Cumulative effects of biomass harvesting and herbicide application on litter-dwelling arthropod communities in jack pine-dominated forests: 7th year postharvest assessment
Bibliographic record
Abstract
Forest biomass harvest has the potential to provide feedstocks for energy production to offset fossil fuel consumption. However, concerns have been raised regarding the ecological sustainability of removing additional biomass from forests, in particular the impacts on biodiversity. In this paper, we used a suite of ground-dwelling arthropod taxa (ground beetles, spiders, and rove beetles) to measure community compositional changes along a gradient of biomass removal treatments 7 years postharvest, and compared against reference. Based on multivariate regression trees, changes in species composition reflected the intensity gradient of the biomass removal treatments or stand attributes associated with the level of forest floor disturbance across all arthropod groups. For each arthropod group, changes in composition were defined primarily by reductions or loss of abundant forest associated species and increases in the number and abundance of species associated with more xeric conditions and increased disturbance intensity. There were no differences between full-tree and tree-length treatments. Overall, results indicated a strong arthropod response to the removal of overstory, forest floor disturbance, and reductions in understory cover mostly resulting from the glyphosate applications. Arthropod recovery would benefit from overstory retention, reduction in forest floor disturbance, and judicious use of glyphosate.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".