Data for: Year-class strength estimates and biophysical variables for analyses of Lake Whitefish and Cisco recruitment in the Great Lakes and Lake Simcoe, 1956-2015
Data files
Jul 24, 2026 version files 740.04 KB
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PredictorVariableData.csv
619.88 KB
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PredictorVariableDescriptions.csv
4.48 KB
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PredictorVariableMethods.md
27.78 KB
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PredictorVariableSources.csv
9.58 KB
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README.md
9.31 KB
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YearClassStrengthEstimates.csv
69 KB
Abstract
Lake Whitefish (Coregonus clupeaformis) and Cisco (C. artedi) are socioecologically important fishes across the Laurentian Great Lakes region; however, many populations have experienced declining, poor, or sporadic recruitment in recent decades. Increased understanding of the recruitment dynamics and drivers of these two species could help clarify the causes and consequences of recent recruitment trajectories. We characterized the long-term recruitment dynamics and putative biophysical drivers of Lake Whitefish and Cisco in the Laurentian Great Lakes (United States/Canada) and Lake Simcoe (Canada). Here, we provide datasets of year-class strength (i.e., an index of recruitment to the adult population) and predictor variables for analyses of Lake Whitefish and Cisco recruitment variability in six large lakes: Superior, Huron, Michigan, Erie, Ontario, and Simcoe. These data can be leveraged in future research on the causes and consequences of recruitment variability for these two species in the Laurentian Great Lakes region.
Dataset DOI: 10.5061/dryad.bk3j9kdst
Project citation and contact
Brown, T. A., Rudstam, L. G., Sethi, S. A., Bunnell, D. B., Weidel, B. C., and Honsey, A. E., (2026). Year-class strength estimates and biophysical variables for analyses of Lake Whitefish and Cisco recruitment in the Great Lakes and Lake Simcoe, 1956-2015 [Dataset]. Dryad. doi:10.5061/dryad.bk3j9kdst
Contact: Taylor A. Brown. Email: tab289@cornell.edu. ORCID: 0000-0003-0984-5512.
Project Description
Lake Whitefish (Coregonus clupeaformis) and Cisco (C. artedi) are socioecologically important fishes across the Laurentian Great Lakes region of North America; however, many populations have experienced declining, poor, or sporadic recruitment in recent decades. Increased understanding of the recruitment dynamics and drivers of these two species could help clarify the causes and consequences of recent recruitment trajectories. We characterized the long-term recruitment dynamics and putative biophysical drivers of Lake Whitefish and Cisco in the Laurentian Great Lakes (United States/Canada) and Lake Simcoe (Canada). Here, we provide datasets of year-class strength (i.e., an index of recruitment to the adult population) and predictor variables for analyses of Lake Whitefish and Cisco recruitment variability in six large lakes: Superior, Huron, Michigan, Erie, Ontario, and Simcoe.
Year-class strength estimates
This tabular dataset includes year-class strength estimates for Lake Whitefish and Cisco cohorts spanning 1956–2015 across the Great Lakes and Lake Simcoe. The methodology for this dataset is fully described in the publication: Brown et al. 2025. Reconstructing half a century of coregonine recruitment reveals species-specific dynamics and synchrony across the Laurentian Great Lakes. ICES Journal of Marine Science 82(2): fsae160. doi:10.1093/icesjms/fsae160. Users are advised to thoroughly read the publication’s methods to understand appropriate use and data limitations. The long-term survey data underlying the year-class strength estimates were provided by each respective agency to the corresponding author and cannot be shared publicly per data sharing agreements. Data can be obtained by request to the agency responsible for each survey. Prospective users may contact the corresponding author for help with contacting agencies as needed.
Biophysical predictor variables
This tabular dataset includes biophysical predictor variable indices which were summarized for the purpose of analyzing drivers of observed Lake Whitefish and Cisco year-class strength. The dataset spans 1956–2015 across the Great Lakes and Lake Simcoe and is designed to directly interface with the year-class strength estimates. The methodology for this dataset is fully described herein (PredictorVariableMethods.md). Prospective users are advised to thoroughly read these methods to understand how these variables were derived, appropriate use, and data limitations. The primary datasets underlying the predictor variables are either publicly available or were provided to the authors under data sharing agreements and may obtained by request to the institution responsible for each dataset. Prospective users may contact the corresponding author for help with contacting data providers as needed.
Description of the data and file structure
We provide tabular datasets of year-class strength (i.e., index of recruitment to the adult population) and biophysical predictor variables hypothesized to regulate recruitment for Lake Whitefish and Cisco in the Laurentian Great Lakes and Lake Simcoe. We also provide a text file containing the methodology by which each predictor variable was summarized.
Files and variables
Data File: YearClassStrengthEstimates.csv
Description: Contains year-class strength estimates and associated standard errors, as described in Brown et al. (2025).
Brown, T.A., Rudstam, L.G., Sethi, S.A., Ripple, P., Smith, J.B., Treska, T.J., Hessell, C., Olsen, E., He, J.X., Jonas, J.L., Rook, B.J., Blankenheim, J.E., Beech, S.J.H., Brown, E., Berglund, E.K., Cook, H.A., Dunlop, E.S., James, S., Pothoven, S.A., Amidon, Z.J., Sweka, J.A., Carl, D.D., Hansen, S.P., Bunnell, D.B., Weidel, B.C., and Honsey, A.E. 2025. Reconstructing half a century of coregonine recruitment reveals species-specific dynamics and synchrony across the Laurentian Great Lakes. ICES Journal of Marine Science 82(2): fsae160. doi:10.1093/icesjms/fsae160.
Variables
- SpeciesCommonName: Common name of the study species. Two possible text values: “Lake Whitefish” or “Cisco”
- SpeciesScientificName: The genus and species, or scientific name, of the study species. Two possible text values: “Coregonus clupeaformis” or “Coregonus artedi”
- Lake: Name of the study lake. Six possible text values: “Superior”, “Michigan”, “Huron”, “Erie”, “Ontario”, or “Simcoe”
- Method: Method by which year-class strength was estimated. Two possible text values: catch at age or catch-per-unit-effort.
- Cohort: Cohort for which year-class strength was estimated. Defined as the year each cohort hatched. For example, an age-5 fish observed in 2025 would belong to the 2020 cohort (also known as year-class). Format: Integer; 4-digit year (YYYY).
- YearClassStrength: Year-class strength estimate. Year-class strength estimates are unitless and relativized to each study species and lake. Format: floating-point.
- StandardError: Standard error associated with each year-class strength estimate. Format: floating-point.
Text File: PredictorVariableMethods.md
Description: Contains methodology for predictor variable data summarization.
Data File: PredictorVariableDescriptions.csv
Description: Contains descriptions of each predictor variable indexed for the purpose of analyzing Lake Whitefish and Cisco recruitment in the Laurentian Great Lakes and Lake Simcoe.
Variables
- PredictorVariableID: Predictor variable ID number (integer). Artificial sequence number for unique predictor variables. PredictorVariableID is used as a linking variable between tables.
- PredictorVariable: Name of each predictor variable.
- PredictorVariableDescription: Brief description of each predictor variable. See "PredictorVariableMethods" text file for details.
- Unit: Unit of measurement for each predictor variable.
- Standardization: Describes if and how each predictor variable was standardized (e.g., z-score normalization).
- PrimaryDataSourceID: Primary data source ID number (integer). Artificial sequence number for unique primary datasets. PrimaryDataSourceID is used as a linking variable between tables.
Data File: PredictorVariableSources.csv
Description: Contains descriptions of primary data sources used to index predictor variables.
Variables
- PrimaryDataSourceID: Primary data source ID number (integer). Artificial sequence number for unique primary datasets. PrimaryDataSourceID is used as a linking variable between tables.
- PrimaryDataSource: Name of the primary dataset originator (e.g., authors, institutions).
- PrimaryDataDescription: Description of the primary dataset.
- DataCitationURL: Citation or website URL for the primary dataset. NA values indicate that no information was available.
- PublicationCitationURL: Citation for any publication(s) describing the primary dataset. NA values indicate that no information was available.
Data File: PredictorVariableData.csv
Description: Contains predictor variable data indexed for the purpose of analyzing Lake Whitefish and Cisco recruitment in the Laurentian Great Lakes and Lake Simcoe.
Variables
- PredictorVariableID: Predictor variable ID number (integer). Artificial sequence number for unique predictor variables. PredictorVariableID is used as a linking variable between tables.
- PredictorVariable: Name of each predictor variable.
- Lake: Name of the study lake. Six possible values: “Superior”, “Michigan”, “Huron”, “Erie”, “Ontario”, or “Simcoe”.
- Cohort: Cohort for which a predictor variable was indexed, corresponding to Cohort in the "YearClassStrengthEstimates" table. Note that cohort does not necessarily correspond to calendar year, depending on the predictor variable. See "PredictorVariableMethods" text file for details. Format: Integer; 4-digit year (YYYY).
- Season: Seasonality of each predictor variable value: Annual, Winter, Spring, Summer, or Autumn. Temporal extent differs based on predictor variables and primary data sources. See "PredictorVariableMethods" text file for details.
- Value: Value of the predictor variable. See "PredictorVariableDescriptions" table for associated units.
- Imputed: Indicates whether the predictor variable value was imputed. Refer to Methods for full details.
- PrimaryDataSourceID: Primary data source ID number (integer). Artificial sequence number for unique primary datasets. PrimaryDataSourceID is used as a linking variable between tables.