Changes in Water and Carbon Fluxes in the USA Southern Great Plains Grassland Due to Evergreen Forest Encroachment
Bibliographic record
Abstract
The southern Great Plains (SGP) grassland of the United States has been largely encroached by evergreen forest in recent decades. The response of the grassland water and carbon cycles to the encroachment is not clear yet. Given so, this study quantified the changes in gross primary production (GPP), evapotranspiration (ET), and ecosystem water use efficiency (EWUE) between grassland pixels with evergreen forest encroachment and neighboring pure grassland pixels (500 m). We also assessed the spatial variation of the changes in relation to precipitation (mm), air temperature (°C), and evergreen forest coverage (%). These analyses were repeated, respectively for the years of 2004, 2008, 2016, and 2019 as robustness check. Results suggest that across the 4 years, 62–72% of encroached grassland pixels exhibit higher annual GPP, 67–74% exhibit higher annual ET, whereas 65–71% exhibit lower annual EWUE. The change ratio of ET is positively correlated with that of GPP but negatively correlated with that of EWUE. Additionally, the spatial variation in the change ratios of annual GPP and ET can be explained to a certain degree by the encroachment amount. These results further clarify the response of water and carbon cycles to evergreen forest encroachment in the SGP grassland.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".