Changing elemental cycles, stoichiometric mismatches, and consequences for pathogens of primary producers
Bibliographic record
Abstract
Human‐induced changes in biogeochemical cycles alter the availability of carbon (C), nitrogen (N) and phosphorus (P) in the environment, leading to changes in the elemental stoichiometry of primary producers. These changes in elemental ratios may, in turn, alter the degree of stoichiometric mismatch between primary producer hosts and their pathogens. Here, we outline how ecological stoichiometry could be used as a framework to predict the effects of changing nutrient supply on stoichiometric mismatches in autotroph–pathogen interactions. We discuss empirical evidence linking pathogen performance to stoichiometric mismatches arising from shifts in elemental availability. Our synthesis indicates that fungi may be particularly sensitive to changes in N supply and viruses generally respond strongly to changes in the supply of either of these elements, but it also highlighted the need for additional data, especially for bacteria. Consequently, fungal pathogens may respond more strongly to changes in host C:N stoichiometry, whereas viruses may be highly sensitive to both changes in C:N and C:P of hosts. Additionally, our synthesis suggests that viruses may be more homeostatic than fungi, and therefore respond more strongly to changing elemental supplies. Revealing stoichiometric mismatches may greatly support our understanding of how host–pathogen interactions in primary producers will respond to changes in global biogeochemical cycles, controlling disease incidence in primary producers under scenarios of global change.
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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".