Paleogenetic evidence for a past invasion of Onondaga Lake, New York, by exotic Daphnia curvirostris using mtDNA from dormant eggs.
Bibliographic record
Abstract
Cladocerans possess traits such as resistant diapausing eggs and rapid parthenogenetic reproduction that make them efficient invaders of new habitats. Nearly all known invasions have been successful, perhaps because failed invasions are difficult to detect. It is possible, however, to identify past failed invasions, by studying the diapausing egg bank. Daphnia ephippia were found in the sediments of Onondaga Lake, New York that could neither be hatched nor identified using egg-case morphology. Instead, we used sequences of the 12S ribosomal ribonucleic acid (rRNA) gene of mitochondrial deoxyribonucleic acid (mtDNA) extracted from diapausing eggs to identify the unknown Daphnia. We compared these DNA sequences with those generated from morphologically identified Daphnia species collected in Onondaga Lake, and with published sequences for other North American Daphnia species. The invader was identified as Daphnia curvirostris, a Eurasian species that has been only reported once before from North America, in extreme northwestern Canada. The discovery of it in Onondaga Lake signifies a greater than 4,500-km range extension for this species. On the basis of the sediment ephippial data, D. curvirostris first appeared in the lake about 1952, reached maximum abundance during the period of peak pollution (1950s-1980s), and then essentially disappeared after 1983 when lake water quality improved. As with the finding of another exotic cladoceran, D. exilis, in Onondaga Lake (Hairston et al. 1999a), it is likely that chemical industry activities on the lakeshores were the original source of invading D. curvirostris, that pollution allowed this species to become established in the lake, and that the reduction in pollution ultimately led to its disappearance from the water column.
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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 | 0.000 |
| 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 | 0.001 |
| 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".