Long-term soil productivity study: 25-year vegetation response to varying degrees of disturbance in aspen-dominated forest spanning the Upper Lake States.
Bibliographic record
Abstract
Installations of the Long-Term Soil Productivity Study were established in northern Minnesota and Michigan at the Chippewa, Ottawa, and Huron-Manistee National Forests (NFs) in the early 1990s and have since provided a wealth of data for assessing the response of aspen-dominated forest ecosystems to varying levels of organic matter removal and soil compaction. An assessment of 25-year standing woody biomass indicates that neither whole-tree harvest nor whole-tree harvest combined with forest floor removal reduced forest productivity on silt-loam soils compared with conventional, stem-only harvest; however, moderate and heavy compaction did negatively impact aspen biomass and stem densities. In contrast, whole-tree harvest reduced standing biomass of aspen and all species combined on sandy soils at the Huron NF while compaction had no discernable impact. Neither treatment factor affected vegetation response at the Ottawa NF (clay soils), but reduced sample size at this site may have increased variability. Over all, the response of standing biomass and forest structure to organic matter removal and compaction treatments demonstrate that the sustainability of practices such as whole-tree harvesting and associated potential for soil impacts varies with site conditions, even when stands are dominated by the same species (e.g., Populus tremuloides).
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) | 0.001 | 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 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".