Sampling Methods and Survey Designs for Larval Lampreys
Bibliographic record
Abstract
Abstract Knowledge of the biology, distribution, and abundance of lampreys (Petromyzontiformes) is critical to inform conservation actions for native species and to inform control measures for the invasive Sea Lamprey Petromyzon marinus of the Laurentian Great Lakes. Lampreys have complex life cycles that include a freshwater larval stage in which they burrow into substrates consisting of fine sediment and organic matter. The larval stage is frequently targeted in research and monitoring; given this interest, a review of survey designs and methods is needed. Our review identified 12 different sampling methods for larval lampreys and focused on one common method—backpack electrofishing in wadeable habitats. Our review also identified eight research and monitoring questions that have been addressed for larval lampreys in field studies, including distribution, species identification, life stage occurrence, abundance, length frequency, habitat use, residence and movement phenology, and species status. Each question provides unique information and poses distinct challenges to data acquisition and interpretation. The objectives guide decisions about study design and scope of inference. The scope of inference is determined by the size, spatial distribution, selection method, and number of sampling units within and across habitats, which determine the spatial and temporal scales under which results can be interpreted. The sampling unit size can span orders of magnitude from microhabitats to river drainages, ultimately informing management decisions at several spatial scales. The intended scope of inference and the interaction between biological questions and the fiscal and logistical capabilities of the study are integral considerations when designing an effective larval lamprey survey.
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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 | 0.051 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".