Spectral analysis discerns pattern and feedback in natural‐ and anthropogenic‐disturbed boreal black spruce forests
Bibliographic record
Abstract
The two major disturbance types of boreal black spruce forest in north–central Quebec, Canada – natural disturbance by wildfire and anthropogenic disturbance by harvest – may affect processes of recovery differently and leave distinct post‐disturbance soil and vegetation spatial patterns. We tested whether 1) spatial patterns of physico‐chemical soil organic layer properties, black spruce diameter and density, and understory ericaceous shrub cover, differ between these two principal disturbance types; 2) operations associated with forest harvest result in distinct, regular spatial patterns of these same variables related to presence of machine trails; and 3) ericaceous shrub presence is a potential factor contributing to the legacy of spatial patterns after harvest. We explored these patterns on black spruce‐feathermoss forest stands, including fire‐origin stands (18 and 98 years) and stands originating from harvest (16 and 62 years) in central Quebec, Canada. We used two spatial analysis methods, spectral analysis and principal component analysis in the frequency domain, to characterize and relate spatial patterns of these soil and vegetation variables, measured along 50‐m transects on each site. Spatial patterns of distribution of soil and vegetation variables were different on the burned and the harvested forest sites. Wildfire gave rise to spatial patterns in soil and vegetation variables at multiple scales, reflecting the complexity generated by variable burn intensity. Patterns following forest harvest were mainly related to the regular structure defined by trails created by logging operations. In contrast to burned sites, ericaceous shrub patterns on harvested sites were strongly associated with spatial arrangements of spruce diameter and density, promoting absence of canopy closure and persistence of trails. Moreover, different spatial signatures did not converge in the long‐term (62–98 years) between the two disturbance types. The divergence in spatial structure between natural and anthropogenic disturbances has implications for ecosystem structure and function in the longer term.
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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) | 0.001 | 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 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".