Synthesizing professional opinion and published science to build a conceptual model of Walleye recruitment
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Abstract
Understanding and predicting recruitment, longstanding goals in fisheries science and ecology, are complicated by variation in the importance of environmental drivers coupled with the dynamic nature of individual ecosystems. Developing an understanding of recruitment from well-monitored stocks offers an opportunity to overcome these complexities. We used a systematic literature review, a survey, and a workshop attended by professionals with expertise in recruitment of Walleye Sander vitreus to identify common environmental drivers of Walleye recruitment and additional sources of variation (i.e., context dependencies) among populations. The importance of individual environmental drivers, as well as the direction of their influence, differed as a function of geographic region, lake surface area, and Walleye life stage. The literature suggested abiotic conditions (e.g., temperature) during the first year of life were influential in determining recruitment. Professional opinion noted the importance of biotic factors, with prey availability and predation risk having the most consistent relationships with recruitment. We synthesized this information to propose a conceptual model that illustrates the suite of characteristics that shape Walleye recruitment over large spatial and temporal scales. Our findings emphasize the importance of first-year growth and system-specific contextual factors, which can alter the relative importance of the environmental drivers of recruitment.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Synthesizing professional opinion and published science to build a conceptual model of Walleye recruitment |
| Series title | Fisheries Magazine |
| DOI | 10.1002/fsh.10884 |
| Volume | 48 |
| Issue | 4 |
| Year Published | 2023 |
| Language | English |
| Publisher | American Fisheries Society |
| Contributing office(s) | Midwest Climate Adaptation Science Center |
| Description | 16 p. |
| First page | 141 |
| Last page | 156 |
| Google Analytic Metrics | Metrics page |