Habitat Structures Rainbow Trout Population Dynamics Across Spatial Scales
Bibliographic record
Abstract
Density-dependent processes play an important role in structuring population dynamics – as the number of organisms within a set area increases, population vital rates and life history traits will also change arising from increased competition for limited food and space. In this thesis I explore how variation in the quantity of habitat available impacts size-structured animal populations using lake-dwelling rainbow trout (Oncorhynchus mykiss). First, I developed hypotheses on the biological processes by which habitat impacts population dynamics using a multi-habitat age-structured population model. This theoretical model showed that habitat limitations at any life stage can bottleneck the population and impact its dynamics, but that the timing of regulation influences population outcomes. Limited habitat in early life led to high early mortality, resulting in low overall population density of larger fish, while limited habitat in adult life led to high early survival and a high density of stunted fish populations. I then compared the model predictions to empirical data from 39 wild rainbow trout populations and to results of a harvest experiment. The field results corroborated the model predictions and showed that lakes with a higher early (stream) to late (lake) life stage habitat ratio presented higher number of recruits, later age at maturity and a smaller maximum size than lakes in which stream habitat was limiting. The density manipulation also supported the model predictions as the lake with the lowest habitat ratio presented the lowest compensatory reserve and showed a density-dependent growth response to harvest. Finally, I used the knowledge acquired at the lake-scale to predict rainbow trout production at the landscape-scale. I developed a methodology that describes rainbow trout distribution based on stream network characteristics and connectivity. Then I used a landscape-scale proxy of stream habitat availability, stream order, and lake area to predict stream to lake habitat ratio and infer population dynamics. I combined this landscape-scale production information with recreational fishing demand to identify regions more prone to being impacted by overfishing or habitat perturbations. My research details how local habitat availability influences fish populations and can be used to predict population dynamics across a landscape of lakes providing a valuable tool to managers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".