Global‐scale patterns of nutrient resorption associated with latitude, temperature and precipitation
Bibliographic record
Abstract
ABSTRACT Aim Nutrient resorption from senescing leaves is an important mechanism of nutrient conservation in plants, but the patterns of nutrient resorption at the global scale are unknown. Because soil nutrients vary along climatic gradients, we hypothesize that nutrient resorption changes with latitude, temperature and precipitation. Location Global. Methods We conducted a meta‐analysis on a global data set collected from published literature on nitrogen (N) and phosphorus (P) resorption of woody plants. Results For all data pooled, both N resorption efficiency (NRE) and P resorption efficiency (PRE) were significantly related to latitude, mean annual temperature (MAT) and mean annual precipitation (MAP): NRE increased with latitude but decreased with MAT and MAP. In contrast, PRE decreased with latitude but increased with MAT and MAP. When functional groups (shrub versus tree, coniferous versus broadleaf and evergreen versus deciduous) were examined individually, the patterns of NRE and PRE in relation to latitude, MAT and MAP were generally similar. Main conclusions The relationships between N and P resorption and latitude, MAT and MAP indicate the existence of geographical patterns of plant nutrient conservation strategies in relation to temperature and precipitation at the global scale, particularly for PRE, which can be an indicator for P limitation in the tropics and selective pressure shaping the evolution of plant traits. Our results suggest that, although the magnitude of plant nutrient resorption might be regulated by local factors such as substrate, spatial patterns are also controlled by temperature or precipitation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".