Black spruce boreal forest soil solution inorganic nitrogen is highly resilient to 20 years of elevated nitrogen deposition
Bibliographic record
Abstract
Abstract Soil solution is the liquid phase of soil containing nutrients that are essential for vegetation’s health and growth. As such, soil solution chemistry is directly related to nutrient cycling and productivity in forest ecosystems. However, the long-term impacts of elevated N deposition on boreal forest soil solution composition remain uncertain. In this study, we investigate the effects of two decades of ammonium nitrate addition applied at rates of 3 (LN treatment) and 10 (HN treatment) times the ambient N deposition on soil solution collected weekly during the snow-free period at a black spruce boreal forest site located in eastern Canada. We show that N addition corresponding to 60 years (LN treatment) and 200 years (HN treatment) of accelerated ambient N deposition had nearly no important nor lasting impacts on soil solution NO3 − and NH4 + concentrations. This reveals that N deposition will most likely not significantly impact Canadian boreal forests soil solution inorganic N concentration in the future. Based on these results and along with NOx emissions data measured globally in North America and on NO3–N deposition recorded at our experimental forest site, it is also likely that N deposition never affected Canadian forests’ soil chemistry in the past, even at the peak of N emission in North America in the 70 s. Our results indicate a surprisingly strong and widespread resilience of the eastern Canadian boreal forest soil solution chemistry and inorganic N content to long-term N deposition. This resilience can be partially explained by an important N-limitation in high-latitude forest ecosystems.
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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 | 0.001 | 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".