Patch dynamics and the development of structural and spatial heterogeneity in Pacific Northwest forests
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over time, chronic small-scale disturbances within forests should create distinct stand structures and spatial patterns. We tested this hypothesis by measuring the structure and spatial arrangement of gaps and canopy patches. We used airborne LiDAR data from 100 sites (cumulative 11.2 km 2 ) in the Pacific Northwest, USA, across a 643 year chronosequence to measure canopy structure, patch and gap diversity, and scales of variance. We used airborne LiDAR’s ability to identify strata in canopy surface height to distinguish patch spatial structures as homogeneous canopy structure, matrix–patch structures, or patch mosaics. We identified six distinct stand structure classes that were associated with the canopy closure, competitive exclusion, maturation, and three patch mosaics stages of late seral forest development. Structural variance peaked in all classes at the tree-to-tree and tree-to-gap scales (10–15 m), but many sites maintained high variance at scales >30 m and up to 200 m, emphasizing the high patch-to-patch heterogeneity. The time required to develop complex patch and gap structures was highly variable and was likely linked to individual site circumstances. The high variance at larger scales appears to be an emergent property that is not a simple propagation of processes observed at smaller spatial scales.
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.
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 | 0.001 | 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 | 0.001 |
| 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 it