Nitrogen Retranslocation Response of Young <i>Picea mariana</i> to Nitrogen‐15 Supply
Why this work is in the frame
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Bibliographic record
Abstract
Nutrient loading stimulates N retranslocation, an important mechanism of N reuse in plants to support new growth. We quantified N retranslocation in young black spruce [ Picea mariana (Mill.) BSP] using tracer and nontracer techniques to examine enhanced field performance after nutrient loading. Nursery reared seedlings were transplanted to sand‐filled pots fertilized with 15 NH 4 15 NO 3 at rates equivalent to 0 and 200 kg N ha −1 simulating poor and rich soils. After one growing season (120 d), biomass increased (118%) on the poor soil without N gain demonstrating the significance of internal N reserves for retranslocation to new growth. Nutrient loading improved retranslocation (218%) and new biomass (156%) after planting confirming the advantage of higher preplant N reserves (175%) for later nutrient demand. Enhanced N availability in the rich soil accelerated growth (236%), N uptake (258%), and retranslocation (23%) in seedlings. Retranslocation increased with time reflecting higher N demand as seedlings become larger and suggest the process is driven by sink strength. Nontracer estimates of N retranslocation in seedlings fell short of isotopic determinations because of inability to discriminate between soil and plant derived N in tree components. Although fertilization promoted N uptake (125–258%), 15 N recovery in plants averaged 12 to 19% indicating low fertilizer efficiency in young trees. Total reliance of unfertilized plants on internal N reserves for growth on the poor soil affirms the importance of retranslocation to meet plant N demands, and also exemplifies initial short‐term independence on soil N for newly planted seedlings that can be prolonged by nutrient loading.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it