Climate‐induced decrease in biomass flow in marine food webs may severely affect predators and ecosystem production
Bibliographic record
Abstract
Climate change impacts on marine life in the world ocean are expected to accelerate over the 21st century, affecting the structure and functioning of food webs. We analyzed a key aspect of this issue, focusing on the impact of changes in biomass flow within marine food webs and the resulting effects on ecosystem biomass and production. We used a modeling framework based on a parsimonious quasi-physical representation of biomass flow through the food web, to explore the future of marine consumer biomass and production at the global scale over the 21st century. Biomass flow is determined by three climate-related factors: primary production entering the food web, trophic transfer efficiency describing losses in biomass transfers from one trophic level (TL) to the next, and flow kinetic measuring the speed of biomass transfers within the food web. Using climate projections of three earth system models, we calculated biomass and production at each TL on a 1° latitude ×1° longitude grid of the global ocean under two greenhouse gas emission scenarios. We show that the alterations of the trophic functioning of marine ecosystems, mainly driven by faster and less efficient biomass transfers and decreasing primary production, would lead to a projected decline in total consumer biomass by 18.5% by 2090-2099 relative to 1986-2005 under the "no mitigation policy" scenario. The projected decrease in transfer efficiency is expected to amplify impacts at higher TLs, leading to a 21.3% decrease in abundance of predators and thus to a change in the overall trophic structure of marine ecosystems. Marine animal production is also projected to decline but to a lesser extent than biomass. Our study highlights that the temporal and spatial projected changes in biomass and production would imply direct repercussions on the future of world fisheries and beyond all services provided by Ocean.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".