A century of intermittent eco‐evolutionary feedbacks resulted in novel trait combinations in invasive Great Lakes alewives (<i>Alosa pseudoharengus</i>)
Bibliographic record
Abstract
) are native to the East Coast of North America where they ascend coastal rivers to spawn in lakes and then return to the ocean. Some populations have become landlocked within the last 350 years and diverged phenotypically from their ancestral marine population. More recently, alewives were introduced to the Laurentian Great Lakes (~150 years ago), but these populations have not been compared to East Coast anadromous and landlocked populations. We quantified 95 years of evolution in foraging traits and overall body shape of Great Lakes alewives and compared patterns of phenotypic evolution of Great Lakes alewives to East Coast anadromous and landlocked populations. Our results suggest that gill raker spacing in Great Lakes alewives has evolved in a dynamic pattern that is consistent with responses to strong but intermittent eco-evolutionary feedbacks with zooplankton size. Following their initial colonization of Lakes Ontario and Michigan, dense alewife populations likely depleted large-bodied zooplankton, which drove a decrease in alewife gill raker spacing. However, the introduction of large, non-native zooplankton to the Great Lakes in later decades resulted in an increase in gill raker spacing, and present-day Great Lakes alewives have gill raker spacing patterns that are similar to the ancestral East Coast anadromous population. Conversely, contemporary Great Lakes alewife populations possess a gape width consistent with East Coast landlocked populations. Body shape showed remarkable parallel evolution with East Coast landlocked populations, likely due to a shared response to the loss of long-distance movement or migrations. Our results suggest the colonization of a new environment and cessation of migration can result in rapid parallel evolution in some traits, but contingency also plays a role, and a dynamic ecosystem can also yield novel trait combinations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".