This data release presents part of historical fisheries-dependent data for Cisco (Coregonus artedi) in Green Bay of Lake Michigan and Saginaw Bay of Lake Huron collected by scientists from U.S. Geological Survey's Great Lakes Science Center, including three tables for monthly Cisco-catch and fishing-effort data and two tables for biological data of Cisco individuals. The monthly Cisco-catch and fishing-effort data tables are for small-mesh gill-net fisheries in Green Bay and Saginaw Bay (GBSB_GN.csv), pound-net fisheries in Green Bay and Saginaw Bay (GBSB_PD.csv), and shallow trap-net fishery in Saginaw Bay (SB_ST.csv) in the period 1929–1970.

The biological data of Cisco individuals are from historical Saginaw Bay Cisco scale collections of 1942,1945, 1946, 1948, and 1953. These Ciscoes were caught by commercial trap-net fishing carried out by Bay Port Fish Company, located in Bay Port, Michigan. The table “SB_Scale_Collection.csv” includes data associated with the commercial trap-net fishing operations. The table “SB_Scale_Bio.csv” includes biological data (length, weight, sex, maturity) recorded on scale envelopes, and age (i.e., number of annuli on the scale) and back-calculated total length at annulus formation for a subset of these fish samples.

For questions about availability and physical and digital access for the historical fisheries-dependent data collected by scientists from the Great Lakes Science Center, reach out to the Science Center.

These data describe the catch and biological data from 363 bottom-set gill-net lifts distributed throughout Lake Michigan (including main basin and Green Bay) between April and November in 1930–1932. Data collected from the R/V Fulmar were recorded in notebooks and are now archived at the U.S. Geological Survey’s Great Lakes Science Center. Each lift included 1–7 gangs of linen gill nets. Each gang comprised 3–5 panels each having a length of 155 m, a height of 1.5 m, and a (stretch-)mesh size of either 60, 64, 67, 70, or 76 mm. The digitization of the Fulmar data notebooks was started in the late 1990s and finished in this study.

These data describe the catch and biological data from 363 bottom-set gill-net lifts distributed throughout Lake Michigan (including main basin and Green Bay) between April and November in 1930–1932. Data collected from the R/V Fulmar were recorded in notebooks and are now archived at the U.S. Geological Survey’s Great Lakes Science Center. Each lift included 1–7 gangs of linen gill nets. Each gang comprised 3–5 panels each having a length of 155 m, a height of 1.5 m, and a (stretch-)mesh size of either 60, 64, 67, 70, or 76 mm. The digitization of the Fulmar data notebooks was started in the late 1990s and finished in this study.

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.

This data release presents catch and effort data for Cisco Coregonus artedi and Lake Whitefish Coregonus clupeaformis commercial gill net fisheries in State of Michigan waters of Lakes Superior, Michigan, and Huron during 1929-1970. The data were used to determine if Cisco and Lake Whitefish relative abundance (commercial gill net catch per effort) were correlated (positive and negative) during the historical period. The file is in .csv format and contains columns for: (1) lake (LAKE); (2) commercial fishery management unit (MU); (3) year (YEAR); (4) gill net material used to target Lake Whitefish (WF_MAT); (5) gill net material used to target Cisco (CS_MAT); (6) gill net conversion factors (multipliers) used to convert effort into linen and cotton gill net equivalents for Lake Whitefish (WF_CF); (7) gill net conversion factors (multipliers) used to convert effort into linen and cotton gill net equivalents for Cisco (CS_CF); (8) catch (kg) of Lake Whitefish (WF_KG); (9) catch (kg) of Cisco (CS_KG); (10) corrected effort (km of net) for Lake Whitefish (WF_KM); (11) corrected effort (km of net) for Cisco (CS_KM); (12) corrected catch per effort (kg per km of net) for Lake Whitefish (WF_CPE); (13) corrected catch per effort (kg per km of net) for Cisco (CS_CPE); (14) loge-transformed corrected catch per effort for Lake Whitefish (LN_WF_CPE); (15) loge-transformed corrected catch per effort for Cisco (LN_CS_CPE); (16) standardized Z-scores based on loge-transformed corrected catch per effort for Lake Whitefish (WF_Z); (17) standardized Z-scores based on loge-transformed corrected catch per effort for Cisco (CS_Z); and (18) whether individual data points were removed prior to analyses based on values of corrected effort for either species (i.e., WF_KM or CS_KM) that fell outside the 2.5-97.5 percentile range for all available unit- and species-specific effort data pooled (E_FILTER). Gill net conversion factors were required because different gill net materials with different efficiencies were used throughout the historical period. Efficiencies increased over time with the introduction of each new gill net material (i.e., linen and cotton to nylon-multifilament to nylon-monofilament). All corrected data were expressed as linen and cotton gill net equivalents. To express data as linen and cotton gill net equivalents, nylon-monofilament and nylon-multifilament gill net effort were multiplied by species-, lake-, and year-specific gill net conversion factors (WF_CF and CS_CF). Efficiency curves can be generated for each species and lake by plotting gill net conversion factors over time (i.e., WF_CF and CS_CF vs. YEAR). It is worth noting that gill net conversion factors (WF_CF and CS_CF) were based on data collected prior to increases in water clarity throughout all three lakes and relative efficiencies may have changed in recent years. We encourage users to exercise caution when applying these conversion factors to more recent data (post-1970s). The effort filter was used to ensure that individual data points used for analyses (i.e., paired Cisco–Lake Whitefish catch per effort) were not based on unusually high or low levels of targeted effort for either species.

This data release presents catch and effort data for Cisco Coregonus artedi and Lake Whitefish Coregonus clupeaformis commercial gill net fisheries in State of Michigan waters of Lakes Superior, Michigan, and Huron during 1929-1970. The data were used to determine if Cisco and Lake Whitefish relative abundance (commercial gill net catch per effort) were correlated (positive and negative) during the historical period. The file is in .csv format and contains columns for: (1) lake (LAKE); (2) commercial fishery management unit (MU); (3) year (YEAR); (4) gill net material used to target Lake Whitefish (WF_MAT); (5) gill net material used to target Cisco (CS_MAT); (6) gill net conversion factors (multipliers) used to convert effort into linen and cotton gill net equivalents for Lake Whitefish (WF_CF); (7) gill net conversion factors (multipliers) used to convert effort into linen and cotton gill net equivalents for Cisco (CS_CF); (8) catch (kg) of Lake Whitefish (WF_KG); (9) catch (kg) of Cisco (CS_KG); (10) corrected effort (km of net) for Lake Whitefish (WF_KM); (11) corrected effort (km of net) for Cisco (CS_KM); (12) corrected catch per effort (kg per km of net) for Lake Whitefish (WF_CPE); (13) corrected catch per effort (kg per km of net) for Cisco (CS_CPE); (14) loge-transformed corrected catch per effort for Lake Whitefish (LN_WF_CPE); (15) loge-transformed corrected catch per effort for Cisco (LN_CS_CPE); (16) standardized Z-scores based on loge-transformed corrected catch per effort for Lake Whitefish (WF_Z); (17) standardized Z-scores based on loge-transformed corrected catch per effort for Cisco (CS_Z); and (18) whether individual data points were removed prior to analyses based on values of corrected effort for either species (i.e., WF_KM or CS_KM) that fell outside the 2.5-97.5 percentile range for all available unit- and species-specific effort data pooled (E_FILTER). Gill net conversion factors were required because different gill net materials with different efficiencies were used throughout the historical period. Efficiencies increased over time with the introduction of each new gill net material (i.e., linen and cotton to nylon-multifilament to nylon-monofilament). All corrected data were expressed as linen and cotton gill net equivalents. To express data as linen and cotton gill net equivalents, nylon-monofilament and nylon-multifilament gill net effort were multiplied by species-, lake-, and year-specific gill net conversion factors (WF_CF and CS_CF). Efficiency curves can be generated for each species and lake by plotting gill net conversion factors over time (i.e., WF_CF and CS_CF vs. YEAR). It is worth noting that gill net conversion factors (WF_CF and CS_CF) were based on data collected prior to increases in water clarity throughout all three lakes and relative efficiencies may have changed in recent years. We encourage users to exercise caution when applying these conversion factors to more recent data (post-1970s). The effort filter was used to ensure that individual data points used for analyses (i.e., paired Cisco–Lake Whitefish catch per effort) were not based on unusually high or low levels of targeted effort for either species.

Assessing the distribution and abundance of both predator and prey (forage) fish species is a cornerstone of ecosystem-based fishery management, and supports decision making that considers food-web interactions. In support of binational Great Lakes fishery management the objectives of this survey were to: provide estimates of densities of key forage and predator species in the western basin of Lake Erie, to assess seasonal and spatial distributions of fishes in tandem with water quality information, and to assess year class strength. A systematic grid sampling approach with 41 stations was sampled via bottom trawl during June (Spring) and September (Autumn), starting in 2013. This data release adds 2022 data to the set for a total of ten years observation using the same gear and sampling design.

Assessing the distribution and abundance of both predator and prey (forage) fish species is a cornerstone of ecosystem-based fishery management, and supports decision making that considers food-web interactions. In support of binational Great Lakes fishery management the objectives of this survey were to: provide estimates of densities of key forage and predator species in the western basin of Lake Erie, to assess seasonal and spatial distributions of fishes in tandem with water quality information, and to assess year class strength. A systematic grid sampling approach with 41 stations was sampled via bottom trawl during June (Spring) and September (Autumn), starting in 2013. This data release adds 2022 data to the set for a total of ten years observation using the same gear and sampling design.

Assessing the distribution and abundance of both predator and prey (forage) fish species is a cornerstone of ecosystem-based fishery management, and supports decision making that considers food-web interactions. In support of binational Great Lakes fishery management the objectives of this survey were to: provide estimates of densities of key forage and predator species in the western basin of Lake Erie, to assess seasonal and spatial distributions of fishes in tandem with water quality information, and to assess year class strength. A systematic grid sampling approach with 41 stations was sampled via bottom trawl during June (Spring) and September (Autumn), starting in 2013. This data release adds 2020 data to the set for a total of eight years observation using the same gear and sampling design.

Assessing the distribution and abundance of both predator and prey (forage) fish species is a cornerstone of ecosystem-based fishery management, and supports decision making that considers food-web interactions. In support of binational Great Lakes fishery management the objectives of this survey were to: provide estimates of densities of key forage and predator species in the western basin of Lake Erie, to assess seasonal and spatial distributions of fishes in tandem with water quality information, and to assess year class strength. A systematic grid sampling approach with 41 stations was sampled via bottom trawl during June (Spring) and September (Autumn), starting in 2013. This data release adds 2020 data to the set for a total of eight years observation using the same gear and sampling design.