Age‐dependent variation in the biophysical properties of boreal forests
Bibliographic record
Abstract
The changes in boreal forest hydrology, biogeochemistry, and biophysics during succession have critical implications for the sign and magnitude of the vegetation‐climate feedbacks that might occur with a change in fire frequency, and also for the identification and attribution of changes in boreal forest to climate. We combined in situ measurements from eddy covariance sites located along an age transect in a Canadian boreal forest with spectral vegetation indices (SVIs) derived from Landsat and MODIS imagery. We found tight spatial relationships between Landsat SVIs and in situ measurements of three important biophysical properties: albedo, maximum daily uptake of CO 2 ( F CO2‐max ), and leaf area index (LAI). The tasseled cap indices were particularly well suited for tracking biophysical variation along an age transect. Trends in brightness, greenness, and wetness from 1984 to 2005 indicated how succession drives temporal trends in biophysical properties. Albedo and F CO2‐max increased rapidly in the decade following fire and then decreased for the remainder of succession, while LAI continued to increase until ∼135 years and may decrease thereafter. The ratio of greenness to wetness indicated that photosynthesis was limited by leaf area before 10–12 years and by reduced leaf‐level photosynthetic rates thereafter, coinciding with the successional replacement of broadleaf deciduous species by evergreen conifer species. The timing of phenological events was also strongly age‐dependent, but the normalized difference vegetation index (NDVI) confounded the disappearance of the snowpack in spring for the onset of photosynthesis. Secondary succession was the dominant source of temporal variability in the biophysical properties we examined.
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.
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".