A Stoichiometric Model of Early Plant Primary Succession
Bibliographic record
Abstract
The relative importance of plant facilitation and competition during primary succession depends on the development of ecosystem nutrient pools, yet the interaction of these processes remains poorly understood. To explore how these mechanisms interact to drive successional dynamics, we devised a stoichiometric ecosystem-level model that considers the role of nitrogen and phosphorus limitation in plant primary succession. We applied this model to the primary plant community on Mount St. Helens, Washington State, to check the validity of the proposed mechanisms. Our results show that the plant community is colimited by nitrogen and phosphorus, and they confirm previous suggestions that the presence of a nitrogen-fixing legume, Lupinus lepidus, can enhance community biomass. In addition, the observed nutrient supply rates may promote alternative successional trajectories that depend on the initial plant abundances, which may explain the observed heterogeneity in community development. The model further indicates the importance of mineralization rates and other ecosystem parameters to successional rates. We conclude that a model framework based on ecological stoichiometry allows integration of key biotic processes that interact nonlinearly with biogeochemical aspects of succession. Extension of this approach will improve the understanding of the process of primary succession and its application to ecosystem rehabilitation.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".