Effects of long-term fertilization of forest soils on potential nitrification and on the abundance and community structure of ammonia oxidizers and nitrite oxidizers
Why this work is in the frame
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Bibliographic record
Abstract
Forest fertilization in British Columbia is increasing, to alleviate timber shortfalls resulting from the mountain pine beetle epidemic. However, fertilization effects on soil microbial communities, and consequently ecosystem processes, are poorly understood. Fertilization has contrasting effects on ammonia-oxidizing bacteria and archaea (AOB and AOA) in grassland and agricultural ecosystems, but there are no studies on AOB and AOA in forests. We assessed the effect of periodic (6-yearly application 200 kg N ha⁻¹) and annual (c. 75 kg N ha⁻¹) fertilization of lodgepole pine and spruce stands at five long-term maximum productivity sites on potential nitrification (PN), and the abundance and diversity of AOB, AOA and Nitrobacter and Nitrospira-like nitrite-oxidizing bacteria (NOB). Fertilization increased AOB and Nitrobacter-like NOB abundances at some sites, but did not influence AOA and Nitrospira-like NOB abundances. AOB and Nitrobacter-like NOB abundances were correlated with PN and soil nitrate concentration; no such correlations were observed for AOA and Nitrospira-like NOB. Autotrophic nitrification dominated (55–97%) in these forests and PN rates were enhanced for up to 2 years following periodic fertilization. More changes in community composition between control and fertilized plots were observed for AOB and Nitrobacter-like NOB than AOA. We conclude that fertilization causes rapid shifts in the structure of AOB and Nitrobacter-like NOB communities that dominate nitrification in these forests.
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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 | 0.001 |
| 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 it