best management practices (BMPs) and modeling of nonpoint source (NPS) pollution. Plots were established on pasturelands receiving phosphorus-based livestock waste applications to measure the concentrations of Escherichia coli (E. coli), fecal coliform (FC), and Enterococcus present in overland flow at the edge of the field. The flow-weighted bacteria concentrations were highest in runoff samples from the plots treated with cowpies (1.37 × 10 5 colony forming units (cfu)/100 ml of E. coli) followed by liquid dairy manure (1.84 × 10 4 cfu/100 ml of E. coli) and turkey litter (1.29 × 10 4 cfu/100 ml of E. coli). The temporal distribution of fecal bacterial concentrations appeared to be dependent upon both the animal waste treatment and the indicator species, with peak concentrations occurring either at the beginning of the runoff event or during peak flow rates. BMPs could be selected to reduce peak flows or first flush effects depending upon the litter or manure applied to the land. The commercial Biolog System was used to identify the dominant species of Enterococcus present in the cowpie source manure (Enterococcus mundtii 55%) and in the runoff collected from the transport plots treated with cowpies (Enterococcus faecalis 37%). The identification of predominant species of Enterococcus that are associated with specific sources of fecal pollution could greatly assist with identifying the origins of NPS pollution.

As part of a larger microbial source tracking (MST) study, several laboratories used library-based, phenotypic subtyping techniques to analyse fecal samples from known sources (human, sewage, cattle, dogs and gulls) and blinded water samples that were contaminated with the fecal sources. The methods used included antibiotic resistance analysis (ARA) of fecal streptococci, enterococci, fecal coliforms and E. coli; multiple antibiotic resistance (MAR) and Kirby-Bauer antibiotic susceptibility testing of E. coli; and carbon source utilization for fecal streptococci and E. coli. Libraries comprising phenotypic patterns of indicator bacteria isolated from known fecal sources were used to predict the sources of isolates from water samples that had been seeded with fecal material from the same sources as those used to create the libraries. The accuracy of fecal source identification in the water samples was assessed both with and without a cut-off termed the minimum detectable percentage (MDP). The libraries (approximately 300 isolates) were not large enough to avoid the artefact of source-independent grouping, but some important conclusions could still be drawn. Use of a MDP decreased the percentage of false-positive source identifications, and had little effect on the high percentage of true-positives in the most accurate libraries. In general, the methods were more prone to false-positive than to false-negative errors. The most accurate method, with a true-positive rate of 100% and a false-positive rate of 39% when analysed with a MDP, was ARA of fecal streptococci. The internal accuracy of the libraries did not correlate with the accuracy of source prediction in water samples, showing that one should not rely solely on parameters such as the average rate of correct classification of a library to indicate its predictive capabilities.

We have developed a mechanical absolute-rotation sensor capable of resolving ground rotation angle of less than 1 nrad/ √ Hz above 30 mHz and 0.2 nrad/ √ Hz above 100 mHz about a single horizontal axis. The device consists of a meter-scale beam balance, suspended by a pair of flexures, with a resonance frequency of 10.8 mHz. The center of mass is located 3 µm above the pivot, giving an excellent horizontal displacement rejection of better than 3 × 10 −5 rad/m. The angle of the beam is read out optically using a high-sensitivity autocollimator. We have also built a tiltmeter with better than 1 nrad/ √ Hz sensitivity above 30 mHz. Colocated measurements using the two instruments allowed us to distinguish between background rotation signal at low frequencies and intrinsic instrument noise. The rotation sensor is useful for rotational seismology and for rejecting background rotation signal from seismometers in experiments demanding high levels of seismic isolation, such as Advanced LIGO.

We present an "interferometric quasi-autocollimator" that employs weak value amplification to measure angular deflections of a target mirror. The device has been designed to be insensitive to all translations of the target. We present a conceptual explanation of the amplification effect used by the device. An implementation of the device demonstrates sensitivities better than 10 picoradians per root hertz between 10 and 200 Hz.

Antibiotic resistance analysis (ARA) was used to determine if enterococci of human origin were present in a stream (Spout Run) that passes through a rural nonsewered community (Millwood, VA). Millwood consists of 82 homes, all served by individual septic systems, and Spout Run drains a 5,800-ha karst topography watershed that contains large populations of livestock and wildlife. Periodic monitoring by state regulatory officials had resulted in Spout Run being placed on the Virginia impaired stream list and Millwood being categorized as an at-risk community. Stream samples were collected monthly and analyzed for fecal coliforms and enterococci (May 1999-May 2000); ARA was performed on enterococci stream isolates on a quarterly basis. All 117 stream samples were positive for fecal coliforms, and 32% exceeded the Virginia recreational water standard (1,000 fecal coliforms/100 mL). A library of 1,174 known source Enterococcus isolate antibiotic resistance profiles was constructed, and yielded correct classification rates of 94.6% for 203 human isolates, 93.7% for 734 livestock isolates, and 87.8% for 237 wildlife isolates. Antibiotic resistance analysis of 2,012 enterococcal isolates recovered from stream samples indicated isolates of human origin appeared throughout the stream as it passed through Millwood, with a yearly average of approximately 10% human, 40% wildlife, and 50% livestock. There were no human origin isolates in samples collected upstream from Millwood, and the percent human origin isolates declined downstream from Millwood. While a human signature was found in Spout Run, it was small compared with the proportion of isolates from livestock and wildlife.