Food Webs and Ecosystems: Linking Species Interactions to the Carbon Cycle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
All species within ecosystems contribute to regulating carbon cycling because of their functional integration into food webs. Yet carbon modeling and accounting still assumes that only plants, microbes, and invertebrate decomposer species are relevant to the carbon cycle. Our multifaceted review develops a case for considering a wider range of species, especially herbivorous and carnivorous wild animals. Animal control over carbon cycling is shaped by the animals’ stoichiometric needs and functional traits in relation to the stoichiometry and functional traits of their resources. Quantitative synthesis reveals that failing to consider these mechanisms can lead to serious inaccuracies in the carbon budget. Newer carbon-cycle models that consider food-web structure based on organismal functional traits and stoichiometry can offer mechanistically informed predictions about the magnitudes of animal effects that will help guide new empirical research aimed at developing a coherent understanding of the interactions and importance of all species within food webs.
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.
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 it