Increasing atmospheric CO2 concentrations outweighs effects of stand density in determining growth and water use efficiency in Pinus ponderosa of the semi-arid grasslands of Nebraska (U.S.A.)
Bibliographic record
Abstract
This study investigated the impacts of environmental (e.g., climate and CO2 level) and ecological (e.g., stand density) factors on the long-term growth and physiology of ponderosa pine (Pinus ponderosa) in a semi-arid north American grassland. We hypothesized that ponderosa pine long-term growth patterns were positively influenced by an increase in atmospheric CO2 concentrations and a decrease in stand density. To test this hypothesis, comparison of long-term trends in tree-ring width and carbon and oxygen stable isotopic composition of trees growing in dense and sparse forest stands were carried out at two sites located in the Nebraska National Forest. Results indicated that tree-ring growth increased over time, more at the sparse than at the dense stands. In addition, the carbon and oxygen isotopic ratios showed long-term increases in intrinsic water use efficiency (WUEi), with little difference between dense and sparse stands. We found a clear trend over time in ponderosa pine tree growth and WUEi, mechanistically linked to long-term changes in global CO2 concentration. The study also highlighted that global factors tend to outweigh local effects of stand density in determining long-term trends in ponderosa pine growth. Finally, we discuss the implications of these results for woody encroachment into grasslands of Nebraska and we underlined how the use of long-term time series is crucial for understanding those ecosystems and to guarantee their conservation.
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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 | 0.000 |
| 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".