A Mechanistic Study of Plant and Microbial Controls over R* for Nitrogen in an Annual Grassland
Bibliographic record
Abstract
Differences in species' abilities to capture resources can drive competitive hierarchies, successional dynamics, community diversity, and invasions. To investigate mechanisms of resource competition within a nitrogen (N) limited California grassland community, we established a manipulative experiment using an R* framework. R* theory holds that better competitors within a N limited community should better depress available N in monoculture plots and obtain higher abundance in mixture plots. We asked whether (1) plant uptake or (2) plant species influences on microbial dynamics were the primary drivers of available soil N levels in this system where N structures plant communities. To disentangle the relative roles of plant uptake and microbially-mediated processes in resource competition, we quantified soil N dynamics as well as N pools in plant and microbial biomass in monoculture plots of 11 native or exotic annual grassland plants over one growing season. We found a negative correlation between plant N content and soil dissolved inorganic nitrogen (DIN, our measure of R*), suggesting that plant uptake drives R*. In contrast, we found no relationship between microbial biomass N or potential net N mineralization and DIN. We conclude that while plant-microbial interactions may have altered the overall quantity of N that plants take up, the relationship between species' abundance and available N in monoculture was largely driven by plant N uptake in this first year of growth.
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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 | 0.001 | 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 | 0.001 |
| 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 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".