Soil respiration and net ecosystem productivity in a chronosequence of hybrid poplar plantations
Bibliographic record
Abstract
Forest stand age can affect ecosystem carbon (C) cycling and net ecosystem productivity (NEP). In Canada, establishment of short-rotation plantations on previously agricultural lands has been ongoing, but the effect of stand development on soil respiration (Rs) and NEP in such plantations is poorly understood. These types of data are essential for constraining ecosystem models that simulate C dynamics over the rotation of a plantation. We studied Rs (including autotrophic, Ra, and heterotrophic, Rh) and NEP in 2008 and 2009 in a chronosequence of 5-, 8-, 14-, and 16-yr-old (ages in 2009) hybrid poplar (Populus deltoides × Populus × petrowskyana var. Walker) plantations in northern Alberta. The highest Rs and NEP were generally found in the 14-yr-old stand. Seasonal variations in Rs were similar among the plantations, with most of the variation explained by soil temperature at the 10 cm depth in 2008 with far less explained in 2009, a much drier year. In diurnal measurements, hysteresis was found between soil respiration and soil temperature, with the patterns of hysteresis different among stand ages. Soil respiration in the 14-yr-old plantation had the greatest sensitivity to temperature changes. Stand age did not affect the Rh:Rs ratio, whereas the NEP exhibited strong inter-annual variability. We conclude that stand age was a major factor affecting Rs and NEP, and such effects should be considered in empirical models used to simulate ecosystem C dynamics to evaluate potentials for C sequestration and the C source–sink relationship in short-rotation woody crop systems.
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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 | 0.001 |
| 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".