Comparing annual population growth estimates of,the exotic invader Bythotrephes by using sediment and plankton records
Bibliographic record
Abstract
The annual population growth of the exotic invader Bythotrephes cederstroemi was calculated from the spatial distribution and rate of accumulation of its diagnostic caudal processes in the sediments of Harp Lake, Ontario. To our knowledge, this is the first use of the sediment record to quantify the annual population growth of a zooplankton species on a whole-lake scale with confidence estimates. In 1994, 553-1-254 (95 % C.L.) animals m-2 were produced in Harp Lake, an estimate statistically indistinguishable from that developed independently from the plankton data and temperature-dependent growth models (459 animals m-2). When annual population growth estimates will suffice, the sediment record offers several advantages. It requires less fieldwork than do plankton-based approaches and requires the quantification of the means and variances of fewer parameters. It also can provide population growth estimates for the past. For example, the sediment record indicated that one-third of all B. cederstroemi ever produced in Harp Lake predated the start of our plankton records in 1994. The sediment record may have other uses. The breakage of caudal processes may provide clues to the rates of fish predation on B. cederstroemi, suggesting, for example, that 40 % of the Harp Lake B. cederstroemi were eaten by fish in 1994. Bythotrephes cederstroemi Schoedler (Cercopagidae, Onychopoda) is a large, predaceous, Palearctic cladoceran zooplankter
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".