Niche Dimensions in Fishes: An Integrative View
Bibliographic record
Abstract
Current shifts in ecosystem composition and function emphasize the need for an understanding of the links between environmental factors and organism fitness and tolerance. The examples discussed here illustrate how recent progress in the field of comparative physiology may provide a better mechanistic understanding of the ecological concepts of the fundamental and realized niches and thus provide insights into the impacts of anthropogenic disturbance. Here we argue that, as a link between physiological and ecological indicators of organismal performance, the mechanisms shaping aerobic scope and passive tolerance set the dimensions of an animal's niche, here defined as its capacity to survive, grow, behave, and interact with other species. We demonstrate how comparative studies of cod or killifish populations in a latitudinal cline have unraveled mitochondrial mechanisms involved in establishing a species' niche, performance, and energy budget. Riverine fish exemplify how the performance windows of various developmental stages follow the dynamic regimes of both seasonal temperatures and river hydrodynamics, as synergistic challenges. Finally, studies of species in extreme environments, such as the tilapia of Lake Magadi, illustrate how on evolutionary timescales functional and morphological shifts can occur, associated with new specializations. We conclude that research on the processes and time course of adaptations suitable to overcome current niche limits is urgently needed to assess the resilience of species and ecosystems to human impact, including the challenges of global climate change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".