The effects of harvesting and decaying logs on oribatid (acari: oribatida) mite assemblages in eastern Canadian mixedwood boreal forest
Bibliographic record
Abstract
Ecosystem-based management (e.g. partial cut harvesting) retains some components of natural forest structure such as downed woody material (DWM) and may have less impact than clear cutting on forest floor fauna. I tested how partial cut harvesting affects oribatid mite assemblages and explored the spatial influence of decomposing logs on oribatids on the forest floor at the sylviculture et aménagement forestiers écosystémique (SAFE) research station in Abitibi, Québec. The importance of determining the extraction duration of the specific apparatus used in biodiversity studies was also demonstrated. In June 2006, litter and soil were sampled in mixedwood boreal forest where the following treatments were replicated three times: clear cut harvest, 1/3 partial cut harvest, 2/3 partial cut harvest, controlled burn (after harvest) and uncut control. As well, six decayed logs were sampled at three distances each: directly on top of the log (ON), directly beside the log (ADJ) and at least one metre away from the log and any other fallen wood (AWAY). Samples ON logs consisted of a litter layer sample, an upper wood sample and an inner wood sample. Samples at the ADJ and AWAY distances consisted of litter samples and soil cores. Eight years after harvest, clear cutting appears to have had a homogenizing effect on oribatid species composition, and partial cuts had more similar species composition to the uncut control within their respective blocks. In litter, diversity decreased with increasing harvesting intensity but in soil it increased. In the burn, species richness was significantly different from the other treatments, and there was some change in species-specific abundance. The highest species richness was collected ON logs, and logs harboured a distinct oribatid species composition compared to the forest floor. There were species-specific changes in relative abundance with increasing distance away from DWM, and each layer (litter, wood and soil) exhibited a uniqu
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".