Temperature- and ontogeny-dependent metabolism in invasive early juvenile round goby (Neogobius melanostomus)
Bibliographic record
Abstract
The round goby (Neogobius melanostomus) is the fastest spreading invasive fish in the Laurentian Great Lakes, and concurrent invasions are occurring globally. To inform management and mitigation strategies, metabolic rate of adult round goby has been rigorously quantified, but metabolism of the juvenile life stages represents an important knowledge gap. Here, we measured routine and maximum metabolic rates (RMR and MMR) of early juvenile round goby (mass 0.007–0.07 g, mean 0.02 g; total length 6.6–19.4 mm, mean 13.7 mm), ~100× smaller than any round goby measured previously. To understand how metabolism may be affected by a warming climate, we reared round goby at several ecologically relevant temperatures (15°C, 19°C, and 23°C) and a projected surface temperature under climate change scenarios (27°C). We tested early juveniles at two separate and distinct ages (6–7 weeks and 12–14 weeks post-hatch). Growth was highest at 23°C compared to 15°C and 27°C, but this pattern only emerged after 12–14 weeks of development. Routine metabolic rates increased over 2-fold between fish reared at 15°C vs. 27°C (Q10 = 1.98), but we found no clear difference in our estimation of the “scope for activity” (i.e., maximum—routine metabolic rate) across temperatures, suggesting a wide thermal performance curve. We also found that the bioenergetics models previously developed for adults do not effectively translate to juveniles; the current models underestimated observed RMR values by ~20–60% depending on temperature. Overall, data from this study can be used to improve bioenergetic modeling in the round goby by considering these earlier life stages and fill an important gap of knowledge in our understanding of an ecologically invasive species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".