Perspectives on development of definitions and values related to old-growth forests
Bibliographic record
Abstract
Old-growth forests are those that meet some threshold(s) determined by a scientific and political process. The main issue is what criteria to use to determine these thresholds; they must be practical enough to allow managers to delimit and manage old-growth stands in the field. People value forests with old and (or) big trees and primary forests that have a continuous heritage of natural disturbance and regeneration, even though the latter may include all stages of stand development and succession. We advocate uniting these two and using "primary forest", also called "natural heritage forest", as the criterion for delimiting old growth in regions where primary forest still exists. This criterion recognizes that the stage of development with big, old trees is part of a cycle of development, and it is necessary to have all the parts to continue to produce new examples of the older stages. The best available second-growth stands can be used in regions where primary forests are not available. Alternatively, threshold criteria for delimiting old growth can be based on tree size and age, but arbitrary criteria based on human size and age scales should be avoided in favour of criteria that specify stands dominated by trees relatively large and old for the species and site. Such criteria allow for old growth to occur across a variety of levels of site productivity, with trees of widely varying stature and with varying life-history characteristics, such as longevity, shade tolerance, and successional status. In any case, managers and scientists should work together to make sure that definitions work in the field but also include the ecological processes necessary to maintain the unique biological resources of old growth. The biological resources present in old growth may help to restore the second-growth landscape and allow reconstitution of forests in new places after global warming. Old-growth forests provide a baseline for comparison of effects of logging and natural disturbance, with respect to resilience to climatic change and disturbance, maintenance of species richness, and natural genetic structure of tree populations, which respond to different selective regimes in old growth and harvested forests. The species in old-growth remnants, their interactions and the resilience of the system after disturbance are as important or perhaps more so than the age and size of the trees at a given point in time. Key words: dwarf forest, Minnesota, old-growth processes, tree height.
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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 | 0.000 | 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 | 0.002 |
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; both teacher heads agree on what is shown here.
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".