Spatial distribution of carbon sources and sinks in Canada’s 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
Annual spatial distributions of carbon sources and sinks in Canada’s forests at 1 km resolution are computed for the period from 1901 to 1998 using ecosystem models that integrate remote sensing images, gridded climate, soils and forest inventory data. GIS-based fire scar maps for most regions of Canada are used to develop a remote sensing algorithm for mapping and dating forest burned areas in the 25 yr prior to 1998. These mapped and dated burned areas are used in combination with inventory data to produce a complete image of forest stand age in 1998. Empirical NPP age relationships were used to simulate the annual variations of forest growth and carbon balance in 1 km pixels, each treated as a homogeneous forest stand. Annual CO2 flux data from four sites were used for model validation. Averaged over the period 1990–1998, the carbon source and sink map for Canada’s forests show the following features: (i) large spatial variations corresponding to the patchiness of recent fire scars and productive forests and (ii) a general south-to-north gradient of decreasing carbon sink strength and increasing source strength. This gradient results mostly from differential effects of temperature increase on growing season length, nutrient mineralization and heterotrophic respiration at different latitudes as well as from uneven nitrogen deposition. The results from the present study are compared with those of two previous studies. The comparison suggests that the overall positive effects of non-disturbance factors (climate, CO2 and nitrogen) outweighed the effects of increased disturbances in the last two decades, making Canada’s forests a carbon sink in the 1980s and 1990s. Comparisons of the modeled results with tower-based eddy covariance measurements of net ecosystem exchange at four forest stands indicate that the sink values from the present study may be underestimated.
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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 it