Item talk:Q66028: Difference between revisions

{"@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "USGS Numbered Series", "name": "Algal Attributes: An Autecological Classification of Algal Taxa Collected by the National Water-Quality Assessment Program", "identifier": [{"@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "ds329", "url": "https://pubs.usgs.gov/publication/ds329"}, {"@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 80994}, {"@type": "PropertyValue", "propertyID": "DOI", "value": "10.3133/ds329", "url": "https://doi.org/10.3133/ds329"}], "inLanguage": "en", "isPartOf": [{"@type": "CreativeWorkSeries", "name": "Data Series"}], "datePublished": "2008", "dateModified": "2012-02-02", "abstract": "Algae are excellent indicators of water-quality conditions, notably nutrient and organic enrichment, and also are indicators of major ion, dissolved oxygen, and pH concentrations and stream microhabitat conditions. The autecology, or physiological optima and tolerance, of algal species for various water-quality contaminants and conditions is relatively well understood for certain groups of freshwater algae, notably diatoms. However, applications of autecological information for water-quality assessments have been limited because of challenges associated with compiling autecological literature from disparate sources, tracking name changes for a large number of algal species, and creating an autecological data base from which algal-indicator metrics can be calculated. A comprehensive summary of algal autecological attributes for North American streams and rivers does not exist. This report describes a large, digital data file containing 28,182 records for 5,939 algal taxa, generally species or variety, collected by the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program. The data file includes 37 algal attributes classified by over 100 algal-indicator codes or metrics that can be calculated easily with readily available software. Algal attributes include qualitative classifications based on European and North American autecological literature, and semi-quantitative, weighted-average regression approaches for estimating optima using regional and national NAWQA data. Applications of algal metrics in water-quality assessments are discussed and national quartile distributions of metric scores are shown for selected indicator metrics.", "description": "Report: iv, 18 p.; Data Files", "publisher": {"@type": "Organization", "name": "Geological Survey (U.S.)"}, "author": [{"@type": "Person", "name": "Porter, Stephen D.", "givenName": "Stephen D.", "familyName": "Porter"}], "funder": [{"@type": "Organization", "name": "U.S. Geological Survey", "url": "https://www.usgs.gov/"}]}