Integrated Assessment of Ocean Acidification Risks to Pteropods in the Northern High Latitudes: Regional Comparison of Exposure, Sensitivity and Adaptive Capacity
Bibliographic record
Abstract
Exposure to the impact of ocean acidification (OA) is increasing in high-latitudinal productive habitats. Pelagic calcifying snails (pteropods), a significant component of the diet of economically important fish, are found in high abundance in these regions. Pteropods have thin shells that readily dissolve at low aragonite saturation state (Ωar), making them susceptible to OA. Here, we conducted a first integrated risk assessment for pteropods in the Eastern Pacific subpolar gyre, the Gulf of Alaska (GoA), Bering Sea, and Amundsen Gulf. We determined the risk for pteropod populations by integrating measures of OA exposure, biological sensitivity, and resilience. Exposure was based on physical-chemical hydrographic observations and regional biogeochemical model outputs, delineating seasonal and decadal changes in carbonate chemistry conditions. Biological sensitivity was based on pteropod morphometrics and shell-building processes, including shell dissolution, density and thickness. Resilience and adaptive capacity were based on species diversity and spatial connectivity, derived from the particle tracking modeling. Extensive shell dissolution was found in the central and western part of the subpolar gyre, parts of the Bering Sea, and Amundsen Gulf. We identified two distinct morphotypes:L. helicina helicinaandL. helicina pacifica, with high-spired and flatter shells, respectively. Despite the presence of different morphotypes, genetic analyses based on mitochondrial haplotypes identified a single species, without differentiation between the morphological forms, coinciding with evidence of widespread spatial connectivity. We found that shell morphometric characteristics depends on omega saturation state (Ωar); under Ωardecline, pteropods build flatter and thicker shells, which is indicative of a certain level of phenotypic plasticity. An integrated risk evaluation based on multiple approaches assumes a high risk for pteropod population persistence with intensification of OA in the high latitude eastern North Pacific because of their known vulnerability, along with limited evidence of species diversity despite their connectivity and our current lack of sufficient knowledge of their adaptive capacity. Such a comprehensive understanding would permit improved prediction of ecosystem change relevant to effective fisheries resource management, as well as a more robust foundation for monitoring ecosystem health and investigating OA impacts in high-latitudinal habitats.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".