Long-term canopy dynamics analyzed by aerial photographs and digital elevation data in a subalpine old-growth coniferous forest
Bibliographic record
Abstract
We analyzed the long-term canopy dynamics of a 2-ha permanent plot in subalpine old-growth coniferous forest over 43 y using digital surface models (DSMs) and a digital elevation model (DEM). The models contoured canopy and ground surface elevation, respectively. Abies mariesii, A. veitchii, Betula ermanii, Picea jezoensis var. hondoensis, and Tsuga diversifolia were the main species in the forest canopy. Canopy surface DSMs (2.5- × 2.5-m grids) were constructed of the area including the 2-ha plot using aerial photographs from 1959, 1969, 1979, 1989, and 2002, and a DEM was constructed from ground survey data collected in 1991. Canopy height profiles were obtained by calculating the difference between the canopy and the ground surface, and the status of the forest in each grid cell for each year was classified as gap or closed canopy, depending on whether the canopy height was ≤ 25 m or > 25 m, respectively. Tree census data were collected in 2000. The threshold value was decided by comparing the gap from digital elevation data with the result of the field survey. The total gap area in 1959 was greater than 1 ha, indicating that some disturbances had occurred in this plot, probably related to the Isewan Typhoon. A large change occurred during 1969–1989, when mean canopy closure rates were significantly higher than mean gap formation rates. Abies mariesii and B. ermanii tended to occur in the canopy layer in grid cells that contained gaps in 1959 and closed canopy in 2002. The presence of A. veitchii in the canopy layer was also associated with the change from gap to closed canopy, although not significantly so. These results suggest that Abies spp. regenerate more effectively than the other species by establishing seedling or sapling banks before gap formation. Large-scale disturbances, such as the Isewan Typhoon, do not favour the regeneration of spruce over subalpine fir, and species other than spruce are responsible for recovery following such disturbances, according to our analyses of long-term canopy dynamics.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".