Do N‐fixing legumes promote neighbouring diversity in the tropics?
Bibliographic record
Abstract
Abstract 1. Although nitrogen‐fixing plants play a crucial role in maintaining high ecosystem productivity, their effects on forest diversity are greatly debated. Legumes can reduce local diversity because of the fertilization effect; however, they can also facilitate species coexistence through complementary resource utilization. 2. In natural forests, nitrogen requirements and biological nitrogen fixation (BNF) vary widely among legumes. We used leaf nitrogen isotopic composition to differentiate the level of BNF activity among seven legumes across a steep gradient of soil available nitrogen within a 60‐ha stem‐mapping plot in a montane tropical rainforest in Hainan Island, China, and we evaluated their spatial distribution and neighbourhood diversity. 3. Results show that the levels of BNF activity are tightly correlated with legume association to available soil nitrogen, where legumes associated with nitrogen‐rich habitats exhibit surprisingly greater BNF activity and a more diverse neighbourhood. 4. Synthesis. These findings indicate that legumes satisfy their nitrogen‐demanding metabolism through a synergy of habitat preference and BNF activity. High BNF activity drives local diversity by promoting complementary resource utilization rather than intensifying above‐ground competition. This may be achieved by improving litter quality and stimulating mycorrhizal and microbial diversity. The abundance of nitrogen fixers in nitrogen‐rich habitats also explains how legumes contribute to maintaining high levels of soil nitrogen in tropical forests.
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 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 | 0.001 | 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 | 0.000 |
| 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".