Investigating Black Crappie (Pomoxis nigromaculatus) populations using age and growth data in Whiteshell Provincial Park, Manitoba
Bibliographic record
Abstract
Increasing water temperatures due to climate change may offer some warm water fishes the opportunity to establish sustainable populations in systems that were historically not suitable. Black Crappie (Pomoxis nigromaculatus) were introduced into the Whiteshell Provincial Park, in southern Manitoba, in the mid-1940’s, which is at the northernmost edge of their distribution range. However, it was not until recently (in the past 10-15 years) that this population has begun to expand and increase in abundance. With the potential for a shifting distribution as a result of warming temperatures, the purpose of this study was to better understand the characteristics of Black Crappie at the northern extent of their range for the goal of successful management.This thesis examined six lakes within the Whiteshell Provincial Park located in southern Manitoba, as well as Lac du Bonnet located just outside the park boundary. I hypothesized that Black Crappie in Manitoba would show differences in population characteristics in relation to more southern populations as a result of cooler temperatures and a shorter growing season associated with northern latitudes. Results of this study showed that Black Crappie in Manitoba grew slower, but were older and larger than more southern populations. Relative weights indicated the Whiteshell Provincial Park population was within the normal range for body condition for this species. Stock density measurements determined that each lake contained high proportions of large sized fish, which is important for recreational fishing. Values of δ13C and δ15N suggest that Black Crappie feed on different prey items at the same trophic levels between sites. Organ (gonadosomatic and hepatosomatic) indices suggested that Black Crappie begin to spawn in late May and energy stores recover more quickly post-spawn than southern populations. It is apparent that Black Crappie in the Whiteshell Provincial Park have established thriving populations as an introduced species that contribute to a growing fishery. As range expansion potentially continues, this thesis provides initial data on established Black Crappie population characteristics and provides information on how they may impact new systems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".