Habitat availability and ontogenetic shifts alter bottlenecks in size‐structured fish populations
Bibliographic record
Abstract
For species that utilize different habitats throughout their life cycle, the habitat limitation at a given stage can act as a bottleneck on population abundance, impacting density-dependent processes such as individual growth and survival. We explore the influence of habitat limitation on population dynamics by developing a multi-stage population model based on lake-dwelling rainbow trout (Oncorhynchus mykiss) populations where adults occupy the lake habitat but use tributaries for spawning and juvenile rearing. The model details density-dependent ecological processes and ontogenetic habitat shifts, harvest mortality, and the impact of climate on growth. We ran model simulations using a range of early life stage habitat availabilities and climatic conditions representative of the native range of rainbow trout in Canada and compared the results to empirical data. The results suggest that (1) increases in early life stage habitat leads to increases in population abundance but, due to density-dependent processes, also results in slower growing stunted populations; (2) population bottlenecks can occur at any life stage, even at the adult stage if spawning and rearing habitats are abundant; (3) when the level of competition for early life stages is increased, inter-cohort competition can lead to population cycles. The model's conclusions are further reinforced by empirical data showing a similar trend in the relationship between fish density and maximum size and providing evidence that limited early life stage habitat leads to lower fish densities and larger fish size. We provide a model that links environmental conditions to population dynamics and is useful for fisheries management and habitat conservation decisions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".