Increased Peatland Nutrient Availability Following the Fort McMurray Horse River Wildfire
Bibliographic record
Abstract
Northern peatlands are experiencing increased wildfire disturbance, threatening peatland biogeochemical function and ability to remain major stores of carbon (C) and macronutrients (nitrogen—N, and phosphorus—P). The impacts of climate change-driven drying on peatland nutrient dynamics have been explored previously; however, the impacts of wildfire on nutrient dynamics have not been examined when comparing burned and unburned areas in a post-fire fen. This study assessed the impact of wildfire on N and P bioavailability, change in CNP stoichiometric balance and feedback on plant nutrient limitation patterns in a fen peatland, one-year post-wildfire, by comparing Burned and Unburned areas. Water extractable P increased up to 200 times in shallow leachate, 125 times in groundwater and 5 times in peat. Surface ash leachate had increased concentrations in Ammonium (NH4+) and Nitrate (NO3−), and through groundwater mobility, increased extractable N concentrations were observed in peat throughout the entire fen. The net mineralization of N and P were minimal at the Burned areas relative to Unburned areas. Fire affected plant nutrient limitation patterns, switching from dominantly N-limited to NP co-limited and P-limitation in moss and vascular species respectively. The top 20 cm of the Burned area C concentrations was higher relative to the Unburned area, with increased CN and CP ratios also being found in the Burned area. These findings suggest that the long-term effects of elevated C, N, and P concentrations on plant productivity and decomposition must be re-evaluated for fire disturbance to understand the resiliency of peatland biogeochemistry post-wildfire.
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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 | 0.000 | 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) | 0.001 | 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".