The temporal window of ecological adaptation in postglacial lakes: a comparison of head morphology, trophic position and habitat use in Norwegian threespine stickleback populations
Bibliographic record
Abstract
BACKGROUND: Studying how trophic traits and niche use are related in natural populations is important in order to understand adaptation and specialization. Here, we describe trophic trait diversity in twenty-five Norwegian freshwater threespine stickleback populations and their putative marine ancestor, and relate trait differences to postglacial lake age. By studying lakes of different ages, depths and distance to the sea we examine key environmental variables that may predict adaptation in trophic position and habitat use. We measured trophic traits including geometric landmarks that integrated variation in head shape as well as gillraker length and number. Trophic position (Tpos) and niche use (α) were estimated from stable isotopes (δ(13)C, δ(15)N). A comparison of head shape was also made with two North American benthic-limnetic species pairs. RESULTS: We found that head shape differed between marine and freshwater sticklebacks, with marine sticklebacks having more upturned mouths, smaller eyes, larger opercula and deeper heads. Size-adjusted gillraker lengths were larger in marine than in freshwater stickleback. Norwegian sticklebacks were compared on the same head shape axis as the one differentiating the benthic-limnetic North American threespine stickleback species pairs. Here, Norwegian freshwater sticklebacks with a more "limnetic head shape" had more and longer gillrakers than sticklebacks with "benthic head shape". The "limnetic morph" was positively associated with deeper lakes. Populations differed in α (mean ± sd: 0.76 ± 0.29) and Tpos (3.47 ± 0.27), where α increased with gillraker length. Larger fish had a higher Tpos than smaller fish. Compared to the ecologically divergent stickleback species pairs and solitary lake populations in North America, Norwegian freshwater sticklebacks had similar range in Tpos and α values, but much less trait divergences. CONCLUSIONS: Our results showed trait divergences between threespine stickleback in marine and freshwater environments. Freshwater populations diverged in trophic ecology and trophic traits, but trophic ecology was not related to the elapsed time in freshwater. Norwegian sticklebacks used the same niches as the ecologically divergent North American stickleback species pairs. However, as trophic trait divergences were smaller, and not strongly associated with the ecological niche, ecological adaptations along the benthic-limnetic axis were less developed in Norwegian sticklebacks.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".