Geology topics

A.T. Herlihy

Publications and source records attributed to A.T. Herlihy.

3 recordsLinked to original sources

USGS2012

Target loads of atmospheric sulfur and nitrogen deposition for protection of acid sensitive aquatic resources in the Adirondack Mountains, New York

The dynamic watershed acid-base chemistry model of acidification of groundwater in catchments (MAGIC) was used to calculate target loads (TLs) of atmospheric sulfur and nitrogen deposition expected to be protective of aquatic health in lakes in the Adirondack ecoregion of New York. The TLs were calculated for two future dates (2050 and 2100) and three levels of protection against lake acidification (acid neutralizing capacity (ANC) of 0, 20, and 50 eq L -1). Regional sulfur and nitrogen deposition estimates were combined with TLs to calculate exceedances. Target load results, and associated exceedances, were extrapolated to the regional population of Adirondack lakes. About 30% of Adirondack lakes had simulated TL of sulfur deposition less than 50 meq m -2 yr to protect lake ANC to 50 eq L -1. About 600 Adirondack lakes receive ambient sulfur deposition that is above this TL, in some cases by more than a factor of 2. Some critical criteria threshold values were simulated to be unobtainable in some lakes even if sulfur deposition was to be decreased to zero and held at zero until the specified endpoint year. We also summarize important lessons for the use of target loads in the management of acid-impacted aquatic ecosystems, such as those in North America, Europe, and Asia. Copyright 2012 by the American Geophysical Union.

Water Resources Research↗

USGS2008

The relative influence of geographic location and reach-scale habitat on benthic invertebrate assemblages in six ecoregions

The objective of this study was to determine the relative influence of reach-specific habitat variables and geographic location on benthic invertebrate assemblages within six ecoregions across the Western USA. This study included 417 sites from six ecoregions. A total of 301 taxa were collected with the highest richness associated with ecoregions dominated by streams with coarse substrate (19-29 taxa per site). Lowest richness (seven to eight taxa per site) was associated with ecoregions dominated by fine-grain substrate. Principle component analysis (PCA) on reach-scale habitat separated the six ecoregions into those in high-gradient mountainous areas (Coast Range, Cascades, and Southern Rockies) and those in lower-gradient ecoregions (Central Great Plains and Central California Valley). Nonmetric multidimensional scaling (NMS) models performed best in ecoregions dominated by coarse-grain substrate and high taxa richness, along with coarse-grain substrates sites combined from multiple ecoregions regardless of location. In contrast, ecoregions or site combinations dominated by fine-grain substrate had poor model performance (high stress). Four NMS models showed that geographic location (i.e. latitude and longitude) was important for: (1) all ecoregions combined, (2) all sites dominated by coarse-grain sub strate combined, (3) Cascades Ecoregion, and (4) Columbia Ecoregion. Local factors (i.e. substrate or water temperature) seem to be overriding factors controlling invertebrate composition across the West, regardless of geographic location. ?? The Author(s) 2008.

Environmental Monitoring and Assessment↗

USGS2004

The effects of macroinvertebrate taxonomic resolution in large landscape bioassessments: An example from the Mid-Atlantic Highlands, U.S.A.

1. During late spring 1993-1995, the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) sampled 490 wadeable streams in the mid-Atlantic Highlands (MAH) of the U.S. for a variety of physical, chemical and biological indicators of environmental condition. We used the resulting data set to evaluate the importance of differing levels of macroinvertebrate taxonomic resolution in bioassessments by comparing the ability of family versus genus to detect differences among sites classified by type and magnitude of human impact and by stream size. We divided the MAH into two physiographic regions: the Appalachian Plateau where mine drainage (MD) and acidic deposition are major stressors, and the Ridge and Valley where nutrient enrichment is a major stressor. Stream sites were classified into three or four impact classes based on water chemistry and habitat. We used stream order (first to third Strahler order) in each region as a measure of stream size. Ordination, 2 x 2 chi-square and biotic metrics were used to compare the ability of family and genus to detect differences among both stressor and size classes. 2. With one notable exception, there were only a small number of different genera per family (interquartile range = 1-4). Family Chironomidae, however, contained 123 different genera. As a result, significant information loss occurred when this group was only classified to family. The family Chironomidae did not discriminate among the predefined classes but many chironomid genera did: by chi-square analysis, 10 and 28 chironomid genera were significant in discriminating MD and nutrient impacts, respectively. 3. Family and genus data were similar in their ability to distinguish among the coarse impacts (e.g. most severe versus least severe impact classes) for all cases. Though genus data in many cases distinguished the subtler differences (e.g. mixed/moderate impacts versus high or low impacts) better than family, differences in significance levels between family and genus analyses were relatively minor. However, genus data detected differences among stream orders in ordination analyses that were not revealed at the family level. In the ordinations, both family and genus levels of analysis responded to similar suites of environmental variables. 4. Our results suggest that identification to the family level is sufficient for many bioassessment purposes. However, identifications to genus do provide more information in genera-rich families like Chironomidae. Genus or finer levels of identification are important for investigating natural history, stream ecology, biodiversity and indicator species. Decisions about the taxonomic level of identification need to be study specific and depend on available resources (cost) and study objectives.

Freshwater Biology↗