The incredible HALK: Borrowing data for age assignment
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Abstract
Understanding age and growth are important for fisheries science and management; however, age data are not routinely collected for many populations. We propose and test a method of borrowing age–length data across increasingly broader spatiotemporal levels to create a hierarchical age–length key (HALK). We assessed this method by comparing growth and mortality metrics to those estimated from lake–year age–length keys ages using seven common freshwater fish species across the upper Midwestern United States. Levels used for data borrowing began most specifically by borrowing within lake across time and increased in breadth to include data within the Hydrologic Unit Code (HUC) 10 watershed, HUC8 watershed, Level III Ecoregion, and finally a species-wide data ALK using all available data with our study for a species. Median deviation in mean length of age-3 fish was within 1 cm for the most specific HALK levels, and median deviation in total annual mortality was close to 0 for most species when borrowing occurred within HUC10 and HUC8 watersheds. Percent error in growth curves increased with data borrowing, but plateaued—or even decreased—for some species when data borrowing expanded across spatial levels. We present the HALK as a method for gaining age information about a fishery when age data are unavailable.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | The incredible HALK: Borrowing data for age assignment |
| Series title | Fisheries Magazine |
| DOI | 10.1002/fsh.11019 |
| Volume | 49 |
| Issue | 3 |
| Year Published | 2024 |
| Language | English |
| Publisher | American Fisheries Society |
| Contributing office(s) | Coop Res Unit Leetown |
| Description | 12 p. |
| First page | 117 |
| Last page | 128 |
| Country | United States |
| Other Geospatial | upper Midwest |
| Google Analytic Metrics | Metrics page |