Allocation and residence time of photosynthetic products in a boreal forest using a low‐level <sup>14</sup>C pulse‐chase labeling technique
Bibliographic record
Abstract
Abstract Much of our understanding about how carbon (C) is allocated in plants comes from radiocarbon (14C) pulse‐chase labeling experiments. However, the large amounts of 14C required for decay‐counting mean that these studies have been restricted for the most part to mesocosm or controlled laboratory experiments. Using the enhanced sensitivity for 14C detection available with accelerator mass spectrometry (AMS), we tested the utility of a low‐level 14C pulse‐chase labeling technique for quantifying C allocation patterns and the contributions of different plant components to total ecosystem respiration in a black spruce forest stand in central Manitoba, Canada. All aspects of the field experiment used 14C at levels well below regulated health standards, without significantly altering atmospheric CO2 concentrations. Over 30 days following the label application in late summer (August and September), we monitored the temporal and spatial allocation patterns of labeled photosynthetic products by measuring the amount and 14C content of CO2 respired from different ecosystem components. The mean residence times (MRT) for labeled photosynthetic products to be respired in the understory (feather mosses), canopy (black spruce), and rhizosphere (black spruce roots and associated microbes) were <1, 6, and 15 days, respectively. Respiration from the canopy and understory showed significantly greater influence of labeled photosynthates than excised root and intact rhizosphere respiration. After 30 days,∼65% of the label assimilated had been respired by the canopy,∼20% by the rhizosphere, and∼9% by the understory, with∼6% unaccounted for and perhaps remaining in tissues. Maximum 14C values in root and rhizosphere respiration were reached 4 days after label application. The label was still detectable in root, rhizosphere and canopy respiration after 30 days; these levels of remaining label would not have been detectible had a 13C label been applied. Our results support previous studies indicating that a substantial portion of the C fueling rhizosphere respiration in the growing season may be derived from stored C pools rather than recent photosynthetic products.
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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 | 0.000 | 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 | 0.001 | 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 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".