Isoscape Models of the Southern Ocean: Predicting Spatial and Temporal Variability in Carbon and Nitrogen Isotope Compositions of Particulate Organic Matter
Bibliographic record
Abstract
Abstract Polar marine ecosystems are particularly vulnerable to the effects of climate change. Warming temperatures, freshening seawater, and disruption to sea‐ice formation potentially all have cascading effects on food webs. New approaches are needed to better understand spatiotemporal interactions among biogeochemical processes at the base of Southern Ocean food webs. In marine systems, isoscapes (models of the spatial variation in the stable isotopic composition) of carbon and nitrogen have proven useful in identifying spatial variation in a range of biogeochemical processes, such as nutrient utilization by phytoplankton. Isoscapes provide a baseline for interpreting stable isotope compositions of higher trophic level animals in movement, migration, and diet research. Here, we produce carbon and nitrogen isoscapes across the entire Southern Ocean (>40°S) using surface particulate organic matter isotope data, collected over the past 50 years. We use Integrated Nested Laplace Approximation‐based approaches to predict mean annual isoscapes and four seasonal isoscapes using a suite of environmental data as predictor variables. Clear spatial gradients in δ 13 C and δ 15 N values were predicted across the Southern Ocean, consistent with previous statistical and mechanistic views of isotopic variability in this region. We identify strong seasonal variability in both carbon and nitrogen isoscapes, with key implications for the use of static or annual average isoscape baselines in animal studies attempting to document seasonal migratory or foraging behaviors.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".