Effects of experimental harvesting on spider (Araneae) assemblages in boreal deciduous forests
Bibliographic record
Abstract
Abstract Two large-scale forestry experiments, in Quebec (Sylviculture et aménagement forestiers écosystémique (SAFE)) and Alberta (Ecosystem Management by Emulating Natural Disturbance (EMEND)), were established in the late 1990s to test the effects of alternative silvicultural strategies ( e.g. , partial cutting) on biodiversity in northern boreal forests. We collected spiders in pitfall traps 2 years after the application of partial-cutting treatments in deciduous stands at EMEND and 6 years after similar treatments in deciduous stands at SAFE. Although we are aware of the challenges imposed by disparate locations and whole-scale experimental methods, our objective was to compare the effects of partial cutting on spider assemblages (diversity and community composition), and in doing so, to formulate a few general statements. Overall, 98 species (6107 individuals) were collected from Alberta and 86 species (3414 individuals) from Quebec. Of these, 44 species were common to both regions. Ordination and indicator-species analyses revealed a distinct effect of geographic separation: the spider assemblages in deciduous stands within the boreal plains ecoregion of Alberta and the boreal shield in Quebec were distinct. However, the effects of partial cutting on spider assemblages within each project were similar: removal of 25%–33% of trees shifted a characteristic old-growth fauna toward one more typical of clearcuts. Indicator-species analysis also revealed the dominance of wolf spider (Lycosidae) species in clearcuts within both experiments and we present evidence that clear-cutting homogenizes spider assemblages. Old-growth forests contain spider faunas that are easily disrupted by moderate partial cutting. In the face of intense harvesting practices, managing for the maintenance of biodiversity and conservation of spider faunas in northern forests will require retention of old-growth forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".