Differences in Characteristics of Photosynthesis and Nitrogen Utilization in Leaves of the Black Locust (Robinia pseudoacacia L.) According to Leaf Position
Bibliographic record
Abstract
Robinia pseudoacacia L. has been widely planted worldwide for a variety of purposes, but it is a nonindigenous species currently invading the central part of Japanese river terraces. To understand and control this invasion, we investigated how this species invests nitrogen resources in different functions depending on the leaf location, and how these resources are used in physiological reactions such as photosynthesis. The Tama river terrace was examined in Tokyo, Japan. The leaf nitrogen (N) concentration, chlorophyll (Chl) concentration, Chl a/b ratio, leaf mass per unit area (LMA) and ribulose-1,5-bisphosphate carboxylase oxygenase (RuBisCo) concentration were all significantly lower in shade leaves than in leaves exposed to the sun. Conversely, the net photosynthetic rate in saturated light conditions (Pmax), the net photosynthetic rate under enhanced CO2 concentration and light saturation (Amax), the maximum carboxylation rate of RuBisCo (Vcmax) and the maximum rate of electron transport driving RUBP regeneration (Jmax) were all significantly lower in shade leaves than in leaves exposed to the sun. We also found that RuBisCo/N and Chl/N were significantly less in shade leaves, and values of Jmax/N, Vcmax/N less in shade leaves than in sun leaves, but not significantly. Allocation of nitrogen in leaves to photosynthetic proteins, RuBisCo (NR) was broadly less in shade leaves, and NL (light-harvesting complex: LHC, photosystem I and II: PSI and PSII) and NE (electron transport) were also lower. The N remaining was much greater in shade leaves than in sun leaves. We suggest that N remobilization from RuBisCo is more efficient than remobilization from proteins of NE, and from NL. This study shows that R. pseudoacacia has an enhanced ability to adapt to environmental changes via characteristic changes in N allocation trade-offs and physiological traits in its sun and shade leaves.
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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".