Density data for Lake Ontario benthic invertebrate assemblages from 1964 to 2018
Bibliographic record
Abstract
Benthic invertebrates are important trophic links in aquatic food webs and serve as useful bioindicators of environmental conditions because their responses integrate the effects of both water and sediment qualities. However, long-term data sets for benthic invertebrate assemblages across broad geographic areas are rare and, even if collected, historic data sets are often not readily accessible. This data set provides densities of benthic macroinvertebrates for all taxa collected during lake-wide surveys in Lake Ontario, a Laurentian Great Lake, from 1964 to 2018. This information resulted from surveys funded by the governments of the United States and Canada to investigate the status and changes of Lake Ontario benthic community. Of the 13 lake-wide benthic surveys conducted in Lake Ontario over the course of 54 yr, we were able to acquire taxonomic data to the species level for 11 of the surveys and data to the group level for the other two surveys. Density data are provided for taxa representing the Annelida, Arthropoda, Mollusca, Cnidaria, Nemertea, and Platyhelminthes phyla. Univariate and multivariate analyses revealed that the compositional structure of Lake Ontario invertebrate assemblages differed markedly by depth and were also significantly altered by the Dreissena spp. invasion in early 1990s. The introduction of invasive dreissenids has changed the community historically dominated by Diporeia, Oligochaeta, and Sphaeriidae, to a community dominated by quagga mussels and Oligochaeta. Considering the rarity of long-term benthic data of high taxonomic resolution in lake ecosystems, this data set could be useful to explore broader aspects of ecological theory, including effects of different environmental factors and invasive species on community organization, functional and phylogenetic diversity, and spatial scale of variation in community structure. The data set could also be useful for studies on individual species including abundance and distribution, species co-occurrence, and how the patterns of dominance and rarity change over space and time. Use of this data set for academic or educational purposes is encouraged as long as the data source is properly cited using the title of this Data Paper, the names of the authors, the year of publication, the journal name, and the article number.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 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) | 0.011 | 0.003 |
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".