The quick and the dead: copepods dominate as cladocerans decline following invasion by <i>Hemimysis anomala</i>
Bibliographic record
Abstract
The North American invasion of a non-native mysid, Hemimysis anomala, has been expanding since 2006, with the first inland lake invasions detected for Oneida Lake in 2009 and Seneca Lake in 2010. Although we know that Hemimysis primarily consumes zooplankton, our ability to predict the community-level impact of an invasion is hampered by a lack of information on taxon-specific effects. To investigate the effects of Hemimysis on native zooplankton, we conducted two mesocosm experiments that compared composition between communities with and without Hemimysis and studied how the effects of this predator on zooplankton species composition varied across a natural gradient of low to high invader densities (0.01–0.1 individuals·L−1). Our first experiment found that Hemimysis primarily affected cladocerans, and particularly Daphnia, shifting communities towards dominance by copepods. Our second experiment showed that Hemimysis invasions may do little to suppress Daphnia abundances until between 0.067–0.11 individuals·L−1 or higher. Cladocerans are important links in freshwater trophic transfer and the nutrient cycle, and disruption of these linkages following Hemimysis invasion could result in both bottom-up and top-down impacts in nearshore food webs. However, Hemimysis can also fill a similar trophic role as the zooplankton they consume, and longer-term experiments are required to better assess their eventual impacts on native communities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".