Using natural analogues to investigate the effects of climate change and ocean acidification on Northern ecosystems
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
Abstract Northern oceans are in a state of rapid transition. Still, our knowledge of the likely effects of climate change and ocean acidification on key species in the food web, functionally important habitats and the structure of Arctic and sub-Arctic ecosystems is limited and based mainly on short-term laboratory studies on single species. This review discusses how tropical and temperate natural analogues of carbonate chemistry drivers, such as CO2 vents, have been used to further our knowledge of the sensitivity of biological systems to predicted climate change, and thus assess the capacity of different species to show long-term acclimation and adaptation to elevated levels of pCO2. Natural analogues have also provided the means to scale-up from single-species responses to community and ecosystem level responses. However, to date the application of such approaches is limited in high latitude systems. A range of Arctic and sub-Arctic sites, including CO2 vents, methane cold seeps, estuaries, up-welling areas, and polar fronts, that encompass gradients of pH, carbonate saturation state, and alkalinity, are suggested for future high latitude, in-situ ocean acidification research. It is recommended that combinations of monitoring of the chemical oceanography, observational, and experimental (in situ and laboratory) studies of organisms around these natural analogues be used to attain better predictions of the impacts of ocean acidification and climate change on high latitude species and ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it