Conversion of boreal forests to agricultural systems: soil microbial responses along a land-conversion chronosequence
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Boreal regions are warming at more than double the global average, creating opportunities for the northward expansion of agriculture. Expanding agricultural production in these regions will involve the conversion of boreal forests to agricultural fields, with cumulative impacts on soil microbial communities and associated biogeochemical cycling processes. Understanding the magnitude or rate of change that will occur with these biological processes will provide information that will enable these regions to be developed in a more sustainable manner, including managing carbon and nitrogen losses. This study, based in the southern boreal region of Canada where agricultural expansion has been occurring for decades, used a paired forest-adjacent agricultural field approach to quantify how soil microbial communities and functions were altered at three different stages post-conversion (< 10, > 10 and < 50, and > 50 years). Soil microbial functional capacity was assessed by quantitative PCR of genes associated with carbon (C), nitrogen, and phosphorous (P) cycling; microbial taxonomic diversity and community structure was assessed by amplicon sequencing. RESULTS: Fungal alpha diversity did not change, but communities shifted from Basidiomycota to Ascomycota dominant within the first decade. Bacterial alpha diversity increased, with Gemmatimonadota groups generally increasing and Actinomycetota groups generally decreasing in agricultural soils. These altered communities led to altered functional capacity. Functional genes associated with nitrification and low molecular weight C cycling potential increased after conversion, while those associated with organic P mineralization potential decreased. Stable increases in most N cycling functions occurred within the first decade, but C cycling functions were still changing 50 years post conversion. CONCLUSIONS: Microbial communities underwent a rapid shift in the first decade, followed by several decades of slower transition until stabilizing 50 years post conversion. Understanding how the microbial communities respond at different stages post-conversion improves our ability to predict C and N losses from emerging boreal agricultural systems, and provides insight into how best to manage these soils in a way that is sustainable at the local level and within a global context.
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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 | 0.000 |
| 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 it