The Dynamics of Ecology, Demography, Dispersal, Habitat Selection, and Life History in a Crayfish Cambarus bartonii Population in Ontario
Bibliographic record
Abstract
A fundamental goal in ecology is to understand how organisms operate and organize in ecosystems. Yet, there is much to be gleaned about the underlying drivers of these ecological mechanisms. I used mark-recapture methodology to study a Cambarus bartonii population in Ontario. I examined ecology, demography, dispersal, habitat selection, their underlying drivers and temporal patterns, and their ecological implications for this population. I identified patterns encompassing capture frequency, size classes, length-weight relationships, life history, and population size estimates. I documented considerable crayfish dispersal within a short period of time, uncovered patterns relating dispersal and life-history traits, and habitat selection and its underlying processes, which helps our understanding of how organisms disperse and choose habitats. My research has implications for understanding population dynamics and resource selection in a changing world, given that crayfish are characterized as keystone species, and they are of particular concern as both invasive and endangered species globally.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".