Cladoceran water column and subfossil abundances from 85 lakes across Canada
Bibliographic record
Abstract
This data set contains cladoceran sub-fossil and water column abundances in 85 lakes across Canada sampled as part of the NSERC Canadian Lake Pulse Network project. Lakes were sampled once, over three summers (2017-2018-2019). For sub-fossil cladocerans, cores were collected using a gravity corer in the deepest point of each lake and were sectioned on site with a vertical extruder. Each lake was sampled for a "top" sediment sample, represented by the first centimeter of the surface of the sediment core, and a "bottom" sediment sample, corresponding to the 1 cm of sediment located between 3 and 4 cm from the base of the core. Cladoceran extraction and preparation followed the protocol from Korhola and Rautio (2001). Cladocerans were identified using DM 2500 Leica compound inverted microscope under 200X-400X magnification with a minimal count size of 100 individuals. Identification at the species, genus, or species complex level followed Szeroczynska and Sarmaja-Korjonen (2007) and Korosi and Smol (2012a; b). Files "relativeabundanceTOP_FWBpaper.csv" and "relativeabundanceBOTTOM_FWBpaper.csv" contain relative abundances in the top and in the bottom sediments respectively. The relative abundances from 85 lakes are a subset of the data from 101 lakes examined across Canada (Paquette et al., 2022). Files "relativeabundanceTOP_pelagic_FWBpaper.csv" and "relativeabundanceBOTTOM_pelagic_FWBpaper.csv" contain relative abundances of pelagic taxa only in the top and bottom sediments respectively, in a subset of 46 lakes. For water column cladocerans, samples were collected at the same location using a 100μm mesh Wisconsin net. Zooplankton were anesthetized with CO2 (Alka-Seltzer) and samples were preserved at room temperature in 70% ethanol. Samples were identified to the species level by BSA Environmental Services (Ohio, U.S.A.) using a dissecting microscope (100x to 400x magnification). The file "abundanceWCFWBpaper.csv" contains the abundances of 17 cladoceran zooplankton taxa from 85 lakes across Canada, while the file "abundanceWC_pelagic_FWBpaper.csv" contains abundances of 10 pelagic cladoceran zooplankton taxa from a subset of 46 lakes. References Korhola, A., and M. Rautio. 2001. Cladocera and other branchiopod crustaceans, p. 225–234. In J.P. Smol, H.J.B. Birks, and W.M. Last [eds.], Tracking Environmental Change Using Lake Sediments. Springer. Korosi, J. B., and J. P. Smol. 2012a. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 1-the Daphniidae, Leptodoridae, Bosminidae, Polyphemidae, Holopedidae, Sididae, and Macrothricidae. J. Paleolimnol. 48: 571–586. doi:10.1007/S10933-012-9632-3 Korosi, J. B., and J. P. Smol. 2012b. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 2-the Chydoridae. J. Paleolimnol. 48: 587–622. Paquette, C., Griffiths, K., Gregory-Eaves, I., & Beisner, B. E. (2022). Sub-fossil crustacean zooplankton relative abundances from 101 lakes across Canada [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6209390 Szeroczyfiska, K., and K. Sarmaja-Korjonen. 2007. Atlas of Subfossil Cladocera from Central and Northern Europe, Friends of the Lower Vistula Society, Warsaw, Pol.
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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 | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".