Allometric Models to Estimate Aboveground Biomass of Individual Trees of Eucalyptus saligna Sm in Young Plantations in Ecuador
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Bibliographic record
Abstract
(1) Background: Nature-based solutions (NbS), particularly through forest biomass, are crucial in mitigating climate change. While forest plantations play a critical role in carbon capture, the absence of species-specific biomass estimation models presents a significant challenge. This research focuses on developing allometric models to accurately estimate the aboveground biomass of Eucalyptus saligna Sm in Ecuador’s Lower Montane thorny steppe. (2) Methods: Conducted at the Tunshi Experimental Station of ESPOCH in Chimborazo, Ecuador, the research involved 46 trees to formulate biomass predictive models using both destructive and non-destructive methods. Sixteen generic models were tested using the ordinary least squares method. (3) Results: The most effective allometric equation for estimating six-year-old E. saligna biomass was Ln(B) = −0.952 + 1.97∗Ln(dbh), where B = biomass in kg/tree, and dbh = diameter at breast height in cm. This model represents a valuable contribution to improve biomass and carbon estimates in mitigation projects in Ecuador. (4) Conclusions: The tested models stand out for their simplicity, requiring only dbh as input, and demonstrate high accuracy and fit to contribute to the field of climate change mitigation.
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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 | 0.001 | 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