Pine caterpillar outbreak and stand density impacts on nitrogen and phosphorus dynamics and their stoichiometry in Masson pine (<i>Pinus massoniana</i>) plantations in subtropical China
Bibliographic record
Abstract
Masson pine caterpillar (MPC, Dendrolimus punctatus Walker) outbreaks periodically occur in Masson pine (Pinus massoniana Lamb.) plantations in southern China; however, their effects on nutrient cycling remain unclear. In 2011, an MPC outbreak occurred in pine plantations with different stand densities, which facilitated a comparison of nitrogen (N) and phosphorus (P) cycling dynamics. Monitoring of soil and foliar nutrients from pre- to post-outbreak years (i.e., from 2010 to approximately 2012) indicated that soil NO3–-N concentration and fluxes were higher after the outbreak in low-density plantations, whereas soil NH4+-N and P availability varied minimally and were not different between the high- and low-density sites. Pine foliage responses to the MPC outbreak were dependent on stand density. At the high-density site, foliar N increased by 40% with an increase of 25% in N resorption efficiency and by approximately 200%–300% in P resorption efficiency, whereas there was an increase of 50% N concentration, a 65% increase in N resorption efficiency, and a >500% increase in P resorption efficiency at the low-density site. Overall, soil nutrients were higher in low-density than high-density plantations, whereas leaf nutrient resorption had the opposite results after an MPC outbreak. The effects of a periodic MPC outbreak could increase plant N:P stoichiometry in these plantations, particularly in the denser stands.
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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 | 0.001 | 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 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".