Harmful algae and climate change on the Canadian East Coast: Exploring occurrence predictions of Dinophysis acuminata, D. norvegica, and Pseudo-nitzschia seriata
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Harmful algal blooms (HABs) are a threat to human health, local economies, and coastal ecosystems. Generalized additive mixed models (GAMMs) were fitted using a 24-y database in order to predict future occurrences of three distinct species of HABs on the Canadian East Coast, the dinoflagellates Dinophysis acuminata and D. norvegica, and the diatom Pseudo-nitzschia seriata. GAMMs produced for each species were combined with two downscaled climate simulations (MPI-ESM-LR and CanESM2) under the representative concentration pathway (RCP) 8.5 over the 21st century. D. acuminata, D. norvegica, and P. seriata GAMMs were fitted using sea surface salinity and sea surface temperature, with wind speed averaged over seven days added to the P. seriata model. GAMMs succeeded at various degrees at reproducing past HAB events, with D. acuminata and D. norvegica being accurately modelled, and P. seriata producing less precise model results. Both climate simulations lead to similar conclusions in regards to the spatio-temporal shift in occurrences of the three studied species. D. acuminata and D. norvegica blooms (≥ 1000 cells L − 1) are predicted to increase in the future, whereas P. seriata bloom events (≥ 5000 cells L − 1) will tend to stabilise/decrease overall on the Canadian East Coast. Dinophysis blooms are most likely to increase in the St. Lawrence Estuary. Pseudo-nitzschia blooms will move to the northeastern part of the Gulf of St. Lawrence and will increase in the Bay of Fundy/Gulf of Maine regions. On average, earlier blooms and larger seasonal windows of opportunity are predicted across all species investigated. We conclude that changes in D. acuminata, D. norvegica, and P. seriata bloom dynamics and their spatial distributions could threaten aquaculture industries and ecosystem health on Canada's East Coast in localities and during seasons which were not previously impacted by these species.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it