Comment on egusphere-2022-1364
Bibliographic record
Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> Ocean temperature and dissolved oxygen shape marine habitats in interplay with species’ physiological characteristics. Therefore, the observed and projected warming and deoxygenation in the 21st century of the world’s oceans may strongly affect species’ habitats. Here, we implement an extended version of the Aerobic Growth Index (AGI), which quantifies whether a viable population of a species can be sustained in a particular location. We assess the impact of projected deoxygenation and warming on the contemporary habitat of 47 representative marine species covering the epipelagic, mesopelagic/bathypelagic, and demersal realms. AGI is calculated for these species for the historical period and into the 21st century using bias-corrected environmental data from six comprehensive Earth System Models. While habitat viability decreases nearly everywhere with global warming, impact of this decrease is strongly species-dependent. Most species lose less than 5 % of their contemporary habitat volume over the 21st century even at 3 °C of global warming relative to preindustrial, although some individual species are projected to incur losses 2–3 times greater than that. We find that the contemporary spatiotemporal variability of O<sub>2</sub> and temperature (and hence AGI) provides a quantifiable measure of a species’ vulnerability to change. Species’ vulnerability is the most important indicator for large (>5 %) potential habitat losses – not relative or absolute changes in habitat viability (i.e., AGI<sup>rel</sup> or ΔAGI), temperature or O<sub>2</sub>. Loss of contemporary habitat is for most epipelagic species driven by warming of ocean water and is therefore expanded with increased levels of global warming. In the mesopelagic/bathypelagic and demersal realms habitat loss is also affected by <em>p</em>O<sub>2</sub> decrease for some species. Our analysis is constrained by the uncertainties involved in species-specific critical thresholds, which we quantify, by data limitations on 3D species distributions as well as by high uncertainty in model O<sub>2</sub> projections in equatorial regions. Focus on these topics in future research will strengthen our confidence in assessing climate-change driven losses of contemporary habitat across the global oceans.
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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 | 0.001 | 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 | 0.000 | 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) | 0.065 | 0.024 |
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; both teacher heads agree on what is shown here.
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".