Nutrient resorption in <i>Claytonia virginica</i> L.: implications for deciduous forest nutrient cycling
Bibliographic record
Abstract
According to the vernal dam hypothesis, spring ephemeral herbs temporarily sequester large nutrient pools in deciduous forests prior to canopy closure and return the nutrients to the soil following senescence of aboveground tissues. However, many species resorb nutrients from their leaves back to belowground tissues during senescence, and the degree of resorption is often associated with soil nutrient availability. Species that store large proportions of their absorbed nutrients between years are not participating in the temporary sequestering and rapid recycling of nutrients implied by the vernal dam. We investigated the extent to which Claytonia virginica L. sequestered and returned nutrients to the soil in response to nitrogen (N) and phosphorus (P) availability. We tested the effect of nutrient availability on nutrient use efficiency, resorption efficiency, and resorption proficiency (% nutrient in senescent leaves) of Claytonia. Nutrient additions significantly decreased N but not P use efficiency of Claytonia, particularly as the growing season progressed. Nutrient additions also significantly reduced N resorption efficiency from 80 to 47% and decreased P resorption efficiency from 86 to 56%. N and P resorption proficiencies were also significantly lower in senesced leaves of fertilized plants: N concentrations were 2.33% when unfertilized and 4.13% when fertilized, while P concentrations were 0.43% when unfertilized versus 0.57% when fertilized. When unfertilized, Claytonia was more efficient at resorption compared with other spring herbs, but similar to other species when fertilized. However, Claytonia was much less proficient in resorbing nutrients than other reported plants, because senescent tissues maintained substantially higher concentrations of N and P, particularly when fertilized. In conclusion, Claytonia, an important spring ephemeral species, exhibits physiological responses that emphasize its role in the vernal dam by its temporary sequestration and substantial, rapid return of nutrients in deciduous forests. Adding nutrients to the site increases the total mass and the relative proportion of nutrients that Claytonia returns to the soil rather than sequestering between seasons, which ultimately increases nutrient recycling rates within the entire system.Key words: Claytonia virginica, nutrient response, resorption efficiency, nutrient cycling, spring ephemerals, vernal dam.
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 | 0.000 | 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".