Estimating local and regional population sizes for an endangered minnow, redside dace (Clinostomus elongatus), in Canada
Bibliographic record
Abstract
ABSTRACT The Laurentian Great Lakes have undergone drastic declines in freshwater fishes, with 22 species having become extinct in the past century and many more currently at risk. One such species is the endangered minnow, the redside dace (Clinostomus elongatus), which is undergoing severe declines across its entire range. Depletion and mark–recapture surveys were used to quantify population estimates of redside dace at several spatial scales (pool, reach and catchment) across several Great Lakes tributaries in Canada. There was large variation in the local population estimates and the rate of occurrence of redside dace populations. In some cases, such as Gully Creek, a Lake Huron tributary, redside dace were widespread (9/10 of pools) but in low abundances (13.5 individuals per pool ± 5.09 ). In other cases, such as in the Don River, redside dace were highly localized (2/27 pools) but in relatively high abundance (99.2 individuals/pool ± 18.1). Extrapolated population estimates at the catchment scale showed that three of the five study populations were below conservative estimates needed for long‐term population viability. Differences in redside dace populations were driven by adjacent land‐use. Post‐hoc analyses revealed strong negative associations between population estimates and impervious land‐use (i.e. urbanization) at both the pool and sub‐catchment level. Immediate recovery actions that will focus on eliminating chronic and episodic impacts of adjacent land‐use and improve connectivity are needed to help ensure redside dace, like many freshwater species in the Laurentian Great Lakes, remain a species at risk of – rather than facing – extinction. Copyright © 2012 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".