Data from: Daphniid zooplankton assemblage shifts in response to eutrophication and metal contamination during the Anthropocene
Bibliographic record
Abstract
Human activities during the Anthropocene result in habitat degradation that has been associated with biodiversity loss and taxonomic homogenization of ecological communities. Here we estimated effects of eutrophication and heavy metal contamination, separately and in combination, in explaining zooplankton species composition during the past 125–145 years using analysis of daphniid diapausing egg banks from four lakes in the northeastern USA. We then examined how these community shifts influenced patterns of diversity and homogenization. Analysis of past lake production (via subfossil pigments) and metal contamination (via sedimentary metals) demonstrated that eutrophication alone (19–39%) and in combination with metal pollution (17–54%) explained 36–79% of historical variation in daphniid species relative abundances in heavily fertilized lakes. In contrast, metal pollution alone explained the majority (72%) of historical variation in daphniid assemblages at the oligotrophic site. Several species colonization events in eutrophying lakes resulted in increased species richness and gamma diversity through time. At the same time, daphniid assemblages in three eutrophied lakes became more similar to each other (homogenized), but this pattern was only seen when accounting for species presence/absence. We did not observe consistent patterns of divergence between the assemblages in the eutrophying lakes and the low-nutrient reference site. Given the pervasive nature of fertilization and metal pollution, and the sensitivity of cladocerans to these factors, we suggest that many inhabited lake districts may already exhibit similar patterns of daphniid assemblage shifts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".