Mixedwood silviculture in North America: the science and art of managing for complex, multi-species temperate forests
Bibliographic record
Abstract
Temperate mixedwoods (hardwood–softwood mixtures) in central and eastern United States and Canada can be classified into two overarching categories: those with shade-tolerant softwoods maintained by light to moderate disturbances and those with shade-intolerant to mid-tolerant softwoods maintained by moderate to severe disturbances. The former includes red spruce (Picea rubens Sarg.), balsam fir (Abies balsamea (L.) Mill.), or eastern hemlock (Tsuga canadensis (L.) Carr.) in mixture with northern hardwood species; the latter includes pine (Pinus) – oak (Quercus) mixtures. Such forests have desirable socio-economic values, wildlife habitat potential, and (or) adaptive capacity, but management is challenging because one or more softwood species in each can be limited by depleted seed sources, narrow regeneration requirements, or poor competitive ability. Appropriate silvicultural systems vary among mixedwood compositions depending on shade tolerance and severity of disturbance associated with the limiting softwoods, site quality, and level of herbivory. Sustainability of mixedwood composition requires that stand structure and composition be managed at each entry to maintain vigorous trees of species with different growth rates and longevities and to encourage development of advance reproduction or seed-producing trees of desired species. Regardless of silvicultural system, maintaining seed sources of limiting softwoods, providing suitable germination substrates, and controlling competition are critical. Here, we describe commonalities among temperate mixedwoods in central and eastern North America and present a framework for managing them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".