Assessing the Effects of Climate Change and Air Pollution on Soil Properties and Plant Diversity in Northeastern U.S. Hardwood Forests: Model Setup and Evaluation
Bibliographic record
Abstract
The integrated forest ecosystem model ForSAFE-Veg was used to simulate soil processes and understory vegetation composition at three-sugar maple, beech, yellow birch-hardwood forest sites in the Northeastern United States (one at Hubbard Brook, NH, and two at Bear Brook, ME). Input data were pooled from a variety of sources and proved coherent and consistent. While the biogeochemical component ForSAFE was used with limited calibration, the ground vegetation composition module Veg was calibrated to field relevés. Evaluating different simulated ecosystem indicators (soil solution chemistry, tree biomass, ground vegetation composition) showed that the model performed comparably well regardless of the site's soil condition, climate, and amounts of nitrogen (N) and sulfur (S) deposition, with the exception of failing to capture tree biomass decline at Hubbard Brook. The model performed better when compared with annual observation than monthly data. The results support the assumption that the biogeochemical model ForSAFE can be used with limited calibration and provide reasonable confidence, while the vegetation community composition module Veg requires calibration if the individual plant species are of interest. The study welcomes recent advances in empirically explaining the responses of hardwood forests to nutrient imbalances and points to the need for more research.
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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 | 0.001 |
| 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".