Catch and Effort Data for Cisco and Lake Whitefish Commercial Gill Net Fisheries in State of Michigan Waters of Lakes Superior, Michigan, and Huron During 1929-1970
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). Conversely, to express data as nylon-monofilament or nylon-multifilament gill net equivalents, linen and cotton gill net effort would be divided 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.
Citation Information
Publication Year | 2021 |
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Title | Catch and Effort Data for Cisco and Lake Whitefish Commercial Gill Net Fisheries in State of Michigan Waters of Lakes Superior, Michigan, and Huron During 1929-1970 |
DOI | 10.5066/P9SQZ206 |
Authors | Benjamin J. Rook, Charles R. Bronte, Michael J Hayden |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Great Lakes Science Center |
Rights | This work is marked with CC0 1.0 Universal |