Lake Michigan: FISH (Polygons, Points)

This data set contains sensitive biological resource data for freshwater fish species in Lake Michigan. Vector polygons in the FISH data set represent fish distribution, concentration areas, and spawning areas. Vector points in the FISHPT data set represent fish spawning locations.

Species specific abundance, seasonality, status, life history, and source information are stored in relational data tables (described below) designed to be used in conjunction with this spatial data layer.

These data sets comprise a portion of the ESI data for Lake Michigan. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

The ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources.

Although these data have been processed successfully on a computer system at the National Oceanic and Atmospheric Administration, no warranty, expressed or implied, is made by NOAA regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty. NOAA warrants the delivery of this product in computer-readable format, and will offer a replacement copy of the product when the product is determined unreadable by computer input peripherals, or when the physical medium is delivered in damaged condition.

A multi-stage error checking process is used to verify both attribute accuracy and logical consistency throughout data production. The process includes a standardized data entry methodology, data review by in-house and external resource experts, a final Quality Assurance/Quality Control (QA/QC) process, and multiple automated logical consistency checks. Quantitative data (such as densities, counts, abundances, or concentrations) provided by resource experts for inclusion in the data set may vary widely in attribute accuracy, depending upon the methodology used to collect and compile such data. For a more detailed evaluation of source data attribute accuracy, contact the sources listed in the Lineage section.

Spatial components for the biological data layers can come from expert interviews, hardcopy, or digital sources. Some of the spatial components of the biological data layers may have been developed using regional experts who estimate concentration areas. It is difficult to estimate the positional accuracy of such data, except to state that they are compiled on hardcopy base maps with a scale of 1:42,000. Some of the spatial components of the biological data sets are developed from pre-existing digital or hardcopy sources and reflect the positional accuracy of these original data. Note that biological resource data by their very nature are considered "fuzzy", and this should be understood when considering the positional accuracy of vector digital objects representing these resources. See the Lineage and Process_Description sections for more information on the original source data and how these data were integrated or manipulated to create the final data set.

These data represent a synthesis of expert knowledge, digital data and hardcopy maps depicting fish distribution, concentration areas, and spawning areas. These data do not necessarily represent all fish occurrences in Lake Michigan. The following species are included in this data set: (Species_ID, Common Name, Scientific Name [n/a if not applicable]): 68, Chinook salmon, Oncorhynchus tshawytscha; 69, Coho salmon, Oncorhynchus kisutch; 70, Pink salmon, Oncorhynchus gorbuscha; 74, Rainbow trout, Oncorhynchus mykiss; 84, Rainbow smelt, Osmerus mordax; 85, Alewife, Alosa pseudoharengus; 100, Brown trout, Salmo trutta; 144, Atlantic salmon, Salmo salar; 152, Yellow perch, Perca flavescens; 159, Banded killifish, Fundulus diaphanus; 161, Lake sturgeon, Acipenser fulvescens; 165, Lake whitefish, Coregonus clupeaformis; 166, Brook trout, Salvelinus fontinalis; 167, Lake trout, Salvelinus namaycush; 174, Longnose sucker, Catostomus catostomus; 175, White sucker, Catostomus commersoni; 178, Rock bass, Ambloplites rupestris; 179, Largemouth bass, Micropterus salmoides; 180, Smallmouth bass, Micropterus dolomieu; 185, Northern pike, Esox lucius; 186, Muskellunge, Esox masquinongy; 187, Sauger, Sander canadensis; 188, Walleye, Stizostedion vitreum vitreum; 201, Channel catfish, Ictalurus punctatus; 205, Freshwater drum, Aplodinotus grunnieus; 229, River redhorse, Moxostoma carinatum; 235, Cisco, Coregonus artedi; 237, Burbot, Lota lota; 238, Round whitefish (menomonee), Prosopium cylindraceum; 240, Greater redhorse, Moxostoma valenciennesi; 247, Emerald shiner, Notropis atherinoides; 498, Bullhead catfish, Ameiurus spp.; 620, Endangered fish, n/a; 621, Threatened fish, n/a; 1231, Sunfish, Lepomis spp.; 1232, Buffalo, Ictiobus spp.; 1266, Lake chub, Couesius plumbeus; 1267, Longnose dace, Rhinichthys cataractae; 1271, Slimy sculpin, Cottus cognatus; 1289, Shortjaw cisco, Coregonus zenithicus; 1290, Spoonhead sculpin, Cottus ricei; 1295, Bloater, Coregonus hoyi; 1296, Round goby, Neogobius melanostomus; 1297, Suckers, Catostomidae spp.; 1298, Deepwater sculpin, Myoxocephalus thompsonii.

A multi-stage error checking process, described in the above Attribute_Accuracy_Report, is used to verify both attribute accuracy and logical consistency throughout data production. This process includes multiple automated logical consistency checks that test the files for missing or duplicate data, rules for proper coding, GIS topological consistencies, and SQL SERVER(R) to ArcGIS(R) consistencies. A final review is made by the ESI manager, where the data are written to CD-ROM and the metadata are written. After the data are delivered to NOAA, they are again subjected to a number of quality and consistency checks. In the process of checking for topological and database consistencies, new ID's and RARNUM's or HUNUM's are also generated, while retaining the original RARNUM or HUNUM stored as MAPRAR and MAPHUN, respectively. The new ID's are a combination of atlas number, element number, and record number. In addition, the value used to represent the element is modified to reflect the type of feature being mapped. In the case of an element that is normally represented by a point or polygon, a value of 20 is added to the standard element value for mapping of linear features. In the case where an element usually mapped as a polygon is represented by a point, a value of 30 is added to the regular element value. The RARNUM's are also modified to include the atlas number, so multiple atlases can be combined and RARNUM's remain unique. RARNUM's are redefined on an element basis, so "resources at risk" groupings will contain only a single element. HUNUM's are also modified to include the atlas number.