Increased soil temperature and atmospheric N deposition have no effect on the N status and growth of a mature balsam fir forest
Bibliographic record
Abstract
Abstract. Nitrogen (N) is a major growth-limiting factor in boreal forest ecosystems. Increases of temperature and atmospheric N deposition are expected to affect forest growth directly and indirectly by increasing N availability due to higher rates of N mineralization. In order to understand the potential impacts of these changes, a mature balsam fir stand in Québec, Canada, was subjected during three consecutive growing seasons (2009–2011) to (i) experimentally increased soil temperature (4 °C) and earlier snowmelt (2–3 weeks) as well as (ii) increased inorganic N concentration in artificial precipitation (3 × current N concentrations using 15NH4-15NO3). Soil inorganic N was measured using buried ion-exchange membranes (PRS™ probes) and standard soil extractions. Dendrometers were used to monitor the variations in diameter growth and needles were analyzed annually for N to assess the nutritional response of trees. Results from the second (2010) and third (2011) year of treatment are reported. After three years of treatment, there was no significant increase in soil nitrate (NO3) or ammonium (NH4) availability either in the organic or in the mineral soil as measured with standard soil extractions. Similar results were obtained with ion-exchange membranes, except for NH4 in the forest floor, which increased by an average of 54% over the two years. No effect of treatments were observed on needle N or diameter growth, but an 8-day earlier peak in diameter growth was measured in heated plots in 2010. We attributed the limited effects of our treatments to the acute soil competition for available N at the site. As a result, the projected modifications of the forest N cycle and concomitant increased forest growth due to an earlier snowmelt, increased soil temperature and N deposition should be considered with caution in similar cold N-poor ecosystems.
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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".