Water table depth affects productivity, water use, and the response to nitrogen addition in a savanna system
Bibliographic record
Abstract
We investigated annual aboveground net primary productivity (ANPP) and transpiration (E) of the dominant plant life forms, longleaf pine (Pinus palustris Mill.) trees and wiregrass (Aristida stricta Michx.), in a fire-maintained savanna. Experimental plots spanned a natural hydrologic gradient (xeric and mesic site types) mediated by soil moisture (θ) and water table depth (WTD), and received additions of either 0 or 100 kg N·ha–1·year–1. Low rates of ANPP (1.3–2.2 Mg·ha–1) and annual E (108–380 mm) were observed in these communities. WTD and N addition explained 95% of the variation in community ANPP, whereas site type and WTD explained 83% of variation in community E. Between tree and grass life forms, longleaf pine ANPP was more coupled to WTD than wiregrass. For any given leaf area supported, ANPP of longleaf pine increased linearly with increasing water use and decreasing WTD. The longleaf pine ANPP response to N addition was greater in sites with high water use compared with those with low water use, indicating that this savanna system is colimited by nutrient and water availability and that water table depth plays a role in regulating savanna productivity.
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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 | 0.000 | 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 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".