Distribution of Yellow Perch Perca fl avescens in Lakes, Reservoirs and Rivers of Alberta and British Columbia, in Relation to Tolerance for Climate and other Habitat Factors, and their Dispersal and Invasive Ability
Bibliographic record
Abstract
Although yellow perch Perca fl avescens Mitchill are widely distributed in inland waters across Canada, east of the Rocky Mountains from the boreal forest southward (Scott and Crossman 1973), their ability to colonize northerly and high elevation river systems appears to be limited (McPhail and Lindsey 1970). Like all Canadian fi sh species their present natural range represents their ability to recolonize a completely glaciated landscape over the last 10-12 millennia by dispersal through postglacial drainage networks (McPhail and Lindsey 1970; Mandrak 1995). The limited northern range is consistent with their preference for warm, weedy littoral habitats of lakes and ponds (Nelson and Paetz 1992; Boisclair and Rasmussen 1996). Although the species has limited capacity to deal with current, yellow perch are sometimes found in rivers, albeit slow moving sections and fl oodplain habitats. Since river networks are the key to dispersal on the landscape, the limited tolerance of yellow perch for fl owing water might be expected to have restricted their range in steep areas such as the eastern slopes of the Rocky Mountains. In this chapter we examine both large and small-scale distribution patterns of yellow perch in Alberta and British Columbia, both native and introduced, by reviewing published and unpublished literature and government databases. We examine these patterns for insights into tolerances for climate, salinity and other habitat factors, and for dispersal and invasive abilities that may impact their future spread and their impacts on other species and fi sheries resources.
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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 | 0.002 | 0.004 |
| 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".