Population viability and perturbation analyses to support recovery of imperilled Eastern Sand Darter<i>(Ammocrypta pellucida)</i>
Bibliographic record
Abstract
Abstract Small‐bodied freshwater fishes are often understudied, with the result that data gaps create uncertainties that can complicate and constrain conservation strategies aimed at species recovery. Use of matrix models and perturbation population viability analyses (PVA) are ideally suited for use in studying the consequences of life‐history parameter variation and environmental stochasticity to better understand the fate of threatened small‐bodied fishes. We use data for Eastern Sand Darter (Ammocrypta pellucida)populations from the Thames River, Canada, to explore the consequences of life‐history uncertainties such as age at maturation, multiple clutch sizes and age‐specific fertility for population recovery in this species. Environmental stochasticity acting on all life‐history parameters was found to pose significant risks for the continued viability of lower Thames River populations, with significant chances of local extinction predicted under current conditions. The intrinsic rate of population increase was most sensitive to 0+ survival rates, clutch size and clutch number. As demonstrated here, population models can successfully provide a means of exploring the population dynamics of small‐bodied fishes and can inform managers of risks posed by factors acting on life‐history parameters to affect continued population viability. Management actions for Eastern Sand Darter should focus on strategies designed to ensure successful spawning and improvement of 0+ survival rates, through programmes aimed at the protection, enhancement or recovery of additional spawning and juvenile rearing habitats.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".