Biomedical subjects

Anthony R Olsen

Publications and source records attributed to Anthony R Olsen.

3 recordsLinked to original sources

PubMed2006

Using relative risk to compare the effects of aquatic stressors at a regional scale.

The regional-scale importance of an aquatic stressor depends both on its regional extent (i.e., how widespread it is) and on the severity of its effects in ecosystems where it is found. Sample surveys, such as those developed by the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP), are designed to estimate and compare the extents, throughout a large region, of elevated conditions for various aquatic stressors. In this article, we propose relative risk as a complementary measure of the severity of each stressor's effect on a response variable that characterizes aquatic ecological condition. Specifically, relative risk measures the strength of association between stressor and response variables that can be classified as either "good" (i.e., reference) or "poor" (i.e., different from reference). We present formulae for estimating relative risk and its confidence interval, adapted for the unequal sample inclusion probabilities employed in EMAP surveys. For a recent EMAP survey of streams in five Mid-Atlantic states, we estimated the relative extents of eight stressors as well as their relative risks to aquatic macroinvertebrate assemblages, with assemblage condition measured by an index of biotic integrity (IBI). For example, a measure of excess sedimentation had a relative risk of 1.60 for macroinvertebrate IBI, with the meaning that poor IBI conditions were 1.6 times more likely to be found in streams having poor conditions of sedimentation than in streams having good sedimentation conditions. We show how stressor extent and relative risk estimates, viewed together, offer a compact and comprehensive assessment of the relative importances of multiple stressors.

Animals↗

PubMed2006

A more cost-effective EMAP benthic macrofaunal sampling protocol.

Benthic macrofaunal sampling protocols in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) are to collect 30 to 50 random benthic macrofauna [defined as animals retained on a 0.5 mm (East and Gulf Coasts, USA) or a 1.0 mm mesh sieve (West Coast, USA)] samples per reporting unit using a 0.044 m(2) (East and Gulf Coasts) or 0.1 m(2) (West Coast) grab. Benthic macrofaunal community conditions in the reporting unit are characterized by cumulative distribution functions (CDFs) on end points of interest, such as number of species (S), abundance (A), and Shannon-Wiener diversity (H'). An EMAP and a companion field study were conducted concurrently in Tillamook Bay (Oregon, USA) to compare the cost effectiveness of benthic macrofauna samples collected using the EMAP West Coast (0.1 m(2) x >or=7 cm deep, 1.0 mm mesh), a 0.01 m(2) x 5 cm deep, 1.0 mm mesh, and a 0.01 m(2) x 5 cm deep, 0.5 mm mesh sampling protocol. Cost was estimated in relative laboratory sample-processing time. Sampling protocols were judged equally effective for EMAP purposes if, after linear transformation to adjust for scale changes in end point distributions, their S, A, and H' CDFs were not significantly different. The 0.01 m(2) x 5 cm deep, 1.0 mm mesh sampling protocol was the most cost effective.

Animals↗

PubMed2005

Watershed-based survey designs.

Watershed-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification of impaired water bodies or watersheds to meet Section 303(d), and development of empirical relationships between causes or sources of impairment and biological responses. Creation of GIS databases for hydrography, hydrologically corrected digital elevation models, and hydrologic derivatives such as watershed boundaries and upstream-downstream topology of subcatchments would provide a consistent seamless nationwide framework for these designs. The elements of a watershed-based sample framework can be represented either as a continuous infinite set defined by points along a linear stream network, or as a discrete set of watershed polygons. Watershed-based designs can be developed with existing probabilistic survey methods, including the use of unequal probability weighting, stratification, and two-stage frames for sampling. Case studies for monitoring of Atlantic Coastal Plain streams, West Virginia wadeable streams, and coastal Oregon streams illustrate three different approaches for selecting sites for watershed-based survey designs.

Data Collection↗