Supplementary material from "Reciprocal abundance shifts of the intertidal sea stars, <i>Evasterias troschelii</i> and <i>Pisaster ochraceus</i>, following sea star wasting disease"
Bibliographic record
Abstract
Disease emergence occurs within the context of ecological communities, and disease driven declines in host populations can lead to complex direct and indirect ecological effects. Varying effects of a single disease among multiple susceptible hosts could benefit relatively resistant species. Beginning in 2013, an outbreak of sea star wasting disease (SSWD) led to population declines of many sea star species along the west coast of North America. Through field surveys and laboratory experiments, we investigated how and why the relative abundances of two co-occurring sea star species, Evasterias troschelii and Pisaster ochraceus, shifted during the ongoing wasting epidemic in Burrard Inlet, British Columbia, Canada. We hypothesized that Evasterias is competitively inferior to Pisaster but more resistant to SSWD. Thus, we predicted that SSWD-induced declines of Pisaster could mitigate the negative effects of SSWD on Evasterias, as the latter would experience competitive release. We document shifts in sea star abundance from 2008–2017: Pisaster abundance and mean size declined during the outbreak, while Evasterias abundance increased from relatively rare to numerically dominant within the intertidal. When exposed to symptomatic sea stars, Pisaster and Evasterias both showed signs of SSWD, but transmission and susceptibility was lower in Evasterias. Despite diet overlap documented in our field surveys, Evasterias was not outcompeted by Pisaster in laboratory trails conducted with the relatively small Pisaster available after the outbreak. Interference competition with larger Pisaster, or prey exploitation by Pisaster during the summer when Evasterias is primarily subtidal, may explain the rarity of Evasterias prior to Pisaster declines. Our results suggest that indirect effects mediated by competition can mask some of the direct effects of disease outbreaks, and the combination of direct and indirect effects will determine the restructuring of a community after disturbance.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.646 | 0.176 |
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".