Attributes and indicators of old-growth and successional Douglas-fir forests on Vancouver Island
Bibliographic record
Abstract
The Douglas-fir forests of coastal British Columbia are within the most heavily modified forest ecosystem types in coastal BC and local land managers are developing new forestry practices to retain elements of old growth within the managed forest area. To determine how successful these practices are requires the selection and monitoring of appropriate attributes and knowledge on how they change with stand development. In this paper we summarize previously published results from an extensive data set on four Douglas-fir dominated sites located on eastern Vancouver Island. Data were collected as part of the Coastal Forest Chronosequences project which was addressing questions on (1) how does conversion to managed forests impact species and forest structural diversity and (2) how does this diversity recover in older second-growth stands. Each site contained four stands, a postharvest chronosequence: regeneration (R, 510 years), immature (I, 2545 years), and maturing (M, 7595 years) stands, and an old growth (O, >240 years) control stand. Over 20 attributes are summarized including structural attributes, and at three sites, detailed biodiversity and process attributes. All old-growth plots exceeded the minimum age criteria and some but not all of the minimum structural attribute criteria for old-growth Douglas-fir forests in the US Pacific Northwest, reflecting regional or site type differences. Most structural attributes showed their greatest change within the first 100 years, although older stands (M and O) still differed based on tree and snag sizes and tree mass or basal area. Most species abundance and richness attributes and process attributes clearly differentiated R from the forested stages but were of less value for differentiating among older (M and O) stands. Arboreal lichen abundance and species richness; the abundance of cryptogams, achlorophyllus plants, litter collembola, and specific species of fungi and carabids; litter fall and gap fraction were the exception, these attributes clearly differentiating M from O stands. In postharvest stands, the overall pattern of change with succession for most attributes, as inferred from the chronosequence, was confirmed to be very different from a previously published conceptual model for post-fire succession. Compared to the post-fire model, the greatest changes in the postharvest stands occurred early in stand development, associated with canopy closure. Although stand structural attributes can clearly be used to distinguish old-growth features in managed forest stands, none-the-less it is important to monitor and demonstrate, at least for a selection of nonstructural attributes, that forestry practices are effective in maintaining biodiversity and associated processes of old-growth forests in the managed forest area. Key words: old-growth forest, succession, Douglas-fir forest, criteria and indicators, biodiversity, managed forest.
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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) | 0.000 | 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".