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Record W3154594963 · doi:10.21203/rs.3.rs-92037/v1

The collapse and recovery potential of carbon sequestration by baleen whales in the Southern Ocean

2020· preprint· en· W3154594963 on OpenAlexaff
Anaëlle Durfort, Gaël Mariani, Marc Troussellier, Vivitskaia Tulloch, David Mouillot

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBaleenCarbon sequestrationOceanographyWhaleEnvironmental scienceGeologyFisheryBiologyCarbon dioxideEcology

Abstract

fetched live from OpenAlex

Abstract Limiting climate warming below 2°C requires both reducing anthropic greenhouse gas emissions and sequestering more atmospheric carbon. Natural Climate Solutions (NCS) rely on the ability of ecosystems to capture and store carbon. Despite the important role of marine megafauna on the ocean carbon cycle, its potential as a NCS has not yet been explored. Here, we quantify the amount of carbon potentially sequestered by five baleen whale species across the Southern Hemisphere between 1890 and 2100 through both the sinking of carcasses after natural death and the fertilisation of phytoplankton by nutrients in faeces. At their pre-exploitation abundances, the five whales could sequester 10.6 106 tonnes of carbon per year (tC.yr-1) but this natural carbon sink was reduced at 2 106 tC.yr-1 in 1965 due to commercial whaling. However, the restoration of whale populations could sequester 8.7 106 tC.yr-1 at the end of the 21st century suggesting an efficient but neglected NCS that remains to be estimated globally including all marine vertebrates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.316
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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